Gene Expression Profiling of Patients With Polycythemia Rubra Vera
Generation of Transgenic Mice Expressing the Human PRV-1 Gene
Inauguraldissertation
Zur Erlangung der Doktorwürde der Fakultät für Biologie der Albert-Ludwigs-Universität Freiburg im Breisgau
vorgelegt von Diplom-Biochemiker Philipp Stefan Goerttler aus Freiburg im Breisgau
Die vorliegende Arbeit wurde im Zeitraum von Juni 2000 bis August 2004 in der Klinik für Tumorbiologie und dem Zentrum für Klinische Forschung in der Abteilung für Experimentelle Anaesthesie der Albert-Ludwigs-Universität Freiburg unter der Betreuung von Frau Prof. Dr. Heike L. Pahl durchgeführt. Vor der Fakultät für Biologie wurde die Arbeit durch Herrn Prof. Dr. Gunther Neuhaus vertreten.
Promotionsvortrag / Promotionsgespräch fanden am 26.10.2004 / 13.12.2004 statt.
Prüfer: Prof. Dr. Heike L. Pahl (direkte Betreuung der Arbeit) Prof. Dr. G. Neuhaus (Vertretung der Arbeit vor der Fakultät für Biologie) Prof. Dr. C. Peters Priv. Doz. Dr. G. Scherer Prof. Dr. K. F. Fischbach (Prüfungs-Vorsitzender)
Ich bestätige hiermit an Eides statt, daß die vorgelegte Arbeit von mir alleine und nur unter Zuhilfenahme der angegebenen Hilfsmittel durchgeführt wurde.
Philipp Goerttler Freiburg, den 14.12.2004
1. Introduction...... 5 1.1 Chronic Myeloproliferative Disorders...... 6
1.2 Chronic Myeloid Leukaemia...... 7
1.3 Essential Thrombocythaemia ...... 9
1.4 Idiopathic Myelofibrosis...... 10
1.5 Polycythaemia Rubra Vera (PV) ...... 11 1.5.1 Disease Pattern...... 11 1.5.2 Diagnosis...... 12 1.5.3 Therapy ...... 14 1.5.4 Molecular Characterisation of PV...... 15 1.5.5 Clonality...... 16 1.5.6 Progenitor Cell Assays ...... 17 1.5.7 Growth Factor Sensitivity ...... 18 1.5.8 Erythropoietin Receptor (EPO-R)...... 18 1.5.9 SHP-1 Phosphatase...... 19 1.5.10 STAT Family of Transcription Factors...... 19 1.5.11 Thrombopoietin Receptor...... 20 1.5.12 Genomic Alterations in PV ...... 21 1.5.13 Familial Polycythaemias...... 21
1.6 PRV-1...... 22 1.6.1 Discovery and Characterisation of PRV-1...... 22 1.6.2 Expression of PRV-1 mRNA in CMPDs ...... 23 1.6.3 Correlation Between PRV-1 Expression and EEC Growth ...... 23 1.6.4 Diagnostic Assay for the Determination of PRV-1 mRNA Levels ...... 24 1.6.5 Expression of the PRV-1 Protein...... 24 1.6.6 A Murine Homologue of PRV-1 ...... 25
Aim of this work ...... 26
2. Methods ...... 28 2.1 Whole Mount in-situ Hybridisation...... 28 2.1.1 Mating of Mice ...... 28 2.1.2 Killing of the Mice ...... 28 2.1.3 Preparation and Fixation of the Embryos...... 28 2.1.4 Dehydration ...... 28 2.1.5 Generation of DIG Labelled RNA Probes ...... 28 2.1.6 In-Situ Hybridisation ...... 29
2.2 DNA Preparation From Tail-biopsies of Mice...... 30
2.3 RNA Preparation ...... 31 1 2.3.1 RNA Isolation From Samples in TRIZOL®...... 31 2.3.2 RNA Isolation From Granulocytes in GTC Solution ...... 31 2.3.3 Isolation of Total RNA From Mouse Embryos...... 32
2.4 Quantification of Nucleic Acids...... 32
2.5 Agarose Gel Electrophoresis...... 32 2.5.1 RNA Electrophoresis ...... 32 2.5.2 DNA Electrophoresis ...... 33 2.5.3 Cleanup of DNA Fragments From Agarose Gels...... 33
2.6 Northern Blot ...... 33 2.6.1 Transfer of RNA to Nylon Membranes ...... 33 2.6.2 Generation of Radio-Labelled Probes...... 34 2.6.3 Membrane Hybridisation and Autoradiography...... 34
2.7 Reverse Transcription (RT)...... 34
2.8 Polymerase Chain Reaction (PCR)...... 35 2.8.1 Standard PCR Protocol ...... 35 2.8.2 Colony PCR...... 36 2.8.3 Semi-Quantitative RT-PCR ...... 36
2.9 FACS Analysis of Mouse Whole Blood...... 37 2.9.1 Single Colour Analysis (PRV-1) ...... 37 2.9.2 Multi Colour Analysis...... 37
2.10 Sequence Analysis of DNA ...... 38
2.11 Ligations ...... 39 2.11.1 Ligation of Restriction Fragments Into Plasmid Vectors ...... 39 2.11.2 Ligation of PCR Products Using TOPOTM TA Cloning ...... 39
2.12 Transformation of Competent E. coli Cells ...... 39
2.13 Preparation of Plasmid DNA ...... 40
2.14 TaqMan® Quantitative RT-PCR ...... 40 2.14.1 Standard PRV-1 and GAPDH TaqMan® Assay...... 42 2.14.2 Assays-on-DemandTM...... 43
2.15 Isolation of Granulocytes From Blood Samples...... 44
2.16 Restriction Digest of DNA ...... 45 2.16.1 Analytical Digestions ...... 45 2.16.2 Preparative Digestions ...... 45 2.16.3 Digestion of PCR Products...... 45
2.17 cDNA Microarrays ...... 46 2.17.1 Production of cDNA Microarrays ...... 46
2 2.17.2 Synthesis of Cy3- and Cy5-dUTP Labelled cDNAs ...... 46 2.17.3 Annealing of the Oligo dT Primers ...... 46 2.17.4 Incorporation of Cy3- and Cy5-dUTP During Reverse Transcription...... 47 2.17.5 cDNA Cleanup...... 47 2.17.6 Hybridisation...... 47 2.17.7 Washing Steps ...... 48 2.17.8 Data Analysis...... 48
3. Materials ...... 50 3.1 Oligonucleotides ...... 50
3.2 General Equipment ...... 51
3.3 Chemicals ...... 52
3.4 Radio-Chemicals ...... 53
3.5 Enzymes...... 53
3.6 Kits ...... 54
3.7 Buffers and Solutions...... 54 3.7.1 General Buffers and Solutions ...... 54 3.7.2 Buffers for RNA Preparation...... 54 3.7.3 Washing Solutions for Northern Blots ...... 54 3.7.4 Buffers for DNA Gel Electrophoresis...... 55 3.7.5 Buffers and Solutions for Western Blotting ...... 55 3.7.6 Buffers, Antibodies and Solutions for In-Situ Hybridisations...... 55 3.7.7 DNA Preparation from Tail-biopsies...... 55
3.8 FACS-Antibodies...... 55
3.9 Other Biochemicals ...... 56
4. Results ...... 57 4.1 In-situ Hybridisation of Mouse Embryos ...... 57
4.2 Generation of PRV-1 Transgenic Mice...... 58 4.2.1 PRV-1/Vav Construct ...... 59 4.2.2 PRV-1/H2K Construct...... 62 4.2.3 Generation of Transgenic Founder Lines...... 64 4.2.4 Single Colour FACS Analysis of Mouse Whole Blood ...... 67 4.2.5 Multi Colour FACS Analysis ...... 68 4.2.6 Analysis of Haematological Parameters...... 72
4.3 cDNA Microarray Analysis of PV Patients...... 75 4.3.1 Methodological Background ...... 76 4.3.2 PV Gene Expression Signature...... 82 3 4.3.3 Differential Gene Expression in PV Patients and Healthy Controls ...... 88 4.3.4 Many Genes Overexpressed in PV are Regulated by SP1...... 92 4.3.5 Chromosomal Clustering of Up- and Downregulated Genes...... 94 4.3.6 Verification of the Microarray Results...... 96
4.4 Molecular Characterisation of ET Patients...... 104 4.4.1 Patients...... 105 4.4.2 Analysis of PRV-1 mRNA and c-Mpl Protein in 20 ET Patients...... 105 4.4.3 Thrombotic Complications in ET Patients ...... 107 4.4.4 Correlation Between PRV-1 mRNA, Clonality and EEC Growth in ET ...... 109 4.4.5 Microarray Analysis of ET Patients ...... 112
4.5 Familial Accumulation of Elevated PRV-1 mRNA Levels...... 117 4.5.1 Elevated PRV-1 mRNA Levels in a Girl With Budd-Chiari Syndrome ...... 117
5. Supplemental Data ...... 119 5.1 Figures ...... 119
5.2 Tables...... 122
5.3 Functional Classification...... 128
6. Summary ...... 135
7. Discussion ...... 137 7.1 Transgenic Mice ...... 137
7.2 cDNA Microarray Analysis of PV Patients...... 141
7.3 Molecular Characterisation of ET Patients...... 149
8. References ...... 152
9. Abbreviations...... 166
4 1. Introduction
All mature haematopoietic cells originate from a small number of pluripotent stem cells in the bone marrow which give rise to the two basic lineages of the haematopoietic compartment: myeloid and lymphoid cells. The resulting lymphoid and myeloid stem cells have the potential to differentiate into all mature cell types of these two compartments thereby loosing their multipotent abilities step by step. Lymphoid stem cells can further differentiate into B- and T-cells whereas thrombocytes, erythrocytes, granulocytes and monocytes display the progeny of the myeloid stem cells. The transition between the different developmental stages is regulated by the presence or absence of distinct haematopoietic growth factors. The term „leukaemia“ covers a large number of neoplastic disorders of the haematopoietic system. Classification is based on two major characteristics: First, the developmental stage of the cells which are involved and second, the compartment of the haematopoietic system which is affected by the diseases. Acute leukaemias are characterised by the hyperproliferation of immature cells or blasts. Abnormal, immature cells occur in bone marrow, peripheral blood and frequently in the liver, spleen, lymph nodes, and other parenchymatous organs. If untreated, most patients die within a time period of six months. Genetic dispositions which can lead to acute leukaemias are described in the literature but exposition to ionising radiation and mutagenic substances seem to be the major reasons for these disorders. In chronic leukaemia the proliferating cells appear mature. The clinical course is relatively indolent, compared with acute leukaemia, and ranges from 2-6 years depending on the subtype of the proliferating cell. Further subdivision and classification is more straightforward in acute than in chronic leukaemias. A first attempt was taken in 1976 when the French-American-British cooperative group (FAB) proposed a classification system for acute myeloid and lymphoid leukaemias (15). In 1985 the revised FAB criteria were published which included seven (M1-M7) subtypes of acute myeloid leukaemias and 3 subtypes of acute lymphoid leukaemias (16). As the FAB classification is based primarily on morphological and cytochemical features it does not always reflect the genetic or clinical diversity of the disease. In 2001 the World Health Organisation (86) proposed a new classification system. 5 In these so-called WHO criteria also genetic, immunophenotypical, biological, and clinical features were taken into account to define specific disease entities. The categorisation includes many of the FAB criteria for classification of the myeloid neoplasms. Additionally, guidelines of the Polycythaemia Vera Study Group (PVSG) were included for classification of the Chronic Myeloproliferative Diseases (CMPDs). Although the WHO criteria allow a more precise categorisation including prognostic values, higher technical demands as compared to the FAB classification have delayed its acceptance.
Figure 1.1: Classification of acute and chronic leukaemias. For acute myeloid and lymphoid leukaemia the FAB criteria (15) are shown.
1.1 Chronic Myeloproliferative Disorders As this work deals predominantly with the molecular characterisation of polycythaemia rubra vera, major attention should be directed to the CMPDs. This term was firstly used in 1951 by Dameshek to group four clinically and pathophysiologically related disorders (44). As shown in Figure 1.1 this group includes chronic myelogenous leukaemia (CML), polycythaemia rubra vera (PV), idiopathic myelofibrosis (IMF) and essential thrombocythaemia (ET). Hallmark of the CMPDs is the malignant clonal expansion of a multipotent stem cell. While all three cell lines (myeloid, erythroid and megakaryocytic) are involved in each disorder, the predominant cell lines allow a subclassification of the disorders. For instance, in PV the proliferation is predominately erythroid, but granulocytes and megakaryocytes are also part of the malignant clone.
6 Transitions between the different members of this group are observed in some cases. For example, patients diagnosed with ET can develop clinical features of PV in later stages (73,169,177). All CMPDs show a variable predisposition to transform into acute leukaemias (about 90% of the CML patients but only 5-10% of all PV patients transform to an acute phase during later stages of the disease). The CMPDs display a group of phenotypically closely related diseases. To date, diagnosis is mostly based on exclusion criteria leading to a relatively high number of misdiagnosed patients. With the exception of CML where the so-called Philadelphia (Ph) chromosome is found in almost all cases, no molecular markers are widely accepted for diagnosis of the other three CMPDs. Thus, a molecular classification of the CMPDs could provide more insight into pathogenesis and allow evaluation of appropriate treatment regimens for newly diagnosed patients.
1.2 Chronic Myeloid Leukaemia CML is the most common CMPD and results in an increase of both, myeloid and erythroid cells and a marked myeloid hyperplasia in the bone marrow. Mature neutrophil granulocytes and their precursors are predominant in peripheral blood and bone marrow. The median age at presentation is 53 years, but also children can be affected. The most common abnormality is splenomegaly, present in up to half of the patients. Progression of the disease, if untreated, normally includes a benign chronic phase, followed by an accelerated phase and a rapidly developing blast crisis within the first three to five years. After transition into blast crisis the cells appear more undifferentiated and resemble the myeloblasts and lymphoblasts found in acute leukaemias. CML is the only CMPD whose molecular cause is known. In 1960 the so-called Philadelphia (Ph) chromosome was firstly described as a shortened chromosome 22 (148) then as a t(9;22) (163). In about 95% of all CML patients this translocation can be found. The remaining 5% have other translocations involving additional chromosomes which can’t be detected by routine cytogenetic analysis. These methods are more and more replaced by more convenient ones such as RT-PCR.
7 The t(9;22) is not exclusive for CML as between 10 and 20% of adults and 2 to 5% of children (164,178) with acute lymphoblastic leukaemia (ALL) and some cases of acute myeloid leukaemia (AML) are also positive for the Philadelphia chromosome. During progression of the disease and evolution of a blast crisis a range of secondary chromosomal changes can occur, including duplication of the Ph chromosome and mutations or deletions of tumor suppressor genes as p16 and p53 (6). In all these cases, including those with more complex cytogenetic abnormalities, the chromosomal translocation leads to the formation of two hybrid genes which involves the BCR gene (breakpoint cluster region) on chromosome 22 and the ABL gene (Ableson leukaemia virus) on chromosome 9. The resulting BCR-ABL fusion gene on the Ph chromosome encodes a constitutively active tyrosine kinase (47) which is the molecular cause of CML as mice transgenic for the BCR-ABL fusion gene show a CML-like phenotype (42,43). The role of the reciprocal fusion gene ABL-BCR on chromosome 9q+ remains unknown (134,135). The size of the resulting BCR-ABL fusion gene varies between 185 and 230 kd which depends on the portion of the BCR gene which is involved whereas the breakpoint region in the ABL gene is more or less invariable. In recent studies correlations between size of the fusion gene and progression of the disease have been found, suggesting that fusion proteins of different size have different tyrosine kinase activities (124,199). CML is the only member in the group of the CMPDs where a molecular cause is known. Discovery of the BCR-ABL fusion gene has focussed some efforts on the development of causative therapeutic agents. In different studies it has been shown that Imatinib® (Gleevec®, STI 571), a 2-phenylamino-pyrimidine derivate can inhibit the tyrosine kinase activity of BCR-ABL by occupying its ATP binding site. In the treatment of CML in chronic phase Imatinib® yields much better results than interferon-α with about 70% of complete responses compared with 7% after interferon treatment. After transition to the accelerated phase these responses are sustained in a smaller percentage of the patients but still higher than under treatment with interferon. In blast crisis the response rates are comparable to those under chemotherapy with a smaller number of patients showing durable response. Combination therapies including both, chemotherapy and Imatinib® treatment are being explored (53).
8 1.3 Essential Thrombocythaemia As in PV and IMF the diagnosis of essential thrombocythaemia (ET) is based more or less on exclusion criteria. In 1997 the modified PVSG criteria for the diagnosis of ET were defined (142). As for the other CMPDs some of these criteria have been adopted in 2001 for the newly defined WHO criteria (86). In general, these criteria include a platelet count of more than 600 x 109/l, proliferation mainly of the megakaryocytic lineage, whereas any evidence for other CMPDs (IMF, PV or CML) as well as reactive thrombocytosis must be excluded. With about 0.5 to 2.5 per 100000 the annual incidence of ET is the same as in PV with a prevalence in young females. Clinical outcome in ET is very heterogeneous. The 10 year survival is between 64 and 80%. About 10% of all patients convert to acute leukaemia and 5% to IMF during progression of the disease (81). Clonality analysis in neutrophils of ET patients diagnosed according to the PVSG criteria has shown clonal haematopoiesis in about 50% of all cases (33,57,75). ET, like the other CMPDs appears to be caused by an acquired mutation of a single pluripotent stem cell. The relatively high number of patients showing polyclonal haematopoiesis could be caused by two reasons: First, clonality analysis including X- chromosomal inactivation patterns (XCIP) might fail to detect a small but increasing population of clonal cells against a polyclonal background. Secondly, oligoclonal results could be interpreted as polyclonal. The formation of Endogenous Erythroid Colonies (EECs) can be observed in 50% of all patients with an initial diagnosis of ET (60). In another study it has been described that EEC-positive ET patients predominantly will transform to PV during progression of the disease (169). Several attempts have been taken to find molecular markers like the BCR-ABL fusion gene in CML which allow clear diagnosis and a curative treatment of ET but to date no such markers have been found. As the elevated megakaryocyte and platelet counts in ET could be caused by a dysregulation in thrombopoietin (TPO) signalling the TPO levels as well as the TPO- receptor (c-Mpl) have been extensively studied. The TPO levels have been found to be normal or slightly elevated (180), a phenomenon which can be also observed in other CMPDs. With the exception of familial cases of ET (67,68,76) no mutations in the TPO gene have been found. A number of common polymorphisms as well as
9 new isoforms were identified for the TPO-receptor c-Mpl but none of them turned out to be causative for ET (98). A reduced level of c-Mpl on platelets of ET patients has been described (120,121) however this was also found in a subset of PV patients (138,140).
1.4 Idiopathic Myelofibrosis With about 0.5 cases per 100000 people/year IMF has the lowest incidence of all four CMPDs. The disease is characterised by a progressive extramedullary haematopoiesis, anaemia and a transformation into acute leukaemia in about 20% of all cases. The median age at diagnosis is 60 years with an average survival of 5 years. The classification as an CMPD results from hyperproliferation of the megakaryocytic lineage in the bone marrow which is accompanied by increased white cell and platelet counts. Bone marrow fibrosis seems to be a rather secondary effect caused by the release of growth factors from the expanding megakaryocytic lineage which in turn leads to an excessive production of collagen in the surrounding fibroblasts. For the diagnosis of IMF the WHO criteria differentiate between two stages of the disease, a prefibrotic and a fibrotic stage (86). As in the other CMPDs with the exception of CML these criteria are exclusively based on morphological and clinical features. Analysis of X-chromosomal inactivation patterns indicate that in IMF granulocytes, erythrocytes and platelets are clonally derived, whereas the fibroblasts are polyclonal (183). To date nothing is known about the initial event leading to the clonal expansion of a myeloid stem cell in IMF. A variety of karyotypic abnormalities, including deletions of the chromosomes 13q and 20q have been reported (160) but no uniform molecular marker for the diagnosis of IMF could be found. Mice exposed to high doses of thrombopoietin, either by administration of pegylated TPO (194) or by systemic overexpression (209) displayed a phenotype similar to that of IMF. This has been attributed to an increased TGF-β activity caused by hyperproliferation of the megakaryocytic and monocytic lineage. TGF-β is one major mediator in the synthesis of etracellular matrix proteins, including collagens type I and III which is secreted by monocytes and macrophages in IMF (132,186). Further studies revealed consistently elevated TPO levels which correlate with the degree of bone marrow fibrosis in IMF (201). The biological and clinical relevance of these
10 results remains to be determined but a molecular mechanism for the development of IMF is a distant prospect.
1.5 Polycythaemia Rubra Vera (PV) As the molecular characterisation of PV is the major topic of this work, special attention should be directed to this member of the CMPDs. After the first phenotypical description in 1892 (197) the term „true polycythaemia“ (later: „polycythaemia vera“) was firstly used in 1903 (154). The appendix „vera“ implicates that there are also other polycythaemia-like syndromes which can't be mixed up with the true polycythaemia. The group of Osler defined three different types of polycythaemias: Group 1 contains the true (primary) polycythaemias, group 2 consists of polycythaemias which are due to other, secondary reasons and group 3 (relative polycythaemia) where the elevated red cell concentration is caused by a reduced plasma volume. The progressive nature of PV was firstly described in 1938 (162), in 1951 PV together with ET, IMF and CML was grouped as a myeloproliferative disorder. Due to the outstanding role in this work, diagnostic, phenotypical and molecular aspects of PV should be discussed in more detail than for the other CMPDs.
1.5.1 Disease Pattern Polycythaemia vera is characterised by excessive erythrocyte production and usually occurs within the age range of 20-80, with 60 being the mean age of onset. At an incidence of 0.5 to 2.5 per 100000 and year male PV patients are slightly overrepresented. The clinical features at onset include headache, weakness, weight loss, sweating and pruritus. 10-15% of patients may also present with gout due to hyperuricemia. At diagnosis 20% of patients display atherosclerotic and thrombotic complications. The percentage increases up to 50% during progression of the disease in spite of therapy with cerebrovascular accidents, myocardial infarction and deep vein thrombosis being the most frequent complications. In 10% of all cases thrombotic syndromes as hepatic vein thrombosis (Budd-Chiary syndrome) and portal vein thrombosis are seen. Splenomegaly, as a result of vascular congestion, is observed in 70% of patients at the time of presentation. Hepatomegaly with a palpable liver is observed in about 30% of cases (19).
11 1.5.2 Diagnosis As described previously the differential diagnosis of CMPDs is based primarily on exclusion criteria as the myeloproliferative disorders display a group of phenotypically closely related diseases. By definition, the hallmark of PV is an elevated number of circulating red blood cells. This criterion, per se is not sufficient to judge a patient with an elevated haematocrit as a PV because there are other circumstances which can lead to a (reactive) elevation of circulating red blood cells. To differentiate between true and secondary polycythaemias a number of parameters can be analysed including the levels of erythropoietin (normal to subnormal in PV) and arterial oxygen saturation (normal in PV). After exclusion of all causes for a potential secondary polycythaemia special confirmation studies are required to rule out haemoglobinopathies, tumours and other possible causes for the abnormal phenotype. In 1966 the so-called Polycythaemia Vera Study Group (PVSG) was initiated as an international study group to evaluate treatment methods in a relatively uniform group of patients at the onset of their disease. To define guidelines for the entry into this study the PVSG developed criteria for the diagnosis of PV (19). These initial criteria were rather strict and highly specific, the rate of false-negative results was around 0.5% but some patients who did not fulfil these strict criteria were left in a grey zone. In 1997 the modified PVSG guidelines were released which are displayed in Table 1.1 (142).
Table 1.1: Proposed modified PVSG criteria for the diagnosis of PV. The diagnosis „polycythaemia vera“ is given if A1, A2 and any other A criterion is fulfilled or if A1, A2 and two B criteria are met.
12 Table 1.2: WHO criteria (2001) for the diagnosis of PV. PV is diagnosed if A1+A2+A3 or A1+A3+A4 or A1+A3 and any two B criteria are met (198).
Comparing the actual WHO criteria from 2001 (Table 1.2) and the proposed criteria of the PVSG, the main differences are the declaration of in vitro colony assays as a major criterium and the inclusion of histopathological features (bone marrow biopsies). Although pathologists appreciated the inclusion of bone marrow histology into the WHO criteria it is very difficult to standardise the preparation and evaluation of histological samples. The same is true for in vitro colony forming assays. These are difficult to establish as an objective and widely applicable diagnostic method. Another point which is controversially discussed is the measurement of the so-called red cell mass (RCM). The measurement is performed by labelling of the circulating erythrocytes with 51Cr and iodine-labelled serum albumin (125I, earlier 131I was used) to measure the plasma volume. The RCM is expressed as ml of red blood cells per kg body weight (ml/kg). The definition of limits for men and women is relatively difficult as the values for healthy people show a wide range which is influenced for example by the mass of body fat in obese subjects. Many attempts have been taken to normalise for these inter-individual differences including the determination of body density and body water volume. Measurement of the fat free lean body mass (LBM) by bioelectric conductance (18) has also been proposed. Predominantly american research groups insist on the use of the RCM as a diagnostic criterium which is not routinely performed in other countries where the measurement of the haematocrit is the method of choice to determine an increased red cell volume. These examples, taken together, demonstrate the difficulties in defining clear criteria for the diagnosis of PV. Some of these difficulties are based on technical reasons 13 whereas others are caused by the reluctance of some established scientists to accept new diagnostic assays beside classic clinical and pathological methods.
1.5.3 Therapy If patients with polycythaemia vera remain untreated, 50% die within 18 months after onset of the first symptoms mainly from thrombosis (32). Early attempts in the treatment of PV included venesection, the use of phenyl hydrazine and X-radiation to long bones. In 1939 the Lawrence-Donner laboratory began the cytoreductive treatment with 32P. This method was widely used during the Second World War and in 1948 the first case of 32P mediated leukaemia was reported (74). In 1955 a committee around W. Dameshek developed guidelines for the treatment of PV in which the use of 32P was recommended (45). Nevertheless, Dameshek and others insisted on phlebotomy as the method of choice. Phlebotomy as a therapeutic tool intends to lower the number of circulating blood cells. At onset of therapy about 500 ml of blood are taken in relatively short intervals to lower the haematocrit until the normal range is reached. For the maintenance of this level further phlebotomies are performed every few weeks or months, depending of the patient’s haematocrit. Phlebotomy reduces symptoms which are caused by the elevated haematocrit per se. The incidence of thrombotic complications has to be lowered by a myelosuppressive therapy. The first PVSG study has compared the outcome of patients treated with phlebotomy alone or by myelosuppressive agents as either 32P or the alkylating agent chlorambucil. The incidence of thrombotic events in the group treated with phlebotomy alone was relatively high as compared to myelosuppressive treatment. On the other hand, both agents, 32P and chlorambucil turned out to result in a strongly elevated number of patients who transform to an acute leukaemia during the first 3 to 5 years. In 1977 the PVSG has initiated a new trial where the efficacy of the non-alkylating agent hydroxyurea (HU) should be evaluated. The results were presented in 1984; since then HU has become the most commonly used therapeutic agent. The mechanism by which HU exerts its myelosuppressive action is inhibition of the enzyme ribonucleotide diphosphate reductase which leads to a decreased synthesis of DNA. In later studies in which the long-term effects of HU treatment should be discovered, a higher incidence of leukemic transformation was observed (144,204). The quinazoline derivate Anagrelide® lowers the platelet count without reducing the number of megakaryocytes in the bone marrow. Anagrelide® causes some side 14 effects with the result that many patients discontinue the treatment. It is used primarily in association with phlebotomy to manage thrombocytosis in young patients who are refractory to other treatment regimens. Interferon alpha (IFN-α) has been successfully used in the therapy of CML (187) and ET (165). Although IFN-α is not a drug without side effects its myelosuppressive effects in combination with the reduction of splenomegaly make it a valuable tool for alleviating the complications of cell accumulation in PV. Predisposition to acute leukaemia has not been observed to date. The requiry for subcutaneous administration about three times a week is due to the short half-life time of the recombinant IFN-α. Studies exploring the efficiency of chemically modified Interferon derivatives with longer half-life time could circumvent these inconveniences, thereby reducing side effects by maintaining lower steady-state levels of the drug. Long-time studies evaluating the effects of treatment with pegylated Interferon on the formation of Endogenous Erythroid Colonies (EECs) and the further requirement of phlebotomies have also been set up. It has been described that the administration of Imatinib®, a drug which is normally used for treatment of CML due to its inhibiting effect on the BCR-ABL tyrosine kinase, could also serve as a therapeutic tool in PV (90,175). However, the mechanism by which a tyrosine kinase inhibitor can exert a growth-suppressive effect in a Ph- negative CMPD remains to be determined.
1.5.4 Molecular Characterisation of PV As the other chronic myeloproliferative disorders PV arises from the clonal expansion of a single haematopoietic stem cell. This dogmatic theorem implies that the progeny of the cell which has acquired this mutation is also affected. For none of the CMPDs, with the exception of CML where in 95% of all cases the Philadelphia chromosome is present, a mutation has been found which allows unambiguous diagnosis and a causative therapy. Most of the molecular and cytogenetic abnormalities which were found in PV to date are restricted to a relatively small sub-population of all patients. The question arises: why ?
Two possible explanations could be:
• The unique mutation causing PV has not been found to date • There is no unique mutation in PV as the syndrome can result from a pattern of different mutations which cause the phenotype of PV 15 1.5.5 Clonality About 30 years ago a clonal origin of PV was firstly discussed (4). Beside this initial study where the clonal origin of peripheral erythrocytes, granulocytes, monocytes and platelets was demonstrated in two female PV patients more recent studies have confirmed these findings in larger cohorts of patients (108,109). The T-lymphocytes, in contrast to the bone marrow derived cell populations are not clonal in PV patients. The diagnostic value of this pattern of clonal granulocytes and polyclonal T-cells is limited by technical reasons. The assays which are performed for clonality analysis are based on the fact that in females one of the two X-chromosomes is randomly inactivated due to dose compensation of X-chromosomally encoded genes. Consequently, genes with different polymorphisms are present with only one isoform in cell populations which are clonally derived. In the beginning most studies have used the gene encoding glucose-6-phosphate dehydrogenase (G6PD) for clonality analysis. To date more X-linked genes which can be used in clonality analysis are known, including the analysis of hypermethylation patterns. Nevertheless the method of clonality analysis is only suitable for female patients who are heterozygous for the marker genes used in the assay. The percentage of women who are informative in the assay with respect to the marker genes can reach up to 90%. Another problem which limits the diagnostic value of clonality analysis is a phenomenon called „skewing“. This term describes the occurrence of clonally derived cell populations in elder women which may be caused by the loss of original stem cells thereby providing a selective advantage for the remaining cells (65). Due to these limitations clonality analysis will remain a valuable tool for research purposes without an application in diagnostic procedures.
16 1.5.6 Progenitor Cell Assays The excessive production of erythrocytes is the major hallmark of PV. In the Figure on the right hand side the subsequent stages of erythropoiesis from the pluripotent stem cell to the mature erythrocyte are depicted. Further differentiation of the intermediate developmental stages is triggered by the availability of different growth factors, including stem cell factor (SCF), interleukin 3 (IL-3) or erythropoietin (EPO). Normally the generation of haemoglobinised erythroid colonies (mature BFU-Es and CFU-Es) in vitro is strictly dependent on the availability of erythropoietin generated in liver and kidneys. In 1974 a key observation for the understanding of PV was published (159): Cultures of early haematopoietic progenitor cells from PV patients yielded erythroid colonies without the addition of exogenous EPO. Clonality analysis of these so-called Endogenous Erythroid Colonies (EECs) has shown that all EPO-independent colonies are clonal and derived from the neoplastic clone (3). By contrast, not all colonies growing in the presence of exogenous EPO were clonally derived but in two patients the percentage of cells expressing the dominant allele has increased over three years (5,125). This indicates that normal progenitor cells persist in PV which are more and more repressed by the malignant clone. More recent results have shown that one individual BFU-E from PV patients can give rise to both, EPO-dependent and EPO-independent colonies (29). This, together with other findings raises the question if EPO-independence in PV is a secondary effect which is not genetically determined. The use of EEC assays has been rated as a major criterion in the new WHO guidelines for the diagnosis of PV. Nevertheless, no standardised technical guidelines for the setup of this time-consuming and demanding assay have been proposed. As a result every lab has its own protocol for EEC assays, uses different cell culture media and cell preparation protocols. In addition, the judgement of a single colony as being erythroid or non-erythroid is a very subjective procedure which 17 may yield a large range of results when evaluated by different people. These technical limitations reduce the practical value of progenitor cell assays in diagnosis and may also account for some contradictory results in assays performed for research purposes.
1.5.7 Growth Factor Sensitivity The growth of EECs from progenitor cells of PV patients in the absence of exogenous EPO has been described. Together with the finding that serum-EPO levels in PV patients are sub-normal (49) the question arises whether these colonies are in fact independent of EPO or only hypersensitive to the minimal amounts of EPO present in the serum which was used for preparation of the culture medium. Experiments including monoclonal antibodies directed against EPO and the EPO receptor (63) and the use of strictly serum-free media (38) have been performed to test the sensitivity of PV progenitor cells towards EPO. The dose-response curves in serum-free medium turned out to be indistinguishable in patients and controls. These findings have unambiguously demonstrated the total independence of EPO rather than a hypersensitivity as previously postulated (28,55,112,211). Analysing earlier studies which led to the hypothesis of EPO-independence, Correa et al have found that in all these studies culture media have been used which all contained high levels of insulin. In colony assays using their strictly serum free medium they have shown a hypersensitivity to insulin like growth factor (IGF-1). These data, together with the finding that without EPO and IGF-1 no differences in colony growth between PV patients and controls occur, suggest that in serum-free medium EPO can be substituted with IGF-1. Exploring the background of IGF-1 hypersensitivity it was found that one of the six currently known proteins binding IGF-1 (IGFBP-1) is more than fourfold overexpressed in PV patients (137). Beside EPO and IGF-1 the sensitivity of PV progenitor cells has also been tested with respect to other growth factors. In these studies hypersensitivity has also been found to granulocyte/monocyte colony stimulating factor (GM-CSF) and IL-3 (40) as well as to SCF (41) and TPO (131).
1.5.8 Erythropoietin Receptor (EPO-R) Due to the outstanding role of erythropoietin in the understanding of PV the cell surface receptor for EPO was intensively studied. It belongs to a cytokine receptor family which forms a homodimer upon binding of its ligand and leads to the
18 phosphorylation of an intracellular domain by a JAK2 tyrosine kinase. Mutations of the EPO-R or other abnormalities would be logical explanations for different features in PV. In some familial cases of polycythaemia such abnormalities including truncations of the receptor molecule could be found but none of them turned out to be directly linked to pathogenesis (107). An alternatively spliced form of the EPO-R which leads to truncation of the cytoplasmic region was also described (31). To date there is no evidence about the physiological relevance of these findings. Taken together, the mutations involving the EPO-R are rather stochastic events than consistent hallmarks of PV.
1.5.9 SHP-1 Phosphatase Another component of the EPO signalling pathway which has been studied is the tyrosine phosphatase SHP-1. It plays a major role in the modulation of EPO signalling by dephosphorylating both, the intracellular receptor domain and the tyrosine kinase JAK2. Mice carrying loss-of-function mutations of the SHP-1 gene display a PV-like phenotype with growth of EECs (174). Extensive studies have not shown any abnormality with respect to SHP-1 in PV neither on mRNA- nor on protein-level (7,10).
1.5.10 STAT Family of Transcription Factors The STAT family of transcription factors (signal transducers and activators of transcription) plays an important role in the signal transduction via cytokine receptors. As shown in Figure 1.2, STAT signalling is induced by binding of polypeptide ligands to cytokine receptors. Conformational changes induce receptor dimerisation which in turn leads to a high affinity of the cytoplasmic domain for Janus kinases (JAKs). Activated JAKs induce tyrosine phosphorylation of the receptor homodimers. The phosphorylated tyrosine residues in the cytoplasmic domain of the receptors constitute binding sites for members of the STAT family. After binding, these are also phosphorylated by the JAKs, dimerise, translocate to the nucleus and bind to their cognate DNA sequences to activate transcription of the target genes (46). STATs are involved in GM-CSF, EPO and IGF-1 signalling and therefore interesting targets for further investigations with respect to the CMPDs. In a variety of other haematological disorders constitutive activation of STAT family members has been observed (72,203,208). Studies in 14 PV patients showed a constitutive activation of STAT3 in four cases (161). These data suggest that constitutive activation of STAT family
19 members is one of some possible alterations in PV which might influence clinical progression of the disease. With respect to more recent findings where a response of PV patients to the tyrosine kinase inhibitor STI 571 has been described, (90,175) the JAK/STAT pathway of signal transduction should be kept in mind.
Figure 1.2: Schematical illustration of the JAK/STAT pathway of signal transduction. Upon ligand binding on cytokine receptors JAKs induce tyrosine phosphorylation of intracellular receptor domains. STAT family members are in turn phosphorylated by the JAKs, dimerise and are translocated to the nucleus. In the nucleus the activated STAT dimers induce transcription of their target genes.
1.5.11 Thrombopoietin Receptor Beside granulocytes and erythrocytes the platelets are also part of the malignant clone in PV. After binding of thrombopoietin to its receptor c-Mpl the signal is transduced via the JAK/STAT pathway. In a study involving patients with PV, ET, IMF, CML and secondary erythrocytosis (SE) it was demonstrated that signal transduction induced by TPO was significantly reduced in PV and IMF (140). Further studies indicated that this was due to very low levels of c-Mpl on the platelets of patients with PV and IMF but not in CML and SE (138). Other studies investigating the expression of c-Mpl on the platelets of ET patients (82) have also found elevated levels. These results are contradictive to the reduced TPO signal transduction in ET. It must be kept in mind that the determination of c-Mpl levels is performed by Western Blot analysis which may be a valuable tool for research purposes but is also very susceptible to technical modifications especially when different primary antibodies are used. Looking for the molecular reason for reduced c-Mpl levels in PV a hypoglycosylation of the protein was found which led to lower c-Mpl levels on the cell surface. Surprisingly the extent of hypoglycosylation which is specific for the c-Mpl protein
20 correlates with duration of disease and the degree of extramedullary haematopoiesis. The inability to detect the posttranslationally modified c-Mpl protein could also account for the contradictive results described above which were obtained by the use of different primary antibodies. In contrast, the reduced levels in ET have been described to be the caused by reduced mRNA levels for c-Mpl (82,120).
1.5.12 Genomic Alterations in PV As already mentioned CML is the only member in the group of CMPDs where a consistent chromosomal abnormality is known. However, in PV approaches were taken to find such disease-causing mutations as well. Beside some rare cytogenetic changes which occur predominantly in familial cases of PV no such markers have been found to date. This might be in coincidence with the theory that in PV as well as in other CMPDs some mutations are acquired successively what causes the phenotype which we call PV. The most common mutation which can be observed in PV is a deletion of the long arm of chromosome 20 (20q-) in about 10% of all PV patients but also in patients with myelodysplastic syndrome (13,79). Another mutation which has been described is a deletion on the short arm of chromosome 9 (9pLOH) which leads to loss of heterocygosity (LOH) in this region (105). This was described in 6 out of 20 PV patients. One gene which was found to be affected by this LOH is the transcription factor NF-1B. Only in two of these six patients a semiquantitative RT-PCR was performed to demonstrate the altered mRNA levels for NF-1B. Subsequent studies in a larger cohort of seven PV patients with 9pLOH have demonstrated that increased expression of NF-1B is independent from the occurrence of 9pLOH (104).
1.5.13 Familial Polycythaemias Familial accumulations of PV-like phenotypes seem to present a useful source for genome-wide mutational screening. Nevertheless, the results must be regarded critically. Most of the mutations found in these cases are only present in a subset of the group. They don’t reach significance in „normal“ PVs what rather indicates a familial PV-like syndrome than a useful finding for PV as a member of the CMPDs.
21 These cases include various mutations affecting the EPO receptor (106), haemoglobin mutants with elevated oxygen affinity or a deficiency in the enzyme 2,3 Bisphosphoglycerate Mutase (64).
1.6 PRV-1 Taken together, the previously described molecular and cytogenetical markers as well as the progenitor cell assays are either difficult to use for diagnostic purposes (EECs, c-Mpl expression) or are only present in a subset of patients (9pLOH or 20q-, constitutively active STAT3).
1.6.1 Discovery and Characterisation of PRV-1 In 2000 the results of a subtractive hybridisation experiment involving granulocyte cDNAs from 5 PV patients and 12 healthy controls were published (184). In Northern Blot analysis of 19 PV patients and 21 healthy controls overexpression of a previously unknown gene was detected only in the PV patients. Additional patients with other CMPDs and secondary erythrocytosis did not show expression of this novel gene which was named PRV-1 (polycythaemia rubra vera-1). The examination of the open reading frame (ORF) for PRV-1 revealed two signal peptides which allow either secretion of the protein or insertion into the plasma membrane. Also detected were 2 cysteine-rich domains with homology to the so-called uPAR domains (urokinase-type plasminogen activator receptor) which are specific for a family of cell surface receptors (uPAR/Ly6/CD59/snake toxin-family). The occurrence of a GPI- anchor (glycosyl-phosphatidyl-inositol) suggests membrane attachment of the according protein. This was confirmed later by enzymatic cleavage of PRV-1 from the lipid anchor followed by FACS detection of the released protein (101). The PRV-1 gene itself consists of 9 exons and is located on chromosome 19 at the position q13.2. The exons 4 to 9 have been found twice on chromosome 19 with conserved exon-/intron structure but in an inverted orientation. To date nothing is known about the relevance of the truncated coding sequence but it most likely represents an untranscribed pseudogene. No differences have been found between PV patients and healthy controls with respect to the gene structure of PRV-1. In Northern Blot analysis four different mRNA transcripts for the PRV-1 gene could be detected which turned out to be caused by differential polyadenylation. The ORF itself encodes 437 amino acids with a molecular weight of the resulting protein of 44 kDa. Western Blot analysis using anti PRV-1 antibodies yielded a signal at 22 approximately 60 kDa. N-Glycosidase-digestion resulted in the detection of the predicted 44 kDa protein indicating N-glycosylation of the PRV-1 protein which was previously also described for other members of the uPAR-family. As other GPI-linked proteins, PRV-1 was shown to be shed from the cell surface which led to detectable levels of the protein in the supernatant of stably transfected 293-cells. Recently it became obvious that PRV-1 is identical with the well-known neutrophil antigen NB1/CD177 whose cDNA was cloned in 2001 (99).
1.6.2 Expression of PRV-1 mRNA in CMPDs The subtractive hybridisation experiments leading to the discovery of PRV-1 have demonstrated a strong overexpression of the PRV-1 mRNA in PV patients but not in healthy controls with the exception of patients with severe sepsis or acute immune response (103). Later studies using Real-time Quantitative RT-PCR have demonstrated this on larger cohorts of patients diagnosed according to the WHO criteria. Analysis of the PRV-1 expression in secondary erythrocytosis yielded normal PRV-1 mRNA-levels as obtained for healthy controls. The same was found for patients with AML, CML and 4 out of 5 cases with familial PV. In ET as well as in IMF analysis of PRV-1 mRNA results in approximately 50% of patients with elevated PRV-1 levels whereas the remainder behaved like healthy controls. This, together with other findings which will be discussed later raises the possibility that the PRV-1 positive ET patients will later transform to PV. Due to these striking results in distinguishing PV from SE and other CMPDs the German Society of Internal Medicine has recommended the use of PRV-1 as a molecular marker for differential diagnosis of PV.
1.6.3 Correlation Between PRV-1 Expression and EEC Growth The ability to grow EPO-independent erythroid colonies has been judged as an „A- criterion“ in the current WHO guidelines for the diagnosis of PV. Beside PV, the growth of EECs can also be observed in a subset of ET and IMF patients. Among the markers described above the growth of EECs is relatively close to that what we regard as the molecular cause of PV: proliferation of a progenitor cell which possesses a growth advantage (EPO-independence). Unfortunately, as mentioned previously, technical limitations, lack of a standardised protocol and difficult interpretation disqualify this assay for diagnostic use. Thus, it is very desirable to
23 replace this unreliable technique by a method which provides clear results and can be used in standard diagnostic routine. The correlation between elevated levels of PRV-1 mRNA and the growth of EECs has been tested in PV, ET and IMF. In all three CMPDs the patients who displayed elevated PRV-1 levels were also EEC-positive (104). The authors have also tested the correlation of PRV-1 mRNA expression with the occurrence of 9pLOH and the levels of c-Mpl on platelets. All individuals in the cohort who displayed a 9pLOH were also PRV-1 positive (1 ET patient and 7 PV patients). In contrast, no correlation between PRV-1 mRNA levels and the expression of the thrombopoietin receptor c- Mpl on platelets could be observed.
1.6.4 Diagnostic Assay for the Determination of PRV-1 mRNA Levels As mentioned above, the German Society of Internal Medicine has included the determination of PRV-1 mRNA levels into its guidelines for the diagnosis of PV. The use of PRV-1 as a diagnostic marker requires an assay which is highly reproducible for the measurement of small amounts of RNA. The quantification of gene specific transcripts by radioactive Northern Blot analysis requires large amounts of RNA. A relatively new technique for the quantitative analysis of RNA is the so-called Real Time Quantitative RT-PCR. It allows analysis of very small amounts of RNA (~ 5 ng) and is less time-consuming than Northern Blot analysis. Using this technique the expression of PRV-1 mRNA levels in a cohort of 71 PV patients, 11 patients with SE and 80 healthy controls was determined (102). In all PV patients the levels for PRV-1 mRNA were significantly higher than in patients with SE or in healthy controls. Thus the quantitative RT-PCR provides a rapid and highly specific tool for the diagnosis of PV in patients who display erythrocytosis.
1.6.5 Expression of the PRV-1 Protein The central dogma of molecular biology comprises the translation of mRNA into protein. Thus, overexpression of a specific mRNA should result in high protein levels. Nevertheless, no such overexpression of PRV-1 protein could be found on different blood cell populations (101). Using Western Blot and FACS analysis it has been demonstrated that both, PV patients as well as healthy controls can display surface PRV-1 levels within a large range and with considerable overlap. GPI-linked proteins can be shed from the membrane and lead to elevated plasma or serum levels. In a cell culture system involving stably transfected cell lines expressing PRV-1 protein on
24 the surface it was shown that such membrane-shedding really occurs (unpublished data). To test the hypothesis that PV patients display elevated levels of PRV-1 protein in their serum compared to healthy controls an ELISA based assay was developed. Using this very sensitive technique the protein levels in a large cohort of patients and healthy controls were tested. The data argue for slightly higher serum protein levels in PV patients but did not reach statistical significance. Anyway, the difference is some orders of magnitude apart from that observed on RNA level.
1.6.6 A Murine Homologue of PRV-1 To date, nothing is known about the molecular function of the PRV-1 protein. In some cases described in the literature, the function of previously unknown genes could be elucidated by the generation of transgenic or knockout animals for the gene of interest. To identify the murine homologue of the human PRV-1 gene database analysis was performed. After identification of mouse cDNA sequences with a high degree of homology compared to the human gene, the complete murine homologue was amplified using 5‘ RACE (Rapid Amplification of cDNA Ends). Analysis of the genomic structure revealed that the murine gene consists of 17 exons compared to 9 in the human gene. Due to differential splicing the murine PRV-1 gene encodes two proteins of 817 and 820 amino acids.
25 Aim of this work The finding that the mRNA for the PRV-1 protein is highly overexpressed in patients with polycythaemia vera provides a valuable tool for differential diagnosis in the heterogeneous group of the chronic myeloproliferative disorders. However, the physiological function of this molecular marker remains unclear. Preliminary in vitro experiments performed by S. Klippel in our laboratory have demonstrated growth inhibition of endogenous erythroid colonies (EECs) when these are treated with a PRV-1 containing tissue culture supernatant. This was obtained from tissue culture cells shedding GPI-less PRV-1 protein into the medium. The results obtained in this rather artificial system might provide first hints for a role of PRV-1; nevertheless a system which is closer to the human haematopoietic environment is required for further analysis.
One of the two major projects in this work is the generation of transgenic mice expressing the human PRV-1 protein in their haematopoietic system. An animal model for the PRV-1 protein could provide insight into its physiological role and a possible implication in the pathogenesis of polycythaemia vera. Using a promoter construct which drives transgene expression throughout the haematopoietic compartment transgenic mouse strains should be generated as a model which is in closer proximity to the pathophysiological background of polycythaemia vera. The phenotypical analysis of transgenic mice expressing the human PRV-1 protein can provide starting points for challenging follow-up projects.
The pathological heterogeneity within the chronic myeloproliferative disorders together with the fact that no specific molecular markers are available for the single disease entities of this group leads to a diagnostic routine which is based more or less on exclusion criteria (Table 1.1 and 1.2). Analysis of single molecular markers as PRV-1 mRNA or c-Mpl protein expression can be of benefit in differential diagnosis but seems to be of limited value in the process of obtaining a more global impression of these diseases. Due to this, gene expression analysis of patients with polycythaemia vera using cDNA microarrays is the main project in this work. This relatively new technique which was first described in 1995 (168), allows a global gene expression monitoring based on up to 15000 cDNAs which are analysed at the same time. The definition of a molecular signature consisting of a number of genes which allows a clear distinction between PV patients and the diagnostically relevant 26 group of patients with secondary erythrocytosis could be of benefit in diagnostic procedures. In addition, differential gene expression between patients with polycythaemia vera and healthy controls could provide more insight into a possible pathomechanism for PV.
In additional studies, patients with essential thrombocythaemia should be analysed for expression of the molecular markers PRV-1 mRNA and c-Mpl protein. The correlation of possible subgroups with the risk for thromboembolic complications could allow a more precise risk stratification for ET patients as compared to the clinical routine which is based on criteria as age, platelet count and the occurrence of previous complications.
27 2. Methods
2.1 Whole Mount in-situ Hybridisation
2.1.1 Mating of Mice To obtain mouse embryos in different developmental stages female mice were mated with male mice in a proportion of 1:2. The next morning (embryonic day 0.5) female mice were controlled for vaginal plaques. Plaque-positive mice were isolated from the male animals. At different time-points pregnant mice were sacrificed.
2.1.2 Killing of the Mice Prior to killing the mice were put into a box containing some dry ice. Following this the animals were anaesthetised by pouring some water onto the dry ice which results in the development of carbon dioxide. After about one minute the mice were killed by cervical dislocation.
2.1.3 Preparation and Fixation of the Embryos Depending on the developmental stage embryos and yolk sac were prepared (94,143). In brief the abdominal cavity was opened, the uterus was controlled for implanted embryos and transferred to a 8 cm Petri dish containing PBS. Using transillumination the decidua was teased apart with fine forceps taking care not to destroy the yolk sac. To allow a good perfusion of the embryos during hybridisation, the distinct parts (amnion, brain, neural tube, heart, eyes and ears) were perforated using micro needles (Fine Science Tools). Next, the embryos were transferred into 2 ml glass tubes prerinsed with PBS/BSA (1 mg/ml) containing 2 ml of 4% PFA in PBS. Overnight the embryos were fixed under rotation at 4°C.
2.1.4 Dehydration After removal of the solution used for fixation the embryos were washed three times with PBS. Following this they were stepwise dehydrated by incubating them in PBS containing 25, 50 and 75% MeOH and a final treatment in 100% MeOH. All washing/incubation steps were performed for 5 minutes each under continuing rotation at 4°C. Dehydrated embryos can be stored at –20°C for several months.
2.1.5 Generation of DIG Labelled RNA Probes
Preparation of Expression Vectors: The DNA fragments to be used for the generation of DIG labelled RNA probes were prepared by restriction digest of vectors containing the cDNAs for murine PRV-1 with appropriate restriction enzymes. Two different cDNA fragments for mPRV-1, 600 bp and 1000 bp in size were used. After isolation of the fragments from 1% agarose gels, these were cloned into vectors which contain transcriptional start sites for T3, T7 and SP6 RNA polymerases. The orientation of the inserts was determined. Using an appropriate restriction enzyme the obtained expression vectors were linearised to allow the generation of specific sense (negative control) and antisense probes for the corresponding cDNAs. The obtained linearised expression vectors were then purified from agarose gels and an aliquot was quantified by comparison with a DNA marker containing bands with known amounts of DNA.
28 In Vitro Transcription: To generate specific sense and antisense RNA probes from the linearised expression vectors an in vitro transcription was performed using T3, T7 and SP6 RNA polymerases depending of the vectors used for cloning and the orientation of the cDNA inserts. The DIG labelling reactions were performed using the DIG RNA Labelling Kit (Roche Diagnostics) 1 µg of the linearised cDNA construct, 2 µl of 10 x NTP labelling mixture, 2 µl of T3, T7 or SP6 RNA polymerase (20 units/µl), 2 µl of the appropriate 10 x transcription buffer and 1 µl of RNase inhibitor were mixed on ice and ddH2O was added to a final volume of 20 µl. After mixing and incubation for 2 h at 37°C in a thermocycler 2 µl of 0.2 M EDTA pH 8.0 were added to stop the reaction. 2 µl of the reaction mixture were analysed in 1% agarose gels to visualise the generated single stranded RNA probes. The remaining 18 µl of the RNA probe solution were precipitated for 30 minutes on ice after addition of 2.5 µl of 4 M LiCl and 75 µl of ice cold EtOH. Next, the RNA was pelleted for 30 minutes at 4°C in a cooled benchtop centrifuge at 13000 rpm. After washing the pellet once with 70% EtOH it was resuspended in 50 µl of RNase free H2O and stored at –80°C until usage.
2.1.6 In-Situ Hybridisation
Incubation with DIG Labelled RNA Probes: Rehydration of the embryos was performed by stepwise incubation in 75, 50 and 25% MeOH in PBST followed by a final treatment in 100% PBST. All these steps were performed for 2 minutes on ice. After washing the embryos three times for 5 minutes each in PBST under rotation at room temperature these were treated with 2 or 10 ml (for embryos in later developmental stages) of a solution containing Proteinase K (4.5 µg/ml) in PBST. The incubation time depends on the developmental stage of the embryos:
• Embryonic day 6.5 and less: 5 minutes • Embryonic day 7.5: 6 minutes • Embryonic day 8.5: 7 minutes • Embryonic day 9.5: 9 minutes • Embryonic day 10.5: 11 minutes • Embryonic day 11.5 and more: 13 minutes
After incubation the embryos were washed in a freshly prepared solution of Glycine (2 mg/ml) in PBST. Then 90% of the washing solution were removed and replaced by PBST. The tube was inverted three times and the embryos were washed two times for 5 minutes each under rotation at room temperature. After refixation on ice during 15 minutes in a solution containing 4% PFA and 0.2% Glutardialdehyde in PBST, 90% of the washing solution were removed and replaced by PBST and the embryos washed two times for 5 minutes each in PBST under rotation at room temperature. In 2 ml glass tubes the samples were stepwise transferred into prehybridisation buffer: After 3 minutes in 500 µl 50% PBST / 50% prehybridisation buffer and 3 minutes in 100% prehybridisation buffer at room temperature the embryos were pre- hybridised at 65°C in the water bath. For hybridisation 35 to 350 ng of the DIG labelled RNA probe were heated in 100 µl of hybridisation buffer for 5 minutes at 95°C, 250 µl of the prehybridisation solution were removed from the samples and replaced by the probe solution. This resulted in
29 a final probe concentration of 0.1 to 1 µg/ml. The hybridisation took place overnight at 65-70°C in a water bath.
Blocking of the Hybridised Embryos: After removal of the hybridisation solution the samples were firstly washed for 5 minutes in 800 µl prehybridisation buffer. After adding 400 µl of 2 x SSC (pH 4.5) the embryos were washed for 10 minutes. The next two washing steps were performed in 2 x SSC for 30 minutes each followed by two times 10 minutes in maleic acid buffer. All these washing steps were performed at hybridisation temperature in 15 ml Falcon Tubes. After two times 10 minutes and once 5 minutes at room temperature in PBST the embryos were re-transferred to 2 ml glass tubes with 1.5 ml of filtered antibody blocking buffer and incubated for 2 h at 4°C under rotation. At the same time the anti-DIG antibody (Roche Diagnostics) was preabsorbed to 1.5 ml of antibody blocking buffer in a dilution of 1:5000 to 1:10000 for 2 h at 4°C. After 2 h the antibody blocking buffer on the samples was replaced by the solution containing the preabsorbed antibody and blocking took place overnight at 4°C under rotation.
Washing Steps: The antibody solution was removed and the embryos were washed for two times at room temperature with a solution containing 0.1% BSA in PBST. The embryos were transferred to 15 ml Falcon Tubes and washed five times for 45 minutes each in 0.1% BSA/PBST under rotation. These washing steps can be extended to several days at 4°C to reduce unspecific background.
Antibody Detection: The samples were washed two times for 30 minutes each in PBST at room temperature and for two times 10 minutes with alkaline phoshatase (AP) buffer. After transfer to a 12-well tissue culture plate the embryos were stained for about 3 h at room temperature with BM Purple® (Roche Diagnostics). During this period of time the 12-well plates were covered with aluminium foil to prevent photo-bleaching. If there was no significant staining to be detected under the binocular, staining was performed overnight at 4°C. When the desired degree of staining was obtained, the reaction was stopped by washing the samples five times with PBS at room temperature. For storage of the stained embryos at –20°C, these were dehydrated in MeOH as described previously.
2.2 DNA Preparation From Tail-biopsies of Mice In this work gene constructs for transgenic mice expressing the human PRV-1 and Pim-1 genes have been generated. To screen for transgenic offspring after microinjection of the corresponding gene constructs, genomic DNA of these mice had to be analysed for transgene expression. After weaning of the pups tail biopsies of about 1 cm in length were taken, 750 µl of tail-buffer and 40 µl of a solution containing 10 mg/ml of Proteinase K were added. After 6 to 18 h at 56°C, 250 µl of saturated NaCl solution were added and the mixture was vigorously shaked for 5 minutes. Following 10 minutes at 13000 rpm in a benchtop centrifuge, 750 µl of the supernatant were transferred to a new microcentrifuge tube containing 500 µl of Isopropanol. After shaking the mixture for about 2 minutes the precipitated genomic DNA was pelleted during 5 minutes at
30 13000 rpm. The pellet was washed once with 500 µl of 70% EtOH and air-dried for 10 minutes by placing the tube upside down. The DNA was resuspended in 150 µl of 1 x TE (pH 7.5) during 1 h at 42°C. 150 µl of a mixture consisting of Phenol and Chloroform in a ratio of 1:1 were added, vortexed and the phases were separated by short (10 sec) centrifugation in the benchtop centrifuge. The upper, aqueous phase containing the DNA was carefully transferred to a new microcentrifuge tube and extracted a second time using one volume of Phenol:Chloroform to ensure complete removal of the protein-containing interphase. The genomic DNA was precipitated by adding 1/10 volume of 3 M NaAc (pH 5.5) and 2 volumes of 100% EtOH to the aqueous phase. After vortexing the DNA was pelleted during 5 minutes at 13000 rpm at 4°C. The pellet was washed once using 70% EtOH, air-dried for about 5 minutes and resuspended in 100 µl of 1 x TE buffer (pH 7.5). For PCR analysis of transgene expression 1 to 5 µl of the DNA solution were used in a standard PCR reaction.
2.3 RNA Preparation
2.3.1 RNA Isolation From Samples in TRIZOL® After lysis in TRIZOL® the samples (tissues, cells) can be stored up to 1 year at – 80°C. To isolate total RNA 0.2 ml of Chloroform were added per ml of TRIZOL® used for homogenisation of the samples. The tubes were vortexed to mix the two phases. After 3 minutes at room temperature, organic and aqueous phase were separated by centrifugation at 12000 x g and 4°C for 15 minutes. The upper, aqueous phase containing the RNA was transferred to a new tube containing 0.5 ml Isopropanol per ml of TRIZOL® taking care not to withdraw the protein-containing interphase. After 10 minutes at room temperature the RNA was pelleted by centrifugation at 12000 x g and 4°C for 10 minutes. The supernatant was discarded, the pellet was washed once with 1 ml of 75% EtOH and the RNA spun down by centrifugation at 7500 x g and 4°C for 5 minutes. After removal of the supernatant the pellet was dried by incubation of the opened tube at 55°C for about 10 minutes. The RNA was dissolved in an appropriate volume of RNase free water pre-heated to 55°C. The RNA concentration was determined by spectrophotometric analysis. The obtained RNA was stored at – 80°C.
2.3.2 RNA Isolation From Granulocytes in GTC Solution The samples were homogenised by passing them 15 to 20 times through a 20 G needle. Then 7.6 ml of the solution were carefully overlaid to a cushion of 3.3 ml of 5.7 M CsCl solution in a polyallomer tube (Beckman). After a centrifugation of 16 to 20 h at 25°C and 32000 rpm in a SW 41 Ti rotor (Beckman) the supernatant was discarded and the pellets were air-dried for about one hour at room temperature by placing them upside down. The gel-like pellet was resuspended in 300 µl of RNase free water, 33 µl of 3 M NaAc (pH 5.5) and 750 µl of EtOH were added, mixed, transferred to 1.5 ml microcentrifuge tubes and precipitated overnight at –20°C or during 30 minutes at –80°C. After precipitation the RNA was pelleted by centrifugation at 12000 x g and 4°C for 30 minutes. The RNA was washed once with 250 µl of 70% EtOH and spun down at 12000 x g and 4°C for 5 minutes. After resuspension in RNase free water and spectrophotometric quantification the RNA was stored at –80°C.
31 2.3.3 Isolation of Total RNA From Mouse Embryos To obtain total RNA from mouse embryos (embryonic day 6.5 to 8.5) 5 to 10 freshly prepared embryos in the corresponding stage were homogenised in 500 µl of TRIZOL® (Gibco/BRL) using a 20 G syringe in 1.5 ml microcentrifuge tubes. RNA preparation was performed as described.
2.4 Quantification of Nucleic Acids The quantification of aqueous DNA and RNA solutions is based on the absorption maximum of nucleosides at a wavelength of 260 nm. Following the law of Lambert and Beer the concentration was determined by the absorption at 260 nm and an extinction coefficient specific for the different nucleic acids. Absorption of diluted solutions was measured at 230 nm, 260 nm, 280 nm and 320 nm wavelength in an Ultra-Micro Quartz Cuvette (Hellma) with a path length of 1 cm. Concentrations were calculated on the estimation that an absorption of 1.0 at 260 nm wavelength corresponds to 50 µg ssDNA/ml or 40 µg RNA and dsDNA/ml. Relatively high absorptions at 230 nm or 320 nm wavelength indicated contamination with either organic solvents or inorganic salts, respectively. Solutions showing an absorption of more than 1.0 at 260 nm were further diluted to match the linear range of the photometer. Isolation of RNA from TRIZOL® samples in 1.5 ml microcentrifuge tubes often resulted in relatively high absorptions at 230 nm possibly caused by organic solvents trapped during the cleanup-process. The resulting RNA concentrations calculated by the photometer were to high; this could be reduced by incubating the opened tube for 5 to 10 minutes at 55°C before resuspending the RNA in RNase free water. If the ratio of the absorption wavelengths between 230 nm and 260 nm was above 1 a correction was applied: The RNA concentration calculated by the photometer was divided by the (230 nm/260 nm) ratio. Therefore, a solution showing a (230 nm/260 nm) ratio of 2 and an RNA concentration of 1 µg/µl was corrected to a concentration of 0.5 µg/µl. This procedure resulted in comparable amounts of RNA even at high (230 nm/260 nm) ratios. All measurements were performed using a GeneQuant® spectrophotometer (Amersham Pharmacia). An alternative method for the quantification of small amounts of nucleic acids (restriction fragments) is based on the estimation of the fluorescence intensity compared to given standards (quantified DNA markers with defined amounts of DNA in the single bands) in Ethidiumbromide stained gels.
2.5 Agarose Gel Electrophoresis
2.5.1 RNA Electrophoresis For sample preparation equal amounts of total RNA, reaching from 1 to 10 µg were mixed with an adequate volume of RNA sample buffer and RNA loading dye (for a total volume of 20 µl to be loaded into one lane of the gel, the samples were adjusted to the same volume using ddH2O, 3 µl of loading dye were added and the total volume was adjusted to 20 µl using RNA sample buffer). For obtaining 100 ml of a 1% (w/v) gel solution 1g Agarose was heated in 88.2 ml DEPC treated H2O to complete liquidation in a microwave oven. Thereafter, 10 ml 10 x MOPS buffer were added. After the liquid had cooled down to about 50°C 1.8ml of Formaldehyde and 1 - 2 µl Ethidiumbromide solution (10 mg/ml) were added. The solution was poured into an appropriate gel tray and left until complete fixation.
32 Samples were mixed with an appropriate volume of RNA loading dye and sample buffer and loaded on the gel; electrophoresis was performed in 1 x MOPS buffer at 80 - 120 V. RNA was visualised by Ethidiumbromide fluorescence at 312 nm wavelength and documented using an Eagle Eye® II Still Video System (Stratagene).
2.5.2 DNA Electrophoresis Horizontal gel electrophoresis was used for the separation of DNA fragments according to their size. The percentage of Agarose in a gel was chosen from 0.6 to 3.0 (w/v) according to the size of the DNA fragments. The gel volume was fitted to the number and volume of the samples to be analysed. Gels were prepared by heating the Agarose in 1 x TAE buffer (25 - 150 ml) until complete liquidation in a microwave oven was achieved. According to the gel volume, 0.5 - 4 µl Ethidiumbromide (10 mg/ml) were added. The solution was poured into an appropriate gel tray and left until complete fixation. Samples were mixed with an adequate volume of DNA loading dye and loaded on the gel. Appropriate DNA size markers were handled in the same way. Electrophoresis was performed in 1 x TAE buffer at 80 - 120 V. DNA was visualised by Ethidiumbromide fluorescence at 312 nm wavelength and documented using an Eagle Eye® II Still Video System (Stratagene). For cloning purposes DNA was visualised by Ethidiumbromide fluorescence at 365 nm wavelength on a UV-transilluminator (Biotec-Fischer) to avoid DNA damaging.
2.5.3 Cleanup of DNA Fragments From Agarose Gels DNA fragments generated by PCR or restriction digest were purified by separation on agarose gels followed by a cleanup using the QIAquick Gel Extraction Kit (QIAGEN). The desired DNA fragments were cut under UV light above 365 nm to prevent the formation of thymidine dimers. 3 volumes of Buffer QG were added to the gel slices and incubated for 10 minutes at 50°C under shaking until the gel slices were completely dissolved. One volume of Isopropanol was added, mixed and the solution was applied to a QIAquick spin column. After 1 minute at 13000 rpm in a benchtop centrifuge the flow-through was discarded, 750 µl of Buffer PE were added and centrifuged for 1 minute. Following removal of the flow-through the column was re- centrifuged for an additional minute to ensure complete removal of Buffer PE. After placing the column into a new 1.5 ml microcentrifuge tube, the DNA was eluted by adding 30 µl of ddH2O and centrifugation at 13000 rpm for 1 minute.
2.6 Northern Blot
2.6.1 Transfer of RNA to Nylon Membranes RNA samples were separated by Agarose gel electrophoresis as described and blotted onto Hybond™N nylon membranes (Amersham Pharmacia) using a TURBOBLOTTER™ (Schleicher & Schuell). After electrophoresis, the gel was washed four times in ddH2O and maintained in 2 x SSC. 20 GB004 and 8 GB002 papers (Schleicher & Schuell) as well as the Hybond™N nylon membrane were cut to gel size. A buffer wick of the gel length and double width was cut from the GB002 paper. The membrane was pre-soaked in 20 x SSC for 5 minutes. The GB004 papers (Schleicher & Schuell) were placed in the stack tray with 4 GB002 papers on top. One GB002 paper and the membrane were soaked in 20 x SSC transfer buffer and placed on the stack with the membrane on top. The gel was placed on the membrane and covered with 3 GB002 papers 33 (Schleicher & Schuell) soaked in 20 x SSC transfer buffer. The buffer wick was put on top of the gel stack with its ends reaching the buffer tray. The buffer tray was filled with 20 x SSC transfer buffer and the RNA blotted onto the nylon membrane overnight. To avoid desiccation of the gel stack the TURBOBLOTTER™ was covered with saran wrap. After transfer the membrane was washed in 2 x SSC for 5 minutes. Finally the RNA was fixed on the membrane using the „Auto Crosslink“ program of a UV Stratalinker 1800 (Stratagene).
2.6.2 Generation of Radio-Labelled Probes To generate (α-32P)-dCTP labelled gene specific cDNA probes the Prime-It® II Random Primer Labelling Kit (Stratagene) was used. In this work PCR products representing parts of cDNAs (hPim-1, Leukocystatin, h18S rRNA) or total cDNAs (hNF-E2) for the genes of interest were used as probes for hybridisation experiments. These were generated by using gene specific primers (hPim-1 fwd and hPim-1 rev, Leukocystatin fwd and Leukocystatin rev, hNF-E2 fwd and hNF-E2 rev, h18S fwd and h18S rev) what yielded PCR products of 500 – 1300 bp in length which were gel-purified, quantified and labeled as described below. About 20-100 ng of cDNA in a total volume of 24 µl were mixed with 10 µl of random oligonucleotide primers and denaturated for 5 minutes at 95°C. After addition of 10 µl of 5 x dCTP buffer, 5 µl of (α-32P)-dCTP (3000 Ci/mmole) and 1 µl of Exo (-) Klenow polymerase (5 U/µl) the labelling reaction was performed for 30 minutes at 37°C. To remove un-incorporated nucleotides the labelled probes were purified using MicroSpin S-200 HR columns (Amersham Pharmacia). After resuspension of the resin by vortexing and removal of the bottom closure the column was spun down during 1 minute at 735 x g and placed into a new 1.5 ml microcentrifuge tube. The labelled probe was added onto the resin eluted at 735 x g for 2 minutes. Labelling efficiency was checked in a beta counter (Bioscan).
2.6.3 Membrane Hybridisation and Autoradiography The membranes were placed into glass hybridisation bottles (Thermo Hybaid) and pre-hybridised for 1 h at 68°C under rotation in a hybridisation oven (Thermo Hybaid) using ExpressHyb solution (Clontech). Following pre-hybridisation the radio-labelled cDNA probes were denaturated at 95°C for 5 minutes, spun down and added to the pre-hybridisation mixture. After 2-20 h of hybridisation at 68°C (depending on the probe) the membranes were washed twice for 15 minutes each using Wash Solution 1 at room temperature and twice for 15 minutes each at 50°C with Wash Solution 2. The membranes were air-dried, transferred to X-ray film cassettes (Rego), covered with saran wrap and exposed at –80°C. The films were visualised using a Curix 60 film processor (Agfa).
2.7 Reverse Transcription (RT) The reverse transcription of total RNA into complementary DNA (cDNA) was performed using the SUPERSCRIPT™II Reverse Transcriptase (Invitrogen). In general, 1-2 µg of total RNA were added to a master-mix containing 10 µl of 2mM dNTPs (MBI), 2 µl of Random Hexamer Primers (Invitrogen), 1 µl (5 units) of RNase Inhibitor (Roche Diagnostics), 4 µl of 0.1 M DTT, 2 µl (400 units) of Reverse Transcriptase, 8 µl 5 x First Strand Buffer (Invitrogen). RNase free H2O was added to a total volume of 40 µl. The incubation was performed for 1-2 h at 42°C in a thermocycler.
34 2.8 Polymerase Chain Reaction (PCR) The polymerase chain reaction is a versatile tool to amplify specific DNA fragments with the help of sequence specific oligonucleotides („primers“). PCR is a repeated three step reaction. First, double stranded template DNA is denaturated by heating to 94°C. Then, the oligonucleotide primers are annealed to the template DNA at a specific temperature. The last step is the elongation of the primers annealed to their target sequences. The elongation temperature depends on the enzyme used (68°C for Pfu Turbo polymerase, 72°C for Taq polymerase). The Annealing temperature (TAn) was chosen according to the melting temperature of the PCR primers used. In general, 2°C were subtracted from the melting temperature calculated by the Nearest Neighbour (NN) method which resulted in the initial TAn. If this TAn resulted in the generation of unspecific amplification products, the temperature was elevated stepwise. If no amplification products were obtained the temperature was lowered to generate less stringent annealing conditions. The duration of the elongation was chosen between 1 and 3 minutes depending of the size of the expected PCR product. In this work PCR was used for different purposes:
• Preparative PCR: One major application was the generation of gene constructs to be used in different experiments (hybridisation of Northern blots, microinjection to generate transgenic mice, transfection experiments, spotting onto aminosilane coated glass slides for microarray experiments).
• Analytic PCR: Colony PCR was performed to screen bacterial colonies obtained after transformation of competent bacterial cells. To generate different founder lines of transgenic mice genomic DNA from tail-biopsies was isolated and tested for presence of the transgene in PCR experiments.
• Semi-quantitative and quantitative RT-PCR: To quantify gene transcripts semi-quantitative and quantitative RT-PCR were performed.
2.8.1 Standard PCR Protocol This protocol was used to perform preparative and analytic PCR reactions. For preparative purposes the proofreading Pfu Turbo DNA polymerase (Stratagene) was used to avoid point mutations in the resulting PCR products. For analytic PCR reactions Taq DNA Polymerase (QIAGEN) was used. The amount of template DNA or cDNA was depending on the application. When plasmid DNA was used as a template, 50 - 200 ng of DNA were used. For cDNAs resulting from RT reactions different amounts were tested in the PCR reactions (undiluted, 1:10, 1:100, 1:1000; 1 - 5 µl each). This large range in the amount of template used has different reasons: The efficiency of RT reactions strictly depends on the quality of RNA used for the reverse transcription. Another critical parameter is the occurrence of the desired gene specific transcript in the generated cDNA pool. PCR reactions were performed either in 0.2 ml PCR tubes (Eppendorf) or in 96 well amplification plates (Nunc). For a standard PCR reaction the template DNA was added to 2 µl of 10 x reaction buffer (supplied with the enzyme), 2 µl 2 mM dNTPs
35 (MBI), 10 pmol of fwd and rev primers each and 2.5 - 5 units of DNA polymerase to a final volume of 20 µl. General Thermocycler Settings: • Initial denaturation: 94°C for 10 minutes • Denaturation: 94°C for 30 seconds • Annealing: TAn for 1 minute 30 – 40 cycles • Elongation 68°C(Pfu), 72°C (Taq) for 1 to 3 minutes • Final elongation 68°C(Pfu), 72°C (Taq) for 10 minutes
2.8.2 Colony PCR A simple and rapid method to screen bacterial plaques obtained after transformation of competent bacterial cells is colony PCR. Bacterial plaques grown on LB-Amp plates were picked using pipette tips and resuspended in 20 µl of ddH2O. 2 – 5 µl of this suspension were subjected to a standard PCR using specific primer pairs. Colonies containing the desired DNA insert were expanded in liquid cultures and subjected to plasmid preparation.
2.8.3 Semi-Quantitative RT-PCR To quantify specific mRNAs semi-quantitative RT-PCR was used. This technique is less time-consuming than the Northern blot, the classical technique for mRNA quantification, but in most cases also less precise. The Polymerase Chain Reaction results in the exponential amplification of the target DNA sequences. After a certain number of cycles the reaction reaches a plateau where no more amplification is obtained. Due to these reasons, a semi-quantitative analysis must be performed in the linear range of the exponential amplification. The method described here does not allow an absolute quantification as no quantified standard DNA was used which provides information about the exact copy number of the transcript. Therefore only a relative quantification of cDNAs run in parallel can be performed. In order to normalise for different RT efficiencies and different amounts of total RNA used for reverse transcription the reaction described below always has to be performed for both, the gene of interest and a housekeeping gene such as 18S ribosomal RNA. To get information about the relation of gene specific transcripts in different cDNAs a standard PCR reaction was set up and from a certain cycle on small aliquots (2 – 3 µl) were removed from the reaction mixture. The cycle number to start taking the aliquots depends on the occurrence of the specific transcript (for 18S ribosomal RNA the range of exponential amplification lies between about 10 to 16 cycles due to its high copy number, whereas a rare transcript may require 30 to 35 cycles using the same amount of cDNA as template for the reaction). After all aliquots have been taken, the samples were analysed by agarose gel electrophoresis and the amount of the generated PCR products was compared, either by eye or using densitometric assays. The semi-quantitative RT-PCR experiments described in this work were performed in two steps: In a first step, using different numbers of amplification cycles the linear range of exponential amplification was determined for both, the gene of interest an the housekeeping gene. Then, in a second step, a cycle number situated in this range of linear amplification was used for the quantification of the two genes. In most cases, the use of accurately quantified RNA for the RT reaction resulted in almost equal amounts of cDNA as quantified by RT-PCR for the housekeeping genes.
36 Note: For accurate quantification of TRIZOL-prepared RNAs the correction for high absorption values at 230 nm as described previously has to be applied.
2.9 FACS Analysis of Mouse Whole Blood Transgenic mice expressing PRV-1 mRNA were tested for expression of the corresponding protein using flow cytometry. In the first experiments Single Colour Analysis was performed using only one antibody (N1F4) directed against the human PRV-1 protein. Later, Multi Colour Analysis with additional antibodies against cell surface markers was used to determine PRV-1 protein expression on distinct blood cell populations.
2.9.1 Single Colour Analysis (PRV-1) About 700 µl of whole blood from the tail-vein were anticoagulated using EDTA. Three 200 µl aliquots were transferred to 5 ml Polystyrene Round-Bottom Tubes (Becton Dickinson). To the first aliquot 20 µl of N1F4 anti-PRV-1 monoclonal antibody were added and incubated during 20 minutes at room temperature. The cells were washed twice using CellWash (Becton Dickinson) and pelleted during 7 minutes at 1200 rpm. 20 µl of Streptavidin-FITC (Pharmingen) were added to the first and another aliquot, the third aliquot remained untreated as an IgG control. After 20 minutes at room temperature and centrifugation as above, the cells were washed twice with CellWash. 2 ml of FACS Lysing Solution (Becton Dickinson) were added, incubated during 15 minutes in the dark and centrifuged for 7 minutes at 1200 rpm. If the lysis was insufficient, it was repeated. The cells were washed using 7 ml of CellWash, pelleted and resuspended in 500 µl of FACSFlow Buffer (Becton Dickinson). The measurements were performed on a FACSCaliburTM system equipped with a 488 nm laser.
2.9.2 Multi Colour Analysis 700 µl of whole blood were transferred to 5 ml Polystyrene Round-Bottom Tubes (Becton Dickinson) containing 3 ml of Calcium-free PBS and 200 units of heparin. The cells were sedimented during 1 minute at 4500 rpm, 2.5 ml of 140 mM NH4Cl were added to the pellet and vortexed. After a lysing time of 3 minutes the cells were collected by centrifugation (1 minute at 4500 rpm), the supernatant was discarded and the cells were washed twice using a solution containing 2% FCS in PBS. Cell debris was removed using a pipet tip. 100 µl of Mouse BD Fc Block™ (Becton Dickinson) were added and incubated on ice for 15 minutes. After two washing steps with 2 ml of (PBS/2% FCS )the supernatant was discarded and the remaining „pellet“ (volume ~ 100 µl) was splitted in three (2 x 40 µl for staining and 1 x 20 µl as an IgG control). For the staining reactions two different mastermixes were prepared for each sample:
37 Mastermix 1: • 25.000 µl (PBS/2% FCS) • 10.000 µl N1F4 (α-PRV-1, diluted 1:8) • 0.750 µl α-CD3 epsilon • 0.750 µl α-NK1.1 • 0.375 µl α-CD19 Mastermix 2: • 25.000 µl (PBS/2% FCS) • 10.000 µl N1F4 (α-PRV-1, diluted 1:8) • 1.500 µl α-F4/80 • 0.750 µl α-CD11b • 0.750 µl α-GR1
35 µl of the mastermixes were added to one 40 µl aliquot of cells. After incubation at 4°C and a washing step with (PBS/2% FCS) the „pellet“ was incubated for 15 minutes on ice with 1 µl of Streptavidin/PerCP Cy 5.5 (Becton Dickinson). After washing the cells twice with PBS/2% FCS, the fluorescence was measured at the four different wavelengths corresponding of the fluorophores used in the Max Planck Institute, Freiburg, Germany.
2.10 Sequence Analysis of DNA Sequencing of DNA was performed based on the didesoxy-chain-termination method described by Sanger (166). In a modified „single-strand“ PRC-reaction a DNA dependent DNA polymerase is used for the incorporation of desoxynucleoside triphosphates (dNTPs) as used in a normal PCR reaction as well as didesoxynucleoside triphosphates (ddNTPs) into the newly synthesised strand of DNA. The four ddNTPs (ddATP, ddCTP, ddGTP and ddTTP) are marked with four different fluorescence markers. Incorporation of a ddNTP in the newly synthesised strand causes a chain termination, as no further nucleotides can be added to the end of the growing strand due to lack of free 3‘ hydroxyl groups. The ratio between „normal“ dNTPs and ddNTPs statistically causes one chain termination over a range of about 700 base pairs. After this linear amplification the PRC products are run on large denaturing polyacrylamide gels and analysed using 4 colour fluorescence detectors. Due to the order of the fluorescence marked termination products in the gel, the sequence of the corresponding template DNA was determined using the Edit View 1.0.1 software (Perkin Elmer). For sequence analysis the DNAstar software package (DNAstar Inc.) was used. All steps following cleanup of the PCR products were performed by the CORE facility as a support for all research groups. In a total volume of 20 µl 100 to 300 ng of plasmid DNA were mixed with 3.2 pmol of an appropriate template specific oligonucleotide and 4 µl of ABI PRISM® BigDye™ Mix (Applied Biosystems) containing dNTPs, ddNTPs and the thermostable DNA polymerase. Thermocycler Settings: • Initial denaturation: 96°C for 10 minutes • Denaturation: 96°C for 30 seconds • Annealing: 50°C for 15 seconds 25 cycles • Elongation 60°C for 4 minutes
After cycling 80 µl of 75% Isopropanol were added to the reaction mixture and vortexed. The DNA was precipitated during 30 minutes at 13000 rpm in a cooled benchtop centrifuge at 4°C. The pellet was washed once with 75% Isopropanol and 38 spun down during 5 minutes at 13000 rpm and 4°C. After the pellets were air-dried for about 30 minutes in the dark standing upside down the samples were stored at – 20°C till analysis by the CORE facility.
2.11 Ligations
2.11.1 Ligation of Restriction Fragments Into Plasmid Vectors Cloning of restriction fragments into plasmid vectors was performed using T4 DNA Ligase (NEB). This enzyme catalyses the formation of phosphodiester bonds between free 5‘ phosphate groups and 3‘ hydroxyl groups under consumption of ATP.
Dephosphorylation of Vectors Bearing Compatible Ends: Plasmid vectors with compatible ends after the restriction digest (only one restriction enzyme used) were dephosphorylated with Calf Intestine Phosphatase (CIP) to avoid religation of the vector during ligation. 17 µl of the digested plasmid vector (after gel extraction) were mixed with 2 µl of 10 x CIP buffer and 1 µl of enzyme (Promega). Dephosphorylation was performed during one hour at 37°C.
Ligation: To ligate DNA fragments into plasmid vectors, both digested with the same restriction enzymes, an excess of the DNA fragment compared to the vector DNA in a stoichiometric ratio of about 1:3 to 1:5 was used. This turned out to ensure the best ligation efficiencies. A typical ligation reaction is composed of DNA fragments and vector in the described ratio, 2 µl of 10 x ligase buffer containing ATP and 200 units of enzyme in a total volume of 20 µl.
2.11.2 Ligation of PCR Products Using TOPOTM TA Cloning The direct ligation of PCR amplified DNA fragments was performed using the TOPOTM TA Cloning Kit (Invitrogen). The basic principle of this cloning technology is the use of specific vectors bearing covalently bound molecules of topoisomerase I and 3‘ T overhangs. PCR products generated by using Taq polymerase contain 5‘ A overhangs. In the TA cloning reaction the bound topoisomerase catalyses insertion of the PCR product into the vector backbone. PCR products generated using DNA polymerases without terminal transferase activity (Pfu Turbo) can be used for TA cloning after addition of 5‘ A overhangs. This is performed by incubation of these PCR products with 2.5 to 5 units of Taq polymerase, 2 µl of 2 mM dNTPs (MBI) and 2 µl of 10 x reaction buffer in a total volume of 20 µl for 10 minutes at 72°C. The TOPOTM TA Cloning reaction was set up by adding 1 to 4 µl of the 5‘ A containing PCR product to 1 µl of the pCR TOPO II vector and 1 µl of salt solution (both components of the TOPOTM TA Cloning Kit) in a total volume of 6 µl. After mixing the components the ligation was performed for 5 minutes at room temperature. Until transformation the reaction mixture was kept on ice.
2.12 Transformation of Competent E. coli Cells Chemically competent TOP 10 F‘ bacterial cells (Invitrogen) were thawed on ice, 10- 100 ng of plasmid DNA or up to 5 µl of ligation products were added, mixed and incubated on ice for 30 minutes to allow attachment of DNA to the bacterial cell walls. 39 Internalisation of the plasmid DNA was performed during 30 sec at 42°C in a water bath. After 2 minutes on ice, 250 µl of room temperature SOC medium (provided with the competent cells) were added and the mixture was incubated for one hour at 37°C under gentile shaking to allow expression of the antibiotic resistance gene. Two different volumes of each transformation reaction (50 and 200 µl) were spread onto LB plates containing 100 µg/ml Ampicillin. After incubation at 37°C overnight bacterial colonies were analysed using colony PCR.
2.13 Preparation of Plasmid DNA To obtain large amounts of plasmid DNA for preparative purposes, chemically competent bacterial cells were transformed using the plasmid of interest and clones bearing the desired constructs were expanded in liquid cultures containing LB medium and 100 µg/ml Ampicillin. The volume of the bacterial cultures depends on the type of plasmid preparation performed (200 to 500 ml for maxi and 50 to 100 ml for midi-preps). All plasmid preparations during this work were performed using the QIAGEN Plasmid Midi and Maxi kits (QIAGEN). Overnight cultures of transformed E. coli in LB/Amp. were pelleted for 15 minutes at 6000 x g and 4°C. The bacterial pellets were resuspended in 4 ml (Midi prep) or 10 ml (Maxi prep) of chilled buffer P1. After addition of 4 (10) ml of Buffer P2 and 5 minutes at room temperature 4 (10) ml of chilled Buffer P3 were added and incubated for 15 (20) minutes on ice. Following centrifugation at 20000 x g for 30 minutes at 4°C the supernatant was removed and re-centrifuged for 15 minute. During these steps QIAGEN midi/maxi prep columns were equilibrated by applying 4 (10) ml of Buffer QBT. following centrifugation the plasmid-containing supernatant was added to the columns. After the supernatant has passed the columns these were washed twice using 10 (30) ml of Buffer QC. Elution of the plasmid DNA was performed by applying 5 (15) ml of Buffer QF (pre-heated to 65°C) onto the columns. After addition of 3.5 (10.5) ml of Isopropanol the DNA was precipitated during 30 minutes at 15000 x g and 4°C. The DNA pellet was washed once with 2 (5) ml of 70% EtOH and centrifuged for 10 minutes at 15000 x g and 4°C. After air-drying the pellet for about 10 minutes the plasmid DNA was resuspended in an appropriate volume of H2O. After quantification the plasmid DNA was stored at –20°C.
2.14 TaqMan® Quantitative RT-PCR A relatively new method for the quantification of mRNA is the TaqMan® technique (Applied Biosystems) as shown in Figure 2.1. The basic difference compared to a standard PCR reaction is the use of one additional gene specific oligonucleotide (TaqMan® probe) beside the classical PCR primers. This oligonucleotide carries two modifications: At the 5‘-end a reporter fluorophore (FAM for PRV-1; JOE for GAPDH) is attached and at the 3‘-end a so-called quencher is situated. The co-localisation of quencher and fluorophore on this oligonucleotide prevents the fluorophore from emitting light upon excitation. When amplification of the target cDNA sequence occurs, the 5‘ exonuclease activity of the DNA polymerase causes degradation of the TaqMan® probe and liberation of the reporter from the quencher. This results in emission of fluorescence light from the fluorophore which can be measured by spectrophotometry. As the fluorescence intensity is in direct proportion to the amount of mRNA present in the reaction mixture, the TaqMan® assay is a sensitive method to quantify gene specific transcripts. Compared to the semi-quantitative RT-PCR it also allows high- 40 throughput screening of many samples as no gel-electrophoresis is required for detection.
Figure 2.1: Basic principle of TaqMan® Real-Time Quantitative RT-PCR experiments. In the polymerisation step specific PCR-primers amplify the target cDNA. If the reaction reaches the region where the gene-specific probe is situated, the reporter fluorophore is cleaved from the probe by the 5’- exonuclease activity of the DNA polymerase. In the same step the probe is displaced by the growing cDNA strand. This causes an increase in the reporter fluorescence which is measured by a fluorescence detector. The fluorescence intensity obtained in this step is proportional to the amount of a specific mRNA present in the reaction mixture and allows an absolute quantification.
The TaqMan® assays performed in this work were so-called singleplex experiments. In contrast to duplex measurements, where two different genes of interest can be measured in the same reaction tube, only one TaqMan® probe and primers for amplification of a single gene are present in the reaction mixture. To normalise for the total amount of cDNA, each sample has also to be measured using primers specific for a housekeeping gene (here: GAPDH or 18S ribosomal RNA). The comparability of results obtained for different RNA preparation protocols seemed to be a critical step. For example, if from the same tissue samples RNA was prepared at the same time using the standard TRIZOL® protocol and GTC, the TRIZOL® RNAs yielded higher amounts of PRV-1 mRNA than the RNAs prepared by the GTC method. As the primer pairs used for the quantification of PRV-1 were not exon/intron spanning, we suggest that higher levels of DNA contamination were present in the TRIZOL® samples thus leading to higher amounts of the PRV-1 amplification product. Due to this one has to stick to one RNA preparation method to get comparable results from different measurements. For the quantification of PRV-1 mRNA the TRIZOL® method was used throughout all experiments. There are different evaluation strategies for TaqMan® data described in the literature. In this work a method based on the relation between the CT values for the target gene and a housekeeping gene (GAPDH for the quantification of PRV-1 and 18S
41 ribosomal RNA for the genes analysed using the Assays-on-DemandTM system) was used. In brief, a scatter plot showing the cycle numbers on the x-axis and the fluorescence intensities on the y-axis yields an exponential curve. The cycle number at which the fluorescence reaches a distinct threshold (individually defined for each gene to be ® measured in the TaqMan assay) is called the Cycle of Threshold (CT). To normalise for different amounts of cDNA present in samples, a ratio CT(PRV-1)/CT(GAPDH) was calculated. A sample in which more PRV-1 mRNA is present results in a higher ratio than a sample with less PRV-1 mRNA. Using this strategy results obtained in different runs can be directly compared.
2.14.1 Standard PRV-1 and GAPDH TaqMan® Assay The PRV-1 TaqMan® assays were performed as so-called one-step reactions. In contrast to two-step experiments as performed using the Assays-on-DemandTM system, in a one step-experiment the RT reaction is performed in the same tube as the quantitative PCR, whereas a separate RT reaction is performed in the two-step reaction. All RNA samples to be analysed in the TaqMan® assay for expression of the human PRV-1 gene have been prepared using the TRIZOL® method. Normally, 5 to 50 ng of RNA per sample were assayed in triplicate for PRV-1 and GAPDH. This, in most cases yielded results which were in a suitable range for quantification as judged by the CT values for GAPDH. Otherwise undiluted RNA was used for analysis. In a standard TaqMan® experiment 14 samples were measured in triplicate; one positive control, one negative control and a blank sample in duplicate for PRV-1 and GAPDH each. For TaqMan® experiments MicroAmp® 96-well reaction plates (Applied Biosystems) were used. GAPDH primers and probe were taken from the TaqMan® GAPDH Control Reagents (Applied Biosystems)
42 PRV-1 mastermix: • 7.75 µl DEPC-H2O • 1.25 µl 40 x Multiscribe and RNase Inhibitor Mix * • 25.00 µl 2 x MasterMix without UNG * • 5.00 µl PRV-1 TaqMan® fwd Primer (9 µM) • 5.00 µl PRV-1 TaqMan® rev Primer (0.5 µM) • 5.00 µl PRV-1 Probe (2.5 µM) GAPDH mastermix: • 19.75 µl DEPC-H2O • 1.25 µl 40 x Multiscribe and RNase Inhibitor Mix * • 25.00 µl 2 x MasterMix without UNG * • 1.00 µl GAPDH TaqMan® fwd Primer (9 µM) • 1.00 µl GAPDH TaqMan® rev Primer (0.5 µM) • 1.00 µl GAPDH Probe (2.5 µM)
* Components of the TaqMan® One Step RT-PCR Master Mix Reagent Kit (# 4309169, Applied Biosystems)
In a 1.5 ml microcentrifuge tube 3 µl of RNA solution were added to 150 µl of the mastermixes for PRV-1 and GAPDH. 50 µl of the mixture were added to three wells on the amplification plate. For the positive and negative controls, 2 µl of RNA were added to 100 µl of mastermix and 50 µl of the mixture were distributed on 2 wells of the plate. In the blank sample RNA was replaced by 2 µl of RNase free water. After removal of air- bubbles by short centrifugation the PCR reaction was run in a TaqMan® ABI PRISM ® 7700 or 7000 Sequence Detection System (Applied Biosystems) with the following cycling parameters:
• Reverse transcription 48°C for 30 minutes • Initial denaturation: 95°C for 10 minutes • Denaturation: 95°C for 15 seconds • Annealing and Elongation: 60°C for 1 minute 40 cycles
For measurements using the ABI PRISM ® 7700 the threshold for FAM (PRV-1) was set to 0.2 and for JOE (GAPDH) to 0.04. Samples measured on the ABI PRISM ® 7000 were analysed with a FAM threshold set to 0.4 and the threshold for JOE set to 0.15. For each sample an average cycle of threshold (CT) value for each triplicate measurement of either PRV-1 or the housekeeping gene GAPDH was calculated. Subsequently the CT(PRV-1)/CT(GAPDH) ratio was determined. Based on our previous analysis of a cohort of 80 healthy controls and 71 PV patients, a CT(PRV- 1)/CT(GAPDH) ratio < 1.17 was used to diagnose PRV-1 overexpression (103).
2.14.2 Assays-on-DemandTM For verification of some differentially expressed genes in the microarray experiments performed in this study Assays-on-DemandTM products (Applied Biosystems) were used. These assays consist of a 20 x Target Assay Mix consisting of sequence-specific primers and the FAM-labelled TaqMan® probe. As mentioned above Reverse Transcription and PCR-Quantification were carried out in two different steps. RT was performed using the TaqMan® Reverse Transcription Kit (Applied Biosystems).
43 Reverse Transcription: • 5.00 µl 10xTaqMan® RT buffer * • 11.00 µl MgCl2 (25 mM) * • 10.00 µl dNTPs * • 2.50 µl Random-Primers * • 1.00 µl RNAse inhibitor * • 1.25 µl Multiscribe RT-Mix * • 5.00 µl RNA (10 ng/µl) • 14.25 µl H2O
* Components of the TaqMan® One Step Reverse Transcription Kit ( Applied Biosystems) Thermocycler Settings: • 25°C for 10 minutes • 48°C for 30 minutes • 95°C for 5 minutes
Quantitative PCR: • 25.00 µl 2xMasterMix without UNG • 2.50 µl 20 x Assay-on-Demand Mix (or 20 x 18S-Mix) • 17.50 µl ddH2O
For triplicate experiments 135 µl of this mix were combined with 15 µl of an appropriate dilution of the cDNAs to be analysed. For the experiments performed here (PLAUR, PIM-1, THBD, CEACAM-1 and NF-E2) the cDNAs obtained in the RT were diluted by a factor of four (4.5 µl of the cDNAs were added to 13.5 µl of RNAse free water). 15 µl of the resulting solution were added to 135 µl of the mix and three 50 µl aliquots were measured by quantitative PCR. Thermocycler Settings: After removal of air-bubbles by short centrifugation the PCR reaction was run in a TaqMan® ABI PRISM ® 7000 Sequence Detection System (Applied Biosystems) with the following cycling parameters:
• Initial denaturation: 95°C for 10 minutes • Denaturation: 95°C for 15 seconds • Annealing and Elongation: 60°C for 1 minute 40 cycles
2.15 Isolation of Granulocytes From Blood Samples To isolate granulocytes from peripheral blood samples, the anticoagulated blood (not more than 20 h after taking) was mixed with an equal volume of 3% of Dextran in 0.9% NaCl. After 20 minutes at room temperature, the upper phase containing the white blood cells was removed, transferred to 50 ml Falcon Tubes and the cells pelleted for 8 minutes at 1600 rpm in a Megafuge (Heraeus). The cell pellet was completely resuspended in 35 ml of PBS and carefully overlaid to 15 ml of Ficoll- PaqueTMPlus (Amersham Pharmacia) in a new 50 ml tube. After 35 minutes of centrifugation at 1800 rpm with the centrifuge’s brake turned off the small interphase containing mononuclear cells was carefully removed and saved for different experiments (including EEC Assays). The remaining supernatant was discarded. Next, contaminating erythrocytes were hypotonically lysed by resuspending the pellet
44 in 20 ml of 0.2% NaCl for 30 s. Then 20 ml of 1.6% NaCl were added to stop the lysis. After 10 minutes at 1600 rpm the supernatant was discarded. If necessary, hypotonic lysis was repeated until the granulocyte pellet was free of contaminating erythrocytes. Depending of the experiments to be performed, the granulocytes were either lysed in TRIZOL® or in Guanidinium thiocyanate solution (add 72µl of β-mercaptoethanol per 10 ml of GTC solution prior to lysis). The lysed granulocytes were stored at –80°C.
2.16 Restriction Digest of DNA The restriction digest of DNA using sequence specific type II restriction enzymes is a standard laboratory technique in a widespread area of applications. In my work, restriction digest was used to determine the orientation of plasmid- inserts, to check for the correct insert size or to allow cloning of PCR fragments with distinct restriction sites into plasmids which were digested with the same enzyme. The enzymes used in this work were purchased from NEB. Incubation conditions (temperature, buffers, addition of BSA) were performed as recommended in the data sheets for the concerning enzymes. The incubation time was between 30 minutes and several hours in a total volume of 20 – 40 µl. Double digests were performed as recommended in the NEB guidelines. Double digests with restriction enzymes requiring different incubation temperatures were performed for 1 h at the lower temperature, followed by 1 h at the higher temperature. As a guideline 1 to 5 units of restriction enzyme were used per µg of DNA used in the reaction.
2.16.1 Analytical Digestions To check the size or orientation of plasmid-inserts 1 – 3 µg of plasmid-DNA were added to 3 – 15 units of enzyme in the recommended buffer. Analysis was performed by agarose gel electrophoresis.
2.16.2 Preparative Digestions To prepare plasmid inserts or vectors for cloning, 3 – 10 µg of plasmid DNA were subjected to a restriction digest in the appropriate buffers using 3 – 30 units of enzyme. After gel electrophoresis the desired DNA fragments were extracted using the Qiagen Gel Extraction Kit.
2.16.3 Digestion of PCR Products PCR products can be generated using oligonucleotide primers which encode recognition sites for specific restriction enzymes. After gel electrophoresis the desired DNA fragments were extracted, eluted in a small volume of H2O and digested with the appropriate enzyme. The digested fragments were again subjected to gel electrophoresis and extracted.
45 2.17 cDNA Microarrays
2.17.1 Production of cDNA Microarrays Production of the cDNA microarrays used for this work was performed in collaboration with the genomics CORE facility (Dept. of Nephrology, University Hospital Freiburg). The cDNA microarrays were produced and processed essentially according to the Stanford protocol described by Eisen and Brown (56). Approximately 7000 annotated genes from the RZPD were obtained as bacterial stocks. Plasmids were purified using the Qiagen 96-well Turbo Kit (QIAGEN, Hilden, Germany), and inserts were purified by polymerase chain reaction (PCR) using vector primers flanking the individual inserts (5'-CTG CAA GGC GAT TAA GTT GGG TAA C-3' and 5'-GTG AGC GGA TAA CAA TTT CAC ACA GGA AAC AGC-3'). PCR products were purified by Ethanol precipitation and resuspended in H2O. Aliquots were transferred into 384- well plates, dried, and resuspended in 3 x standard saline citrate or 10% DMSO to a final concentration of approximately 40 ng/µl. Printing was performed on aminosilane- coated slides (CMT-GAPII Slides, Corning), using an arrayer that was assembled according to specifications by the Stanford group with software provided by J. de Risi (http://cmgm.stanford.edu/pbrown/mguide/index.html)
2.17.2 Synthesis of Cy3- and Cy5-dUTP Labelled cDNAs For a two-colour microarray experiment two differently labelled cDNA populations are required. In this work all experiments were performed in duplicate using the dye-swap technology. Further information about the experimental setup is given in the results section. A schematical overview about the labelling process is given in Figure 2.2. Except for the cDNA cleanup after the RT reaction the protocol presented here was performed throughout all experiments without major changes. For the first cDNA microarrays in this work (until April 2002), an old chip layout was used which required 24 µg of patient and control RNA each. This was due to the large spacing of the spotted cDNAs on the glass slides which could later be diminished, so that only 12 µg of each RNA species were required per slide. For the generation of Cy3- and Cy5-dUTP labelled cDNAs the use of CsCl-purified total RNA turned out to be the method of choice as the use of TRIZOL® prepared RNA resulted in insufficient incorporation of one of the two labeled nucleotides. RNA prepared using TRIZOL® could only be used for microarray experiments after cleanup using RNeasy columns (QIAGEN) which resulted in the loss of large amounts of RNA. 2.17.3 Annealing of the Oligo dT Primers 2 x 12 µg (2 x 24 µg for the old chip layout) of patient and control RNA per sample were mixed with 1 µl of Oligo dT (4 µg/µl) to a total volume of 10 µl in 0.2 ml PCR tubes. The annealing reaction was performed during 10 min at 65°C in a thermocycler and kept on ice until reverse transcription.
46 2.17.4 Incorporation of Cy3- and Cy5-dUTP During Reverse Transcription A mastermix for the reverse transcription was prepared for each slide: • 10.56 µl 5x1st strand buffer • 3.96 µl 0.1 M DTT • 0.79 µl unlabelled dNTP Mix 25 mM dATP, dCTP, dGTP; 15 mM dTTP • 3.17 µl H2O • 2.64 µl Superscript II RT (200 u/µl) • 1.32 µl RNase Inhibitor
For each dye-swap experiment 10.2 µl of the mastermix were added to 1.8 µl aliquots of Cy3- and Cy5-dUTP, each. 10 µl of the Cy3- and of the Cy5-dUTP containing mixtures were mixed with an aliquot of the annealing reaction in 0.2 ml PCR tubes. After 2 h at 50°C in the thermocycler 15 µl of 0.1 N NaOH were added, RNA was degraded during 10 min at 70°C. After 10 min the reaction was stopped by adding 15 µl of 0.1 N HCl.
2.17.5 cDNA Cleanup Components of the MinElute PCR Purification Kit (QIAGEN) were used for the cleanup of the Cy3- and Cy5-labelled cDNAs. Two differently labelled aliquots of patient and control RNA were combined and added to 600 µl of buffer PB on a MinElute column. After 1 minute at 11000 rpm and 4°C in a benchtop centrifuge the flow-through was discarded, 750 µl of 35% Guanidinium-HCl (w/v) were added, the column was eluted for 1 minute at 11000 rpm. After washing with 750 µl of buffer PE the flow-through was discarded and the column was re-centrifuged for an additional minute at 11000 rpm to completely remove the washing buffer. A mixture of 8 µl of buffer EB, 2 µl of Poly A-RNA (10 µg/µl) and 2 µl of tRNA (10 µg/µl) were directly added to the membrane, incubated 1 minute at room temperature and centrifuged for 1 minute at 11000 rpm. 3.4 µl of 20 x SSC, 3 µl of 2% SDS and 2 µl of Cot-1 DNA were added to the eluate. After 2 minutes at 95°C and 20 minutes at room temperature the samples were centrifuged for 5 minutes at 11000 rpm. 18 µl of the supernatant were carefully transferred to a new tube and mixed by pipetting up and down. Until hybridisation the samples were stored in the dark to avoid photo- bleaching.
2.17.6 Hybridisation Cover slips (22 x 22 mm) were rinsed with water washed in 96% EtOH for up to 1 h and air-dried. The printed microarray slides were pre-hybridised during 20 minutes at 65°C in the following solution in a plastic slide container in a water bath: • 7 ml 20xSSC • 33 ml ddH2O • 400 µl 10% SDS • 400 mg BSA
The slides were rinsed with water to remove traces of SDS and dried in a slide-holder during 5 minutes at 500 rpm with the printed surface of the slides aligned to the outer side of the rotor (arrangement of the slides in another orientation causes smears and renders the feature analysis more difficult). The printed slides were placed into the hybridisation chambers, 3 rolls of Kimwipe® papers, about 1 cm in length were placed onto both sides of the slides (as far from the printed area as possible).
47 The labelled cDNAs (18 µl) were carefully pipetted onto the printed area and immediately covered using the dried cover slips. The chambers were screwed up and incubated overnight for 16 to 20 h at 62 to 65°C in a water bath.
2.17.7 Washing Steps After hybridisation all slides were transferred to a slide-holder in a solution containing 1 x SSC and 0.03% SDS. By taking the slides out of the washing solution for a few seconds the cover slips were removed and during two minutes the slides were carefully washed by moving the holder horizontally once a minute. Next, the slides were transferred to the second washing solution (0.2 x SSC) for 5 minutes. After a final washing step for 5 minutes in 0.05 x SSC the slides were dried in a centrifuge as described previously and stored in the dark till scanning.
2.17.8 Data Analysis Signal intensities were measured by an Axon 4000A scanner using GenePix 3.0 software (Axon Instruments Inc., Union City, CA). Image and data files, array layout, as well as all relevant information according to the MIAME guidelines (Minimum Information About a microarray Experiment (20) were transferred into the GeneTrafficDuo database (Microarray Data Management and Analysis Software, Iobion Informatics, LLC, USA). The experimental design was based on colour-reversal experiments for every patient sample versus the healthy control pool to correct for dye-specific effects. To exclude artefacts near background range, all spots were eliminated when sample intensity or reference intensity was less than 50 or less the local background. Local background was subtracted from spot intensities. Normalisation was performed with Lowess (Locally weighted scatter plot smoother) sub-grid normalisation method. Sub-grid normalisation calculates the normalisation factor for each of the 32 subgrids independently and therefore is, compared to global normalisation, relatively insensitive to local variations on the array (207). The log to the base of two (logRatio) of the measured Cy3 and Cy5 values obtained from the image analysis software was computed. All genes with 80% present flagged values in each group were subjected to statistical analysis. For analysis of the genes discriminating between PV and SE a two-sample t-test was used for a statistical analysis of differentially expressed genes after application of the above mentioned normalisation and filtering criteria. To control for multiple testing the obtained p-values were adjusted by calculating the false discovery rate (FDR) using the method by Benjamini and Hochberg (14). Differential expression was defined by p-values below 0.01 (FDR). Agglomerative hierarchical clustering introduced by Kaufman et al. (93) was performed using the R statistical software package (www.r- project.org). To identify differentially expressed genes between PV patients and healthy controls 2437 genes were subjected to statistical analysis which fulfilled the normalisation criteria. Differential expression was defined by at least 1.5-fold change versus control at a false discovery rate below 0.01. 644 genes show a significant difference between PV patients and healthy controls.
48
Figure 2.2: Generation of Cy3- and Cy-5 dUTP labelled cDNA probes for the microarray experiments.
49 3. Materials
3.1 Oligonucleotides h18S fwd AGG ACC GCG GTT CTA TTT TGT TG h18S rev CGG GCC GGG TGA GGT TT desmocollin-2 fwd AAG GAT TGG CGG TGG AGG AGT A desmocollin-2 rev CAC CAA GAC GGG GCT GAG TAA AA glycogenin fwd CTC GGA AGA ACTG GAA GGA ACG glycogenin rev AAG GGA GTG ACT GAT TTT GAA CCA hGAPDH fwd ACC ACA GTC CAT GCC ATC AC hGAPDH rev TCC ACC ACC CTG TTG CTG TA hNF-E2 fwd GCC CAG TAG GAT GTC CCC GTG TC hNF-E2 rev TGT TGC CAT TGT CAT CCT CTT CTG hPim-1 fwd GTC GCC GGG GCC CAG CAA ATA G hPim-1 Not I rev GCA TCA GCG CGG CCG CCT ATT TGC TGG GCC CCG G hPim-1 P1 sequencing TCG GCT CGG TCT ACT CAG GCA TCC hPim-1 P2 sequencing CGA GCG GCC CGA CAG TTT hPim-1 P3 sequencing GGG TCC CAT CGA AGT CCG TGT AGA hPim-1 P4 sequencing TCT CAG GGC CAA GCA CCA TCT AAT hPim-1 P5 sequencing CCA TTA GGC AGC TCT CCC CAG TCG hPim-1 P6 sequencing CAC TTC CAT GGG CAC TCG hPim-1 rev CAC AGC CGG AGT CCC CAC AGA AGG hPim-1 Sfi fwd GCA GGC CCG TAC GGC CAT GCT CTT GTC CAA AAT C hPRV-1 Not I fwd GCA TCA GCG CGG CCG CAT GAG CGC GGT ATT ACT G hPRV-1 Not I rev GCA TCA GCG CGG CCG CTT AGC AGG AAG GGC AAA C hPRV-1 P12 TAG TGC CAG CAG CAG CAG CG hPRV-1 Sfi I fwd GCA GGC CCG TAC GGC CAT GAG CGC GGT ATT ACT G hPRV-1 TaqMan® fwd Primer GCT GTC CAC CAA AAT GAG CAT hPRV-1 TaqMan® Probe FAM-TTC TTG TTG AAC CAC ACC AGA CAA ATC GG-TAMRA hPRV-1 TaqMan® rev Primer TTC TCA CGC GCA GAG AAG ATC leukocystatin fwd GGC CCT TCC CCA GAT ACT TGT TCC leukocystatin rev CAC TTC ACC CGC TCA CTC GTC AGA M13 fwd GAT AAA CGA CGG CCA GT M13 rev GGA AAA CAG CTA TGA CCA TG mPim-1 Not I rev GCA TCA GCG CGG CCG CCT ACT TGC TGG ATC CCG G mPim-1 P1 sequencing AGC TGG CGC CGG GCA AAG AGA AG mPim-1 P2 sequencing CTG GCC CGA GGA TTC TTC T mPim-1 P3 sequencing CTT CTT TAG GCC TTG GTA G mPim-1 P4 sequencing GAT GGT AGC GAT GGT GCC GTC C mPim-1 P5 sequencing CGA GAG GCC CGA TAG TTT C mPim-1 Sfi I fwd GCA GGC CCG TAC GGC CAT GCT CCT GTC CAA GAT C mPRV-1 Not I rev GCA TCA GCG CGG CTC AGC AGA GAG GAC AGA T mPRV-1 P 1 TCT GCA CTT GAG CTG GAC G mPRV-1 P 15 GGA CTG CAG CGC TCG CT mPRV-1 P 18 TGT CAT TAG AAA GGC AGA GT mPRV-1 P39 GGA GGG CTG GGT CTG GGT GGC CAA GAG mPRV-1 P41 CAT GAA TTC TAT ACC AGT GCT GAC CCT TCT GGG GG Vav vector fwd CAA ATC AAA GAA CTG CTC CTC A Vav vector rev CCA AAC TCA ATG TAT CTT ATC
50 3.2 General Equipment
1 ml Serological Pipettes, (# 357520) Becton Dickinson, Heidelberg, Germany 1.5 ml PCR tube, (# 0030 102.002) Eppendorf, Hamburg, Germany 15 ml Falcon® Tubes, (# 352095) Becton Dickinson, Heidelberg, Germany 5 ml Polystyrene Round-Bottom Tube, (# 352054) Becton Dickinson, Heidelberg, Germany 50 ml Falcon® Tubes, (# 352070) Becton Dickinson, Heidelberg, Germany 96 Well Amplification Plate, (# 259676) Nunc, Karlsruhe, Germany ABI PRISM® 377 DNA Sequencer Applied Biosystems, Darmstadt, Germany ABI PRISM® 7000 Sequence Detection System Applied Biosystems, Darmstadt, Germany ABI PRISM® 7700 Sequence Detection System Applied Biosystems, Darmstadt, Germany Avanti J-25 Centrifuge Beckman, Munich, Germany Biofuge fresco (benchtop microcentrifuge) Heraeus, Fellbach, Germany Blotting Paper GB002, (# 10426694) Schleicher & Schuell, Dassel, Germany Blotting Paper GB004, (# 10426994) Schleicher & Schuell, Dassel, Germany Cellstar® 145/20 mm TC-Plate, (# 664 160) Greiner, Frickenhausen, Germany Cellstar® 250 ml TC Flasks, (# 658 175) Greiner, Frickenhausen, Germany Cellstar® 50 ml TC Flasks, (# 690 175) Greiner, Frickenhausen, Germany Cellstar® 650 ml TC Flasks, (# 660 175) Greiner, Frickenhausen, Germany Cellstar® 94/16 mm TC-Plate, (# 628 160) Greiner, Frickenhausen, Germany Cellstar® TC-Plate 24 Well, (# 662 160) Greiner, Frickenhausen, Germany Cellstar® TC-Plate 6 Well, (# 657 160) Greiner, Frickenhausen, Germany Centricon® YM-30 Centrifugal Filter Devices, (# 4208) Millipore, Eschborn, Germany Corex Glass Tubes for Centrifuges (15 ml and 30 ml) NeoLab, Heidelberg, Germany Costar® 10 ml Stripette® Corning Inc., Corning, NY, USA Costar® 2 ml Stripette® Corning Inc., Corning, NY, USA Costar® 25 ml Stripette® Corning Inc., Corning, NY, USA Costar® 5 ml Stripette® Corning Inc., Corning, NY, USA Costar® 50 ml Stripette® Corning Inc., Corning, NY, USA Cover slips (22 x 22 mm) Langenbrinck, Emmendingen, Germany CryoTube™ Vials, (# 375353) Nunc, Karlsruhe, Germany Curix 60 Film Processor Agfa, Cologne, Germany DNAstar Software DNAstar Inc., Konstanz, Germany Eagle Eye® II Still Video System, (# 400276) Stratagene, La Jolla, CA, USA FACSCalibur™ System, (# 343020) Becton Dickinson, Heidelberg, Germany Function line Incubators for TC Heraeus, Fellbach, Germany GAPS II coated microarray slides, (# 40005) Corning Inc., Corning, NY, USA GeneAmp® PCR System 2400 Applied Biosystems, Darmstadt, Germany GeneAmp® PCR System 9700 Applied Biosystems, Darmstadt, Germany GeneQuant Spectrophotometer, (# 80210598) Amersham Pharmacia, Freiburg, Germany Glass Hybridisation Bottles Thermo Hybaid, Ulm, Germany Hera Safe Class II Laminar Flow Cabinet Heraeus, Fellbach, Germany Hybond™N Nylon Membranes, (# RPN303N) Amersham Pharmacia, Freiburg, Germany Hybridisation chambers (for microarrays) Die-Tech Company, Ca, USA Immobilon P Blotting Membrane, (# IPVH 00010) Millipore, Eschborn, Germany Kodak X-Omat, AR, (# 853 2665) Kodak, Stuttgart, Germany Megafuge 1.0, (# 75003490) Heraeus, Fellbach, Germany MicroAmp® 96-well Reaction Plate, (# N801-0560) Applied Biosystems, Darmstadt, Germany MicroAmp® Optical Caps, (# N801-0935) Applied Biosystems, Darmstadt, Germany Microcentrifuge Tube, 1.5 ml, (# 616 201) Greiner, Frickenhausen, Germany Microcon® YM-30 Centrifugal Filter Devices, (# 42410 Millipore, Eschborn, Germany Microplate Reader SPECTRAmax® PLUS Molecular Devices, Ismaning, Germany MicroSpin G25 Columns, (# 27-5325-01) Amersham Pharmacia, Freiburg, Germany MicroSpin S-200 HR Columns, (# 27-5120-01) Amersham Pharmacia, Freiburg, Germany Mighty-Small™-Gel Electrophoresis Chamber, (# SE250) Hoefer, Freiburg, Germany Mighty-Small™-Gel Preparation Unit Hoefer, Freiburg, Germany Neubauer Chamber Superior Marienfeld, Lauda-Königshofen, Germany NucTrap® Probe Purification Columns Stratagene, La Jolla, CA, USA 51 Optima LE-80 K Ultracentrifuge Beckman, Munich, Germany Parafilm, (# 2569.1) Roth, Karlsruhe, Germany Polyallomer tubes, (# 331372) Beckman, Munich, Germany Quick-Count™ 2000 Beta Counter Bioscan, Washington D.C., USA Shake´n´Stack Hybridisation Oven Thermo Hybaid, Ulm, Germany Surgical instruments for In-Situ Hybridisation Fine Science Tools GmbH, Heidelberg, Germany TURBOBLOTTER™ Schleicher & Schuell, Dassel, Germany Ultra-Micro Quarz Cuvette Hellma, Müllheim, Germany UV Stratalinker 1800 Stratagene, La Jolla, CA, USA UV-Transilluminator Biotec-Fischer, Reiskirchen, Germany Western Blotter SD-1 GR ltf-Labortechnik, Wasserburg, Germany X-ray Film Cassettes Rego, Augsburg, Germany
3.3 Chemicals
β-Mercaptoethanol, (# 63689) Fluka, Buchs, Switzerland µN,N,N´,N´-Tetramethylethylenediamine (TEMED), (# T 8133) Sigma, Steinheim, Germany 3-(N-morpholino) propanesulfonic acid (MOPS), (# 6979.3) Roth, Karlsruhe, Germany 6-amino-n-hexanoic acid, (# A 7824) Sigma, Steinheim, Germany Acetic acid, glacial, (# 100058) Merck, Darmstadt, Germany Agarose, (# 35-1020) Peqlab, Erlangen, Germany Ammonium peroxydisulfate (APS), (# 101201) Merck, Darmstadt, Germany Ampicillin, (# A 2804) Sigma, Steinheim, Germany Bromphenol blue, (# A 512.1) Roth, Karlsruhe, Germany Butanol, (# 7171.1) Roth, Karlsruhe, Germany
Chloroform (CHCl3), (# 102445) Merck, Darmstadt, Germany Cy3-dUTP, (# PA53022) Amersham Pharmacia, Freiburg, Germany Cy5-dUTP, (# PA55022) Amersham Pharmacia, Freiburg, Germany Dextran, (# US14495) Amersham Pharmacia, Freiburg, Germany Diethyl pyrocarbonate (RNase free), (# D 5758) Sigma, Steinheim, Germany Dimethyl sulfoxide (DMSO), (# 109678) Merck, Darmstadt, Germany
Disodium hydrogen phosphate (Na2HPO4), (# 106573) Merck, Darmstadt, Germany Dithiothreitol (DTT), (# 6908.2) Roth, Karlsruhe, Germany Ethanol (EtOH), (# 100974) Merck, Darmstadt, Germany Ethidiumbromide, (# 7870.2) Roth, Karlsruhe, Germany Ethylenediaminetetraacetic acid (EDTA), (# 8043.2) Roth, Karlsruhe, Germany Formaldehyde, (# F 8775) Sigma, Steinheim, Germany Formamide, (# F 7508) Sigma, Steinheim, Germany Gel 30 (Acrylamide/N,N´-bisacrylamide 29:1), (# 3029.1) Roth, Karlsruhe, Germany Glucose, (# G 8270) Sigma, Steinheim, Germany Glutardialdehyde; (# 820603) Merck, Darmstadt, Germany Glycerol, (# G 5516) Sigma, Steinheim, Germany Glycine, (# 3790.2) Roth, Karlsruhe, Germany Goat serum, (# 16210-064) Invitrogen, Karlsruhe, Germany Guanidine isothiocyanate, (# 0017.2) Roth, Karlsruhe, Germany Heparin (10000 IE/ml) B. Braun, Melsungen, Germany Human Cot-1 DNA, (# 15279-011) Invitrogen, Karlsruhe, Germany Hydrochloric acid (HCl), (# 159415) Merck, Darmstadt, Germany Isopropanol, (# 109634) Merck, Darmstadt, Germany Kanamycin, (# K 0879) Sigma, Steinheim, Germany Low Melt Agarose, (# 6351.2) Roth, Karlsruhe, Germany
Magnesium chloride (MgCl2), (# 105934) Merck, Darmstadt, Germany Maleic acid, (# M 0375) Sigma, Steinheim, Germany Methanol (MeOH), (# 106009) Merck, Darmstadt, Germany
Monopotassium dihydrogen phosphate (KH2PO4), (# 105105) Merck, Darmstadt, Germany
Monosodium dihydrogen phosphate (NaH2PO4), (# 106370) Merck, Darmstadt, Germany N,N,N´,N´-tetraacetic acid (EGTA), (# 3054.3) Roth, Karlsruhe, Germany N-Laurylsarcosine, (# L5125) Sigma, Steinheim, Germany
Oligo (dT)12-18, (# 27-7610-01) Amersham Pharmacia, Freiburg, Germany 52 Paraformaldehyde (PFA), (# 76240) Fluka, Buchs, Switzerland Phenylmethylsulfonyl fluoride (PMSF), (# P 7626) Sigma, Steinheim, Germany Poly(A) potassium salt, (# P9403) Sigma, Steinheim, Germany Potassium chloride (KCl), (# 6781.1) Roth, Karlsruhe, Germany Sodium acetate, (# 6779.1) Roth, Karlsruhe, Germany Sodium chloride (NaCl), (# 3957.1) Roth, Karlsruhe, Germany Sodium citrate, (# 106448) Merck, Darmstadt, Germany Sodium dodecyl sulfate (SDS), (# 4360.1) Roth, Karlsruhe, Germany Sodium hydroxide (NaOH), (# 106495) Merck, Darmstadt, Germany Tris(hydroxymethyl)aminomethane (Tris), (# 4855.3) Roth, Karlsruhe, Germany Tween® 20, (# 9127.1) Roth, Karlsruhe, Germany Urea, (# 2317.1) Roth, Karlsruhe, Germany Yeast tRNA (Lyophilised), (# 15401-011) Invitrogen, Karlsruhe, Germany
3.4 Radio-Chemicals
(α-32P)-dCTP (3000 Ci/mmol), (# PB10205) Amersham Pharmacia, Freiburg, Germany (gamma-32P-ATP) (3000 Ci/mmol), (# PB10168) Amersham Pharmacia, Freiburg, Germany
3.5 Enzymes
Blocking Reagent (# 1096176) Roche Diagnostics, Mannheim, Germany BM Purple® , (# 1442074) Roche Diagnostics, Mannheim, Germany Calf Intestine Alkaline Phosphatase (C.I.P.), (# M2825) Promega, Mannheim, Germany DNA Polymerase Pfu Turbo™, (# 600250) Stratagene, La Jolla, CA, USA Proteinase K, (# P6556) Sigma, Steinheim, Germany Restriction Enzyme BamHI, (# R0136S) NEB, Frankfurt am Main, Germany Restriction Enzyme EcoRI, (# R0101S) NEB, Frankfurt am Main, Germany Restriction Enzyme HindIII, (# R0104S) NEB, Frankfurt am Main, Germany Restriction Enzyme NotI, (# R0189S) NEB, Frankfurt am Main, Germany Restriction Enzyme XbaI, (# R0145S) NEB, Frankfurt am Main, Germany Restriction Enzyme XhoI, (# R0146S) NEB, Frankfurt am Main, Germany RNase A, (# 109 142) Roche Diagnostics, Mannheim, Germany SUPERSCRIPT™II Reverse Transcriptase, (# 18064-022) Invitrogen, Karlsruhe, Germany T3 RNA Polymerase, (# 1031163) Roche Diagnostics, Mannheim, Germany T4 DNA Ligase, (# M0202S) NEB, Frankfurt am Main, Germany T4 Polynucleotide Kinase, (# M0201S) NEB, Frankfurt am Main, Germany T7 RNA Polymerase, (# 1031171) Roche Diagnostics, Mannheim, Germany Taq DNA Polymerase, (# 1005476) QIAGEN, Hilden, Germany
53 3.6 Kits
ABI PRISM® BigDye™ Sequencing Ready Reaction Kit Applied Biosystems, Darmstadt, Germany DIG RNA Labelling Kit (SP6/T7), (# 1175025) Roche Diagnostics, Mannheim, Germany ECL™ Western Blotting Analysis Systems, (# RPN 2108) Amersham Pharmacia, Freiburg, Germany Human CEACAM-1 Assay-on-demand Hs00236077 m1 Applied Biosystems, Darmstadt, Germany Human NF-E2 Assay-on-demand Hs00232351 m1 Applied Biosystems, Darmstadt, Germany Human Pim-1 Assay-on-demand Hs00171473 m1 Applied Biosystems, Darmstadt, Germany Human PLAUR Assay-on-demand Hs00182181 m1 Applied Biosystems, Darmstadt, Germany Human THBD Assay on demand Hs00264920 s1 Applied Biosystems, Darmstadt, Germany MinElute PCR Purification Kit, (# 280004) QIAGEN, Hilden, Germany Mouse Embryo RNA (gestation day 9.5 to 16.5) Quantum Appligene,Heidelberg,Germany One Shot® E.coli TOP10F´ Competent Cells, (# C3030-03) Invitrogen, Karlsruhe, Germany Prime-It® II Random Primer Labelling Kit, (#300385) Stratagene, La Jolla, CA, USA QIAGEN Plasmid Maxi Kit, (# 12163) QIAGEN, Hilden, Germany QIAGEN Plasmid Midi Kit, (# 12143) QIAGEN, Hilden, Germany QIAprep 96 Turbo Miniprep Kit, (# 27191) QIAGEN, Hilden, Germany QIAquick Gel Extraction Kit, (#28704) QIAGEN, Hilden, Germany RNeasy Mini Kit, (# 74104) QIAGEN, Hilden, Germany TaqMan® 18S rRNA (20 x ), (# 4310893E) Applied Biosystems, Darmstadt, Germany TaqMan® 2xUniversal PCR Master Mix, no UNG, (# 4324018) Applied Biosystems, Darmstadt, Germany TaqMan® GAPDH Control Reagents, (# 402869) Applied Biosystems, Darmstadt, Germany TaqMan® One Step RT-PCR Master Mix Reagent Kit, (# Applied Biosystems, Darmstadt, Germany 4309169) TaqMan® Reverse Transcription Kit, (# N 808-0234) Applied Biosystems, Darmstadt, Germany TOPO™ TA Cloning Kit, (# K4550-01) Invitrogen, Karlsruhe, Germany
3.7 Buffers and Solutions
3.7.1 General Buffers and Solutions
0.5 M EDTA, pH 8.0 185.6 g EDTA; ddH2O ad 1 l 80 g NaCl; 2 g KCl; 2 g KH PO ; 14.42 g Na HPO · 2H O; 10 x PBS 2 4 2 4 2 ddH2O ad 1 l; pH 7.3 10 x TBS 100 mM Tris, pH8.0; 1.5 M NaCl 20 x SSC 3 M NaCl; 0.3 M Sodium citrate; pH 7.0 1% (w/v) Peptone; 0.5% (w/v) Yeast Extract; 1% (w/v) NaCl; pH Luria Bertani (LB)-Medium 7.0 PBST 1 x TBS; 0.5 % Tween 20
3.7.2 Buffers for RNA Preparation
200 mM MOPS; 50 mM Sodium acetate; 10 x MOPS 10 mM EDTA; in RNase free H2O, pH 7.0 23.6 g Guanidine isothiocyanate; 250 mg N-Laurylsarcosine; 1.25 ml 1 M Na citrate, GTC solution pH 8.2; RNase free H20 ad 50 ml; pH 7.0; RNA Loading Dye 50% Glycerol; 1mM EDTA; 0.4% Bromphenol blue; 0.4% Xylene cyanole FF
RNA Running buffer 100 ml 10x MOPS; 180 ml Formaldehyde; RNase free H2O ad 1 l
RNA Sample buffer 20 µl 10x MOPS; 35 µl Formaldehyde; 100 µl Formamide; RNase free H2O ad 1 ml
3.7.3 Washing Solutions for Northern Blots
Wash Solution 1 2 x SSC; 0.05% SDS Wash Solution 2 0.1 x SSC; 0.1% SDS
54 3.7.4 Buffers for DNA Gel Electrophoresis
50 TAE 242 g Tris; 57.1 ml Acetic acid, glacial; 100 ml 0.5 M EDTA, pH 8.0; ddH2O ad 1 l 6 x DNA Loading Dye 0.09% Bromphenol blue; 0.09% Xylene cyanole FF; 60% Glycerol; 60 mM EDTA
3.7.5 Buffers and Solutions for Western Blotting
4 x Separating Gel buffer 1.5 M Tris/HCl; 0.4% SDS; pH 8.8 4 x Stacking Gel buffer 0.5 M Tris/HCl; 0.4% SDS; pH 6.8 10 mM Monosodiumphosphate, pH 7.2; 1% SDS; 6 M Urea; 1% beta- 5 x SDS Loading Dye Mercaptoethanol; 0.5% Bromphenol blue 5 x SDS Running buffer 125 mM Tris; 1 M Glycine; 0.5% SDS Anode buffer I 300 mM Tris; 10% MeOH; pH 10.4 Anode buffer II 25 mM Tris; 10% MeOH; pH 10.4 25 mM Tris; 40 mM 6-amino-n-hexanoic acid; Cathode buffer 10% MeOH; pH 9.4
TBST 100 ml 10 x TBS; 1 ml Tween20; ddH2O ad 1 l
3.7.6 Buffers, Antibodies and Solutions for In-Situ Hybridisations
10% Goat Serum in PBST (1 h inactivated at 56°C), 1% Antibody blocking buffer Blocking Reagent Anti-Dig.-AP Fab Fragments (# 1093274) Roche Diagnostics, Mannheim, Germany 10 ml 1 M Tris/HCl pH 9.5; 2 ml 5 M NaCl; 5 ml 1M MgCl ; AP (Alkaline Phosphatase) buffer 2 ddH2O ad 100 ml Fixation buffer 4% (v/v) PFA in PBS Glycine solution 2 mg/ml Glycine (w/v) in PBST Maleic acid buffer 100 mM Maleic acid; 150 mM NaCl, pH 7.5 25% MeOH in PBS (v/v 50% MeOH in PBS (v/v) MeOH series for dehydration/rehydration 75% MeOH in PBS (v/v) 100% MeOH 5 ml deionised formamide; 2.5 ml 20 x SSC; 5 µl heparin; 10 µl ® Prehybridisation buffer Tween 20; 2.05 ml ddH20; pH adjusted to 6.0 with 1 M Citric acid Proteinase K solution 4.5 µg/ml Proteinase K in PBST Refixation buffer 4% PFA, 0.2% Glutardialdehyde in PBST
3.7.7 DNA Preparation from Tail-biopsies
Proteinase K 10 mg/ml Proteinase K in ddH2O, store at -20°C 5 ml 5 M NaCl; 12.5 ml 1 M Tris/HCl, pH 8.0; 50 ml 0.5 M Tail buffer EDTA, pH 8.0; 25 ml 10% SDS; ddH2O ad 250 ml
3.8 FACS-Antibodies
Anti-mouse CD11b, FITC conjugated, (# 557396) Pharmingen, Heidelberg, Germany Anti-mouse CD19, PE conjugated, (# 557399) Pharmingen, Heidelberg, Germany Anti-mouse CD3ε, APC conjugated, (# 553066) Pharmingen, Heidelberg, Germany Anti-mouse F4/80, PE conjugated, (# MCA 497) Serotec, Düsseldorf, Germany Anti-mouse GR1ε, APC conjugated, (# 553129) Pharmingen, Heidelberg, Germany Anti-mouse NK 1.1, FITC conjugated, (# 553164) Pharmingen, Heidelberg, Germany N1F4 (monoclonal mouse anti-PRV-1), biotinylated Genovac, Freiburg, Germany Streptavidin, FITC conj., (# 554060) Pharmingen, Heidelberg, Germany Streptavidin, PerCP Cy 5.5 conj., (# 551419) Pharmingen, Heidelberg, Germany
55 3.9 Other Biochemicals
Bovine Serum Albumin (BSA), (# A 9647) Sigma, Steinheim, Germany Broad Range Biotinylated Protein Marker, (# 7726) NEB, Frankfurt am Main, Germany CellWASH, (# 349524) Becton Dickinson, Heidelberg, Germany Deoxynucleoside Triphosphate Set, PCR Grade, (# 1969064) Roche Diagnostics, Mannheim, Germany DNA Marker, Lamda DNA-Hind III Dig. , (# SM 0101) MBI Fermentas, St. Leon-Rot, Germany dNTP Mix (2 mM), (# R 0241) MBI Fermentas, St. Leon-Rot, Germany ExpressHyb Solution, (# 8015-3) Clontech, Heidelberg, Germany FACSFlow Buffer, (# 342003) Becton Dickinson, Heidelberg, Germany FACSLysing Solution, (# 349202) Becton Dickinson, Heidelberg, Germany FACSRinse Solution, (# 340346) Becton Dickinson, Heidelberg, Germany FACSSafe Solution, (# 340345) Becton Dickinson, Heidelberg, Germany Ficoll-Paque™Plus, (# 17-1441-03) Amersham Pharmacia, Freiburg, Germany Gene Ruler 100 bp DNA Ladder Plus, (# SM 2100) MBI Fermentas, St. Leon-Rot, Germany Mouse BD Fc Block™ (# 553141) Becton Dickinson, Heidelberg, Germany Random Hexamer Primers (# 48190-011) Invitrogen, Karlsruhe, Germany RNase Inhibitor, (# 799 017) Roche Diagnostics, Mannheim, Germany TRIZOL®, (# 15596-018) Invitrogen, Karlsruhe, Germany Yeast Extract, (# 30393-029) Fluka, Buchs, Switzerland
56 4. Results
4.1 In-situ Hybridisation of Mouse Embryos To date very little is known about possible functions of the human PRV-1 protein. The murine homologue of the PRV-1 gene is expressed in different tissues of adult mice, including bone marrow, spleen and lung. In RT-PCR experiments using RNA isolated from mouse embryos in different stages the expression of the murine PRV-1 gene during embryonal development was determined. In these experiments expression of the mPRV-1 mRNA could be detected from embryonic day 6.5 on (Figure 4.1).
Figure 4.1: RT-PCR experiments showing the expression of mPRV-1 mRNA expression during different developmental stages. Total RNA from mouse embryos was isolated, subjected to reverse transcription and analysed using the specific primers mPRV-1 (P39 and P41 obtained from S. Klippel) for the murine PRV-1 gene. As a positive control a plasmid vector containing the full length mPRV-1 coding sequence was used. The expected PCR product has a size of 2516 bp.
As a next step, whole mount in-situ hybridisation experiments were initiated to get further information about localisation of the gene specific transcripts in the developing embryo. Several in-situ hybridisation experiments with mouse embryos isolated from different stages (embryonic day 6.5 to 14.5) were performed. The assay performed here is based on the generation of digoxygenin (DIG) labelled RNA probes from a plasmid vector containing the gene specific cDNA sequence and binding sites for SP6/T3 and T7 RNA polymerase surrounding the insert. By performing an in-vitro transcription using either SP6, T3 or T7 RNA polymerase and DIG-labelled nucleotides sense- and antisense probes for the concerning genes can be generated (Figure 4.2 A). The sense probes serve as a negative control whereas 57 the antisense probes hybridise to the target mRNA. After incubation the bound DIG- labelled antisense probe was visualised using an anti-DIG antibody coupled to alkaline phosphatase, which in turn causes a colour reaction of the BM Purple AP substrate (Roche Diagnostics). As a positive control, a plasmid construct for the murine FHL-2 gene (Four and a half LIM domains protein 2), obtained from J. Müller (laboratory of Prof. R. Schüle) was used. The mRNA for FHL-2 is highly expressed in the heart during embryogenesis (34). Incubation of mouse embryos in different stages with FHL-2 specific antisense DIG probes yielded good staining results in the cardiac region (Figure 4.2). Two different constructs were used for the generation of PRV-1 specific probes, 600 and 1000 bp in length. The 600 bp probe consisted of a BamH1 fragment of the murine cDNA clone in the pcDNA 3.1 Zeo- plasmid from S. Klippel. The larger construct was obtained by PCR using gene specific primers (mPRV-1 P1 and mPRV-1 P15). Nevertheless the use of these probes in the in-situ hybridisation experiments did not result in distinct staining patterns (Figure 4.2 B).
Figure 4.2: Vectors used for the generation of probes for in-situ hybridisation experiments are shown in part (A) of the figure. In the pBluescript vector T7 and T3 RNA-polymerase binding sites were used for the generation of sense and antisense probes in contrast to T7 and SP6 binding sites in the pCR TOPO II vector. (B): Staining patterns representing in-situ hybridisation experiments for PRV-1 (left) and FHL-2 (right). In contrast to FHL-2 where a distinct staining in the cardiac region could be obtained, incubation with mPRV-1 specific probes did not yield reproducible results.
4.2 Generation of PRV-1 Transgenic Mice The function of the PRV-1 protein, the human as well as the murine homologue, remains unclear. Analysis of protein expression on different blood cell populations has revealed expression of the PRV-1 protein on granulocytes, monocytes and B- cells of PV patients and healthy controls.
58 To elucidate the physiological function, transgenic mice overexpressing the PRV-1 protein were generated. In light of RNA and protein expression patterns an expression of the transgene throughout the haematopoietic compartment was a prerequisite for this project. After screening the literature for promoter constructs providing overexpression of target genes in the haematopoietic system of transgenic animals, two expression systems turned out to be well-suited for our purposes. Both of them were used for the generation of transgenic mice in parallel to ensure transgene expression in at least one transgenic strain.
4.2.1 PRV-1/Vav Construct The human vav oncogene is widely expressed in the haematopoietic compartment (92). All mature haematopoietic cell lines irrespective of their developmental stage express RNA and protein, whereas outside this compartment only embryonic stem cells, developing teeth, testicular germ cells and the extra-embryonic trophoblast display vav expression (25,96,153,214). Analysis of the murine promoter for the vav gene has revealed different regions which are required for pan-haematopoietic expression (150). Later studies in which vav-driven expression of cell surface reporter genes in transgenic mice was assayed have demonstrated transgene expression in all nucleated haematopoietic cells but not in non-haematopoietic tissues (150). The ability to drive multi-lineage expression makes the vav-promoter construct a valuable tool for the functional analysis of genes in the whole haematopoietic compartment. Beside this, overexpression of the anti-apoptotic protein Bcl-2 in transgenic mice under the control of the vav-promoter has revealed a possible role of Bcl-2 in enhancing clonogenic survival of haematopoietic progenitor cells (151). For the construction of transgenic mice overexpressing human or murine PRV-1 in haematopoietic cells the vector construct was kindly provided by J. M. Adams (Walter and Eliza Hall Institute, Melbourne, Australia). As shown in Figure 4.3 the construct consists of four DNAse I hypersensitive regions within the vav gene. Two of them (HS2 and HS1) are originally located in the 5‘ untranslated region (5‘- UTR) of the vav gene, whereas two are derived from intron 1 (HS4 and HS5). The targeting construct also contains the SV40 small intron and a SV40 Poly A-site.
59
Figure 4.3: In A the murine vav locus is shown. Black boxes () show the exons 1 to 13. Grey boxes () designate introns and 5‘ UTR. The DNAse I hypersensitive sites involved into transcriptional regulation are shown by triangles (▲). (B) Enlarged view of the constructs used for the pan- haematopoietic expression of a Bcl-2 transgene in mice (152). SV40 intron and Poly A sequence are designated by blue boxes (). (C) Construct used for the generation of mice expressing PRV-1. The restriction sites used for cloning of the construct and linearisation prior to microinjection are marked by arrows. The vector backbone (pIC-19H) is symbolised by small black lines. In (D) the PCR primer- pairs used for directional cloning of the murine and human PRV-1 cds into the expression vector are shown.
For directional cloning of murine and human PRV-1 cDNA into the expression vector, the following strategy was used: Murine and human PRV-1 cDNA were amplified with PCR primer-pairs inducing a 5‘-Sfi I site and a 3‘-Not I site (hPRV-1 Sfi I fwd; hPRV-1 Not I rev; mPRV-1 Sfi I fwd; mPRV-1 Not I rev) followed by a 18 nt overlap to the 5‘ and 3‘ end of the coding sequence (cds). As a template 10 ng of plasmid DNA containing the full-length hPRV-1 in a pOS36 vector (P16 from S. Klippel) and mPRV-1 cDNA in a pCR-II vector (pCRII-G-13 from S. Klippel, coding for the short splice variant of PRV-1) were used. The obtained PCR products, 1346 (hPRV-1) and 2486 bp (mPRV-1) in length were purified from 1% agarose gels by Gene Clean (GC) using the QIAquick Gel
Extraction Kit (QIAGEN), eluted in 20 µl of ddH2O, digested for one hour each at 37°C and 50°C with a mixture consisting of NEB buffer 2, Not I, Sfi I and 100 µg/ml of BSA. 10 µg of the expression vector were linearised in the same manner. After gel-
60 purification of the restriction products and elution in ddH2O, ligations and transformation of competent bacterial cells were performed as described in the materials and methods section. Bacterial clones bearing the desired insert in a colony PCR reaction (Figure 4.4) were used for plasmid preparation using the QIAGEN Plasmid Midi Kit.
Figure 4.4: Screening of bacterial clones for the 1346 bp hPRV-1 cds in the Vav expression vector by colony PCR using the PCR primer pair hPRV-1 Sfi I fwd and hPRV-1 Not I rev. 10 out of 12 bacterial clones bear the desired insert. Bacterial clone No. 1 was used for microinjection after sequence verification and linearisation of the expression vector in a Hind III digest.
The plasmid clones were sequence verified to exclude mutational effects. Prior to microinjection the vector backbone was removed in a Hind III digest. The linearised plasmids were quantified on an agarose gel with a DNA ladder containing bands with a known amount of DNA (Figure 4.5). In addition to the hPRV-1/Vav and mPRV- 1/Vav constructs described here, expression vectors for the human and murine Pim-1 proto-oncogene have also been generated. Pim-1 has turned out as a significantly overexpressed gene in the cDNA microarray experiments discussed later with respect to patients with polycythaemia vera. These constructs can be used for the generation of transgenic mice which overexpress the Pim-1 proto-oncogene in the haematopoietic system what might allow further insight into a possible role of Pim-1 in the pathomechanism underlying PV. Generation of these constructs was performed using the PCR-primer pairs hPim-1 Sfi I fwd and hPim-1 Not I rev for the human construct and mPim-1 Sfi I fwd and mPim-1 Not I rev for the murine construct. For sequence verification the primers mPim-1 P1 to P5 and hPim-1 P1 to P6 were used.
61
Figure 4.5: Hind III digest of the hPRV-1/Vav expression vector for removal of the pIC-19H vector backbone and linearisation of the expression construct. The left part of the figure shows a 8.5 kb fragment containing the Vav expression construct including the hPRV-1 cds and a 2.7 kb fragment representing the pIC-19H vector backbone. The 8.5 kb fragment was cut from the gel, purified and 2 µl were quantified using a marker with known amounts of DNA.
4.2.2 PRV-1/H2K Construct The second construct used for the generation of transgenic mice was used only for the human PRV-1 gene. The promoter sequences are derived from the murine H2K gene which is a member of the MHC family (Major Histocompatibility Complex). The expression vector was kindly provided by J. Domen (Stanford University School of Medicine, Stanford, California). First used in 1998 the construct provides transgene expression in haematopoietic stem cells, all other haematolymphoid cells as well as in all cell types expressing MHC class I (52). Taken together, the expression pattern expected with the H2K construct is more widespread as compared to the previously described Vav construct. As shown in Figure 4.6 the construct consists of regulatory sequences from the 5‘ UTR of the H2K gene, followed by the transgene, intron sequences of H2K and the Murine Moloney Virus Long Terminal Repeat with Poly A Sequence.
62
Figure 4.6: In (A) the construct for generation of transgenic mice is shown. Black boxes () show the hPRV-1 cds, grey boxes () designate 5‘ UTR and introns from the H2K gene. A blue box () shows the regulatory sequences, including Poly A Signal from the Murine Moloney Virus Long Terminal Repeat (MMV-LTR). In (B) the PCR-primer-pairs used for cloning of the human PRV-1 cds into the expression vector are shown. The vector backbone (pSP65) is symbolised by small black lines.
Amplification of the hPRV-1 cds was performed as described above for the PRV- 1/Vav construct with the exception that a forward primer was used which also introduces a Not I site instead of Sfi I in the Vav constructs (hPRV-1 Not I fwd). After Not I digest of the PCR product and the expression vector, the vector was dephosphorylated to prevent self-ligation. Bacterial clones obtained after ligation and transformation of competent bacterial cells were checked for insert size and orientation by PCR (Figure 4.7). The latter was performed by using a primer located in the hPRV-1 cds (hPRV-1 P12) in combination with the M13 rev primer located in the vector backbone. Correct orientation of the vector insert yields a 1926 bp PCR product.
Figure 4.7: Screening of bacterial clones for the 1926 bp PCR product in the H2K expression vector by colony PCR. The bacterial clones 11, 16 and 18 bear the desired insert which indicates the presence of the hPRV-1/H2K construct in the correct orientation. The clones 11 and 16 were used for microinjection after sequence verification and linearisation of the expression vector in a Hind III digest. 63 As described for the hPRV-1/Vav construct, the plasmid clones were sequence verified and linearised in a Hind III digest prior to microinjection (Figure 4.8).
Figure 4.8: Hind III digest of the hPRV-1/H2K expression vector for removal of the vector backbone and linearisation of the expression construct. The left part of the figure shows a 4.8 kb fragment containing the H2K expression construct including the hPRV-1 cds and a 2.9 kb fragment representing the pSP65 vector backbone. The 4.8 kb fragment was cut from the gel, purified and 2 µl were quantified using a marker with known amounts of DNA.
4.2.3 Generation of Transgenic Founder Lines The transgenic mice generated during this project are based on a FVB background. Embryos derived from the FVB strain have pronuclei which can be easily manipulated for transgenic microinjection projects. This, together with high reproductive performance, makes the FVB strain ideally suited for transgenic studies. Microinjection of the constructs into the paternal pronucleus of isolated embryos was performed in the Roland Schüle transgenic animal core facility by Dr. Thomas Günther and Sandra Vomstein (R. Schüle, Dept. of Obstetrics and Gynaecology, University Hospital, Freiburg). FVB foster mothers were provided by the animal facility of the Center for Clinical Research of the University of Freiburg. After weaning of the newborn pups tail-biopsies were analysed for transgene expression as described. To exclude so-called founder effects two different founder animals for each construct were generated. The founder effect describes phenotypical manifestations in transgenic animals which are due to random effects (e.g. disruption of genetic loci by the inserted DNA sequences) rather than to the intrinsic function of the transferred genes. These effects can antagonise or mask the transgene’s effect. For the hPRV-1/Vav construct two founder animals were obtained and backcrossed with non-transgenic littermates. As shown in Figure 4.9 for the Vav construct transgenic offspring for the hPRV-1 constructs was confirmed by PCR analysis of DNA prepared from tail-biopsies using the same primer-pairs as described for the
64 generation of the Vav (hPRV-1 Sfi I fwd and hPRV-1 Not I rev) and H2K (hPRV-1 Not I fwd and hPRV-1 Not I rev) expression vectors, both yielding a 1346 bp PCR product. Concerning the transgenic animals which express the murine PRV-1 gene under control of the Vav promoter, transgenic offspring was confirmed using PCR- primer pairs located in the backbone of the Vav expression vector (Vav vector fwd and Vav vector rev) what gives a 550 bp PCR product. Animals expressing the transgenes were further backcrossed to obtain homozygous animals. Expression of the hPRV-1 transgene has been demonstrated on RNA level for both hPRV-1/Vav founder animals (# 145 and # 253) as well as for the hPRV-1/H2K founder animals. Pedigrees for the different founder lines are displayed in Figure 4.10.
Figure 4.9: Confirmation of transgenic offspring by PCR performed with DNA obtained from tail biopsies and by RT-PCR performed with whole blood RNA from transgenic animals of the hPRV-1/Vav founder line. The PCR reactions were performed using hPRV-1 Sfi I fwd and hPRV-1 Not I rev primer pair what results in a 1346 bp product for transgenic animals.
65 Figure 4.10: Founder lines # 253 and # 145 for the hPRV-1/Vav and # 434 for the mPRV-1/Vav transgenic lines. Asterisks indicate animals which were transferred to the LMU, Munich for further phenotypical analysis. Mice which were tested for expression of the hPRV-1 protein in FACS analysis are indicated by blue (single colour FACS analysis, section 4.2.4) and green boxes (multi colour FACS analysis, section 4.2.5).
66 4.2.4 Single Colour FACS Analysis of Mouse Whole Blood Expression of the hPRV-1 transgene on the protein level was tested by FACS analysis of mouse whole blood. For analysis of the PRV-1 protein the monoclonal, biotinylated antibody N1F4, generated by Genovac (Freiburg, Germany) was used. Detection of the immunocomplexes was performed using Streptavidin-FITC (Pharmingen). The first approach to evaluate protein expression in the transgenic mice was a single colour analysis of mouse peripheral blood obtained by bleeding of the mice at the tail-vein. One transgenic animal from each of the two hPRV-1/Vav founder lines was tested for expression of the PRV-1 protein. From the founder line # 145 animal # 27 of the F3 generation was tested; for the founder line # 253 animal # 18 was taken from F2. As a control two wild-type littermates were analysed. Both transgenic mice displayed expression of the PRV-1 protein as displayed in Figure 4.11. Nevertheless there are differences with respect to the cells expressing the PRV-1 protein. The animal derived from the founder line # 145 displayed two populations of cells staining positive for PRV-1 (one lower- and one higher-expressing) whereas in the animal derived from founder line # 253 only one positive population could be observed which seems to be smaller in size as compared to the other founder line. The relatively low amount of cells staining positive for PRV-1 in the transgenic mice with respect to the total cell number could be due to a very mild lysis of the red blood cell population using FACSLysing Solution (Becton Dickinson). This might cause the high unspecific background. To gain further information about the cell populations which express the transgene a multi-colour analysis of mouse whole blood was performed using labelled antibodies directed against different blood cell populations.
67
Figure 4.11: (A) Histogram representing FACS analysis of two wild-type (green and black) and two transgenic mice (hPRV-1/Vav). Animal # 27 (red) derived from the F3 generation of founder line # 145; # 18 (blue) derived from the F2 generation of founder line # 253. (B) Dot plot representing cells staining positive for PRV-1 in a transgenic animal (# 18).
4.2.5 Multi Colour FACS Analysis The data obtained by single colour analysis indicate that in both founder lines the PRV-1 protein is expressed in whole blood. Exact determination of the blood cell populations expressing the transgene requires the use of cell-type specific antibodies in combination with the antibody directed against the human PRV-1 protein. In four transgenic mice (two derived from founder line # 253, one from # 145, both bearing the PRV-1/Vav construct and one animal bearing the PRV-1/H2K construct) and one wild-type animal the expression of PRV-1 was tested in combination with the cell-type specific markers CD3 epsilon, CD11b, F4/80, NK1.1 and GR1 (common epitope of LY-6C and LY-6G).
Table 4.1: Antibodies used for two-colour FACS analysis of mouse whole blood
Antigen Cell Type Fluorophore Clone Manufacturer Cat. No.
granulocytes (eosinophiles and GR1 Allophycocyanin (APC) RBC-8C5 BD Pharmingen 553129 neutrophiles),monocytes
F4/80 mature macrophages/monocytes Phycoerythrin (PE) C1:A3-1 Serotec MCA497 Fluorescein- NK1.1 Natural killer cells and NK-T cells PK 136 BD Pharmingen 553164 Isothiocyanate (FITC)
thymocytes, mature T-lymphocytes, CD3ε Allophycocyanin (APC) 145-2C11 BD Pharmingen 553066 NK-T-cells
granulocytes, macrophages, myeloid- Fluorescein- CD11b (Mac-1) derived dendritic cells, natural killer M1/70 BD Pharmingen 557396 Isothiocyanate (FITC) cells, microglia, B-1 cells 68 As displayed in Figure 4.12, the use of NH4Cl for lysis of the red blood cells resulted in a much higher purity of the leukocytes and a higher percentage of PRV-1 expressing cells as compared to the relatively inefficient lysis with FACSLysing Solution (Becton Dickinson) in Figure 4.11.
Figure 4.12: (A) Histogram representing FACS analysis of one wild-type (green) and three transgenic mice (hPRV-1/Vav). Animals # 14 (red) and # 18 (blue) derived from the F2 generation of founder line # 253; animal # 19 (black) derived from the F3 generation of founder line # 145. (B) Dot plot representing cells staining positive for PRV-1 in a transgenic animal (# 14).
Figure 4.13: (A) Histogram representing FACS analysis of GR1 positive cells in one wild-type (green) and three transgenic mice (hPRV-1/Vav). Animals # 14 (red) and # 18 (blue) derived from the F2 generation of founder line # 253; animal # 19 (black) derived from the F3 generation of founder line # 145. (B) Dot plot representing cells staining positive for GR1 (WT animal).
69
Figure 4.14: (A) Histogram representing FACS analysis of NK1.1 positive cells in one wild-type (green) and three transgenic mice (hPRV-1/Vav). Animals # 14 (red) and # 18 (blue) derived from the F2 generation of founder line # 253; animal # 19 (black) derived from the F3 generation of founder line # 145. (B) Dot plot representing cells staining positive for NK1.1 (WT animal).
Figure 4.15: (A) and (B) Histogram representing FACS analysis of CD3 positive cell populations in one wild-type (green) and three transgenic mice (hPRV-1/Vav). Animals # 14 (red) and # 18 (blue) derived from the F2 generation of founder line # 253; animal # 19 (black) derived from the F3 generation of founder line # 145. (C) Dot plot representing cell populations staining positive for CD3 (WT animal).
The data obtained in the FACS analysis demonstrate expression of the human PRV- 1 protein in different cell populations of the transgenic animals bearing the hPRV- 1/Vav construct, including granulocytes and monocytes (Figure 4.13), natural killer cells, NK-T cells (Figure 4.14). In thymocytes and mature T-lymphocytes the CD3high population in the upper gate seems to represent natural killer T-Cells (NK-T- Cells) and activated T-cells (Figure 4.15). These cells as well as the CD3low cells in the left gate show expression of the PRV-1 protein in the transgenic animals. Analysis for the expression of the PRV-1 protein on CD11b (Mac-1) and F4/80 positive cells did not show relevant differences between WT and transgenic animals 70 (Figures 4.16 and 4.17). With respect to CD11b, the very small number of CD11b positive cells in this FACS analysis may mask differences in expression of the PRV-1 protein.
Figure 4.16: (A) Histogram representing FACS analysis of CD11b positive cells in one wild-type (green) and three transgenic mice (hPRV-1/Vav). Animals # 14 (red) and # 18 (blue) derived from the F2 generation of founder line # 253; animal # 19 (black) derived from the F3 generation of founder line # 145. (B) Dot plot representing cells staining positive for CD11b (WT animal).
Figure 4.17: (A) Histogram representing FACS analysis of F4/80 positive cells in one wild-type (green) and three transgenic mice (hPRV-1/Vav). Animals # 14 (red) and # 18 (blue) derived from the F2 generation of founder line # 253; animal # 19 (black) derived from the F3 generation of founder line # 145. (B) Dot plot representing cells staining positive for F4/80 (WT animal).
One animal derived from the hPRV-1/H2K line was also included into this FACS analysis. Despite expression of the hPRV-1 mRNA in whole blood RNA this animal did not express the human PRV-1 protein (data not shown). 71 Based on these results (two different founder lines for the hPRV-1/VAV construct, both expressing the transgene on RNA and protein level), further phenotypical analysis was performed with offspring of these two founder lines.
4.2.6 Analysis of Haematological Parameters In order to get further insight into possible phenotypical changes in the hPRV-1 transgenic mice a collaboration with the Faculty of Veterinary Medicine of the Ludwig Maximilian University in Munich was initiated. The aim of this collaboration was to analyse several blood parameters in mice from the two different founder lines for the hPRV-1/Vav construct. In August 2003 17 transgenic animals from the hPRV-1 founder line # 145 (7 male; 10 female) and 20 transgenic animals from the hPRV-1 founder line # 253 (10 male; 10 female) were transferred to the LMU, Munich. In addition, 30 wild-type FVB mice (15 male; 15 female) were included as controls. To get comparable results both, transgenic and wild-type mice were in the same age. Four age groups were defined as 172-195 days (I), 200-215 days (II), 220-246 days (III) and 250-283 days (IV). The data presented here are based only on animals for which data were obtained at all four different time-points. This gives a total number of 56 animals (15 in the # 145 founder line; 8 in the # 253 founder line and 33 WT animals). The blood parameters which were determined in this analysis do not show large variability across the different time points. Therefore, in Table 4.2 and Figure 4.18 the summarised results across all measurements at the different time points are shown without respect to the age groups. For this the mean value for each parameter across all animals in the different lines and at all four time points was calculated. The detailed data and the corresponding plots for the different age groups are included in the data supplements (Figure 5.1 and Table 5.1).
72 Table 4.2: Cross-line blood parameters for wild-type and transgenic animals (# 145 and # 253). Given are the mean values (range) for animals in the corresponding lines across all four time points. With the number of animals included in each founder line this resulted in 60 data points for the line # 145; 32 for # 253 and 132 for WT. Asterisks indicate significance with respect to the WT group at a level of less than 0.01 (*), 0.001 (**), 0.0001 (***) as obtained in a One-Way ANOVA followed by Dunnet’s t- test (2-sided).
Founder line # 145 Founder line # 253 Wild-type
(n = 15; 8♀, 7♂) (n = 8; 1♀, 7♂) (n = 33; 19♀, 14♂)
Granulocytes (% of total leukocytes) 32.3 (17.9 - 62.7) *** 41 (23.8 - 55.1) *** 26.95 (16.8 - 47.8)
Granulocyte count (x 103/µl) 1.9 (0.5 - 6.8) 2.7 (1 - 4.9) *** 1.9 (0.9 - 4.9)
Haematocrit (%) 42.98 (24.73 - 57.95) 41.62 (34.98 - 50) 42.54 (28.51 - 50.55)
Haemoglobin (g/dl) 14.26 (8.99 - 18.4) 13.82 (12.11 - 16.74) 14.34 (10.03 - 16.68)
Lactate dehydrogenase; LDH (U/l) 373 (208- 841) 517 (221 - 2387) *** 322 (169 - 823)
Lymphocytes (% of total leukocytes) 55.4 (30.6 - 71.1) *** 48.6 (27.5 - 65.7) *** 60.1 (42.8 - 72.9)
Lymphocyte count (x 103/µl) 3 (1.1 - 5.4) *** 3.1 (1.4 - 6.9) * 3.8 (2 - 6.3)
Mean corp. haemoglobin conc.; MCHC (%) 32.89 (28.66 - 36.33) *** 33.52 (31.73 - 36.37) 33.85 (32 - 39.05)
Mean corp. haemoglobin; MCH (pg/cell) 15.27 (13.52 - 16.8) ** 15.23 (14.37 - 16.83) * 15.57 (14.34 - 18.52)
Mean corp. volume; MCV (fl) 46 (45 - 48) 45 (44 - 47) 46 (44 - 49)
Mean platelet volume; MPV (fl) 5.88 (5.29 - 7.06) 5.88 (5.13 - 6.55) 5.72 (4.89 - 6.92)
Monocytes (% of total leukocytes) 12 (6.7 - 17.5) 10.5 (7.3 - 17.4) * 12.5 (8.2 - 17.2)
Monocyte count (x 103/µl) 0.6 (0.2 - 1.1) *** 0.6 (0.3 - 1.1) 0.8 (0.4 - 1.2)
Platelet count; PLT (x 103/µl) 874 (480 - 1211) * 906 (653 - 1400) 936 (551 - 1279)
Red blood cell count; RBC (x 106/µl) 9.3 (5.35 - 12.44) 9.11 (7.56 - 11.22) 9.21 (6.45 - 11.25)
Red cell distribution width; RDW (%) 12.94 (12.48 - 14.12) 13.13 (12.59 - 14.46) 13.13 (12.16 - 14.99)
Serum ferritin level (µg/l) 86.2 (30 - 255.6) *** 84.3 (55.2 - 133) *** 64.4 (35.2 - 133)
Serum iron level (µg/dl) 232.5 (74 - 366.6) * 206.4 (134.2 - 293.1) 206.5 (89.6 - 353.7)
Serum transferrin level (mg/dl) 127.4 (76.5 - 163.1) * 139.2 (101.9 - 168.8) 144.7 (86.4 - 162.1)
Unsat. iron binding capacity; UIBC (µmol/L) 28.8 (8.4 - 51.3) 35.2 (20.7 - 43.3) 31.9 (5.4 - 71.1)
White blood cell count; WBC (x 103/µl) 5.55 (1.84 - 10.85) * 6.39 (3.07 - 12.59) 6.57 (3.36 - 9.96)
A One-Way Analysis of variance (ANOVA) followed by Dunnet’s t-test for pairwise comparisons was performed to determine statistically significant differences between the two transgenic founder lines and the WT animals. As indicated in Figure 4.18 transgenic animals from both founder lines show a significantly elevated percentage of granulocytes with respect to the total number of leukocytes in both transgenic lines. In turn, these animals show decreased lymphocyte counts. Significant changes can be observed in the parameters which are linked to iron metabolism. Both transgenic lines display highly elevated serum ferritin levels. Ferritin plays a major role in the storage of iron in liver, spleen and serum. In addition, 73 animals derived from founder line # 145 are present with elevated serum iron levels. In contrast, the levels for transferrin, the major iron transporter protein in plasma are decreased in these animals. Taken together, these data argue for an elevated transferrin saturation in mice from the founder line # 145. In contrast, the differences concerning haemoglobin level and haematocrit don’t reach statistical significance.
Figure 4.18: Box plots representing the cross-line blood parameters as displayed in Table 4.2 for the two transgenic founder lines hPRV-1/Vav # 145 (red) and hPRV-1/Vav # 253 (blue) and wild-type FVB-mice (green). In the upper part of the figure parameters are shown for which significant differences were observed with respect to WT animals in at least one founder line. For the parameters in the lower part no significant differences were observed. All measurements were performed in the Faculty of Veterinary Medicine of the Ludwig Maximilian University, Munich. The box-plots display median, and range. Outliers, defined by a distance of more than 1.5-fold box-length are not displayed in the plot. Asterisks indicate significance with respect to the WT group at a level of less than 0.01 (*), 0.001 (**) and 0.0001 (***).
74 4.3 cDNA Microarray Analysis of PV Patients Phenotypical and molecular characterisation of patients with myeloproliferative disorders, including PV, implies a high degree of variability in this group with respect to gene expression. Most molecular markers which have been described in CMPD patients, including c-Mpl protein expression, clonality and EEC growth are not applicable for diagnostic procedures, either because of their presence in only a subset of patients or because of technical limitations. In addition, CMPDs, in contrast for example to chronic myelogenous leukaemia, could be due to several mutations which are acquired subsequently and cause the observed phenotype. Such a rather complex mechanism for the pathogenesis of PV could explain the heterogeneity among the CMPDs and difficulties in the subclassification. As a hypothesis, one or more „first hits“ on the stem cell level could be required for the development of a CMPD. In this initial stage the phenotypical differences among the patients are more or less diffuse and can cause misdiagnosis. As a second step, additional mutations could occur which give rise to the distinct phenotypes of PV, ET or IMF. Given the fact that CMPDs are not caused by one distinct mutation on the stem cell level, analysis of single markers can be a valuable tool in differential diagnostics. With respect to pathophysiological mechanisms, these markers seem to be of limited value as they only reflect one component of the malignant phenotype. Therefore, to get more insight into the CMPDs, especially on the level of gene expression, a more global view could be required. In the last few years, a new technique which allows high-throughput screening for thousands of genes simultaneously has enriched the panel of classic tools for gene expression analysis (21). In 1995 the first cDNA microarray experiments were performed (168), the basic principle is as follows: cDNA fragments coding for different genes are generated by PCR-amplification. In the next step these cDNAs are immobilised on pre-treated glass slides. The number of different cDNAs on such a chip ranges from 50 in the first publications up to about 15000 on modern oligonucleotide arrays. RNA, isolated from tissues or cell lines is reverse-transcribed and labelled via incorporation of fluorescent nucleotides. The labelled cDNA samples are hybridised to the glass slides bearing the immobilised
75 probes. The hybridised slides are scanned in a fluorescence reader and for each spotted cDNA the fluorescence intensity is determined which indicates the amount of labelled cDNA bound to this spot. In so-called comparative hybridisation experiments two RNA populations are labelled with different fluorescent dyes. The ratio between the fluorescence values provides information about the differential expression of the concerning genes in the two RNA populations. Two-colour experiments allow the measurement of different RNA populations versus a defined reference sample included in each experiment. Two major advantages compared to one-colour experiments are an improved comparability between different experiments and the possibility to normalise gene expression values with respect to a baseline level (for example: hybridisation of differentiated cell-lines versus an undifferentiated control cell-line or different patients versus healthy controls).
4.3.1 Methodological Background
Array-setup: cDNA microarray experiments were performed to determine differential gene expression in PV patients with respect to healthy controls and patients with secondary erythrocytosis (SE). The microarray Core Facility (G. Walz, Dept. of Nephrology, University Hospital, Freiburg) provided the technology for the microarray experiments, including the cDNA clones to be spotted and the machinery for production of the arrays. 7000 PCR-amplified cDNAs derived from a Unigene library were spotted onto aminosilane-coated glass slides.
Control-RNA Pool: As previously described, cDNA microarrays allow the comparative hybridisation of two, differently labelled cDNA populations to the same chip (Figure 4.19). One aim of the studies presented here is to determine a gene expression signature which is specific for patients with PV. To get reliable results which are not affected by inter-individual differences the noise of unspecific background has to be reduced. Our approach was to generate a pool of RNAs from 50 healthy controls as a reference in each hybridisation experiment. This strategy allows a direct comparison between different hybridisation experiments and compensates for the genetic variability within the control group.
76
Figure 4.19: Basic principle of comparative hybridisation experiments with two different fluorophores. After isolation of granulocytes from whole blood (1) total RNA is isolated (2). During reverse transcription fluorescent nucleotides (Cy3- and Cy5-dUTP) are incorporated into the synthesised cDNAs (3). Both labelled cDNA populations are combined and hybridised to the same chip (4). Fluorescence detection for both emission wavelengths is performed and the data are displayed as a false-colour image with the red colour for Cy5 and the green one for Cy3 (5).
The reference RNA pools for the hybridisation experiments were generated using buffy coats obtained from the blood bank of the University Hospital Freiburg. Granulocytes were purified as described in the materials and methods section and total RNA was prepared by CsCl ultracentrifugation. Equal amounts of RNA from 50 buffy coats were combined and the quality was tested by agarose gel electrophoresis. During the whole panel of experiments performed in this study two different RNA- pools were used. The comparability between these two pools was demonstrated in three independent hybridisation experiments. In these experiments cDNA from pool I was directly compared to pool II, both labelled with different fluorescent nucleotides. The differences in expression of individual genes between the two pools were below the variability between duplicate experiments. Therefore, data obtained with either of the two pools were compared directly without applying any correction.
77 Labelling Strategy: As described in the materials and methods section, RNAs from patient and control are reverse-transcribed into cDNA and labelled with two different fluorescent nucleotides (Cy3-dUTP and Cy5-dUTP). To compensate for different incorporation of these two labelled nucleotides so-called dye-swap experiments as shown in Figure 4.20 were performed: Instead of simple duplicates, on a first slide cDNA from the patient is labelled with Cy3-dUTP and the control cDNA with Cy5-dUTP. On a second slide the dyes are exchanged and the experiment is repeated.
Figure 4.20: Typical false-colour images obtained in a dye-swap experiment. On the first slide the patient cDNA is labelled with Cy5- and the pool cDNA with Cy3-dUTP. In the duplicate experiment the dyes are exchanged. Therefore a spot which appears red in the first image (due to higher expression of the concerning gene in the patient) is shown in green on the second slide and the other way around.
Data Acquisition and Normalisation: Image acquisition was performed using the Gene Pix 4000 Microarray Scanner and the GenePix Pro Software (Both: Axon Instruments, Inc. Union City, CA). The scanned image contains information about the Cy3- and Cy5-fluorescence intensity for each individual spot. A grid, defining position and identity of the spotted cDNAs is overlaid on the image. The mean fluorescence intensities for each array element are calculated by subtraction of the local background for each spot. In contrast to a global background calculation across the whole slide this method allows compensation for spatial effects like smearing. With these corrected values the expression ratio is calculated. Values for the expression ratio between patients and healthy controls are difficult to handle (for a
78 certain gene a ratio of 2 designates 2-fold overexpression whereas 0.5 designates 2- fold underexpression and 1 indicates no difference between two groups). The so- called logRatio is defined as the logarithm to the base of two of the ratio “log2 (ratio)” as shown in Figure 4.21. The expression values obtained by this operation are better to handle because genes with the same degree of over- or underexpression get the same expression value with different prefixes. (therefore genes with 2-fold over- and underexpression get logRatios of +1 and -1 respectively; a logRatio of 0 designates no difference). Image acquisition and local background subtraction are performed using the GenePix Pro Software. For data mining and further normalisation procedures the raw data are transferred to a microarray database (IOBION Informatics GeneTraffic 4.8) which allows storage and handling of large numbers of microarray datasets, including normalisation procedures (global background subtraction) and links to external databases (PubMed, Gene Ontology DB). An overview about the data acquisition steps is given in Figure 4.21.
79
Figure 4.21: Example for data acquisition and normalisation as performed in the microarray experiments. Displayed is a typical dye-swap experiment with the patient’s cDNA labelled with Cy5 and the pool with Cy3 in the upper part and the dye-swap in the lower part of the figure. After feature recognition (1) the fluorescence intensities for both labelled nucleotides are determined using the GenePix software package; at the same time the local background intensities for the two dyes are measured for each spot (2). Using the background-corrected intensities the ratio (Cy5/Cy3) is calculated (3). By using the log2 transformation described in the text the logRatio is calculated (4). To compare results between different slides the median logRatio of all spots on a slide is calculated and normalised to a value of 0. To achieve this the median logRatio (slide) is subtracted from each single logRatio. In the example shown here the median logRatio for the first slide is 0.5 and 0.3 for the dye- swap on the second slide (5). The logRatio for each gene in a dye-swap experiment is finally calculated as the mean of the logRatios (Cy5/Cy3) for the concerning gene on both slides of a dye- swap experiment (6). Steps (1) – (4) were performed using the GenePix Pro Software. After this, the data were transferred to a server-based database (IOBION Informatics GeneTraffic 2.8 ) for the steps (5) and (6).
Direct comparability of microarray results obtained in different hybridisation experiments requires normalisation within each slide. To achieve this, the median logRatio for each chip is calculated and the obtained value is subtracted from each logRatio for the individual genes (Step 5 in Figure 4.21). By this procedure the median logRatio for each chip is normalised to a value of 0. The effect of this operation on the distribution of the logRatios on a slide is demonstrated in Figure 4.22.
80
Figure 4.22: By subtraction of the median logRatio across the whole slide all expression values are normalised to a median of 0. The effect of this operation is displayed in a dye-swap experiment. On the y-axis the logRatios obtained on chip 1 are displayed, on the x-axis for chip 2. Such a plot yields a diagonal line as a logRatio of +2 on slide 1 should correspond to a logRatio of -2 in the dye-swap experiment. After applying the normalisation to a median logRatio of 0 for both slides the diagonal line is shifted to the origin of the grid.
Further analysis of the raw data was performed in collaboration with the Freiburg Center for Data Analysis and Modelling (FDM) as described in the materials and methods section.
81 4.3.2 PV Gene Expression Signature
Patients: Granulocyte RNA from 40 PV patients was analysed by cDNA microarrays. As an inclusion criterion all of them fulfilled the WHO criteria for the diagnosis of PV as described in the introduction. In addition, all patients displayed overexpression of the PRV-1 mRNA in granulocytes. The major hallmark of PV is erythrocytosis. Molecular markers like PRV-1 can be valuable tools in differential diagnosis in order to identify patients with other causes for elevated red blood cell levels. On the other hand, a gene expression signature for PV must exactly differentiate between primary polycythaemia (PV) and secondary effects which lead to erythrocytosis. Beside smoking this can be due to elevated serum levels for erythropoietin or mutations affecting the erythropoietin-receptor. Pellagatti et al (156) have analysed gene expression in 11 PV patients and 10 healthy controls. As they did not analyse any pathological controls, there is no evidence that the gene expression signature of 11 genes which they propose is not due to secondary effects of erythrocytosis. Due to this, the aim of the study performed here is to define a molecular signature which has the power to discriminate between patients with PV and individuals with secondary causes for erythrocytosis. Therefore, in addition to 40 PV patients, 12 patients with secondary erythrocytosis (SE) were included in the study. All of them were PRV-1 negative as determined by TaqMan® Quantitative RT-PCR. Detailed characteristica of these patients, including sex, age and expression of the PRV-1 mRNA are included in the supplemental data section in Table 5.2.
Experimental Design: A two-step model was applied to investigate a molecular signature which differentiates between patients with PV and SE. In a first step, 10 patients each out of the 40 PVs and 12 SEs were randomly chosen. In this so-called training set class predictor genes were determined which discriminate best between PV and SE. In a second step, the remaining patients were classified using these class predictor genes. This experimental approach allows us to test the discriminative power of the class predictor genes on a larger set of samples (Figure 4.23).
82
Figure 4.23: Illustration of the experimental design for the definition of a PV-specific gene expression signature. In the left part of the figure the determination of the class predictor genes on a test cohort of 10 PV and 10 SE patients is shown. On the right these class predictor genes are used to classify the remaining patients.
83 Determination of Class Predictor Genes: Genes differentiating between PV and SE in the training set were obtained by using two criteria: • A p-value of less than 0.01, corrected for the false-discovery rate (FDR), with respect to the discrimination between PV and SE (14) • The corresponding genes have yielded evaluable signals in at least 80% of all hybridisation experiments performed within this cohort
After performing these two steps of analysis on the gene expression data which were obtained for the learning cohort, a set of 64 genes was obtained which discriminates between PV and SE patients. Detailed information about these genes can be found in the supplemental data section (Table 5.3). Using these class predictor genes a two-dimensional hierarchical clustering analysis was performed across all patients included in the training set. The resulting cluster dendrogramm shows two major branches; in one of them all PV patients and in the other all SE patients are located without any outliers (Figure 4.24). This demonstrates that these 64 class predictor genes discriminate between PV and SE within the training set.
84
Figure 4.24: Two-dimensional hierarchical clustering analysis across all patients included in the training set. Columns show the corresponding patient UPNs. Each line shows one of the 64 class predictor genes defined by statistical analysis. The colour scale on the bottom displays logRatios (patients vs. healthy control) between -4 and +4.
85 Out of Sample Classification: The 64 class predictor genes which were generated within the training set have demonstrated a 100% specificity in this cohort. In the second step these genes were used to perform a hierarchical clustering analysis based on the total cohort of patients, including 40 patients with polycythaemia vera and 12 secondary erythrocytosis patients. The resulting dendrogramm in Figure 4.25 displays a perfect discrimination between patients with polycythaemia vera (PV) and those with secondary erythrocytosis (SE). This demonstrates that PV patients show a unique gene expression pattern. Additionally, the predictive power of gene expression analysis using cDNA microarrays is underlined.
86
Figure 4.25: Two-dimensional hierarchical clustering analysis. All 40 PV and 12 SE patients were subjected to hierarchical clustering analysis based on the 64 class predictor genes defined in the training set of 10 PV and 10 SE patients. Columns show the corresponding patient UPN’s. Each line shows one of the 64 class predictor genes.
87 In contrast to the data presented by Pellagatti et al. (156) this molecular signature has been generated by cross-validation versus the clinically relevant group of patients with secondary erythrocytosis (SE). The eleven class predictor genes which were defined by Pellagatti et al. fail to discriminate between PV patients and subjects with secondary erythrocytosis. This is demonstrated in Figure 5.3 (supplemental data section) by hierarchical clustering analysis of our patient cohort using 9 out of these 11 genes which were also included in the microarrays performed here.
4.3.3 Differential Gene Expression in PV Patients and Healthy Controls In the previously described experiments a specific gene expression pattern for PV patients was described. For the evaluation of possible pathogenetic mechanisms and genes involved in the pathogenesis of polycythaemia vera a closer look has to be taken at those genes which are differentially expressed between the healthy control pool and the PV patients. Genes which are differentially expressed between PV patients and healthy controls were determined by three subsequently performed steps of data analysis: • To assure statistical significance of the data the p-value for the discrimination between PV and healthy controls was defined as less than 0.01 (FDR-corrected p-values, (14)) • The corresponding spots are evaluable in at least 80% of all experiments (exclusion of genes which are only spotted on a subset of the arrays due to printing defects) • Only genes which are more than 1.5-fold up- or downregulated across the 40PV patients versus the healthy control pool are included into further analysis
Starting with a total number of 7497 genes spotted on the cDNA microarrays the first step (p-value (FDR) of less than 0.01) reduced this number to 2515 genes. The second criterion (spots evaluable in at least 80% of the 40 PV patients) gave a residual group of 1191 genes. The last step (more than 1.5-fold up- or downregulated in the PV patients vs. healthy controls) resulted in a final number of 644 genes for further analysis.
88 The relation between up- and downregulated genes within this group is 0.65; therefore, in this experimental setup, more genes are underexpressed in the PV patients with respect to the healthy control pool (391 vs. 253). The functional classification of these genes is given in Table 4.3. Table 4.4 shows selected subgroups of differentially expressed genes represented by the four most strongly up- and downregulated members. A detailed list of the genes within the distinct categories is given in section 5.3 (supplemental data).
Table 4.3: Functional classification of differentially expressed genes between patients with polycythaemia vera and the healthy control pool. Only functional subgroups represented by at least 4 genes are shown. Given are the total number of genes within the subgroup and the number of up- and downregulated genes.
Category Genes in Category Upregulated genes Downregulated genes
Transcription Factors 47 18 29 Signal Transduction 75 32 43 Kinase 14 6 8 Cell Cycle Control 16 5 11 Apoptosis 9 5 4 Cytokines and Cytokine Receptors 13 8 5 Cell Surface Receptors 21 5 16 Immune and Inflammatory Response 33 17 16 Thrombosis 6 4 2 Protein Biosynthesis 55 0 55 Chromatin Binding and Remodelling 8 0 8 Carbohydrate metabolism 8 6 2 Calcium binding 7 6 1 Cell Adhesion 26 14 12 Extracellular matrix 4 2 2 Protease 10 3 7 Protease inhibitor 7 6 1 RNA binding 20 4 16
89 Table 4.4: Displayed are the four most strongly up- and downregulated genes within selected functional categories. The table displays the Accession No. (NCBI), gene name and fold up/downregulation.
Acc. No. Name Fold up Fold down
AF016898 B-ATF 4.87 S77763 NF-E2, nuclear factor erythroid-derived 2 2.81 AF012108 Nuclear receptor coactivator 3 2.11 Transcription AB015856 Activating transcription factor 6, ATF-6 2.03 M85164 ELK4, ETS-domain protein 11.57 factors X55122 GATA-3 5.19 D45213 Zinc finger protein 4.74 L49169 FOSB (FBJ murine osteosarcoma viral oncogene) 2.93 AJ005670 Dachshund homolog (Drosophila) 2.76 AB004904 SOCS-3; SSI-3; STAT induced STAT inhibitor-3 2.54 U14575 Protein phosphatase 1, regulatory (inhibitor) subunit 8 2.32 Signal U59877 RAB31, member RAS oncogene family 2.28 M11186 Oxytocin, prepro- (neurophysin I) 10.50 transduction J04132 CD3Z antigen, zeta polypeptide (TiT3 complex) 10.05 X54870 NKG-2 protein 7.13 L13740 Nuclear receptor subfamily 4, group A, member 1 5.99 AB000409 MNK1; MAP kinase-interacting serine/threonine kinase 1 2.74 M18468 Protein kinase, cAMP-dependent, type I, alpha (tissue specific extinguisher 1) 1.92 AF022116 Protein kinase, AMP-activated, beta 1 non-catalytic subunit 1.86 AB015331 BMP-2 inducible kinase 1.75 Kinases S74774 P59fyn (T); OKT3-induced calcium influx regulator 6.33 M61906 Phosphoinositide-3-kinase 2.66 L76200 Guanylate kinase 1 2.42 Y15195 A kinase (PRKA) anchor protein 4 2.36 M59834 Vav 1 oncogene 1.95 D14878 Chromosome 10 open reading frame 7 1.84 M28210 RAB3A, member RAS oncogene family 1.56 Cell cycle J04164 Interferon induced transmembrane protein 1 1.55 D79988 Kinetochore associated 1 7.06 control M14630 Prothymosin, alpha 3.13 D50420 Human OTK27RNA, homolog to yeast NHP2 2.57 AF064105 CDC14 cell division cycle 14 homolog 2.56 L04270 Lymphotoxin beta receptor (TNFR superfamily, member 3) 2.18 U28015 Caspase 5, apoptosis-related cysteine protease 2.06 X84709 Fas (TNFRSF6)-associated via death domain 1.64 Z23115 BCL2-like 1 1.52 Apoptosis M23323 CD3E antigen, epsilon polypeptide (TiT3 complex) 7.16 U78027 Galactosidase, alpha 2.73 L07648 Human MXI1 mRNA 1.91 AF111116 BCL2-associated athanogene 4 1.75 U66198 Fibroblast growth factor 13 3.93 K03222 Transforming growth factor, alpha 2.60 Cytokines X62320 Granulin 2.48 D10923 Putative chemokine receptor 2.36 and cytokine D89078 Leukotriene B4 receptor 5.21 receptors U03858 Fms-related tyrosine kinase 3 ligand 5.15 X02910 Tumor necrosis factor (TNF superfamily, member 2) 3.14 X82540 H.sapiens mRNA for activin beta-C chain 1.87 M95708 CD59 antigen p18-20 3.01 M36035 Benzodiazepine receptor (peripheral) 2.70 M59941 GM-CSF receptor beta chain 1.93 Cell surface U82275 Leukocyte immunoglobulin-like receptor, subfamily A, member 2 1.88 J04132 CD3Z antigen, zeta polypeptide (TiT3 complex) 10.05 receptors M23323 CD3E antigen, epsilon polypeptide (TiT3 complex) 7.16 Z22576 CD69 antigen (p60, early T-cell activation antigen) 4.70 X02228 Major histocompatibility complex, class II, DP beta 1 4.48 AF051151 Toll-like receptor 5 4.00 U88880 Toll-like receptor 4 3.45 Immune and L17418 Complement component (3b/4b) receptor 1 2.69 J03858 CEACAM-1 (biliary glycoprotein) 2.61 inflammatory X58529 Immunoglobulin heavy constant 10.17 response Y14737 Immunoglobulin heavy constant gamma 3 (G3m marker) 7.73 K02882 Immunoglobulin heavy constant delta 6.03 AF067420 Hypothetical protein MGC27165 4.78 J02973 Thrombomodulin 2.51 U92971 Coagulation factor II (thrombin) receptor-like 2 1.60 M14338 Protein S (alpha) 1.54 Thrombosis AF020498 Purinergic receptor P2X, ligand-gated ion channel, 1 1.53 U09937 PLAUR; plasminogen activator, urokinase receptor 2.77 X02419 uPA gene, plasminogen activator 1.95 U31525 Glycogenin 6.86 U51333 Hexokinase 3 (white cell) 3.37 Carbohydrate M14636 Phosphorylase, glycogen; 2.06 D49818 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 4 1.81 metabolism X02747 Aldolase B, fructose-bisphosphate 10.39 D25328 Phosphofructokinase, platelet 2.40
90 A relatively large number of mRNAs encoding transcription factors are differentially expressed in PV patients. In addition, several genes are involved in carbohydrate metabolism, calcium binding or act as protease inhibitors. In addition, a large number of genes play a role in immune and inflammatory response or have been described in the context of thrombosis.
Carbohydrate Metabolism: Upregulation of six genes which are involved in carbohydrate metabolism might possibly reflect a clinical phenomenon called artifactual hypoglycemia which is observed in patients with leukemia, leukocytosis and PV (9). Artifactual hypoglycemia has been reported to occur in polycythaemia vera and is caused by autoglycolysis due to an exaggerated consumption of glucose by blood cells. In polycythaemia vera, this phenomenon can occur even with only modest leukocytosis and may be due to both red and white cell-induced enhanced glycolysis (11,127,210). Other publications report the occurrence of hypoglycemia in patients with granulocytosis receiving haematopoietic cytokine treatment (11).
Immune and Inflammatory Response: Among the genes overexpressed in PV vs. healthy controls many are mediators of inflammation and host defense. This finding might possibly reflect the activated status of the neutrophils in polycythaemia vera. Together with the fact that many upregulated genes are involved in cell-cell interaction processes the high leukocyte counts in PV patients could provide a stimulus for transition to a pro-inflammatory stage. Some of these genes have also been described in the context of sepsis. The finding that the molecular marker PRV-1 is also overexpressed in patients with sepsis provides evidence that the elevated RNA levels for these genes are due to secondary effects of leukocytosis rather than causative for the pathogenesis of PV (103).
Proteases and Protease Inhibitors: Another group of upregulated genes is in close correlation to immune response. • Secretory leukoprotease inhibitor (SLPI), (ALP) 4.8-fold upregulated • Neutrophil elastase (ELA2) 2.1-fold upregulated • Monocyte/Neutrophil elastase inhibitor (MNEI), (SERPINB1) 2.5-fold upregulated • α-1 antitrypsin (SERPINA1) 1.6-fold upregulated
91 As described in the discussion (section 7.2) these and other genes have been described in the context of inflammatory response in neutrophils. In addition, SLPI has been shown to promote the growth of CFU-GM and BFU-E colonies (71).
4.3.4 Many Genes Overexpressed in PV are Regulated by SP1 Coregulation of many genes as observed here in patients with polycythaemia vera can be caused by a variety of factors. One of the most obvious reasons would be a dysregulation of specific transcription factors involved in the generation of the corresponding mRNAs. Literature screening with respect to the transcriptional regulation revealed that among those genes which are significantly upregulated in PV patients vs. healthy controls 27 are regulated by the transcription factor SP1 (Table 4.5 and Figure 4.26).
Table 4.5: Genes regulated by the transcription factor SP1 in PV patients. Given are Accession No., category, the FDR-corrected p-Value (PV vs. HC), fold upregulation and the references for the SP1 binding sites.
Acc. No. Category Name (Unigene ID) p (FDR) Fold up Reference AF146747 Cell surface receptor Polycythaemia rubra vera 1 (PRV-1) 6.77 E-11 22.47 own lab. U31525 Carbohydrate metabolism Glycogenin (GYG) 4.66 E-16 6.86 (196) X56807 Cell adhesion Desmocollin 2 (DSC2) 7.07 E-16 5.04 (130) S90469 Electron transport Cytochrome P450 oxidoreductase (POR) 1.19 E-10 4.80 (149) X13334 Cell surface receptor CD14 antigen (CD14) 9.25 E-13 4.69 (212) X14174 Enzyme Liver type alkaline phosphatase (ALPL) 5.44 E-16 4.66 (205) AF031824 Protease inhibitor Leukocystatin (CST7) 1.13 E-13 3.42 (145) J03407 DNA binding Ret finger protein (RFP) 1.23 E-05 3.28 (85) M24545 Cytokine Monocyte chemoattractant protein (MCAF) 8.30 E-04 2.89 (157,192,193) S77763 Transcription factor Nuclear factor erythroid-derived 2 (NF-E2) 3.31 E-11 2.81 (158) M36035 Cell surface receptor Peripheral benzodiazepine receptor (BZRP) 1.14 E-10 2.70 (122) AB006684 Immune response Autoimmune regulator (AIRE) 3.68 E-06 2.69 (145) M54915 Kinase Pim-1 oncogene (PIM-1) 9.77 E-09 2.69 (133) L00972 Amino acid metabolism Cystathionine-beta-synthase (CBS) 7.79 E-09 2.68 (128) J03858 Immune response CEACAM-1 1.25 E-07 2.61 (30) K03222 Cytokine Transforming growth factor alpha (TGFA) 4.57 E-12 2.60 (200) J02973 Thrombosis Thrombomodulin (THBD) 1.99 E-10 2.51 (182) J03600 Enzyme Arachidonate 5-lipoxygenase (ALOX5) 7.80 E-15 2.50 (83) M16591 Kinase Haematopoietic cell tyrosine kinase (HCK) 8.10 E-10 2.12 (78) D86181 Carbohydrate metabolism Galactosylceramidase (GALC) 1.89 E-07 2.03 (126) L76517 Signal transduction Presenilin 1 (PSEN1) 6.63 E-11 1.95 (155) M57567 Nucleotide metabolism ADP-ribosylation factor 5 (ARF5) 1.06 E-09 1.94 (115) U03688 Electron transport Cytochrome P450 (CYP1B1) 7.69 E-03 1.93 (191,206) J05593 Protease inhibitor Tssue inhibitor of metalloproteinase 2 (TIMP2) 2.31 E-10 1.92 (213) X53961 Immune response Lactotransferrin (LTF) 8.54 E-03 1.65 (97) M14328 Carbohydrate metabolism Alpha-enolase (ENO1) 3.73 E-09 1.64 (69) X51630 Transcription factor Wilms tumor 1 (WT1) 2.45 E-08 1.52 (36)
92
Figure 4.26: Schematical illustration of the promoter region for SP1 regulated genes which were found to be overexpressed in PV patients with respect to healthy controls. Open symbols indicate potential SP1 binding sites based on presence of SP1 consensus sequences within the promoter. Filled ovals show binding sites which have been functionally described for example by electrophoretic mobility shift assays (EMSA) or DNAse footprinting experiments. On the right hand side the degree of overexpression (fold change) with respect to the healthy control pool is displayed.
93 4.3.5 Chromosomal Clustering of Up- and Downregulated Genes As previously described, one possible cause for differentially expressed genes and gene expression patterns on the mRNA level is the coordinated activity or inactivity of transcription factors. During the last years it has become apparent that effects taking place at the DNA level can influence transcriptional regulation. One possible explanation can be microdeletions, intragenic mutations, uniparental disomy and imprinting centre defects as described in Prader-Willi and Angelman syndrome (35,129). Epigenetic regulation is another major aspect of gene regulation control in which changes in gene expression can occur without a change in DNA sequence. Epigenetic control of transcription is mediated through specific states of chromatin structure. Chromatin structure is highly dynamic and its local or global degree of condensation at distinct regions plays an important role in gene expression. Among all the factors which are known to affect chromatin structure, DNA methylation and histone modification seem to be the most important ones. Alterations in chromatin structure can lead to changes in the accessibility of the concerning DNA regions for DNA binding factors. As a result the transcription of genes in this region can be induced or repressed, depending on the steric changes in chromatin structure. In order to identify possible regions of increased or repressed transcriptional activity, clusters of coexpressed genes were identified (i.e. neighbouring genes on a chromosome which are coordinately up- or downregulated). To perform this analysis, further information about the chromosomal location of the genes represented on the cDNA microarrays was required. The initial annotations obtained via the IOBION database contained only cytoband information for the corresponding genes which do not allow exact screening of the chromosomes for regions of altered transcriptional activity. Therefore, additional data about the chromosomal location of the genes included in the microarrays were extracted from the Human Genome Project (HGP), using annotations from the National Center for Biotechnology Information (NCBI). These data consisted of the exact location of the coding sequences which allows to determine the correct order of the concerning genes on the chromosomes. To perform this, the total information for chromosomal locations in the human genome were extracted from the NCBI Genome database (http://www.ncbi.nlm.nih.gov).
94 These data consisted of about 35000 annotated sequences for the 24 human chromosomes. Alignment of these data with the genes included in the microarrays was performed using a shareware application for MS Excel. As a result, a table was obtained which included both, the expression values for all genes measured in the microarray experiments and the exact chromosomal location of these genes (Figure 4.27). As a cut-off for inclusion into further analysis a p-value (FDR) for differential expression between PV patients and healthy controls of less than 0.01 was chosen. This resulted in a group of about 2000 genes which were screened for clusters of coordinately coexpressed genes.
Figure 4.27: Chromosomal location data from the Human Genome Project were extracted from the NCBI Genome database and synchronised with the data obtained in the microarray experiments.
In the total set of these 2000 genes 23 Clusters of six or more neighbouring genes which are coordinately up- or downregulated were found. Distribution of these clusters across the different chromosomes is shown in the supplemental data section in Figure 5.2. For example, as displayed in Figure 4.28, on chromosome 19 one of these clusters contains the human gene for PRV-1 and several other genes. It remains to be determined if the presence of co-localised and co-expressed genes in PV represents a result of chromatin remodelling or other epigenetic effects. As a
95 follow-up project, analysis of possible changes on the chromosomal level using the ChIP technology (Chromatin Immunoprecipitation) is intended.
Figure 4.28: Example for clusters of up- or downregulated genes on the different chromosomes in PV patients. The figure shows the human chromosome No. 19. On this chromosome two clusters of upregulated genes (one with 6, one with 9 genes) could be detected. In part (A) of the figure red bars indicate upregulated genes (logRatio > 0); green bars designate downregulated genes (logRatio < 0). (B) shows the group of 9 upregulated genes between 47.4 and 48.5 Mbp from the telomer region including the two flanking genes which show lower expression levels in the PV patients. Filled boxes indicate genes which were measured in the cDNA microarrays together with their degree of up- or downregulation (fold change). Genes displayed by open boxes were either not included in the chip setup or did not yield significant results (a p-value of less than 0.01 between PV patients and healthy controls was taken as a cut-off for genes included in this analysis).
4.3.6 Verification of the Microarray Results Gene expression data obtained by cDNA microarray analysis require experiments to verify the differential expression of several genes by using other techniques. Possible techniques for such verification experiments are: • Semi-quantitative RT-PCR • Northern Blot Analysis • Real-Time Quantitative RT-PCR (TaqMan®)
To verify the data obtained in the experiments described here these three techniques were applied on several genes which turned out to be differentially expressed between PV patients and healthy controls.
96 Northern Blot and Semi-quantitative RT-PCR: Differential expression of the following genes was verified using semi-quantitative RT-PCR and Northern Blot analysis as described in the materials and methods section. These genes were chosen according to their consistent overexpression across the PV patients included in this study and the presence of binding sites for the transcription factor SP1 in the promoter region as described in section 4.3.4. The results of the verification experiments are displayed in Figure 4.29 • Pim-1 proto-oncogene (PIM-1) 2.7-fold upregulated • Glycogenin (GYG) 6.9-fold upregulated • Desmocollin-2 (DSC2) 5.0-fold upregulated • Leukocystatin (Cystatin F) (CST7) 3.4-fold upregulated • Nuclear factor erythroid-derived 2 (NF-E2) 2.8-fold upregulated
97
Figure 4.29: Verification of the gene expression results obtained in the cDNA microarrays by Northern Blot analysis (Pim-1, Leukocystatin and NF-E2) and semi-quantitative RT-PCR (Glycogenin and Desmocollin-2).
98 Quantitative RT-PCR: TaqMan® Quantitative RT-PCR analysis was performed for five genes which are differentially expressed in PV patients with respect to healthy controls. For this purpose Assay-on-DemandTM gene expression products (Applied Biosystems) were used. With the exception of the Pim-1 proto-oncogene and the transcription factor NF-E2 these genes are located in the genomic region on chromosome 19 which has been described in Figure 4.28. • Pim-1 proto-oncogene (PIM-1) 2.7-fold upregulated • Carcinoembr. antigen-related cell adh. mol. (CEACAM-1) 2.6-fold upregulated • Thrombomodulin (THBD) 2.5-fold upregulated • Plasminogen activator (PLAUR) 2.8-fold downregulated • Nuclear factor erythroid-derived 2 (NF-E2) 2.8-fold upregulated
For these experiments 10 ng of total granulocyte RNA from 5 PV patients and 5 healthy controls (buffy coats from the blood bank) was reverse-transcribed using the TaqMan® Reverse Transcription Kit (Applied Biosystems). For the transcription factor NF-E2 additional cDNAs from 5 healthy controls and 15 PV patients were assayed. As described in the materials and methods section, these cDNAs were diluted by 1:4 and 5µl each were used for quantification in triplicate. The use of these dilutions yielded good amplification results with curves which reach a saturation level within the 40 cycles of PCR reaction for all samples. The patients’ characteristica were as follows:
Table 4.6: Characteristica of the patients included in the Real-Time Quantitative RT-PCR experiments. Given are the Unique Patient Number (UPN), sex and age.
UPN Diagnosis Sex Age (y) 202 PV f 67 206 PV f 43 219 PV m 70 318 PV f 57 630 PV m 64 230 PV m 64 679 PV m 56 824 PV f 46 907 PV m 60 978 PV f 65 1015 PV f 66 1079 PV f 62 1106 PV f 46 1117 PV f 53 1136 PV f 45 1149 PV f 42 1152 PV f 63 2072 PV f 67 2220 PV m 60 2388 PV f 50
99 As performed for the quantification of the human PRV-1 gene a value for each sample was obtained.
Figure 4.30: Determination of CT Ratios for different target genes as performed in the verification experiments for the cDNA microarray results. For each patient CT values are obtained for the gene of interest (part A of the figure) and 18S ribosomal RNA (B). The CT ratio is calculated as CT(target gene)/CT(18S).
This CT value is defined as the cycle number when the emitted fluorescence reaches a certain pre-defined threshold, symbolised by a red line in Figure 4.30. This threshold level was selectively defined for each assay to be situated between background and saturation level of the amplification curve (0.4 for THBD, PLAUR and CEACAM-1; for PIM-1 it was set to 0.15 and for NF-E2 to 0.25). To reduce unspecific background noise during the first cycles of the amplification reaction, the baseline level for the fluorescence within this period is subtracted. This step is performed within the ABIPrism software package. For quantification of 18S ribosomal RNA the threshold level was set to 0.2 in all experiments. After obtaining the mean CT values for each triplicate quantification experiment, the ratio CT(target gene)/CT(18S) for the individual samples was calculated. A high CT ratio indicates a high cycle number for the concerning target gene and therefore a smaller amount of the corresponding RNA in the PCR reaction.
100
Figure 4.31: CT ratios obtained in quantitative RT-PCR experiments for THBD, PLAUR, CEACAM-1 and PIM-1. The bars (from left to right) display the following PV patients and healthy controls: UPN 630; UPN 318; UPN 206; UPN 219; UPN 202 (PV patients, red bars); UPN 544; UPN 546; UPN 547; UPN 548; UPN 549 (healthy controls, green bars). The UPNs 544 to 549 represent buffy coat RNA obtained from healthy blood samples from the blood bank of the University Hospital in Freiburg.
For CEACAM-1 and THBD the results obtained in the cDNA microarrays could be verified in all individuals analysed (Figure 4.31). The PV patients show a lower CT ratio compared to the healthy controls. In the case of PLAUR four out of five PV patients show higher CT ratios compared to healthy controls what indicates a lower amount of PLAUR mRNA in these samples. For PIM-1 in four cases lower CT ratios were obtained for the PV patients. The detailed results of these experiments are included in the supplemental data section in Table 5.4. As the transcription factor NF-E2 might play a key role in the pathogenesis of PV (see discussion), additional PV patients and healthy controls were assayed for expression of the corresponding mRNA. Based on a total cohort of 20 PV patients and 10 healthy controls overexpression of the NF-E2 mRNA could be demonstrated in 19 patients (Figure 4.32).
101
Figure 4.32: In part A relative expression of the RNA for the transcription factor NF-E2 is displayed across the 40 PV patients included in the cDNA microarray studies versus the healthy control pool. (B) CT ratios obtained in quantitative RT-PCR experiments for NF-E2. The bars (from left to right) display 10 healthy controls and 20 PV patients. Detailed information about the patient’s UPN and the exact CT values for NF-E2 and 18S rRNA are given in the supplemental data section in Table 5.4. (C) Expression values for the NF-E2 mRNA as displayed in (B) were transformed into copy numbers determined from a standard curve with known copy numbers for NF-E2 and 18S rRNA. Given is the relative ratio (molecules NF-E2 per 106 molecules 18S rRNA).
Taken together, the results obtained in semi-quantitative RT-PCR, Northern Blot and quantitative RT-PCR demonstrate the reliability of the data obtained in the cDNA microarrays.
Western Blot NF-E2 seems to of special interest concerning pathogenesis of PV. In order to confirm overexpression of this transcription factor on the protein level, Western Blot analysis was performed by Edith Doerner. Using an antibody which was kindly provided by N. C. Andrews (Harvard Medical School, Boston, MA) overexpression of NF-E2 protein could be demonstrated in 5 out of 7 PV patients whereas none of the 2 healthy controls showed detectable amounts of the protein (Figure 4.33).
102
Figure 4.33: Western Blot analysis of 7 PV patients and 2 healthy controls for expression of the transcription factor NF-E2.
Immunohistochemistry In collaboration with Prof. Dr. Schmitt-Graeff (Dept. of Pathology, University Hospital Freiburg, Germany) bone marrow biopsies from 8 PV patients and 6 healthy controls were stained for NF-E2 using specific antibodies (Santa Cruz Biotechnologies). As a result elevated expression of the NF-E2 protein could be demonstrated in PV patients in progenitor cells derived from the erythroid, granulocytic and megakaryocytic lineages (Figure 4.34).
Figure 4.34: Immunohistochemistry performed on bone marrow biopsies from PV patients and healthy controls. Staining was performed in the Dept. of Pathology (University Hospital Freiburg, Germany) using polyclonal antibodies directed against the human NF-E2 protein. In part A and B samples from healthy controls are displayed whereas C to F represent PV patients.
103 4.4 Molecular Characterisation of ET Patients Essential thrombocythaemia (ET) is probably the most heterogeneous disorder among the CMPDs. A subset of these patients does not show any symptoms during many years. In contrast, some patients experience serious thromboembolic complications. A single molecular marker which defines patients with ET has not been found to date. Recent studies have shown overexpression of the PRV-1 mRNA in 50% of the ET population (73). In addition, 50% of all patients display decreased expression of the receptor for thrombopoietin (c-Mpl) on their platelets. Another finding was monoclonal haematopoiesis in half of the ET patients (33,57,75). The question whether these alterations coincide in the same subset of patients or whether they are acquired independently should be answered in the following section. The occurrence of thromboembolic complications during progression of disease seems to be the major risk for ET patients (113). Despite the fact that 20 - 30% will develop thrombotic episodes during their lifetime, the clinical course for individual patients is very heterogeneous. A subclassification of ET patients into groups according to the risk for the occurrence of thrombotic events is largely based on clinical criteria such as age, platelet count and previous complications (12). The cellular and molecular markers which were recently described in subgroups of ET patients could be useful tools for risk stratification profiles. In three independent studies an increased risk of thromboembolic events has been described in patients carrying one of these biomarkers. Patients with monoclonal haematopoiesis have been described to carry a higher risk for thrombotic events compared to polyclonal patients (75). Weak or absent c-Mpl staining in bone marrow megakaryocytes was reported to correlate with a higher risk of thrombosis (185). Finally, two independent studies demonstrated a predictive value for elevated PRV-1 mRNA levels which is associated with a significantly elevated risk of thromboembolic complications (89). The occurrence of clonality, decreased c-Mpl expression and PRV-1 overexpression are reported in only a subset of ET patients (30 – 60%), therefore one has to ask whether they are present concurrently in individual patients or can be acquired separately. A close correlation between PRV-1 overexpression and EEC formation has been described (102,104). The question arises if expression of c-Mpl and clonality are acquired independently from PRV-1. In addition, in a retrospective study
104 it should be determined if expression of PRV-1 mRNA or c-Mpl protein predispose ET patients to thromboembolic complications. Taken together, the three studies performed here are: • Analysis of PRV-1 mRNA and c-Mpl protein expression in ET patients: Expression of c-Mpl protein and PRV-1 mRNA was tested in 48 ET patients • Thrombotic complications in subpopulations of ET patients defined by c-Mpl and PRV-1: Retrospective analysis of 48 ET patients with respect to thromboembolic complications • Correlation between PRV-1 mRNA levels, clonality and EEC growth in ET patients: 10 female, untreated ET patients younger than 65 years were tested for clonality, PRV-1 mRNA expression and growth of Endogenous Erythroid Colonies (EECs)
4.4.1 Patients The total patient collective comprised 53 ET patients, diagnosed according to the updated PVSG criteria (17). Venous blood (40 ml), anticoagulated with EDTA was shipped by courier without cooling. Maximum time interval between venipuncture and arrival in the laboratory was 24 hours. Blood samples from these patients were kindly provided by J. Kutti and P. Johansson (Sahlgrenska University Hospital, Göteborg). Patient characteristica are shown in the supplemental data section in Table 5.5.
4.4.2 Analysis of PRV-1 mRNA and c-Mpl Protein in 20 ET Patients In a cohort consisting of 48 ET patients (# 40 - # A:21 in Table 5.5) expression of the c-Mpl protein on platelets and the expression of the mRNA for PRV-1 in granulocytes were tested.
Separation of Cells, c-Mpl and PRV-1 Quantification: Isolation of platelets from whole blood samples and determination of c-Mpl levels was performed by Edith Doerner (Figure 4.35).
Figure 4.35: Western Blot analysis of c-Mpl protein expression on platelets as performed by Edith Doerner. K5 represents a healthy control to which the expression levels for the patients were normalised. The platelet glycoprotein gpIIIa serves as a loading control and for normalisation of the c- Mpl expression. 105 Platelets were isolated using Sepharose CL-2B columns. Expression of c-Mpl was analysed by immunoblotting as described (104,139). For each patient, expression of both c-Mpl and the platelet glycoprotein IIIa (gpIIIa/CD41) was quantified by densitometric analysis of Western Blots. A c-Mpl /gpIIIa ratio was calculated. If this ratio was below 40% of the average of three healthy controls, decreased c-Mpl expression was documented. Granulocytes were purified as described in the materials and methods section by Dextran sedimentation followed by Ficoll separation. mRNA was isolated and PRV-1 quantified by TaqMan® Quantitative RT-PCR as described (102). Briefly, for each sample an average cycle of threshold (CT) value for each triplicate measurement of either PRV-1 or the housekeeping gene GAPDH was calculated. Subsequently a
CT(PRV-1)/CT(GAPDH) ratio was determined. A CT(PRV-1)/ CT(GAPDH) ratio < 1.17 was used to diagnose PRV-1 overexpression.
Results: Among the 48 ET patients included into this study 17 (35%) displayed decreased c- Mpl expression and 18 (37%) overexpressed PRV-1 (Figure 4.36). However, when compared, there is no correlation between c-Mpl on platelets and the PRV-1 mRNA levels. Both markers are only present concurrently in 10 out of the 48 patients (21%). In contrast, 23 patients (48%) displayed none of these molecular markers and 15 patients (32%) carried only one of the markers. It must be kept in mind that 67% of the patients in this cohort have obtained cytoreductive treatment. This could possibly interfere with the expression of one or both markers.
Figure 4.36: Expression of PRV-1 mRNA and c-Mpl protein in 48 ET patients. Given are the total numbers (left) and the percentage across the total cohort.
106 4.4.3 Thrombotic Complications in ET Patients As mentioned before, recent results suggest a predictive role for the expression of PRV-1 mRNA (89) and c-Mpl protein in megakaryocytes (185) with respect to the occurrence of thromboembolic complications in ET.
Results: After analysis of PRV-1 mRNA and c-Mpl protein expression in the cohort of 48 ET patients (# 40 - # A:21 in Table 5.5) a retrospective analysis was performed regarding the occurrence of thromboembolic complications to find possible subgroups of patients bearing a higher risk for thromboembolic complications. The following endpoints were defined as constituting thromboembolic complications: venous or arterial thrombosis, cerebrovascular events, pulmonary embolism, myocardial infarction, stroke as well as minor complications including erythromelalgia and thrombophlebitis or bleeding episodes. Among the 48 patients 8 have suffered such complications. To assure that there are no significant differences between the patients‘ characteristica and laboratory data, statistical analysis was performed for each of the four subgroups generated by the two biomarkers PRV-1 and c-Mpl as shown in Table 4.7. Hence, by the clinical criteria which are currently used to asses thrombotic risk (age, platelet number and previous history of thrombosis), none of the subgroups clusters patients at higher risk. Unconditional logistic regression yielded the result that overexpression of the PRV-1 mRNA is associated with a statistically significant increased risk of thromboembolic events (Table 4.7 and Figure 4.37). This appeared to be independent of cytoreductive therapy as only 1 of the 9 patients suffering complications was not receiving cytoreduction. Patients with elevated PRV-1 mRNA but normal c-Mpl protein levels had a 10-fold increased odds ratio compared to patients who carry neither of the two markers.
107 Table 4.7: In the cohort of 48 ET patients, the following complications were noted: PRV-1 normal, c-Mpl normal: cerebrovascular occlusion, stroke; PRV-1 high, c-Mpl normal: amaurosis fugax, mesyterial thrombosis, microvascular complications; recurrent in one patient : erythromelalgia, transient ischaemic attack, myocardial infarction; PRV-1 normal, c-Mpl low: gastro-intestinal bleeding; PRV-1 high, c-Mpl low: deep vein thrombosis, microvascular complications.
PRV-1 normal PRV-1 high PRV-1 normal PRV-1 high
c-Mpl normal c-Mpl normal c-Mpl low c-Mpl low Patients 23 8 7 10 Complications 2 (8,7%) 4 (50%) 1 (14.3%) 2 (20%) Odds ratio 1.00 10.50 1.75 2.63 95% Confidence Interval - 1.41 – 78.04 0.13 – 22.77 0.31 – 21.92 P - value - 0.0216 0.6692 0.3729
Regarding the patients characteristica there was a significant difference in haemoglobin level, haematocrit and platelets between several groups at sample collection. Nevertheless, the group of patients which showed the 10-fold increased risk of thrombosis compared to control (PRV-1 normal, c-Mpl normal), was not different from the control group in any of these parameters (Table 5.6 in the supplemental data section). In contrast to a previous study performed on 88 ET patients, a decreased expression of c-Mpl was not associated with an increased risk of thrombosis in this cohort (185). In that study, however, c-Mpl expression was determined in megakaryocytes, not in platelets. Patients who bear both markers (elevated PRV-1 mRNA and decreased c-Mpl protein) appear to be at lower risk for complications than patients overexpressing PRV-1mRNA in the presence of normal c-Mpl levels. It has been described in PV that c-Mpl expression can diminish during progression of the disease; at the same time, the risk for thromboembolic complications is highest in the first two years following diagnosis (17,141). One may speculate that decreased c-Mpl expression counteracts the deleterious effect of PRV-1 overexpression in ET patients.
108
Figure 4.37: Occurrence of thromboembolic events in subgroups of 48 ET patients defined by expression of c-Mpl protein and PRV-1 mRNA.
4.4.4 Correlation Between PRV-1 mRNA, Clonality and EEC Growth in ET The growth of Endogenous Erythroid Colonies (EECs) in patients with ET has been described in about 50% of all cases (60). Additionally, in several studies the analysis of X-chromosomal inactivation patterns has demonstrated clonal haematopoiesis in 50% of ET patients while in the rest granulocytes and platelets are clonal (33,57,75). This led us to investigate a possible correlation between PRV-1 mRNA levels, clonality and EEC growth. As described in the introduction clonality analysis is only applicable in female patients younger than 65 years (65). Keeping in mind the possibility that cytoreductive treatment could restore polyclonal haematopoiesis, the study was limited to untreated objects. Among the ET patients provided from J. Kutti 10 untreated female patients and two patients who remained clonal despite hydroxyurea treatment were analysed.
109 EEC and Clonality Assays As the clonality and EEC assays were performed by Cordula Steimle, these two methods should not be described in detail here.
Humara Assay: • DNA extraction using Dodecyltriammonium bromide (DTAB) • Restriction digest of the samples in 2 aliquots with Rsa I and Hpa II (methylation-sensitive) • PCR: digested DNA is used as a template for the PCR reaction with fluorescence-labelled primers spanning the 5´promoter region containing a variable number of CAG repeats • Capillary electrophoresis on Beckman Coulter CEQ 8000 DNA Genetic Analysis System • Data analysis (determination of the ratio between the two alleles) and interpretation according to the following rules: A ratio of 25:75 or less between the two alleles in the myeloid lineage denotes clonality if at least a 20 point difference between T-cells and granulocytes is also observed and the T-cells show a ratio larger than 25:75
EEC Assay: • Assays were performed as described (73): • Peripheral blood mononuclear cells at 2 x 105 /ml and 6 x 105 /ml were plated in MethoCult™ methylcellulose medium H4230 (without EPO) and MethoCult™ H4330 (with EPO) (Stem Cell Technology, Vancouver, Canada)
• The cells were cultivated at 37°C, 5% CO2 in a humified atmosphere • After 14 days the colonies were scored. EECs were defined as clusters of at least 50 well haemoglobinised cells in the assay without EPO • An assay without EEC growth was considered not informative if less than 40 colonies were obtained in the presence of EPO
Results: Among the 12 patients overexpression of the PRV-1 mRNA was observed in four individuals whereas eight displayed normal levels for this marker. In all PRV-1 positive patients clonal haematopoiesis could be detected whereas this was the case in no member of the PRV-1 negative group. The assays for the growth of Endogenous Erythroid Colonies (EECs) were only informative for one member in the PRV-1 positive group who showed the formation of EPO-independent colonies whereas none of the remaining eight individuals displayed this phenomenon (Table 4.8
110 Transition from ET to PV in EEC-positive ET patients has been described (170). Clonality in turn was reported as a factor which predicts a higher risk for the occurrence of thromboembolic complications (171). The data presented here support the hypothesis that two distinct sets of mutations give rise to the clinical symptoms of ET. These patients seem to form two subgroups: the first that is polyclonal, PRV-1 and EEC-negative, whereas the second shows clonal haematopoiesis and is PRV-1 as well as EEC-positive. These data suggest a potential clinical use for the determination of molecular markers in individual ET patients as retrospective analyses have demonstrated that either clonal haematopoiesis or increased PRV-1 mRNA expression identify ET patients at higher risk for thromboembolic complications. Prospective trials of large cohorts of patients are required to substantiate these data gained by cross sectional and retrospective analysis of a relatively small number of patients.
Table 4.8: Results of the clonality analysis performed by Cordula Steimle. Displayed are the ratio between the two alleles in the HUMARA assays (24), the CT(PRV-1)/CT(GAPDH) Ratio as determined by TaqMan® Real Time Quantitative RT-PCR and growth or absence of Endogenous Erythroid Colonies (EECs). A CT(PRV-1)/CT(GAPDH) ratio < 1.17 was used to diagnose PRV-1 overexpression.
111 4.4.5 Microarray Analysis of ET Patients As described in the introduction, a subpopulation of patients with essential thrombocythaemia shares some clinical and molecular features with PV patients. These include the overexpression of PRV-1 mRNA in about 50% of all ET patients, the formation of Endogenous Erythroid Colonies (EECs) in 50% of all ET patients and the occurrence of PV during progression of disease in PRV-1 positive as well as in EEC positive ET patients. These findings, together with the results which were described previously, including the higher risk of thromboembolic complications in PRV-1 positive ET patients, raise the following question: Are PRV-1 positive patients who get the diagnosis of essential thrombocythaemia PV patients in an early stage of disease who do not yet show the whole clinical repertoire of PV ? The molecular markers in PV and ET allow a sub-classification of the patients which may be of prognostic benefit in the case of PRV-1 expression. Nevertheless, to answer this question, a more global approach for the classification between PV and ET is required. cDNA microarrays allow expression analysis of thousands of genes in only one experiment. During the research project presented here, a molecular signature for patients with PV has been described. As described in section 4.3.2, this molecular signature was established in a cohort of 10 patients each with PV and SE and consists of 64 genes which discriminate between these groups with a p-value (FDR) of less than 0.01. Hierarchical clustering analysis of previously unclassified patients resulted in a specificity of 100% for the discrimination between PV and SE. As an additional experiment granulocyte RNA from two patients with essential thrombocythaemia (# 107: PRV-1 positive; UPN 734: PRV-1 negative) was hybridised to cDNA microarrays (for patient characteristica, see Table 5.2 in the supplemental data section). The PRV-1 positive female with ET (# 107) was initially diagnosed as an essential thrombocythaemia in 1982 due to her elevated platelet count (1392 x 109/l) but a haematocrit within the normal range (41%); in addition she displayed stainable iron deposits in the bone marrow and displayed a discretely enlarged spleen. In 2002, for the studies described before, a blood sample of this patient was analysed for expression of the PRV-1 mRNA; overexpression of the PRV-1 gene was determined. 112 During the re-examination of her clinical record it turned out that her haematocrit, while within the normal range, exceeded that, allowed for a positive diagnosis of ET today. In addition the patient was intermittently treated with busulfan, which lowered her haematocrit so that she was never present with a drastically elevated haematocrit which could give rise to the diagnosis of PV. This example demonstrates the need for a more global insight into the borderline between PV and ET which can’t be obtained by the evaluation of single clinical parameters and molecular markers. Based on the 64 class predictor genes a hierarchical clustering analysis was performed, including the unclassified PV and SE patients as well as the two patients with essential thrombocythaemia.
113
Figure 4.38: Hierarchical clustering analysis of the patient cohort described in the microarray-results, including two patients with essential thrombocythaemia (# 107; PRV-1 positive and UPN 734; PRV-1 negative). 114 As a result, the PRV-1 positive ET patient is being clustered within the PV patients whereas the PRV-1 negative ET patient shows a rather heterogeneous gene expression pattern (Figure 4.38). Especially by taking a look at the genes which are upregulated in PV patients versus healthy controls (red squares) it becomes clear that the PRV-1 positive ET patient shows a very close relationship to the PV patients. The limited number of only two patients included in this study is due to the fact that for the microarrays performed here 2 x 12 µg of total RNA are required. This amount of RNA can easily be obtained by isolating granulocytes from therapeutically performed phlebotomies of PV patients; ET patients are not treated by phlebotomy, therefore such large amounts of blood are not available. One gene which was found to be significantly overexpressed in PV patients with respect to SE patients and healthy controls was the proto-oncogene Pim-1. For the validation of the cDNA microarray experiments performed in this study, a semi- quantitative RT-PCR assay was established for several marker genes, including Pim- 1. In order to get further insight into a possible relationship between the gene expression in PV patients and ET patients, semi-quantitative RT-PCR was performed using cDNA obtained from eight PRV-1 positive and seven PRV-1 negative ET patients. As observed in the PV patients, PRV-1 positive ET patients show overexpression of the Pim-1 mRNA compared to the PRV-1 negative ET patients (Figure 4.39).
Figure 4.39: Expression of the mRNA for the human proto-oncogene Pim-1 is elevated in PRV-1 positive ET patients.
115 The results obtained here corroborate the impressions obtained in the previous experiments using a completely different experimental setup and might indicate that PRV-1 positive ET patients represent an early stage of PV. Based on the impressive differences in the gene expression between these two ET patients a new study has been implemented to analyse gene expression patterns in a larger cohort of ET patients. The trial has been approved by the local ethics committee and will be performed by Britta Will.
116 4.5 Familial Accumulation of Elevated PRV-1 mRNA Levels The annual incidence of polycythaemia vera is about 0.5 to 2.5 per 100000 with a median age of presentation of 60 years. Only 1% of patients present before an age of 25 years which leads, in turn, to a very restricted knowledge about manifestation and progression of „early“ PV. The so-called Budd-Chiary syndrome is characterised by obstruction and occlusion of the suprahepatic veins resulting in liver fibrosis, hepatomegaly and ascites. A relationship to PV has been firstly described in the 50s (26). More recent studies have demonstrated the formation of Endogenous Erythroid Colonies (EECs) in 40 to 80 percent of patients with Budd-Chiary syndrome (2,48,50,80,195). The formation of EECs is a major characteristic of PV and very close to the postulated molecular cause of this disease. Due to this, it was assumed that the Budd-Chiary syndrome could present a pathological manifestation of early PV in patients who may display normal blood counts at the time of diagnosis. In collaboration with H. Cario the following results were obtained by analysis of PRV- 1 mRNA expression in members of a family where two cases of PV are reported.
4.5.1 Elevated PRV-1 mRNA Levels in a Girl With Budd-Chiari Syndrome Due to the postulated relationship between PV and Budd-Chiari syndrome, peripheral blood from an 11-year-old girl was tested for expression of PRV-1 in standard routine diagnosis. The first clinical manifestations were those reported for Budd-Chiari syndrome as liver enlargement or occlusion of major hepatic veins. After analysis of bone marrow biopsies increased counts for all three cell lineages with dominating erythropoiesis were found (27). Quantitative RT-PCR has demonstrated elevated PRV-1 mRNA levels. Additionally, the growth of EECs could be observed in a colony assay performed by Cordula Steimle. During analysis of the medical history it turned out that the girl’s maternal grandmother has been present with an elevated haematocrit which later was diagnosed as polycythaemia vera after histologic evaluation of a bone marrow biopsy. Due to these findings, PRV-1 mRNA measurement and EEC assays were also performed with peripheral blood samples of the grandmother. The results were the same as described for the 11-year-old girl: EEC growth and PRV-1 mRNA overexpression were observed. 117 Due to the occurrence of these markers for PV in two closely related individuals we performed quantitative RT-PCR with blood samples from 12 other family members. With the exception of the child’s mother who displayed boarder-line levels for PRV-1 but no EEC growth, no other family member overexpressed PRV-1 mRNA. It is possible that this slightly elevated level reflects a carrier status of the child’s mother, which would support the hypothesis that additional mutations are required for the pathogenesis of PV.
118 5. Supplemental Data
5.1 Figures
Figure 5.1: Blood parameters for the two transgenic founder lines hPRV-1/Vav # 145 (red) and hPRV- 1/Vav # 253 (blue) and wild-type FVB-mice (green). All measurements were performed in the Faculty of Veterinary Medicine of the Ludwig Maximilian University, Munich. The box-plots display median, and range. Outliers, defined by a distance of more than 1.5-fold box-length are not displayed in the plot. Age group I corresponds to an age of 172 to 195 days, II to an age of 200-215 days, III to an age of 220-246 days and IV to an age of 250-283 days. 119
Figure 5.2: Localisation of clusters of coordinately expressed genes across the human chromosomes. Green bars indicate genes which are underexpressed in healthy controls with respect to PV patients; red bars indicate upregulated genes. Brackets show clusters of more than five genes in close proximity which are up- or downregulated in PV vs. HC. On the x-axis the logRatio (PV vs. HC) and on the y-axis the chromosomal localisation (M bp from the telomer region) are displayed.
120
Figure 5.3: Hierarchical clustering analysis of the 40 PV and 12 SE patients using 9 out of 11 class predictor genes defined by Pellagatti et al. (156). These genes do not allow a precise differentiation between PV patients and subjects with secondary erythrocytosis.
121 5.2 Tables
Table 5.1: Detailed blood parameters for the transgenic founder lines and wild-type FVB-mice. The data represent the median (range) of the concerning blood parameters. Only mice were included for which data were obtained at all four different time points. With the number of animals included in each founder line this resulted in 60 data points for the line # 145, 32 for # 253 and 132 for WT
122 Table 5.2: Patient characteristica for cDNA microarray analysis. In total, 40 patients with PV, 12 patients with secondary erythrocytosis (SE), one PRV-1 positive ET patient and a PRV-1 negative ET patient were included in the cDNA microarray experiments. Given are sex, age, and the CT(PRV- ® 1)/CT(GAPDH) ratio as determined by TaqMan Real Time Quantitative RT-PCR. Grey indicates patients included in the learning cohort. Concerning PV and SE the median (range) for age and the CT(PRV-1)/CT(GAPDH) ratio are displayed on the bottom of the table (*). A CT(PRV-1)/ CT(GAPDH) ratio < 1.17 was used to diagnose PRV-1 overexpression.
123 Table 5.3: 64 class predictor genes defined by statistical analysis of gene expression in 10 PV patients and 10 patients with secondary erythrocytosis. The table shows Accession No., UniGene name and UniGene ID for the concerning genes, the p-value (FDR-corrected) for the discrimination between PV and SE and the logRatio (PV vs. SE).
124 Table 5.4: Detailed results of the Quantitative RT-PCR experiments. Given are baseline and threshold level as used for the data evaluation in the ABI Prism software package, the mean CT value obtained in triplicate measurements and the ratio CT(target gene)/CT(18S rRNA). BC denotes healthy control samples obtained from buffy coats from the blood bank of the University Hospital, Freiburg.
125 Table 5.5: ET patients characteristica. Given are sex, age, platelet count, c-Mpl level and the CT ratio ® CT(PRV-1)/CT(GAPDH) as determined by TaqMan Real Time Quantitative RT-PCR. Grey indicates patients included only in the clonality analysis. A CT(PRV-1)/ CT(GAPDH) ratio < 1.17 was used to diagnose PRV-1 overexpression. A c-Mpl /gpIIIa ratio was calculated. If this ratio was below 40% of the average of three healthy controls, decreased c-Mpl expression was documented. HU: Hydroxyurea; 32P: Phosphorous 32; IFN: Interferon; Ana: Anagrelide; ASA: Acetyl Salicylic Acid.
126 Table 5.6: Characteristica, clinical and laboratory data of the 48 ET Patients. Patients are stratified according to the four subgroups defined by PRV-1 mRNA and c-Mpl protein expression. For laboratory data, both the data at the time of diagnosis and at the time of PRV-1/c-Mpl analysis is given. For the clinical data values denote mean (range). p-values were calculated using the median test, which compares the medians of quantitative variables obtained from 2 or more groups. The p-value gives the statistical significance for comparison of all four groups among each other. Ns: not significant. Asterisks indicate that at least one comparison between two groups show a statistically significant difference. Accordingly, additional median tests were performed to assess which groups were significantly different in those cases:
* Haemoglobin at sample (g/dl): PRV-1 normal c-Mpl normal vs. PRV-1 normal c-Mpl low p=0.0338 PRV-1 normal c-Mpl normal vs. PRV-1 high c-Mpl low p=0.0030 PRV-1 high c-Mpl normal vs. PRV-1 high c-Mpl low p=0.0057 ** Platelet count at sample (x 109/l): PRV-1 normal c-Mpl normal vs. PRV-1 normal c-Mpl low p=0.0338 PRV-1 normal c-Mpl normal vs. PRV-1 high c-Mpl low p=0.0335 *** Haematocrit at sample (%): PRV-1 normal c-Mpl normal vs. PRV-1 high c-Mpl low p=0.0010 PRV-1 high c-Mpl normal vs. PRV-1 high c-Mpl low p=0.0089
PRV-1 normal PRV-1 high PRV-1 normal PRV-1 high p-value c-Mpl normal c-Mpl normal c-Mpl low c-Mpl low Patients 23 8 7 10 Male / female 17 / 6 6 / 2 6 / 1 8 / 2 ns Age* 58 (27 – 86) 57 (50-80) 74 (55 – 90) 73 (32 – 82) ns Duration of disease (months) * 37 (7 – 201) 36 (24 – 177) 46 (24 – 181) 66 (21 – 267) ns Follow-up (months) * 37 (7 – 201) 36 (24 – 177) 46 (24 – 181) 66 (21 – 267) ns Cytoreductive treatment 12 5 6 9 ns
Hb at diagnosis (g/dl) * 13.9 (11.2 – 16.8) 14.1 (12.6 – 16.0) 12.6 (11.2 – 15.3) 13.8 (10.6 – 15.1) ns Hb at sample (g/dl) * 13.7 (10.9 – 16.3) 13.6 (11.3 – 15.4) 12.4 (11.4 – 13.6) 12.7 (10.8 – 13.1) * Hct at diagnosis (%)* 43 (38 - 52) 44 (42 - 48) 38 (33 - 48) 41 (32 - 47) ns Hct at sample (%)* 43 (35 - 49) 43 (39 - 49) 37 (36 - 42) 37 (32 - 40) ** Plts at diagnosis (x 109/l) * 624 (410 - 1850) 774 (504 - 1115) 1260 (752 - 1550) 972 (650 - 1392) ns Plts at sample (x 109/l) * 507 (339 - 946) 442 (232 - 929) 433 (256 - 553) 333 (233 - 776) *** Lcts at diagnosis (x 109/l) * 8 (5,3 -15,1) 9,7 (5,8 - 12,5) 9,8 (7,8 - 14,6) 10,9 (7 - 14,5) ns Lcts at sample (x 109/l) * 7,5 (4 - 10,4) 6,6 (4,1 - 12,2) 5,3 (4 - 9,8) 4,5 (3,4 - 13,5) ns
127 5.3 Functional Classification Transcription Factors: Fold Change Acc. No. Name Up Down
AF016898 Homo sapiens B-ATF gene 4.87 S77763 NF-E2, nuclear factor (erythroid-derived 2) 2.81 AF012108 nuclear receptor coactivator 3 2.11 AB015856 activating transcription factor 6, ATF-6 2.03 M59834 vav 1 oncogene 1.95 AB011141 zinc finger homeobox 1b 1.93 U72621 pleiomorphic adenoma gene-like 1 1.86 U43923 Human homolog of SUPT4H (S. cerevisiae) 1.80 U15655 Ets2 repressor factor 1.75 AB011110 Ca2+-promoted Ras inactivator 1.70 U70663 Kruppel-like factor 4 (gut) 1.65 AB015132 Kruppel-like factor 7 (ubiquitous) 1.63 AB007886 zinc finger protein 305 1.62 M96824 nucleobindin 1 1.58 U11732 ets variant gene 6 (TEL oncogene) 1.57 L05515 cAMP response element-binding protein CRE-BPa 1.52 X51630 Wilms tumor 1 1.52 J04102 Human erythroblastosis virus oncogene homolog 2 (ets-2) 1.52 M85164 ELK4, ETS-domain protein (SRF accessory protein 1) 11.57 X55122 GATA-3 5.19 D45213 zinc finger protein 4.74 L49169 FBJ murine osteosarcoma viral oncogene homolog B 2.93 M31523 transcription factor 3 (E2A immunoglobulin enhancer binding factors E12/E47) 2.62 U07802 zinc finger protein 36, C3H type-like 2 2.57 AJ002607 T-cell leukemia, homeobox 2 (Hox II) 2.50 AF029678 PHD finger protein 1 2.40 L13744 myeloid/lymphoid or mixed-lineage leukemia; human AF-9 mRNA 2.14 X78924 zinc finger protein 266 2.06 U31986 cartilage paired-class homeoprotein 1 2.03 X75042 Human v-rel reticuloendotheliosis viral oncogene homolog 1.99 L07648 Human MXI1 mRNA 1.91 M97796 inhibitor of DNA binding 2, dominant negative helix-loop-helix protein 1.91 U61145 enhancer of zeste homolog 2 (Drosophila) 1.79 X63417 c-myc promoter-binding protein 1.73 D31716 basic transcription element binding protein 1 1.72 U36499 SP140 nuclear body protein 1.72 AF046001 zinc finger protein 207 1.70 X64037 general transcription factor IIF, polypeptide 1, 74kDa 1.68 L39060 TATA box binding protein (TBP)-associated factor, RNA polymerase I, A, 48kDa 1.67 U39361 ubiquitin-conjugating enzyme E2 variant 1 1.66 X89750 TGFB-induced factor (TALE family homeobox) 1.66 M80627 transcription factor 12 (HTF4, helix-loop-helix transcription factors 4) 1.63 X97548 tripartite motif-containing 28 1.59 AF040253 suppressor of Ty 5 homolog (S. cerevisiae) 1.56 Z50781 delta sleep inducing peptide, immunoreactor 1.55 AF020591 zinc finger protein 1.51 D90209 activating transcription factor 4 (tax-responsive enhancer element B67) 1.51
128
Signal Transduction: Fold Change Acc. No. Name Up Down
AJ005670 Dachshund homolog (Drosophila) 2.76 AB004904 SOCS-3; SSI-3; STAT induced STAT inhibitor-3 2.54 U14575 protein phosphatase 1, regulatory (inhibitor) subunit 8 2.32 U59877 RAB31, member RAS oncogene family 2.28 U71127 RAB32, member RAS oncogene family 2.21 AF077346 interleukin 18 receptor accessory protein 2.20 U63721 LIM domain kinase 1 2.07 U38654 RAB27A, member RAS oncogene family 2.05 X62573 Fc fragment of IgG, low affinity IIb, (receptor for CD32) 2.03 U71321 FK506 binding protein 5 1.99 L35263 MAPK14 1.98 L13857 Human son of sevenless homolog 1 (Drosophila) 1.98 L76517 presenilin 1 (Alzheimer disease 3) 1.95 AF037195 regulator of G-protein signalling 14 1.95 U27655 regulator of G-protein signalling 3 1.87 U44403 Src-like-adaptor 1.81 X52220 FK506 binding protein 1A, 12kDa 1.80 M63904 guanine nucleotide binding protein (G-protein), alpha 15 (Gq class) 1.77 J03238 guanine nucleotide binding protein (G-protein), alpha inhibiting activity polypeptide 3 1.71 U33168 G-protein-coupled receptor kinase 4 1.66 M31328 guanine nucleotide binding protein (G-protein), beta polypeptide 3 1.65 X60114 c-src tyrosine kinase 1.64 U41654 Ras-related GTP-binding protein 1.61 X51416 estrogen-related receptor alpha 1.60 X04571 epidermal growth factor (beta-urogastrone) 1.57 X04434 Human IGF-1R; insulin-like growth factor 1 receptor 1.56 M28210 RAB3A, member RAS oncogene family 1.56 L02911 activin A receptor, type I 1.55 U31628 interleukin 15 receptor, alpha 1.53 Y00638 protein tyrosine phosphatase, receptor type, C 1.51 U11050 NIMA (never in mitosis gene a)-related kinase 2 1.51 AF028823 Tax interaction protein 1 1.50 M11186 oxytocin, prepro- (neurophysin I) 10.50 J04132 CD3Z antigen, zeta polypeptide (TiT3 complex) 10.05 X54870 Human NKG-2 protein 7.13 L13740 nuclear receptor subfamily 4, group A, member 1 5.99 X60489 eukaryotic translation elongation factor 1 beta 2 5.67 L05148 zeta-chain (TCR) associated protein kinase 70kDa 5.21 D85245 nuclear receptor subfamily 4, group A, member 1 4.75 X01451 CD3D antigen, delta polypeptide (TiT3 complex) 4.36 Z30425 nuclear receptor subfamily 1, group I, member 3 4.16 M26038 major histocompatibility complex, class II, DR beta 3 4.12 X80200 TNF receptor-associated factor 4 3.79 S46622 protein phosphatase 3 (formerly 2B), catalytic subunit, gamma isoform (calcineurin A gamma) 3.68 L06139 TEK tyrosine kinase, endothelial (venous malformations, multiple cutaneous and mucosal) 3.65 L48211 angiotensin II receptor-like 2 3.17 X06820 ras homolog gene family, member B 3.15 M84371 CD19 antigen 3.08 Z35278 runt-related transcription factor 3 2.82 U78027 galactosidase, alpha 2.73 J03853 adrenergic, alpha-2C-, receptor 2.56 Y15195 A kinase (PRKA) anchor protein 4 2.36 Z35227 ras homolog gene family, member H 2.30 AF098799 importin 7 2.30 Y13493 dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 2 2.13 D16815 nuclear receptor subfamily 1, group D, member 2 2.08 Y15723 guanylate cyclase 1, soluble, alpha 3 2.08 U33052 protein kinase C-like 2 2.08 AF084523 cellular repressor of E1A-stimulated genes 1.98 U56998 cytokine-inducible kinase 1.84 U52819 vascular endothelial growth factor B 1.82 AB007972 protein phosphatase 1, regulatory (inhibitor) subunit 12B 1.80 X80230 cyclin-dependent kinase 9 (CDC2-related kinase) 1.79 AF061836 Ras association (RalGDS/AF-6) domain family 1 1.76 M92424 Human p53-associated mRNA 1.76 AJ000512 Homo sapiens sgk gene 1.75 AF034795 cell matrix adhesion regulator 1.66 U87964 GTP binding protein 1 1.64 L07592 peroxisome proliferative activated receptor, delta 1.63 U78521 aryl hydrocarbon receptor interacting protein 1.62 D63780 serine/threonine kinase 25 (STE20 homolog, yeast) 1.61 D78132 Ras homolog enriched in brain 2 1.61 U77735 pim-2 oncogene 1.60 U12779 mitogen-activated protein kinase-activated protein kinase 2 1.50 Y08698 RAN binding protein 3 1.50
129
Kinase: Fold Change Acc. No. Name Up Down
AB000409 MNK1; MAP kinase-interacting serine/threonine kinase 1 2.74 M18468 protein kinase, cAMP-dependent, regulatory, type I, alpha (tissue specific extinguisher 1) 1.92 AF022116 protein kinase, AMP-activated, beta 1 non-catalytic subunit 1.86 AB015331 BMP-2 inducible kinase 1.75 Y10055 phosphoinositide-3-kinase, catalytic, delta polypeptide 1.65 AB018330 calcium/calmodulin-dependent protein kinase kinase 2, beta 1.61 S74774 p59fyn (T); OKT3-induced calcium influx regulator 6.33 M61906 phosphoinositide-3-kinase, regulatory subunit, polypeptide 1 (p85 alpha) 2.66 L76200 guanylate kinase 1 2.42 Y15195 A kinase (PRKA) anchor protein 4 2.36 M59287 CDC-like kinase 1 2.07 X62535 diacylglycerol kinase, alpha 80kDa 2.03 AF072860 protein kinase, interferon-inducible double stranded RNA dependent activator 2.02 AF012872 phosphatidylinositol 4-kinase, catalytic, alpha polypeptide 1.62
Cell Cycle Control: Fold Change Acc. No. Name Up Down
M59834 vav 1 oncogene 1.95 D14878 chromosome 10 open reading frame 7 1.84 M28210 RAB3A, member RAS oncogene family 1.56 J04164 interferon induced transmembrane protein 1 1.55 L22005 cell division cycle 34 1.54 D79988 kinetochore associated 1 7.06 M14630 prothymosin, alpha (gene sequence 28) 3.13 D50420 Human OTK27RNA, homolog to yeast NHP2 2.57 AF064105 CDC14 cell division cycle 14 homolog 2.56 X61123 BTG-1, B-cell translocation gene 1, anti-proliferative 2.11 M59287 CDC-like kinase 1 2.07 Z34289 nucleolar and coiled-body phosphoprotein 1 1.82 U52819 vascular endothelial growth factor B 1.82 X80230 cyclin-dependent kinase 9 (CDC2-related kinase) 1.79 AF064102 CDC14 cell division cycle 14 homolog A (S. cerevisiae) 1.60 AF040963 MAX dimerisation protein 4 1.58
Apoptosis: Fold Change Acc. No. Name Up Down
L04270 lymphotoxin beta receptor (TNFR superfamily, member 3) 2.18 U28015 caspase 5, apoptosis-related cysteine protease 2.06 X84709 Fas (TNFRSF6)-associated via death domain 1.64 Z23115 BCL2-like 1 1.52 U15173 BCL2/adenovirus E1B 19kDa interacting protein 2 1.52 M23323 CD3E antigen, epsilon polypeptide (TiT3 complex) 7.16 U78027 galactosidase, alpha 2.73 L07648 Human MXI1 mRNA 1.91 AF111116 BCL2-associated athanogene 4 1.75
Cytokines and Cytokine Receptors: Fold Change Acc. No. Name Up Down
U66198 fibroblast growth factor 13 3.93 K03222 transforming growth factor, alpha 2.60 X62320 granulin 2.48 D10923 putative chemokine receptor 2.36 X52425 interleukin 4 receptor 2.14 Z17227 interleukin 10 receptor, beta 1.73 X04571 epidermal growth factor (beta-urogastrone) 1.57 U02020 pre-B-cell colony-enhancing factor 1.50 D89078 leukotriene B4 receptor 5.21 U03858 fms-related tyrosine kinase 3 ligand 5.15 X02910 tumor necrosis factor (TNF superfamily, member 2) 3.14 X82540 H.sapiens mRNA for activin beta-C chain 1.87 AF005058 chemokine (C-X-C motif) receptor 4 1.84
130 Cell Surface Receptors: Fold Change Acc. No. Name Up Down
M95708 CD59 antigen p18-20 3.01 M36035 benzodiazepine receptor (peripheral) 2.70 M59941 colony stimulating factor 2 receptor, beta, low-affinity (granulocyte-macrophage) 1.93 U82275 leukocyte immunoglobulin-like receptor, subfamily A (with TM domain), member 2 1.88 U62027 complement component 3a receptor 1 1.77 J04132 CD3Z antigen, zeta polypeptide (TiT3 complex) 10.05 M23323 CD3E antigen, epsilon polypeptide (TiT3 complex) 7.16 Z22576 CD69 antigen (p60, early T-cell activation antigen) 4.70 X02228 major histocompatibility complex, class II, DP beta 1 4.48 X01451 CD3D antigen, delta polypeptide (TiT3 complex) 4.36 AF004230 leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 1 2.99 M16973 complement component 8, beta polypeptide 2.92 X03100 major histocompatibility complex, class II, DP alpha 1 2.72 X00274 Human gene for HLA-DR alpha heavy chain a class II antigen 2.70 D11466 phosphatidylinositol glycan, class A (paroxysmal nocturnal haemoglobinuria) 2.53 M90657 transmembrane 4 superfamily member 1 L6tumor antigen 2.42 M13560 Human Ia-associated invariant gamma-chain gene, exon 8 2.33 U00672 interleukin 10 receptor, alpha 2.30 X62744 major histocompatibility complex, class II, DM alpha 2.11 U87947 epithelial membrane protein 3 1.76 AF016098 neuropilin 2 1.52
Immune and Inflammatory Response: Fold Change Acc. No. Name Up Down
AF051151 toll-like receptor 5 4.00 U88880 toll-like receptor 4 3.45 L17418 complement component (3b/4b) receptor 1, including Knops blood group system 2.69 J03858 carcinoembryonic antigen-related cell adhesion molecule 1 (biliary glycoprotein) 2.61 D13637 toll-like receptor 1 2.49 AF077346 interleukin 18 receptor accessory protein 2.20 L04270 lymphotoxin beta receptor (TNFR superfamily, member 3) 2.18 X62573 Fc fragment of IgG, low affinity IIb, receptor for (CD32) 2.03 X12830 interleukin 6 receptor 2.03 AF025528 leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 2 1.94 AB008775 aquaporin 9 1.92 U82275 leukocyte immunoglobulin-like receptor, subfamily A (with TM domain), member 2 1.88 M84562 formyl peptide receptor-like 1 1.85 X53961 lactotransferrin 1.65 U94333 complement component 1, q subcomponent, receptor 1 1.60 AF041261 leukocyte immunoglobulin-like receptor, subfamily A (without TM domain), member 4 1.56 AF057169 vitelliform macular dystrophy (Best disease, bestrophin) 1.52 X58529 Human rearranged immunoglobulin mRNA for mu heavy chain enhancer and constant region 10.17 Y14737 immunoglobulin heavy constant gamma 3 (G3m marker) 7.73 K02882 immunoglobulin heavy constant delta 6.03 AF067420 hypothetical protein MGC27165 4.78 U05259 CD79A antigen (immunoglobulin-associated alpha) 4.65 M30894 T cell receptor gamma locus 4.39 M26038 major histocompatibility complex, class II, DR beta 3 4.12 M24364 major histocompatibility complex, class II, DQ beta 1 3.75 AF004230 leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 1 2.99 D90145 chemokine (C-C motif) ligand 3-like 1 2.43 X15998 chondroitin sulfate proteoglycan 2 (versican) 2.34 U28369 sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 2.24 AF072860 protein kinase, interferon-inducible double stranded RNA dependent activator 2.02 M16276 major histocompatibility complex, class II, DQ beta 1 1.97 U87964 GTP binding protein 1 1.64 AF025534 leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 5 1.56
Thrombosis: Fold Change Acc. No. Name Up Down
J02973 thrombomodulin 2.51 U92971 coagulation factor II (thrombin) receptor-like 2 1.60 M14338 protein S (alpha) 1.54 AF020498 purinergic receptor P2X, ligand-gated ion channel, 1 1.53 U09937 PLAUR; plasminogen activator urokinase receptor 2.77 X02419 H.sapiens uPA gene, plasminogen activator 1.95
131
Protein Biosynthesis and Structural Component of Ribosome: Fold Change Acc. No. Name Up Down
X80822 ribosomal protein L18a 12.43 U12404 ribosomal protein L10a 10.84 D14530 ribosomal protein S23 10.43 M17885 ribosomal protein, large, P0 9.39 X64707 ribosomal protein L13 9.38 U62962 eukaryotic translation initiation factor 3, subunit 6 48kDa 9.02 M58458 ribosomal protein S4, X-linked 8.75 U02032 ribosomal protein L23a 8.62 AB007156 ribosomal protein S20 8.43 X53505 ribosomal protein S12 8.41 X67309 ribosomal protein S6 7.06 U65581 ribosomal protein L3-like 6.72 AB007170 ribosomal protein L10 6.69 X69391 ribosomal protein L6 6.43 M81757 ribosomal protein S19 6.20 X63527 ribosomal protein L19 6.18 M17887 ribosomal protein, large P2 5.91 L05091 ribosomal protein S28 5.83 X06705 ribosomal protein L7a 5.68 X60489 eukaryotic translation elongation factor 1 beta 2 5.67 M17886 ribosomal protein, large, P1 5.67 X69181 ribosomal protein L31 5.51 M94314 ribosomal protein L24 5.50 M60854 ribosomal protein S16 4.95 AF037643 ribosomal protein L12 4.90 U25789 ribosomal protein L21 4.85 M84711 ribosomal protein S3A 4.80 X51466 eukaryotic translation elongation factor 2 4.65 X52839 ribosomal protein L23 4.38 J02984 ribosomal protein S15 4.33 Z26876 ribosomal protein L38 4.32 X55715 ribosomal protein S3 4.23 U94855 eukaryotic translation initiation factor 3, subunit 5 epsilon, 47kDa 4.14 X84407 ribosomal protein S15a 3.55 U14972 ribosomal protein S10 3.52 X79238 ribosomal protein L30 3.24 L05094 ribosomal protein L27 3.24 X06617 ribosomal protein S11 3.11 M31520 ribosomal protein S24 3.08 M58459 ribosomal protein S4, Y-linked 3.07 D79205 ribosomal protein L39 3.05 L06499 ribosomal protein L37a 2.97 Z21507 eukaryotic translation elongation factor 1 delta (guanine nucleotide exchange protein) 2.79 M60858 nucleolin 2.65 D50420 Homo sapiens mRNA for OTK27; homologous to NHP2; non-histone chromosome protein 2-like 1 2.57 AF054187 nascent-polypeptide-associated complex alpha polypeptide 1.99 AF000987 eukaryotic translation initiation factor 1A, Y chromosome 1.99 U54558 eukaryotic translation initiation factor 3, subunit 7 zeta, 66/67kDa 1.93 U14973 ribosomal protein S29 1.93 L11567 ribosomal protein L37 1.83 L05096 ribosomal protein L39-like 1.80 AB010874 ribosomal protein L41 1.74 X76013 glutaminyl-tRNA synthetase 1.65 U36764 eukaryotic translation initiation factor 3, subunit 2 beta, 36kDa 1.64 U37230 ribosomal protein L23a 1.54
Chromatin Binding and Remodelling: Fold Change Acc. No. Name Up Down
Z21507 eukaryotic translation elongation factor 1 delta (guanine nucleotide exchange protein) 2.79 M60858 nucleolin 2.65 D50420 Homo sapiens mRNA for OTK27; homologous to NHP2; non-histone chromosome protein 2-like 1 2.57 AF054187 nascent-polypeptide-associated complex alpha polypeptide 1.99 AF000987 eukaryotic translation initiation factor 1A, Y chromosome 1.99 U54558 eukaryotic translation initiation factor 3, subunit 7 zeta, 66/67kDa 1.93 X76013 glutaminyl-tRNA synthetase 1.65 U36764 eukaryotic translation initiation factor 3, subunit 2 beta, 36kDa 1.64
132
Carbohydrate Metabolism: Fold Change Acc. No. Name Up Down
U31525 glycogenin 6.86 U51333 hexokinase 3 (white cell) 3.37 M14636 phosphorylase, glycogen; liver (Hers disease, glycogen storage disease type VI) 2.06 D49818 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 4 1.81 M14328 Alpha-enolase 1.64 X04327 2,3-bisphosphoglycerate mutase 1.61 X02747 aldolase B, fructose-bisphosphate 10.39 D25328 phosphofructokinase, platelet 2.40
Calcium Binding: Fold Change Acc. No. Name Up Down
D83664 S100 calcium binding protein A12 (calgranulin C) 3.08 AF003837 jagged 1 (Alagille syndrome) 2.46 K01911 neuropeptide Y 2.18 M81637 grancalcin, EF-hand calcium binding protein 2.14 AB014536 copine III 1.85 U83246 copine I 1.53 U20760 calcium-sensing receptor (hypocalciuric hypercalcemia 1, severe neonatal hyperparathyroidism) 4.11
Cell Adhesion: Fold Change Acc. No. Name Up Down
X56807 desmocollin 2 5.04 U25956 selectin P ligand 2.45 U71383 sialic acid binding Ig-like lectin 5 2.43 L05424 CD44 antigen (homing function and Indian blood group system) 2.19 AB014536 copine III 1.85 M25322 selectin P (granule membrane protein 140kDa, antigen CD62) 1.73 J05070 matrix metalloproteinase 9 (gelatinase B, 92kDa gelatinase, 92kDa type IV collagenase) 1.72 M35198 integrin, beta 6 1.71 Y10375 protein tyrosine phosphatase, non-receptor type substrate 1 1.69 M15395 integrin, beta 2 (lymphocyte function-associated antigen 1; macrophage antigen 1 (mac-1) beta subunit) 1.69 M31165 tumor necrosis factor, alpha-induced protein 6 1.66 AJ012159 trophoblast glycoprotein 1.65 X15954 mannose-binding lectin (protein C) 2, soluble (opsonic defect) 1.61 AF018081 collagen, type XVIII, alpha 1 1.52 U43901 laminin receptor 1 (ribosomal protein SA, 67kDa) 9.01 X54870 DNA segment on chromosome 12 (unique) 2489 expressed sequence 7.13 U33818 poly(A) binding protein, cytoplasmic 4 (inducible form) 4.38 AF038953 integral membrane protein 2A 2.83 D84145 dynactin 6 2.22 J04765 secreted phosphoprotein 1 (osteopontin, bone sialoprotein I, early T-lymphocyte activation 1) 1.91 U77718 pinin, desmosome associated protein 1.91 U33882 integrin, beta 1 (fibronectin receptor, beta polypeptide, antigen CD29 includes MDF2, MSK12) 1.78 D50532 macrophage lectin 2 (calcium dependent) 1.71 AF034795 cell matrix adhesion regulator 1.66 AF034803 PTPRF interacting protein, binding protein 2 (liprin beta 2) 1.65 AF054840 tetraspan 3 1.63
Extracellular Matrix: Fold Change Acc. No. Name Up Down
J05593 tissue inhibitor of metalloproteinase 2 1.92 X93207 nardilysin (N-arginine dibasic convertase) 1.51 X97324 adipose differentiation-related protein 2.67 X15998 chondroitin sulfate proteoglycan 2 (versican) 2.34
133
Protease: Fold Change Acc. No. Name Up Down
X87212 cathepsin C 2.29 AJ001531 protease, serine, 12 (neurotrypsin, motopsin) 2.27 M34379 elastase 2, neutrophil 2.06 AF013611 cathepsin W (lymphopain) 9.37 J02907 granzyme H (cathepsin G-like 2, protein h-CCPX) 5.79 M23254 calpain 2, (m/II) large subunit 3.00 U62801 kallikrein 6 (neurosin, zyme) 2.74 AB001928 cathepsin L2 2.00 M90696 cathepsin S 1.67 AF022789 ubiquitin specific protease 12 1.60
Protease Inhibitor: Fold Change Acc. No. Name Up Down
AF031824 cystatin F (leukocystatin) 3.42 X94323 specific granule protein (28 kDa) 2.80 AF053630 serine (or cysteine) proteinase inhibitor, clade B (ovalbumin), member 1 MNEI 2.54 J05593 tissue inhibitor of metalloproteinase 2 1.92 X01683 serine (or cysteine) proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1 1.59 AF027205 serine protease inhibitor, Kunitz type, 2 1.53 L19684 serine (or cysteine) proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 4 1.76
RNA Binding: Fold Change Acc. No. Name Up Down
L28010 heterogeneous nuclear ribonucleoprotein F 2.15 M37716 small nuclear ribonucleoprotein polypeptide E 1.64 X77494 RNA binding motif, single stranded interacting protein 1 1.63 AB023967 ROD1 regulator of differentiation 1 (S. pombe) 1.52 D50420 NHP2 non-histone chromosome protein 2-like 1 (S. cerevisiae) 2.57 U28686 RNA binding motif protein 3 2.25 M74002 splicing factor, arginine/serine-rich 11 2.17 Z23064 RNA binding motif protein, X chromosome 2.14 AF000987 eukaryotic translation initiation factor 1A, Y chromosome 1.99 M63483 matrin 3 1.93 AF000364 heterogeneous nuclear ribonucleoprotein R 1.80 U87836 splicing factor, arginine/serine-rich 10 (transformer 2 homolog, Drosophila) 1.79 AL034428 Human DNA sequence from clone RP4-705D16 on chromosome 20p11.22-12.2 1.75 AB010874 Homo sapiens gene for ribosomal protein L41 1.74 AF067730 FUS interacting protein (serine-arginine rich) 1 1.74 L37368 RNA binding protein S1, serine-rich domain 1.71 D59253 nuclear cap binding protein subunit 2, 20kDa 1.69 X76013 glutaminyl-tRNA synthetase 1.65 L10838 splicing factor, arginine/serine-rich 3 1.62 L10910 RNA-binding region (RNP1, RRM) containing 2 1.60
134 6. Summary
In this work, several attempts to elucidate the physiological role of the murine PRV-1 gene by whole mount in-situ hybridisation experiments did not yield reproducible results. Nevertheless, expression of the mPRV-1 mRNA could be demonstrated from embryonic day 6.5 on by RT-PCR experiments. In order to obtain a model system for physiological analysis of the PRV-1 protein, transgenic mouse strains were generated which express the human and the murine PRV-1 gene in their haematopoietic system. Expression of the transgene was demonstrated on mRNA as well as on protein level in the two transgenic founder lines for the human PRV-1 gene. Analysis of different blood parameters of these mice in a collaboration with the LMU in Munich revealed significant differences compared to wild-type littermates with respect to granulocyte counts and different factors involved in iron homeostasis.
Overexpression of the PRV-1 mRNA, decreased c-Mpl protein levels on platelets and the formation of EECs are laboratory findings which can be used for differential diagnosis among the CMPDs. Nevertheless, none of these markers can define a single disease entity and none of them seems to represent the initial step in the pathogenesis of PV. This led us to perform cDNA microarray analysis of PV patients in order to get a more global view of gene expression in this myeloproliferative disorder. Granulocyte RNAs from 40 polycythaemia vera (PV) and 12 secondary erythrocytosis (SE) patients were analysed. Peripheral granulocytes were chosen as the source of RNA, since these cells yield high amounts of RNA and arise clonally from the aberrant stem cell. In order to identify genes which are specifically altered in PV, RNA from purified granulocytes of 10 patients with SE and 10 PV patients was hybridised to a control RNA pool consisting of total granulocyte RNA from 50 healthy controls. Of all the 7000 cDNAs investigated, 64 differentiate between patients with SE and PV in this training set (p<0.01). A hierarchical clustering analysis based on these genes resulted in a correct classification of the remaining 30 PV and 2 SE patients what indicates that these genes represent a unique gene expression pattern discriminating PV from SE. Some of the genes which are differentially expressed in PV patients with respect to healthy controls could play a role in the context of PV by contributing to the malignant
135 phenotype, whereas others may rather represent secondary effects which are predominantly caused by the elevated numbers of circulating blood cells. A large number of genes which show elevated RNA levels in PV patients are regulated by the transcription factor SP1. This raises the hypothesis of a transcriptional dysregulation in PV with respect to SP1 or other related transcription factors. Concerning the pathogenesis of PV elevated mRNA and protein levels could be demonstrated for the erythroid transcription factor NF-E2. NF-E2 seems to be of special interest as this factor has been described to promote the growth of EPO- independent colonies when overexpressed in primary haematopoietic progenitor cells (167) and therefore represents an extremely interesting candidate for the molecular etiology of PV.
The characterization of 48 patients with essential thrombocythaemia (ET) with respect to the markers PRV-1 mRNA, c-Mpl protein, clonality and EEC-growth was also part of this work. As a result it turned out that elevated PRV-1 mRNA and decreased c-Mpl protein expression are acquired independently and do not define the same subgroup of ET patients. In contrast, clonal haematopoiesis and PRV-1 mRNA overexpression correlated in a cohort of 12 ET patients. The subgroup of ET patients which show elevated PRV-1 mRNA levels has been shown to be at a higher risk for thromboembolic complications as compared to those with normal PRV-1 levels. Therefore, this molecular marker could be a valuable tool in the risk stratification procedure for ET patients. cDNA microarray analysis of granulocyte RNA from one PRV-1 positive and one PRV-1 negative ET patient was also performed. The PRV-1 positive patient showed a PV-like gene expression signature. This, together with the recently published finding that PRV-1 positive ETs will transform to PV in later stages of the disease supports the hypothesis of “masked” PV in PRV-1 positive ET patients.
136 7. Discussion
7.1 Transgenic Mice The physiological role of the PRV-1 protein, the human as the murine homologue, remains unknown. No difference in the expression levels could be found between patients and controls via FACS analysis. An ELISA based assay has revealed only slightly elevated plasma levels for the PRV-1 protein in PV which are not concordant with the large differences on RNA level. A possible explanation for the discrepancy between protein and RNA levels could be shedding of PRV-1 from the cell membrane in PV patients leading to higher protein levels. An ELISA based assay has revealed only slightly elevated plasma levels for the PRV-1 protein in PV which are not concordant with the large differences on RNA level. To date, the only observation which could indicate a role of PRV-1 protein in the pathogenesis of PV is growth inhibition of haematopoietic colonies after treatment with PRV-1 containing supernatant. It was obtained from cells which were stably transfected with a plasmid construct coding for a GPI-less PRV-1 protein (Klippel, unpublished observations). Some features of the PRV-1 protein as the homology with members of the uPAR/Ly6/CD59/snake toxin-family could argue for a role as a cell surface receptor. Several attempts to elucidate the physiological role of the murine PRV-1 gene by whole mount in-situ hybridisation experiments did not yield reproducible results. An explanation for these negative results could be very low copy numbers for the murine PRV-1 mRNA in the developing embryos which are below the detection level of the Digoxygenin-based assay used here. Another possibility which can’t be ruled out is a rather uniform expression pattern of the PRV-1 mRNA in the different embryonal tissues. This would explain the high levels of “background-staining” in hybridisation experiments with the labelled PRV-1 probes as compared to the rather clear results when using the an FHL-2 labelled probe as a positive control. Nevertheless, expression of the mPRV-1 mRNA could be demonstrated from embryonic day 6.5 on by RT-PCR experiments (Figure 4.1). The high degree of homology between human and murine PRV-1 protein as well as the corresponding genomic localisation of the
137 two homologues (Klippel, unpublished results), suggests equivalence with respect to the protein function. One major project in this work was the generation of transgenic mice, expressing the human and the murine PRV-1 protein in their haematopoietic system. For this purpose the concerning promoter construct should ensure pan-haematopoietic transgene expression. Following extensive literature-screening two recently described constructs turned out to be well-suited for this project. The first expression construct was based on the well characterised vav promoter and has been shown to provide transgene expression in all mature haematopoietic cell lines. In contrast, outside this compartment only embryonic stem cells, developing teeth, testicular germ cells and the extra-embryonic trophoblast express the transgene (25,96,153,214). Another targeting system which was used for the generation of transgenic mice contains regulatory elements derived from the promoter of the H2K gene, a member of the MHC complex. In several publications H2K expression constructs were used to obtain transgene expression in the haematopoietic compartment and, in addition, in all cells expressing MHC class I (51). Following sequence verification of the hPRV-1 and mPRV-1 expression constructs these were micro-injected into male pronuclei of isolated embryos. Transgenic offspring obtained in these microinjections was further backcrossed with wild-type FVB-mice. For the human PRV-1/Vav construct two different founder lines (# 145 and # 253) were generated to exclude founder effects concerning phenotypical features of the transgenic animals. Crossbreeding of transgenic animals was performed until the F4 generation. Expression of the transgene could be demonstrated on RNA level for both hPRV-1/Vav founder lines (Figure 4.9). Using multi-colour FACS analysis expression of the human transgene could be demonstrated in cells derived from the granulocytic/monocytic lineage as well as on natural killer cells and mature T- lymphocytes (Figures 4.13 – 4.15). One founder-line was generated for the hPRV-1/H2K construct. In analogy to the hPRV-1/Vav transgenic mice FACS analysis was performed. Single colour analysis revealed only little, if any expression of the transgene in peripheral blood from transgenic offspring, whereas multi-colour analysis failed to demonstrate any transgene expression. A possible explanation could be an inappropriate genomic integration site in this founder-line which does not allow regular expression of the
138 transgene. Due to the positive results obtained in FACS analysis for the hPRV-1/Vav transgenic mice the H2K founder-line was discontinued and further experiments were based only on the Vav construct. For analysis of haematological parameters transgenic mice derived from the F3 and F4 generation of both hPRV-1/Vav founder lines were shipped to the Faculty of Veterinary Medicine at the Ludwig Maximilian University in Munich. In both strains significant differences could be observed between transgenic and wild-type animals with respect to different blood parameters (Table 4.2, Figures 4.18 and 5.1). These include increased granulocyte counts. However, the lymphocyte counts in these mice are reduced, what in turn leads to white blood cell counts which resemble those obtained in wild-type FVB mice. Significant changes can also be observed for different parameters related to iron homeostasis. In both lines the serum levels for ferritin, the major iron-storage molecule in liver, spleen, serum and peripheral blood are significantly increased, a phenomenon which indicates iron-overload. This, in turn can be a sign of chronic inflammatory or infectious conditions, release of ferritin by damaged cells and occurs also in haemochromatosis (88). With respect to cell damage, the significantly elevated levels for lactate dehydrogenase (LDH) in animals from the founder line # 253 could result from lysis of blood cells thereby liberating ferritin into serum. In addition to elevated serum ferritin, animals derived from founder line # 145 show also significantly elevated serum iron levels and reduced serum transferrin, a pattern which rather points to a haemochromatosis-like phenotype of these animals. Haemochromatosis is a hereditary autosomal recessive iron-overload disorder associated with mutation of the HFE gene (62). The clinical features include early progressive expansion of the plasma iron compartment, apparently caused by inappropriate iron release, progressive parenchymal iron deposits with the potential for severe organ damage but unimpaired erythropoiesis. As in polycythaemia vera the therapy is mostly based on therapeutic phlebotomies. With respect to the transgenic animals which overexpress the murine PRV-1 gene in the haematopoietic system, the same process for phenotyping as in the hPRV-1 transgenic mice will be performed. The results obtained here indicate significant changes in the blood parameters of both hPRV-1/Vav transgenic lines which seem to be more distinct in the founder line # 145. Further analysis will bring up more insight into the phenotype of these mice.
139 To reduce the probability of founder-effects in the two transgenic lines, the animals will be backcrossed with wild-type littermates before ongoing analysis. The rather mild haematopoietic phenotype of the hPRV-1 transgenic mice in this work does not argue for a key-role of PRV-1 in the pathogenesis of PV. Contribution of PRV-1 overexpression to distinct pathophysiological features in a multistep process would be a possible explanation for some heterogeneity in the clinical manifestation of PV.
140 7.2 cDNA Microarray Analysis of PV Patients The heterogeneous nature of polycythaemia vera as well as of the other myeloproliferative disorders reveals the limitations of molecular characterisation procedures which are based only on a single molecular marker. Despite the fact that polycythaemia vera has been described 100 years ago, the molecular etiology of this disorder remains unknown. Due to this the therapy options are non-specific and can cause severe side-effects as the transformation to acute leukemia. The characterisation of changes in gene expression which are specific for PV allows the identification of candidate genes involved in the pathophysiology of the disorder and might facilitate rational drug design. Beside this, it allows the formulation of hypotheses about changes in signal transduction cascades and transcription factor activation, which may underlie disease development. As described in section 4.3.2 of this work a group of 64 class predictor genes has been established which allow a perfect discrimination between PV patients (primary polycythaemia) and individuals with secondary erythrocytosis. Therefore, these genes represent a specific molecular signature for PV, different from that recently proposed by Pellagatti et al. (156). This research group did not investigate patients with SE, and hence their signature contains many genes which are not specific to PV. The authors define a molecular signature for the diagnosis of PV patients which consists of 11 genes being consistently upregulated in patients with respect to healthy controls. 9 out of these genes were also included in the arrays performed here and as observed by Pellagatti et al., these genes were upregulated in PV patients. Nevertheless, application of hierarchical clustering analysis using these 9 genes on our cohort of 40 PV and 12 SE patients did not result in a distinct separation of these diagnostically relevant groups as shown in Figure 5.3. This demonstrates the requirement of defining a molecular signature for PV not by comparing gene expression patterns in patients with those in healthy controls and underlines the predictive power of the molecular signature which is described in section 4.3.2.
Functional classification of 253 genes which turned out to be upregulated in PV with respect to healthy controls revealed that many genes are controlled by members of the SP1 family of transcription factors (Table 4.5 and Figure 4.26). We thus propose that altered activity of one or several SP1-like transcription factors may contribute to 141 the molecular etiology of PV. In a follow-up study of these findings, the transcriptional activities of some SP1-like factors in PV are currently being analysed in electrophoretic mobility shift assays (EMSA). SP1 is a GC-Box binding zinc finger transcription factor. It was firstly described in 1983 (54). SP1 binding sites have been described in a large number of promoters such as housekeeping genes, myeloid-specific and cell cycle-regulated genes (91). For some time this transcription factor was generally accepted to be an extremely versatile protein which is involved in the expression of many different genes documented by more than 2600 citations. More recently, however, it became clear that SP1 is not the only protein acting through SP1-binding sites but simply represents the first identified and cloned protein of a small protein family. Currently this family consists of four proteins designated SP1, SP2, SP3 and SP4 (179). Cooperative as well as antagonistic effects have been described between the members of this family. For example it has been shown that SP1 and SP3 can compete for the same binding sites. A high SP1:SP3 ratio seems to result in transcriptional activation, whereas a low ratio causes transcriptional repression (66,77,110,114,118,119). In addition to SP1 some other transcription factors, including BTEB1, TIEG1 and TIEG2 were found to bind to the classical GC box (37,84). Nevertheless, upregulation of several genes with common promoter elements provides challenging starting points for further studies. For example, the SP1 binding site in the promoter for the human PRV-1 gene is currently being characterised by another lab member using electrophoretic mobility shift assays (EMSA) in PV patients and healthy controls.
The upregulation of a number of genes which play a role in carbohydrate metabolism might be involved in the clinical phenomenon of artificial hypoglycemia which can be observed in patients with PV. In this context the elevated number of blood cells in PV causes autoglycolysis due to elevated glucose consumption (11,127,210). A rather secondary finding seems to be the overexpression of some acute phase proteins and mediators of inflammation and host defense. This could possibly reflect a pro-inflammatory stage induced by the high leukocyte counts in PV patients.
Another group of genes which turned out to be overexpressed in PV patients contains several proteases and protease inhibitors as neutrophil elastase, secretory leukoprotease inhibitor (SLPI), monocyte/neutrophil elastase inhibitor (MNEI) and α-1
142 antitrypsin. Elevated cellular and serum protein levels for neutrophil elastase, an enzyme involved in the inflammatory response mediated by neutrophil granulocytes have recently been described in patients with polycythaemia vera (61). Upon activation of neutrophils two major serine proteases are secreted, cathepsin G and elastase (202). One major target of elastase is the growth factor G-CSF which plays an important role in the regulation of neutrophil granulopoiesis. It has been shown that secretion of neutrophil elastase can lead to the degradation of G-CSF thereby impairing its growth-promoting activity (58) and providing a negative feedback regulation in the context of excess neutrophil activation. Another target of neutrophil elastase is insulin-like growth factor 1 (IGF-I). The insulin-like growth factor (IGF) system regulates proliferation and differentiation of haematopoietic cells. IGFs exert their effects through specific receptors on growing and differentiating blood cells. Hallmark of the IGF system is the interaction of IGFs and IGF-binding proteins (IGFBPs). IGFs stimulate erythrocytes and lymphocytes but also promote leukemic haematopoietic cell proliferation. Hypersensitivity to IGF-I has been implicated as an underlying cause of polycythaemia vera (38). Neutrophil elastase has been shown to selectively cleave IGF-I as well as the corresponding IGF-I binding protein (IGFBP1); in contrast, cathepsin G only cleaves IGF-1 (70). IGFBPs selectively bind IGFs. Therefore, they might act as modulators of IGF action. There are contradictory opinions about stimulatory or repressive effects of IGFBPs on the action of IGFs. In the context of polycythaemia vera it has recently been described that levels for IGFBP-1 in patients are more than 4-fold elevated and that IGFBP-1 stimulates erythroid burst formation in vivo (137). Recently, a relationship between the dominance of the leukemic clone in CML and sensitivity to the antiproliferative effect of neutrophil elastase has been described (59). In coculture experiments it was shown that CD34 positive precursor cells from CML patients are less sensitive to the growth-inhibitory effect of elastase than those derived from healthy controls. The authors hypothesise that enhanced production of elastase could provide a growth promoting effect for the leukemic clone as compared to the Philadelphia negative cell population. As polycythaemia vera is also caused by the clonal expansion of a single haematopoietic stem cell, a similar assay using CD34 positive progenitor cells from PV patients would be a challenging experiment. Unfortunately, evaluation of the coculture experiments as performed by Ouriaghli et
143 al. is based on the FISH technique (fluorescence in-situ hybridisation) which requires a selection marker like the Philadelphia chromosome in CML to distinguish between normal cells and those which derived from the malignant clone. In the context of neutrophil elastase three other genes which were found to be overexpressed in PV patients seem to be of interest. The three protease inhibitors SLPI (secretory leukoprotease inhibitor), MNEI (monocyte/neutrophil elastase inhibitor) and α-1 antitrypsin (SERPINA1) have a high affinity for neutrophil elastase, trypsin and chymotrypsin, all of which are known to induce apoptosis in neutrophils in the context of inflammation (190). Protease inhibitors play an important role in modulation of the inflammatory response especially by prevention of epithelial damage based on proteolytic enzymes and might thereby confer a growth advantage to neutrophils in PV patients. SLPI for example is induced by high levels of neutrophil elastase as a negative feedback mechanism (1). One major characteristic of polycythaemia vera as well as other haematological disorders is the colony formation of haematopoietic progenitor cells in serum-free medium. In contrast, for growth and differentiation of normal haematopoietic progenitor cells in serum-free medium additional factors like insulin and albumin are required. Normal BSA is frequently used as a source for albumin but it is not 100% serum-free. Therefore undefined proteins bound to albumin can significantly contribute to colony formation. In a study performed in 1996 (71) highly purified clinical grade albumin was used together with serum-free conditioned medium from a carcinoma cell-line which compensates for serum in the colony assays and allows colony growth. By performing HPLC fractionation of the conditioned medium the authors have defined a 15 kD protein as essential for the growth of CFU-GM and BFU-E colonies. This protein was defined as SLPI. The same growth supportive effect could be obtained by addition of α-1 antitrypsin to the cell culture medium which is another inhibitor of neutrophil elastase. These observations, taken together could indicate a possible role of the network built up by neutrophil elastase and several protease inhibitors concerning growth and differentiation of haematopoietic progenitor cells.
A much higher proportion of genes are significantly underexpressed in PV patients with respect to healthy controls. As most of these genes are involved in protein biosynthesis, this might be a hallmark for the rather indolent nature of PV as compared to acute leukaemias.
144 Using additional gene data from the National Center for Biotechnology Information (NCBI) clusters of coexpressed genes distributed among the human chromosomes were identified. 23 clusters with more than six coordinately up- or downregulated genes among the whole genome of PV patients could possibly indicate the occurrence of epigenetic effects such as changes in the DNA methylation pattern as a cause of differential gene expression in addition to basic transcriptional regulation (Figures 4.28 and 5.2). This hypothesis provides a starting point for ongoing studies. As a first approach, establishment of the ChIP technology (Chromatin Immunoprecipitation) has been initiated.
The most promising candidate gene concerning the pathogenesis of PV is the transcription factor NF-E2 (nuclear factor erythroid 2). In the microarray results it was first encountered in the context of its 2.8-fold upregulation in PV patients and the presence of a potential SP1 binding site (158) in the promoter region (Figure 4.26). In these experiments overexpression of NF-E2 occurred in 37 out of the 40 PV patients (92.5%). Verification experiments using Northern Blot analysis confirmed these results in 10 out of 13 PV patients compared to 10 healthy controls (Figure 4.29). In addition, TaqMan® Quantitative RT-PCR analysis was performed with cDNAs from 20 PV patients (8 already included in the microarray analysis; 12 newly diagnosed) and 10 healthy controls (Figure 4.32). Except for one patient who displayed normal levels for the NF-E2 mRNA all PV patients showed elevated expression compared to the healthy controls. Overexpression of the NF-E2 mRNA in PV patients varies from 2.3 to 40 fold as judged by the TaqMan® data with a median increase of 7 fold. Western Blot analysis of to date 7 PV patients and 2 healthy controls underlined the data obtained on the RNA level in 5 out of 7 PV patients (Figure 4.33). One of the two patients who did not express the NF-E2 protein was also tested by Northern Blot analysis where no overexpression on the RNA level could be observed. Immunohistochemistry performed on bone marrow biopsies from 8 PV patients and 6 healthy controls has demonstrated overexpression of NF-E2 protein in megakaryocytic as well as in erythroid and granulocytic precursor cells (Figure 4.34). The basic-leucine zipper protein NF-E2 recognizes an extended binding site for the ubiquitous transcription factor AP1 (136) and was first identified by its tissue-specific DNA binding activity in murine erythroleukaemia cells (MEL). NF-E2 binding sites have been described in the alpha- and beta-globin locus control regions (LCR) and several other enzymes of haeme biosynthesis (39,87,136,147,181). Transcriptionally 145 active NF-E2 protein is a heterodimer of a cell-type specific 45 kDa subunit and a ubiquitous 18 kDa subunit of the Maf protein family. Expression of NF-E2 could be demonstrated in different haematopoietic cell lines as K562 and HEL (erythroid) and KG-1 and HL-60 (myeloid) as well as in the monocytic cell line U937. Relatively high levels could be found in fetal liver, adult bone marrow, peripheral blood mononuclear cells (146) and megakaryocytes (8,116). In addition, Toki et al. have described expression of NF-E2 mRNA in human peripheral granulocytes (189). Therefore, the expression pattern of NF-E2 across the haematopoietic compartment reflects exactly those blood cell lines which are affected in PV. In 1995 the first experiments suggesting a possible role of NF-E2 in erythroid differentiation were published (111). Labbaye et al. have analysed expression of NF- E2 and the related transcription factors GATA-1 and GATA-2 during the differentiation process of purified early haematopoietic progenitor cells (HPCs). Using lineage-specific growth factors these cells were driven into erythroid or granulocytic differentiation. NF-E2 mRNA and protein were undetectable in quiescent HPCs. During early erythroid and granulocytic differentiation the levels increased. In the late differentiation/maturation stage erythroid expression was sustained whereas a gradual suppression was observed in granulocytes. Based on these results the effect of targeted suppression of NF-E2 was checked in colony forming assays using antisense oligonucleotides. In contrast to anti-GATA-1 and anti-GATA-2 which inhibited the growth of both, erythroid and granulocytic/macrophage colonies, anti- NF-E2 showed a selective inhibition of erythroid colony growth. The generation of NF-E2 knockout mice has resulted in surprising findings (117,172,172,173). The erythroid phenotype in these animals is rather mild with only modest anaemia and decreased haemoglobin content in neonates; in contrast, the most notable feature was arrested megakaryocyte maturation leading to the absence of circulating platelets. These results implicate a critical function for NF-E2 in regulating megakaryocytic differentiation in addition to its role in erythroid development. This would be in close accordance with the phenotype observed in PV where erythrocytosis coincides with a varying degree of thrombocytosis. In 2000 Sayer et al. have published results on the effect of ectopically expressed NF- E2 in myeloid and erythroid cells (167). J2E erythroid and M1 monoblastoid cells have the potential to show lineage-switching under certain conditions (22,95,100,123,188). Ectopic expression of NF-E2 in J2E cells resulted in increased
146 proliferation, erythroid maturation and reduced haemoglobin synthesis without addition of erythropoietin whereas normal J2E cells are dependent on EPO. In the M1 cell line monocytic cells switched to an erythroid or megakaryocytic phenotype. These results are in concordance with varying levels of the GATA-1 and EKLF (erythroid Krueppel-like factor) during differentiation of J2E cells (23,176) and suggest a model in which balanced expression of different transcription factors at distinct time points is crucial for progression along the erythroid maturation pathway. Probably the most notable finding of Sayer et al. is the growth of erythropoietin independent colonies in cultures of primary haematopoietic progenitor cells from fetal liver overexpressing NF-E2 which is in analogy to the occurrence of endogenous erythroid colonies (EECs) in PV patients. Summarizing the observations in this work and published data, the transcription factor NF-E2 seems to be in very close proximity to the phenotype which is observed in PV and might therefore help to elucidate the pathomechanism of this disease. As a model, overexpression of NF-E2 in PV precursors could cause an imbalance in the transcriptional machinery of these cells. This, in turn leads to elevated erythrocyte counts which are in some patients accompanied by increased numbers of megakaryocytes and platelets. NF-E2 as a potential key molecule in the pathogenesis of PV would provide a variety of starting points for ongoing projects. Transgenic mice overexpressing the human or the murine NF-E2 gene in their haematopoietic system could yield valuable information about the contribution of NF-E2 dysregulation to the phenotype of PV. In addition, experiments with haematopoietic progenitor cells from these animals in colony forming assays can provide insight into the phenomenon of EEC growth in PV patients. Beside this, in analogy to the antisense experiments performed by Labbaye et al. (111) suppression of NF-E2 expression in EEC assays using siRNA (small interfering RNA) would be another promising experiment to test the findings of Sayer et al. concerning EPO-independent colony growth (167) in progenitor cells from PV patients. In order to evaluate possible dose-dependent effects of NF-E2 expression in PV the retrospective analysis of untreated PV patients could answer the question if the extent of NF-E2 protein expression correlates with the degree of erythrocytosis and the presence or absence of thrombocytosis. The mechanism by which Anagrelide® exerts its lowering effect on megakaryocyte counts in PV patients remains obscure. Due to the previously discussed observations
147 in knockout mice, NF-E2 would be a promising candidate for a possible target of this drug. Cell culture experiments using primary cells from PV patients and incubation with Anagrelide® could be a first attempt to evaluate a possible role of this transcription factor in mediation of the Anagrelide® response in PV.
Taken together, the findings obtained in the cDNA microarray experiments point to a multifactorial process for the pathogenesis of PV with a number of separately acquired mutations in which the transcription factor NF-E2 might play a key role. The different molecular events might occur at earlier or later time-points during the maturation process of haematopoietic progenitor cells what in turn would cause a more widespread manifestation in different mature blood cell lineages or expression in only distinct blood cell populations. Therefore, some clinical and laboratory findings as artificial hypoglycemia or the formation of Endogenous Erythroid Colonies (EECs) in the absence of erythropoietin might be caused by different molecular events. These, in turn, could lead to the differential expression of groups of genes what results in the observed phenotype. The dysregulation of transcription factors or families of transcription factors provides an attractive model for the distinct gene expression profile in PV patients, including overexpression of the PRV-1 mRNA in about 100% of all PV patients.
148 7.3 Molecular Characterisation of ET Patients Differential diagnosis of the myeloproliferative disorders is mostly based on exclusion criteria. In addition, transitions between the different members of this group are observed during disease progression (73,169,177). Patients who are diagnosed with polycythaemia vera share some molecular features with ET patients. Among those are elevated mRNA levels for PRV-1 in granulocytes as well as decreased protein levels for the thrombopoietin receptor c-Mpl in platelets. In order to answer the question if c-Mpl protein and PRV-1 mRNA expression define the same subgroups, 48 ET patients were tested for the two markers. As a result it was shown that both alterations are acquired independently: four different subgroups of ET patients can be defined by c-Mpl protein and PRV-1 mRNA expression (Figure 4.36). Thrombotic complications are the major cause of mortality in patients with essential thrombocythaemia. For risk stratification of ET patients different clinical criteria including age, platelet count and the history of previous thromboembolic complications are currently used. In order to evaluate a possible predictive role of the four subgroups of ET patients defined by c-Mpl protein and PRV-1 mRNA expression a retrospective analysis regarding the occurrence of thromboembolic complications in the cohort of 48 ET patients was performed. A significantly increased risk of such complications could be found in PRV-1 positive patients (Table 4.7 and Figure 4.37). These data corroborate and extend two recently published studies in which an increased risk of thromboembolic complications in PRV-1 positive ET patients compared to PRV-1 negative patients has been shown (73,89). Here it is demonstrated that within the group of PRV-1 positive ET patients, those with normal c-Mpl levels appear to be at highest risk for thromboembolic events. This retrospective analysis must now be confirmed in a large prospective trial of newly diagnosed patients. Such a trial is currently being implemented by the MPD Research Consortium. The ability to grow Endogenous Erythroid Colonies (EECs) is a major characteristic of PV patients; in addition, a subset of ET patients also shows this phenomenon. The same is the case for clonal haematopoiesis in PV which can also be observed in 50% of ET patients. In a cohort of 12 female ET patients the co-occurrence of clonal haematopoiesis and the overexpression of PRV-1 mRNA could be demonstrated (Table 4.8).
149 Regarding the predictive role of clonality for the risk of thrombotic complications (171) these studies imply a model in which ET patients form two distinct subgroups: One is characterised by normal PRV-1 levels, the absence of EECs and polyclonal haematopoiesis. In contrast, the other group displays elevated PRV-1 mRNA levels, grows EECs and shows clonal haematopoiesis. The finding that PRV-1 positive ET patients will transform to PV during progression of disease (170) support the hypothesis that this latter group defines patients in the early stage of PV rather than “true” ETs because they do not yet show all clinical features of PV. As a first step to prove this assumption cDNA microarrays were performed with granulocyte RNA from one PRV-1 positive and one PRV-1 negative ET patient. As the microarray technology is based on analysis of several thousands of genes in the same experiment, this method seems to be well-suited to assign new samples to patient groups which are defined by molecular signatures and not by the current clinical manifestation of the patient (stage of the disease). Hierarchical clustering analysis of these two ET patients using the 64 class predictor genes defined in the cohort of 10 PV and 10 SE patients gave a clear classification of the PRV-1 positive ET patient among the PVs whereas the PRV-1 negative ET patient did not show significant similarity concerning gene expression (Figure 4.38). The clinical history of this PRV-1 positive ET patient seems to support the previously generated hypothesis of an early stage of PV: The patient was initially diagnosed as an ET due to an elevated platelet count but normal haematocrit. During re-examination of the clinical record after 20 years it turned out that the haematocrit, while within the normal range exceeds that which is allowed for a diagnosis of ET today. Together with the cytoreductive treatment (busulfan) which lowers the haematocrit it is very likely that this patient would be diagnosed as a polycythaemia vera today. It must be kept in mind that only two ET patients have been analysed to date using the cDNA microarrays. Due to technical limitations (small blood samples), it was not possible to analyse other ET patients which are presented in this work using this very efficient technology. Nevertheless, together with the findings concerning PRV-1 expression, EEC growth and clonality as mentioned before, the subdivision of ET patients into two groups seems to be very likely: one subset shows an overexpression of the PRV-1 mRNA, a PV-like gene expression profile and will develop polycythaemia vera during progression of the disease, the other represents the classical ET-like phenotype. The hypothesis of two different gene expression
150 profiles within the cohort of ET patients is further underlined by the finding that the human proto-oncogene Pim-1 which is highly overexpressed in granulocytes of PV patients with respect to healthy controls (Figure 4.29) also shows elevated levels in PRV-1 positive ET patients (Figure 4.39). Ongoing experiments are initiated to study gene expression profiles in a larger cohort of about 25 ET patients. This study has been organised in collaboration with different clinical centres in Sweden; the local ethics committee has accepted the requirement for larger blood samples from these patients. The experiments will be performed by Britta Will in cooperation with the Microarray Core Facility (G. Walz, Dept. of Nephrology, University Hospital, Freiburg).
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165 9. Abbreviations
• °C Degree Centigrade • µ Micro • a Year • ALL Acute Lymphoblastic Leukemia • AML Acute Myelogenous Leukaemia • amp Ampicilline • APS Ammonium Peroxodisulfate • ATP Adenosine 5‘ Triphosphate • BFU-E Burst Forming Unit-Erythroid • bp Base pairs • BSA Bovine Serum Albumin • CD Cluster Designation • cDNA Complementary DNA • cds Coding sequence • CFU-E Colony Forming Unit-Erythroid • CFU-GM Colony Forming Unit-Granulocyte/Macrophage • CML Chronic Myelogenous Leukaemia • CMPD Chronic Myeloproliferative Disorder • c-MPL Thrombopoietin receptor
• CT Cycle of Threshold • CTP Cytidine 5‘ Triphosphate • dATP Desoxyadenosine 5‘ Triphosphate • dCTP Desoxycytidine 5‘ Triphosphate • dd Double destilled • ddNTP Didesoxynucleoside triphoshpate • DEPC Diethyl Pyrocarbonate • dGTP Desoxyaguanosine 5‘ Triphosphate • DIG Digoxigenin • DMEM Dulbecco’s Modified Eagle Medium • DMSO Dimethyl Sulfoxide • DNA Desoxyribonucleic Acid • dNTP Desoxynucleoside 5‘ Triphosphate • DTT Dithiothreitol • dTTP Deoxythymidine 5‘ Triphosphate • E Embryonic day • EDTA Ethylendiamine Tetraacetic Acid • EEC Endogenous Erythroid Colony • ELISA Enzyme-Linked Immunosorbant Assay • EPO Erythropoietin • EPO-R Erythropoietin Receptor • ET Essential Thrombocythaemia • EtOH Ethanol • FACS Fluorescence Activated Cell Sorter • FAM 5-Carboxyfluorescein Succinimidyl Ester • FCS Fetal Calf Serum • FDR False Discovery Rate • FITC Fluorescein Isothiocyanate • fwd Forward • g Gravitational force, gramm • GAPDH Glycerinaldehyde-3-Phosphate Dehydrogenase • GC Gene Clean • G-CSF Granulocyte-Colony Stimulating Factor • GPI Glycosyl-Phosphatidyl-Inositol • GTC Guanidinium Isothiocyanate • GTP Guanosine 5‘ Triphosphate • h hour • Hb Haemoglobin • HC healthy control • Hin Haemophilius influenzae 166 • HPCs Haematopoietic Progenitor Cells • HRP Horseradish Peroxidase • HSC Haematopoietic Stem Cell • HU Hydroxyurea • IFN Interferon • IGF-1 Insulin-like Growth Factor-1 • IL-1, -2, -3, -4, -5, -6, -7 Interleukine-1, -2, -3, -4, -5, -6, -7 • IMF Idiopathic Myelofibrosis • kb Kilo base pairs • kD Kilo Dalton • l Litre • LBM Lean Body Mass • LOH Loss Of Heterocygocity • LPS Lipopolysaccharide • Ly6 Lymphocyte antigen 6 • m milli • M mol/l • MCS Multiple Cloning Site • MeOH Methanol • min Minutes • mol Mole • MOPS 3-(M-morpholino) propanesulfonic acid • MPD Myeloproliferative Disorder • mRNA Messenger RNA • n Nano • N Normality • NaAc Sodium Acetate • NaCl Sodium Chloride • NB1 Neutrophil-specific biallelic antigen 1 • NEB New England Biolabs • NN Nearest Neighbour • Not Nocardia Otitidis Caviarum • OMF Osteomyelofibrosis • ORF Open Reading Frame • p Pico • PAGE Polyacrylamide Gelelectrophoresis • PBS Phosphate Buffered Saline • PCR Polymerase Chain Reaction • PE R-Phycoerythrin • PFA Paraformaldehyde • Pfu Pyrococcus furiosus • pH potentia hydrogenii • Ph+/- Philadelphia Chromosome positive/negative • PMSF Phenylmethylsulfonyl Fluoride • PRV-1 Polycythaemia Rubra Vera-1 • PV Polycythaemia rubra vera • PVSG Polycythaemia Vera Study Group • RCM Red Cell Mass • rev Reverse • RNA Ribonucleic Acid • rpm Revolutions per minute • rRNA Ribosomal RNA • RT Reverse Transcription, RoomTemperature • RZPD Resource Center and Primary Database, Berlin, Germany • SDS Sodium Dodecyl Sulfate • SE Secondary Erythrocytosis • sec seconds • SSC Saline Sodium Citrate • TAE Tris-acetate/EDTA
• TAn Annealing Temperature • Taq Thermus Aquaticus • TBS Tris-buffered Saline
167 • TBST Tris-buffered Saline containing Tween® 20 • TPO Thrombopoietin • Tris Tris(hydroxymethyl)aminomethane • U Units • UPN Unique Patient Number • UTP Uridine 5‘-Triphosphate • UTR Untranslated Region • UV Ultraviolet • V Volts • v/v Volume per volume • w/v Weight per volume • WHO World Health Organisation • WT Wild Type
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