ALBERT-LUDWIGS-UNIVERSITÄT FREIBURG IM BREISGAU
JAK Pathway Inhibition as a Novel Therapeutic Strategy in Peripheral T-Cell Lymphomas with Associated Inflammation
INAUGURAL-DISSERTATION zur Erlangung der Doktorwürde der Fakultät für Biologie und der Medizinischen Fakultät der Albert-Ludwigs-Universität Freiburg im Breisgau
vorgelegt von
Amelie Jäger, geb. Proske geboren in Unna
Freiburg im Breisgau, Dezember 2018
Dekan der Fakultät für Biologie: Prof. Dr. Wolfgang Driever Dekan (kommissarisch) der Medizinischen Fakultät: Prof. Dr. Norbert Südkamp
Promotionsvorsitzender: Prof. Dr. Andreas Hiltbrunner
Betreuer der Arbeit: PD Dr. Christine Dierks
Referent: PD Dr. Christine Dierks Koreferent: Prof. Dr. Robert Zeiser Drittprüfer: Prof. Dr. Tilman Brummer
Datum der mündlichen Prüfung: 26.02.2019
Diese Arbeit wurde erstellt in der Abteilung für Innere Medizin I, Hämatologie/Onkologie des Universitätsklinikums der Albert-Ludwigs-Universität Freiburg unter der Leitung von PD Dr. Christine Dierks.
Erklärung
Ich erkläre hiermit, dass ich die vorliegende Arbeit ohne unzulässige Hilfe Dritter und ohne Benutzung anderer als der angegebenen Hilfsmittel angefertigt habe. Die aus anderen Quellen direkt oder indirekt übernommenen Daten und Konzepte sind unter Angabe der Quelle gekennzeichnet. Insbesondere habe ich hierfür nicht die entgeltliche Hilfe von Vermittlungs- beziehungsweise Beratungsdiensten (Promotionsberater oder anderer Personen) in Anspruch genommen. Niemand hat von mir unmittelbar oder mittelbar geldwerte Leistungen für Arbeiten enthalten, die im Zusammenhang mit dem Inhalt der vorgelegten Dissertation stehen.
Die Arbeit wurde bisher weder im In- noch im Ausland in gleicher oder ähnlicher Form einer anderen Prüfungsbehörde vorgelegt.
Die Bestimmungen der Promotionsordnung der Fakultät für Biologie und der Medizinischen Fakultät für Absolventen des interfakultären Diplomstudienganges Molekulare Medizin der Universität Freiburg sind mir bekannt; insbesondere weiß ich, dass ich vor Vollzug der Promotion zur Führung des Doktortitels nicht berechtigt bin.
______Amelie Jäger Table of contents I
Table of contents
Table of contents ...... I
1 Summary ...... 1
2 Introduction ...... 2
2.1 T-cell lymphomas (TCLs) ...... 2
2.1.1 Classification of TCL subtypes ...... 2
2.1.2 Incidence, etiology and morphological features of PTCL ...... 2
2.1.3 Inflammation in PTCL ...... 4
2.1.4 Standard treatment strategies and new therapeutic approaches in PTCL ...... 5
2.2 PTCL biology ...... 6
2.2.1 Normal T-cell development ...... 6
2.2.2 T-cell receptor signaling in normal T-cells and PTCL...... 8
2.2.3 Immunophenotype of PTCL subtypes ...... 10
2.3 ITK-SYK kinase fusion in PTCL-NOS ...... 11
2.3.1 ITK and SYK in TCR signaling ...... 12
2.3.2 ITK-SYK mouse models ...... 13
2.4 Janus kinase (JAK) signaling pathway ...... 14
2.4.1 JAK / signal transducer and activator of transcription (STAT) signaling overview ...... 14
2.4.2 JAK/STAT signaling in normal CD4 + T-helper cell differentiation ...... 17
2.4.3 Aberrant JAK/STAT signaling in TCL ...... 19
2.4.4 Aberrant JAK/STAT signaling in myeloid malignancies ...... 20
2.4.5 JAK inhibitors in the treatment of TCL and MPN ...... 21
3 Aims of the study ...... 22
4 Materials ...... 23
4.1 Laboratory equipment and disposables ...... 23 Table of contents II
4.1.1 Equipment ...... 23
4.1.2 Disposables ...... 24
4.2 Chemicals and reagents ...... 25
4.3 Buffers and solutions ...... 27
4.4 Media ...... 29
4.5 Kits ...... 29
4.6 Cell lines ...... 30
4.6.1 Human cell lines ...... 30
4.6.2 Murine cell lines ...... 30
4.7 Primary human TCL specimen ...... 30
4.8 Antibodies ...... 30
4.8.1 Cell depletion ...... 30
4.8.2 Flow cytometry ...... 30
4.8.3 Co-Immunoprecipitation and western blot ...... 31
4.8.3.1 Primary antibodies ...... 31
4.8.3.2 Secondary antibodies ...... 31
4.8.4 Immunohistochemistry ...... 32
4.8.4.1 Primary antibodies ...... 32
4.8.4.2 Secondary antibodies ...... 32
4.9 Plasmids ...... 32
4.10 Inhibitors ...... 32
4.11 Mouse strains and husbandry ...... 32
4.12 Databases ...... 33
4.13 Software and tools ...... 33
5 Methods ...... 35
5.1 In vitro experiments ...... 35
5.1.1 Cell culture ...... 35
5.1.1.1 Thawing, cultivating and freezing of cells ...... 35 Table of contents III
5.1.1.2 Cell counting ...... 35
5.1.1.3 Serum and growth factor starvation ...... 35
5.1.2 Retroviral transduction of non-adherent cell line D10.G4.1 ...... 36
5.1.2.1 Production of retrovirus ...... 36
5.1.2.2 Retroviral transduction of a murine T-cell line ...... 36
5.1.2.3 Cell sorting ...... 37
5.1.3 Protein analysis ...... 37
5.1.3.1 Isolation of total protein and determination of protein concentration ...... 37
5.1.3.2 SDS-PAGE ...... 38
5.1.3.3 Western blot and detection ...... 38
5.1.3.4 Co-Immunoprecipitation ...... 38
5.2 In vivo experiments ...... 39
5.2.1 Bone marrow transplantation (ITK-SYK mouse model) ...... 39
5.2.1.1 Enrichment, isolation and cultivation of primary murine BM cells ...... 39
5.2.1.2 Production of retrovirus ...... 39
5.2.1.3 Retroviral transduction of primary murine BM cells ...... 40
5.2.1.4 Irradiation of recipients ...... 40
5.2.1.5 BM transplantation ...... 40
5.2.2 Bone marrow retransplantation (ITK-SYK mouse model) ...... 41
5.2.3 Bone marrow transplantation (xenograft model) ...... 41
5.2.3.1 Isolation of primary patient PBMCs by Pancoll ...... 41
5.2.3.2 Transplantation ...... 41
5.2.4 Bone marrow retransplantation (xenograft model) ...... 41
5.2.5 Treatment experiments ...... 41
5.2.5.1 Treatment with granulocyte-depleting antibody ...... 41
5.2.5.2 Treatment with Pacritinib or Ruxolitinib in ITK-SYK mouse model ...... 42
5.2.5.3 Treatment with Ruxolitinib in xenograft mouse model ...... 42
5.2.6 Blood withdrawal and processing ...... 42 Table of contents IV
5.2.7 Mouse follow-up, determination of phenotypic score and survival analysis ...... 42
5.2.8 Mouse sacrifice ...... 43
5.2.9 Mouse organ preparation and processing ...... 43
5.2.10 Flow cytometry ...... 44
5.2.10.1 Extracellular stainings ...... 44
5.2.10.2 Intracellular stainings ...... 50
5.2.10.3 Cell sorting ...... 51
5.2.11 Cytokine arrays ...... 51
5.2.12 Histopathology and immunohistochemistry ...... 51
5.2.12.1 Immunohistochemistry staining using anti-CD3 antibody with VECTASTAIN ABC HRP Kit ...... 51
5.2.12.2 Immunohistochemistry staining using anti-CD11b antibody with Cytomation EnVision + System-HPR ...... 52
5.2.12.3 Immunohistochemistry staining using anti-CD11b antibody with CSA, Catalyzed Signal Amplification System ...... 52
5.3 Statistical analysis ...... 52
6 Results ...... 53
6.1 ITK-SYK expression in primary bone marrow cells causes T-cell lymphoma in mice ...... 53
6.2 Depletion of granulocytes in ITK-SYK mice improves survival, but does not alter T-cell phenotype ...... 54
6.2.1 Single injection of granulocyte depleting antibody in ITK-SYK mice improves phenotypic score ...... 54
6.2.2 Repeated injection of granulocyte depleting antibody in ITK-SYK mice improves survival, but does not alter T-cell phenotype ...... 55
6.3 Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves ITK-SYK phenotype in vivo ...... 56
6.3.1 Ruxolitinib but not Pacritinib treatment improves external ITK-SYK TCL phenotype ...... 57
6.3.2 Ruxolitinib but not Pacritinib improves body and lung weight of ITK-SYK mice ...... 58
6.3.3 Ruxolitinib but not Pacritinib reduces elevated cytokine levels in ITK-SYK mice ...... 59
6.3.4 Ruxolitinib improves survival in ITK-SYK mice to a higher extent than Pacritinib ...... 61
6.3.5 Ruxolinitib but not Pacritinib decreases ITK-SYK expressing cell percentages in ITK-SYK mice ...... 61 Table of contents V
6.3.6 Ruxolitinib but not Pacritinib reduces myeloid cell infiltration ...... 63
6.3.7 JAK1/2 inhibition has no effect on STAT3 and STAT5 activation in splenic granulocytes of ITK-SYK mice ...... 66
6.3.8 Ruxolitinib but not Pacritinib reduces elevated GMP and CMP but not MEP levels in spleens of ITK-SYK mice ...... 68
6.3.9 Ruxolitinib improves T-cell infiltration of skin in ITK-SYK mice to a higher extent than Pacritinib ...... 70
6.3.10 Retransplantation of CD4 + T-cells of ITK-SYK mice causes a similar phenotype in secondary recipients ...... 71
6.3.11 Ruxolitinib but not Pacritinib normalizes malignant CD4 + T-cell levels in thymi of ITK-SYK mice ...... 72
6.3.12 Ruxolitinib reduces activation of JAK downstream signaling mediators in malignant T-cells to a higher extent than Pacritinib ...... 74
6.3.13 Ruxolitinib but not Pacritinib improves the B-cell phenotype in PB and spleens of ITK-SYK mice ...... 78
6.3.14 Ruxolitinib but not Pacritinib improves T-cell levels in PB but not in spleens of ITK-SYK mice ...... 79
6.4 ITK-SYK drives the activation of JAK1 but not JAK2 in vitro ...... 80
6.5 Simultaneous inhibition of JAK1 and JAK2 is an effective treatment strategy in a human angioimmunoblastic TCL xenograft ...... 82
6.5.1 Ruxolitinib reduces organ weight and cell counts in AITL xenograft mice ...... 83
6.5.2 Ruxolitinib reduces inflammatory responses in AITL xenograft mice ...... 84
6.5.3 Ruxolitinib reduces T-cell lymphoma burden in AITL xenograft mice ...... 86
6.5.4 Ruxolitinib impairs increased hIFNγ and mIL-6 levels in AITL xenograft mice ...... 88
7 Discussion and perspectives ...... 91
7.1 Effects of JAK inhibitors on the PTCL phenotype ...... 91
7.2 Effects of JAK inhibitors on the malignant T-cells ...... 92
7.3 Ruxolitinib as a possible treatment option in PTCLs with TCR over-activation ...... 95
7.4 Effects of granulocyte-depletion and JAK inhibition on PTCL induced inflammation ...... 97
7.5 Cytokine signaling in PTCL ...... 98
7.6 A model of ITK-SYK induced PTCL...... 100
7.7 Future perspectives ...... 102 Table of contents VI
8 References ...... 105
9 Appendix ...... 123
9.1 Supplementary Figures ...... 123
9.2 Abbreviations ...... 125
9.3 List of figures ...... 132
9.4 List of tables ...... 135
9.5 Publications ...... 136
Summary 1
1 Summary Peripheral T-cell lymphomas (PTCLs) carry a dismal prognosis with high relapse rates and mortality due to the lack of targeted therapies and resistance to classical chemotherapies. Many patients with PTCLs present with an inflammatory phenotype which clinically often bestows a higher burden to the patients than the malignant T-cell expansion. This study aimed to find a therapeutic strategy to target both, the malignant T-cells and the inflammatory phenotype using a previously described mouse model of PTCL-NOS driven by the oncogene ITK-SYK and a human angioimmunoblastic T-cell lymphoma (AITL) xenograft model. Ruxolitinib is a tyrosine kinase inhibitor targeting JAK1 and JAK2 and is broadly used for the treatment of myeloproliferative neoplasms. Due to frequently observed hyperactivation of JAK/STAT signaling in peripheral T-cell lymphomas as well as in myeloid neoplasias, the effects of Ruxolitinib in the two PTCL models were investigated. Vehicle treated mice carrying the ITK-SYK oncogene developed lethal T-cell lymphomas within 60 days after transplantation with massive weight loss, visible skin infiltrates and inflammation. Ruxolitinib treated mice survived with only mild signs of disease and stable weight during the whole treatment period. Ruxolitinib treatment normalized the distribution of the ITK-SYK + malignant CD4 + T-cells within the thymus. In addition, a strong decrease of inflammatory cytokines in Ruxolitinib treated mice was observed, and secondary granulocytosis in the peripheral blood as well as granulocytic infiltrates in different organs were reduced. In contrast to Ruxolitinib, Pacritinib, which targets exclusively JAK2, had only minor effects on disease development and prolonged mouse survival for a shorter time period than Ruxolitinib. In addition, only Ruxolitinib but not Pacritinib was able to significantly reduce elevated STAT3 phosphorylation levels in the malignant T-cells. This indicates JAK1 and subsequent activation of STAT3 as the major Ruxolitinib target in malignant transformation which was confirmed by in vitro experiments providing evidence that ITK-SYK expression in a murine CD4 + T-cell line activated JAK1, JAK3, STAT3 and STAT6 but not JAK2, STAT4 and STAT5. This study implicates a positive feedback loop by which the malignant ITK-SYK expressing T-cells activate JAK1/3 STAT3/6 signaling to secrete high amounts of inflammatory IFNγ which in turn activates myeloid cells to secrete IL-6 which then again stimulates further T-cell activation. Ruxolitinib has proven to be a highly effective treatment strategy to interrupt multiple steps of this signaling cascade. Finally, Ruxolitinib treatment of a human AITL xenograft had the same beneficial effects on disease development by inhibiting proliferation of the primary malignant T-cells and subsequent mobilization and release into the PB as well as the expansion of inflammatory myeloid cells and the secretion of inflammatory cytokines. In conclusion, these data imply JAK1/2 co-inhibitor Ruxolitinib as a promising treatment strategy for different PTCL subtypes. Introduction 2
2 Introduction
2.1 T-cell lymphomas (TCLs)
2.1.1 Classification of TCL subtypes T-cell lymphomas (TCLs) are a heterogeneous group of lymphoid malignancies and make up approximately 10-15% of all non-Hodgkin lymphomas (NHLs). 1 They are generally subdivided into two distinct groups depending on the differentiation stage of their cellular origin. Precursor T-cell lymphoblastic leukemia/lymphomas make up approximately 1.7% of all NHLs and arise from immature lymphoblasts committed to the T-cell lineage. 1,2 The larger group of TCLs (9.4% of all NHLs) originates from mature T-cells and is summarized under the term peripheral T-cell lymphoma (PTCL). 3,4 The WHO subdivided PTCLs into four distinct categories depending on their primary site of clinical manifestation. 5,6 These groups themselves are comprised of various disease entities depending on morphology, genetic aberrations, immunohistochemical criteria and clinical course. 7 Cutaneous T-cell lymphomas (CTCLs) including the locally confined mycosis fungoides (MF) and the systemic Szézary syndrome (SS) arise from degenerated T-lymphocytes of the skin. Leukemic T-cell lymphomas like the adult T-cell leukemia/lymphoma are usually widely disseminated. The primarily extranodal PTCLs arise from sites outside the lymph nodes. Here, it is worth mentioning the enteropathy-associated TCL and the hepatosplenic TCL. The last category is the nodal PTCLs. They originate primarily from the lymph nodes and can later disseminate to extranodal sites (= extranodal involvement). 5,6 This subgroup represents the largest PTCL subcategory with PTCL not otherwise specified (NOS), anaplastic large cell lymphoma (ALCL) and angioimmunoblastic TCL (AITL) together making up more than half of all PTCL cases. 8,9
2.1.2 Incidence, etiology and morphological features of PTCL Although PTCLs make up the largest subcategory of TCLs, they are in fact quite rare. The overall incidence of PTCL in the United States of America (US) was estimated with 0.61/100,000 persons per year. Looking at the largest PTCL entities, incidences of AITL, ALCL and PTCL-NOS varied widely between cohorts. 8,9 Interestingly, PTCL occurrences show global variation. 10 PTCLs make up a larger number of NHLs in Asia compared to Western countries and incidences among the subtypes vary considerably between North America, Europe and Asia. 8 Furthermore, US studies revealed diverse disease incidences depending on sex, race and age with the highest overall PTCL disease manifestation in black elderly people with male predominance, though these factors vary widely among the different disease entities. 9,11–15 Introduction 3
AITL, ALCL and PTCL-NOS show the highest incidences of PTCLs, together accounting for more than 50% of all cases. 8,9 Although they resemble entirely different disease entities, they share some common features. Most patients present with varying symptoms, including B-symptoms such as fever, night sweat and weight loss as well as enlarged lymph nodes and skin rash. 6,14,16–21 Due to these unspecific symptoms, PTCLs are often diagnosed in advanced disease stages, sometimes after initial misdiagnosis, which contributes to the poor prognosis and low overall survival. 14,16,18,21,22 Unlike other PTCL entities, nodal PTCLs like AITL, ALCL and PTCL-NOS are not linked to infections with the human T-lymphotropic virus, but the cause of disease in many cases is largely unknown. 23,24 Some PTCL-NOS and AITL cases harbor characteristic mutations or translocations like the recurrent t(5;9)(q33;q22) in PTCL-NOS resulting in the expression of the kinase/kinase fusion IL-2 inducible T-cell kinase (ITK)/ spleen tyrosine kinase (SYK; ITK-SYK). 25–30 ALCL is often associated with a translocation involving the gene encoding the anaplastic lymphoma kinase (ALK). 5 In most ALCLs harboring an ALK translocation (ALK +-ALCL), the kinase domain of ALK is fused to the N-terminal part of nucleophosmin (NPM) 31 , though other fusion partners have also been described. 32 ALK +-ALCL is often diagnosed in young people and has a more favorable outcome than ALCL cases without ALK translocations (ALK --ALCL) which primarily affects adults > 60 years. 33 Recent studies have shown that some ALCL cases are also associated with breast implants. 34,35 AITL is sometimes preceded by allergic reactions, infections and drug use, most importantly antibiotics. 36 PTCL-NOS, AITL and ALK --ALCL poorly respond to standard chemotherapy and have a worse prognosis than ALK +-ALCL with 5-year overall survival rates of 32%, 52% and 49%, versus 70% respectively.8,37 Differential diagnosis of these PTCL subtypes requires a tumor biopsy and is mainly facilitated by clinical, morphologic and immunohistochemical features, but also by cytogenetics and molecular biology. 5 ALK +- and ALK --ALCL are morphologically indistinguishable and often feature T- cells with characteristically horseshoe- or kidney-shaped nuclei. 38 The architecture of the lymph node is destroyed by infiltrating neoplastic cells. The most important criteria in ALCL diagnosis is the frequent expression of CD30, the loss of pan T-cell antigens on the surface of the degenerated T-cells and a clonal T-cell receptor rearrangement. 5,39–41 AITL is characterized by infiltrates of small to medium sized malignant CD4 + follicular T-helper cells with clear cytoplasm destroying the nodal architecture. Oftentimes follicular dendritic cells form a meshwork around blood vessels resembling “burnt out” germinal centers. 5,36,42–44 PTCL-NOS has been a “waste-basket” category of PTCL comprised of disease entities that did not fit into any other PTCL category. 5,45 The recent revision of the 2008 WHO Classification of Tumors of Hematopoietic and Lymphoid Tissue has improved categorization of certain TCL entities, regarding follicular T-helper cell neoplasms and the distinction Introduction 4 between AITL and PTCL-NOS, but the major subcategories and their features remain unchanged. 46
2.1.3 Inflammation in PTCL As part of the immune response, inflammation is a mechanism initiated by the body to self-protect it from invading pathogens and damaged cells and plays a critical role in wound healing. Phenotypically, inflammatory processes are normally associated with five cardinal signs: tumor (swelling), rubor (redness), dolor (pain), calor (increased heat) and functio laesa (loss of function). 47 On the molecular level, it involves the coordinated mobilization and recruitment of various cells of the immune system working together to eradicate the pathogen and induce the wound healing process. 48 In simplified terms, neutrophil granulocytes as one of the first cell types to invade the injured tissue are recruited to the inflammation site.49 They release inflammatory cytokines attracting other myeloid cells such as monocytes to infiltrate the site of inflammation. 50,51 Monocytes differentiate into macrophages or dendritic cells which then migrate to the lymph nodes where they can potentially activate the adaptive immune response. 52–54 Furthermore, the released cytokines recruit more phagocytic cells like neutrophils and monocytes from the blood stream to the site of inflammation, aiding in eliminating the pathogen. 53 Finally, apoptotic neutrophils and monocyte-derived macrophages lead to ablation of the inflammatory response. 55,56 Excessive sustained inflammation however causes severe tissue damage and is often associated with diseases such as autoimmune disorders and cancer 57–61 . Inflammatory phenotypes have also been described in PTCL. Several PTCL subtypes display an upregulation of the expression of inflammatory cytokines. RNA levels of interferon (IFN)γ have been shown to be increased in the malignant cells of each PTCL subtype. 62 This could be confirmed for PTCL-NOS using immunohistochemistry staining. 63 The T-cell activating interleukin (IL)-6 was found to be produced by various cell types such as vascular endothelial cells in the lymph nodes of PTCL-NOS and AITL specimen and was elevated in the serum of AITL patients. 64,65 In ALK +-ALCL, elevated IL-6 and IFNγ levels are associated with higher disease stage and lower event-free survival. 66 Finally, the pro-inflammatory IL-17 has also been shown to be expressed by T-cells in AITL patients.64 But not only cytokines hint at an involvement of inflammatory processes in the development and progression of PTCL. Infiltrating inflammatory cells into the afflicted lymph nodes are another characteristic feature of PTCL-associated inflammation. The microenvironment of some AITL cases, for instance, presents with mast-cells secreting inflammatory cytokines and subsequent infiltration of dendritic cells and granulocytes. 64 Invading monoclonal Epstein-Barr virus (EBV)+ B-cells are presumed to induce these inflammatory surroundings.67 Furthermore, ALCL is often characterized by neutrophilic granulocytosis and granulocytic infiltrates in lymph nodes and skin. 68–72 Additionally, increased monocyte and granulocyte levels have been shown in AITL, Introduction 5
ALCL and PTCL-NOS which in each case study correlated with lower overall survival. 73–77 Due to these inflammatory processes, patients at diagnosis of PTCL often present with fever, night sweat and skin rash. These symptoms correspond to the inflammatory phenotype and to the local and systemic expansion of inflammatory cells such as monocytes and granulocytes. Clinically, the inflammatory symptoms oftentimes bestow a higher burden to the patients than the actual malignant T-cell expansion.
2.1.4 Standard treatment strategies and new therapeutic approaches in PTCL Most subtypes of PTCL carry a dismal prognosis with high relapse rates and mortality due to the lack of specific therapies and resistance to classical chemotherapies.8,18,78–81 Despite the differences in clinical presentation and unique morphological features, AITL, ALCL and PTCL-NOS are treated similiarly. 82 Standard treatment is based on the conventional chemotherapy used in diffuse large B-cell lymphoma (DLBCL) and is composed of cyclophosphamide, doxorubicin, vincristine and prednisolone (CHOP) or CHOP with the addition of etoposide (CHOEP). Compared to DLBCL, outcomes in patients with PTCL with the exception of low-risk ALK +-ALCL have been quite disappointing with a 5-year overall survival of PTCL patients reaching only 38.5%.83,84 Due to these unfavorable outcomes of standard chemotherapy in PTCL patients, the development of novel treatment strategies has been pursued excessively in recent years. The finding that histone deacetylase (HDAC)1 expression is significantly increased in PTCL 85 resulted in the approval of the two HDAC inhibitors (HDACi) Romidepsin and Belinostat in treatment of refractory or relapsed PTCL by the US Food and Drug Administration (FDA). HDACi increase histone acetylation and therefore upregulate the expression of certain genes such as the one encoding for the retinoblastoma tumor suppressor protein (RB)86 . They are currently already used in the clinic or in clinical trials for the treatment of various cancer entities. 87 Both, Romidepsin and Belinostat show clinical benefit for patients with refractory or relapsed PTCL, but overall survival rates are still not satisfactory. 88–93 Monoclonal antibody treatment has also emerged as a potential new treatment strategy in PTCL. The humanized monoclonal antibody Alemtuzumab targets the glycoprotein CD52 which is expressed on normal and malignant B- and T-lymphocytes. Administered in combination with CHOP or other agents, it was shown to be effective in PTCL phase II clinical trials. However, due to severe side effects and toxicity, mainly immunosuppression, leukopenia, thrombocytopenia and neutropenia, its use in standard treatment of PTCL is questionable. 94,95 Mogamulizumab targets the CC chemokine receptor 4 (CCR4). This 96 receptor is expressed on regulatory T-cells (T reg s) that impair antitumor immunity. Administration of Mogamulizumab in phase II clinical trials exhibited response rates of 50% in relapsed adult T-cell leukemia/lymphoma and 35% in relapsed PTCL with acceptable side effects. Still, the survival rates were disappointingly low with a median progression-free Introduction 6 survival (PFS) of 3 months in adult T-cell leukemia/lymphoma and 5 months in PTCL and a median overall survival of 13 months in adult T-cell leukemia/lymphoma. 97,98 Another phase II clinical trial investigated the effects of the monoclonal anti-CD4-antibody Zanolimumab in refractory PTCL. While showing acceptable side effects and a 24% response rate in a small number of patients, the beneficial effects of this antibody alone or in combination with chemotherapy on progression-free and overall survival remain to be explored in larger cohorts. 99 Other emerging options in the treatment of refractory or relapsed PTCL which are currently in clinical trials are alkylating agents like Bendamustine, kinase inhibitors, proteasome inhibitors, nucleoside analogs, immunomodulatory drugs or antifolates as single agents, in combination or associated with standard chemotherapy. So far however, all of these therapeutics fail to satisfactorily increase overall survival rates due to disease relapse and/or are accompanied by massive side effects and therefore do not present promising options to cure PTCL. 100–111 Although new strategies for the conventional treatment of PTCL have been postulated over the past years, beneficial effects on response rates and especially long-term effects such as progression-free and overall survival are still highly disappointing and relapse rates are very high. Even after autologous stem cell transplantation (ASCT) as first-line therapy, which is often not applicable due to progressive disease, the 3-year overall survival remains less than 50%. 112
2.2 PTCL biology
2.2.1 Normal T-cell development T-cells derive from pluripotent progenitor cells of the bone marrow (BM). These cells differentiate into common lymphoid progenitors (CLPs) in the BM and can give rise to B-, T- and natural killer (NK) lymphocytes.113 CLPs primed to become T-cells migrate from the BM into the thymus where T-cell differentiation is initiated. The first steps of this differentiation program take place in the cortical region of the thymus. 114 Initially, immature T-cells express neither CD4 nor CD8 and these CD4 -CD8 - cells are therefore also named double negative (DN). Depending on their expression patterns of the adhesion molecule CD44 and the α-chain of the IL-2 receptor CD25, CD4-CD8 - cells are subdivided into 4 sequential subsets (DN1-DN4) in which they gradually loose CD44 and gain CD25 expression. 113–115 To ensure a widespread T-cell receptor (TCR) diversity to recognize an enormous number of antigens, T-cell receptor rearrangement is initiated at DN2 stage. 115,116 T-cell receptors are heterodimers of two proteins each comprised of a cytoplasmic tail, a transmembrane region, a constant region and a variable region which is responsible for antigen detection. 117 There are four genes encoding for the TCR proteins which are termed Introduction 7
TCRα, TCRβ, TCRγ and TCRδ. Most T-cells (95%) will later harbor an α/β-TCR, whereas 5% of T-cells will exhibit an γ/δ-TCR phenotype equipping the respective T-cells with exceptional features such as independency of major histocompatibility complex (MHC) molecules in the detection of antigens. 115,116,118 The rearrangement of the TCR variable region is facilitated by the recombination of a variable (V), a diversity (D) and a joining (J) segment of the TCR genes.116 It is postulated that successful somatic VDJ-recombination determines the lineage commitment of the developing T-cells, meaning that a successful TCR assembly of the TCRγ and TCRδ gene promotes development into a γ/δ-T-cell.116 TCRβ, TCRγ and TCRδ assembly is facilitated during DN2 and DN3 stages. 116 After successful TCRβ recombination, the β-TCR chain associates with a surrogate α-chain and CD3 at the membrane. This pre-TCR signal then drives the developing T-lymphocytes into DN4 phase, induces several rounds of proliferation and finally leads to the expression of both CD4 and CD8 surface markers resulting in CD4 +CD8 + T-cells, also known as double positive (DP) T-cells.113,116 TCRα recombination is initiated at this differentiation stage. 116 T-cells which fail to bind to MHCI or MHCII bound self-peptides on cortical epithelial cells with an affinity high enough to induce survival signals, undergo apoptosis in a process termed positive selection. 119 The surviving immature CD4 +CD8 + T-cells then migrate into the thymic cortico-medullary junction where they undergo negative selection. During this process, they interact with bone marrow derived antigen presenting cells (APCs) with high MHC expression levels. These APCs present self-antigens to the T-cells and high affinity binding to these antigens induces apoptosis. The negative selection ensures that T-cells do not recognize antigens derived from the organism itself and therefore helps to suppress autoimmune reactions. 119 The recognition of either MHCI or MHCII in the positive and negative selection processes also dictates the cell differentiation into CD4 or CD8 expressing single positive T-cells. MHCI binding T-cells differentiate into CD8 positive (CD8 +) cytotoxic T-cells, whereas MHCII recognition leads to the downregulation of CD8 and the differentiation of CD4 + 113–119 + + T-helper cells (T h). Mature CD4 and CD8 T-cells then migrate from the thymic medulla to the periphery where they circulate through secondary lymphoid organs such as lymph nodes. Here they can be activated by APCs presenting foreign antigens. 120 After binding of an antigen-presenting MHCI molecule on the APC and the activation of certain co- receptor signals, CD8 + T-cells proliferate and release cytotoxins to guide the infected target cell into apoptosis. 121 CD4 + T-cells on the other hand start to heavily proliferate upon peptide- MHCII complex binding and, depending on further specific signals such as cytokine binding + to specific receptors on the CD4 T-cell surface, differentiate into T h1, T h2 or Th17 T-cells. They produce and release different cytokines in order to further activate and uphold the immune response until, finally, the invading pathogen is eradicated. Another subtype of CD4 +
T-cells is the Treg s. They typically deactivate the immune response to ensure that Introduction 8 inflammatory processes are inhibited upon pathogen elimination. 122 After pathogen eradication, some CD4 + and CD8 + T-cells will remain alive as long-term memory T-cells. In case of a second infection with the same antigen, these cells will immediately recognize the pathogen and facilitate an instant immune response to eliminate the pathogen much faster than after the first infection. 123
2.2.2 T-cell receptor signaling in normal T-cells and PTCL The TCR complex of normal α/β-T-cells is comprised of a heterodimer of one TCRα and one TCRβ protein chain and CD3.124,125 It is localized at the T-cell membrane and facilitates antigen-binding by the variable domains of its TCR chains. The complex signaling cascade of the TCR is shown in Figure 2.1.
Figure 2.1: T-cell receptor signaling overview. Binding of the TCR complex to a peptide-MHC complex and CD4 or CD8 co-receptor binding to the MHC molecule, lead to the activation of the lymphocyte-specific protein tyrosine kinase (LCK). LCK subsequently phosphorylates immunoreceptor tyrosine-based activation motifs (ITAMs) in the cytoplasmic tails of CD3 which then present binding sites for the ζ-associated protein of 70 kDa (ZAP70). ZAP70 is recruited and then activated by LCK. ZAP70 recruits and activates further proteins such as ITK and generates a large signaling complex. As a consequence, multiple signaling cascades such as the mitogen activated protein kinase (MAPK) pathway and the protein kinase Cθ (PKCθ) pathway are initiated and result in the complex cellular response to TCR stimulation, including cell proliferation, transcriptional upregulation of T-cell response genes and cytoskeletal reorganization. ADAP, adhesion and degranulation promoting adaptor protein; AP-1, activator-protein 1; BCL-10, B-cell lymphoma 10; Ca 2+ , calcium ion; CARMA1, CARD-containing MAGUK protein 1; CDC42, cell division control protein 42 homologue; CRAC, calcium release-activated calcium channel; DAG, diacylglycerol; ER, endoplasmic reticulum; ERK, extracellular signal-regulated kinase; FOS, proto- Introduction 9
oncogene C-Fos; GADS, GRB2-related adaptor protein 2; GRB2, growth factor receptor-bound protein 2; InsP3, inositol trisphosphate; IP3R1, type I inositol 1,4,5-trisphosphate receptor; JNK, Jun N-terminal kinase; JUN, JUN protein; LAT, linker for activation of T-cells; MALT1, mucosa-associated lymphoid tissue lymphoma translocation protein 1; MEKK, MAP/ERK kinase kinase; MKK, MAPK kinase; NFAT, nuclear factor of activated T-cells; NF-κB, nuclear factor kappa-light-chain-enhancer of activated B-cells; p38, p38 mitogen-activated protein kinase; PLCγ1, phospholipase Cγ1; pMHC, peptide bound to MHC molecules; PtdIns(4,5)P2, phosphatidylinositol 4,5- bisphosphate; RAC, RAS-related C3 botulinum toxin substrate; RASGRP1, rat sarcoma guanyl-releasing protein 1; REL, proto-oncogene c-REL; SLP76, SH2-domain-containing leukocyte protein of 76 kDa; SOS1, son of sevenless homologue 1, VAV1, VAV guanine nucleotide exchange factor 1 (adapted from Gaud et al.). 126
Binding of antigen-presenting MHC molecules on the surface of APCs and activation of the CD4 or CD8 co-receptor by MHC binding results in the activation of the Src-family kinases LCK and FYN (proto-oncogene tyrosine-protein kinase FYN) and the SYK-family kinase ZAP70.127–129 LCK and FYN phosphorylate the cytosolic ITAMs of CD3 128,130,131 which form binding sites for ZAP70 via its Src-homology- (SH) domain.132 ZAP70 is then activated via phosphorylation by LCK as well as auto-phosphorylation and in turn phosphorylates and hereby activates further proteins. Additionally, adaptor proteins are recruited, leading to the assembly of a signaling complex in close proximity to the cell membrane. 133 One of the recruited proteins is ITK, a member of the Tec family kinases.134 Its activation by LCK 135 leads to phosphorylation of its downstream target PLCγ1 as well as further auto-phosphorylation of ITK itself. 136–139 Activated PLCγ1 hydrolyses PtdIns(4,5)P2 to InsP3 and DAG 140 which results in diverse signaling processes such as Ca 2+ flux 141 and the activation of the MAPK and PKCθ signaling cascades.142–144 Ultimately, these processes together with the activation of the co-stimulatory CD28 receptor 145 and cytokine binding to their respective receptors 146 fully activate the T-cell and thus induce cell proliferation, transcriptional events, production and release of cytokines and other effector molecules as well as cytoskeletal reorganization to induce adhesion and/or migration, thus executing T-cell responses. 147–149 Constitutive non-modulated TCR signaling would lead to excessive inflammation and would eventually cause severe tissue damage. Therefore, multiple negative regulatory loops have been implemented to modulate TCR signaling after TCR stimulation. Upon TCR stimulation, GRB2-associated binder (GAB2) is phosphorylated by ZAP70. Hereby activated, it recruits the Src-homology region 2 domain-containing phosphatase 2 (SHP2) which in turn dephosphorylates ITAMs, thus inhibiting TCR signaling.150,151 Further mechanisms involved in the downregulation of TCR signaling include internalization of the receptor 152 or recruitment of phosphatase CD45 which dephosphorylates the TCR complex.153 In PTCL, alterations of TCR signaling are frequently observed. Especially in AITL and in PTCL-NOS exhibiting a follicular T-helper cell phenotype, activating mutations in TCR associated genes are quite common. 60% of these cases harbor a recurrent mutation in the Introduction 10
Ras homolog gene family member A (RHOA) guanosine triphosphatase (GTPase) which is activated downstream of TCR stimulation and exerts its functions by modulating cytoskeletal reorganization. Additionally, 50% of patients carry mutations in other TCR-related genes such as PLCγ1 (14.1%), MAPK pathway genes (13%), VAV1 (4.4%) or FYN (3.5%). 154 This indicates that a constitutive over-activation of TCR signaling in general or of certain pathways downstream of TCR signaling can contribute to the development and pathogenesis of follicular T-helper cell PTCL cases. The discovery of the fusion kinase ITK-SYK in 17% of PTCL-NOS further supports the involvement of aberrantly activated TCR signaling in the pathogenesis of PTCL. 25 Mouse models have shown that ITK-SYK constitutively engages in TCR signaling causing PTCL with 100% penetrance resembling human disease.155 ALK +- and ALK --ALCLs however do not depend on constitutive TCR signaling. In fact, lymphoma cells in this disease entities commonly lack TCR and CD3 expression and show no activation of LCK or ZAP70. 156,157 This deficiency in TCR expression can only be found in very few cases of other PTCL entities and therefore represents a hallmark of ALCL.157 Interestingly, it appears that the constitutive activation of ALK in ALK +-ALCL cases substitutes TCR signaling by activating similar transcriptional programs and driving equivalent cellular processes in the malignant T-cells.158
2.2.3 Immunophenotype of PTCL subtypes Immunohistochemical or flow cytometric analysis of the immunophenotype of PTCL cells along with their morphological features are commonly used to distinguish between different disease entities. 6 The majority of nodal PTCLs derive from CD4 + α/β-T-cells. 159 In AITL, follicular T-helper cells account for the malignant T-cell population. Besides the expression of CD4, their immunophenotype normally consists of CD3 and CD10 expression 160,161 , an α/β-TCR with an abnormal clonal immunophenotype of the β-TCR chain and aberrant loss of CD7. 162–164 Additionally, they constitutively express cytoplasmic C-X-C motif chemokine 13 (CXCL13) and exhibit increased expression profiles of programmed cell death protein 1 (PD-1), human inducible T-cell co-stimulator (ICOS), human B-cell lymphoma 6 (BCL-6) and CD200.161,165–169 CD30 is the characteristic marker for ALCL cells and its expression can be detected in virtually all malignant ALCL T-cells. 5 CD4 expression is much more common than CD8 expression in both, ALK +- and ALK --ALCL cells.163,170,171 As mentioned above, malignant T-cells in this PTCL entity oftentimes lack expression of TCR complex components and/or proximal TCR related proteins. 157 The expression of pan T-cell markers such as CD3, CD5, CD7 and/or CD52 is also abolished in many ALCL cases, thus, some patients present with a “null cell”- instead of a T-cell phenotype which represents a distinct disease entity of ALCL PTCLs.5,163,170–172 When comparing ALK +- to ALK --ALCL, both sub-entities frequently loose Introduction 11 the expression of pan T-cells markers, but the expression of CD2 and CD3 is more commonly absent in ALK --ALCL. 39 As described for AITL and ALCL, PTCL-NOS generally presents with a CD4 + T-cell phenotype. Moreover, it harbors an α/β-TCR and exhibits a downregulation of CD5 and CD7 in many cases. 173 Unlike ALCL, the malignant T-cells in PTCL-NOS always express at least some T-cell antigens and are therefore always retraceable to their T-cell origin. CD3 expression, for instance, is retained in 86% of PTCL-NOS cases. 173 Unlike AITL, however, PTCL-NOS lacks the follicular T-helper cell phenotype and its characteristic expression of CD10, BCL-6, CXCL13 and PD-1 with the exception of follicular/perifollicular disease variants.5,174 In general, immunophenotypic characteristics of PTCL-NOS are quite diverse and differ widely between patients. 175 This can be attributed to the fact that PTCL-NOS represents a “waste-basket” category of PTCL rather than a disease entity with classical characteristic features.
2.3 ITK-SYK kinase fusion in PTCL-NOS In recent years, gene fusions leading to a constitutive activation of tyrosine kinases have been identified in various forms of cancer.176–180 These findings led to the development of specific targeted therapies such as the breakpoint cluster region protein-Abelson murine leukemia viral oncogene homologue 1 (BCR-ABL) inhibitor Imatinib in chronic myelogenous leukemia (CML). 181 Consequently, the identification of such kinase fusions in additional malignancies has been pursued to identify novel therapeutic targets in various cancer entities including PTCL. In ALK +-ALCLs, the C-terminal domain of ALK is fused to an N-terminal partner, the most frequent fusion partner being NPM. 31 ALK gene fusions in ALCL have been well characterized and result in the constitutive activation of the ALK kinase domain. 31 The fusion kinase comprised of the N-terminal part of ITK and the C-terminal part of SYK was the first recurrent gene fusion found in PTCL-NOS and can be detected in 17% of this PTCL subtype.25 Figure 2.2 shows a schematic view of the ITK-SYK fusion.
Figure 2.2: Schematic view of the ITK-SYK kinase resulting from a fusion of the N-terminal part of ITK and the C-terminal part of SYK. The resulting kinase/kinase fusion consists of the pleckstrin-homology- (PH) and tec-homology- (TH) domain of ITK and the tyrosine kinase- (TK) domain of SYK (adapted from Streubel et al.). 25
Introduction 12
The resulting protein is comprised of the N-terminal part of ITK with PH- and TH-domains. The PH-domain of ITK is essential for its recruitment to the plasma membrane upon TCR- stimulation and its subsequent activation by phosphorylation. 182 The TH-domain is believed to regulate the basal activity of ITK and plays an important role in LCK mediated activation. 183 The C-terminal part of ITK-SYK contains the TK-domain of SYK. Interestingly, its constitutive activation in the ITK-SYK fusion is strongly dependent on membrane localization by the PH-domain and an intact kinase domain.155,184 Recent studies in ITK-SYK expressing mouse models have revealed further insight into the pathology of ITK-SYK driven PTCL and suggest tyrosine kinase inhibitors as possible treatment strategies in ITK-SYK driven PTCL-NOS (see 2.3.2). 155,185,186
2.3.1 ITK and SYK in TCR signaling To better understand the role of ITK-SYK in the development of PTCL, it is necessary to comprehend the physiological relevance of ITK and SYK in TCR signaling. ITK is a member of the Tec family of non-receptor protein tyrosine kinases and is expressed primarily in T-cells. 187 Mice lacking ITK expression showed decreased numbers of mature naïve T-cells and impaired T-cell proliferation upon TCR activation, suggesting an important role in TCR mediated signaling. 188 As mentioned in 2.2.2, ITK is part of the TCR signaling cascade operating downstream of the T-cell receptor after stimulation by a peptide-MHC complex. 134 Upon recruitment to the ITAMs of the TCR complex and subsequent activation and phosphorylation by LCK, ZAP70 phosphorylates and thus activates LAT and SLP76.189,190 These two adaptor proteins are required for the activation of phosphoinositide 3-kinase (PI3K) 191 which ultimately leads to the accumulation of phosphatidylinositol (3,4,5)- trisphosphate (PtdIns(3,4,5)P3) in the plasma membrane.192 As the preferred binding site for the PH-domain of Tec family kinases, PtdIns(3,4,5)P3 recruits ITK to the plasma membrane.134,193 Direct interaction of ITK with SLP76 and LAT 194,195 via its SH-domains renders it accessible for LCK and thus activates it via LCK mediated phosphorylation.135 After cis autophosphorylation on tyrosine (Y) 180, ITK directly binds and activates its downstream target PLCγ1, thus initiating the signaling network described in 2.2.2, resulting in the complex cellular responses after TCR activation. 136–139 Thus, ITK activation upon TCR stimulation is tightly regulated in benign mature T-cells. Loss of function mutations in the ITK gene in patients suffering from EBV result in immunodeficiency associated with massive proliferation of EBV + B-cells and oftentimes fatal outcome. 196 Furthermore, a knockout (KO) of ITK in CD8 + T-cells of mice produces a memory T-cell like phenotype with high expression of CD44 and CD122 revealing an impaired differentiation into naïve cytotoxic T-lymphocytes. 197 Constitutively activating mutations of ITK , besides the ITK-SYK fusion, have not been reported. It can be assumed, however, that an over-activation of ITK would result in a T-lymphoproliferative disease induced by constitutive activation of the TCR in absence of Introduction 13 peptide-MHC complexes, possibly combined with an inflammatory phenotype as has been shown in mouse models with ITK-SYK over-expression.155,185 The tyrosine kinase SYK is expressed in most hematopoietic cell lineages. 198 It plays a major role in B-cell development and B-cell receptor (BCR) signaling quite similar to that of ZAP70 in T-cells. Deficiency of SYK expression led to a complete absence of mature B-lymphocytes and perinatal mortality of transgenic mice. 199,200 Recent studies have shown beneficial effects of SYK inhibitors in the treatment of chronic lymphocytic leukemia (CLL) in which SYK is activated by various signals from the tissue microenvironment and enforces constitutive BCR signaling. 201 In the T-cell lineage, SYK is mainly expressed in CD4 -CD8 - and CD4 +CD8 + thymocytes as well as γ/δ-T-cells and naïve T-cells, whereas proliferating peripheral T-cells show no detectable SYK protein. 198,202–205 ZAP70 is a close relative of SYK from the same tyrosine kinase family and is comprised of similar protein domains. With the exception of NK cells, it is exclusively expressed by T-cells. 206,207 ZAP70 engages in TCR signaling and mediates downstream effects of T-cell activation as described in 2.2.2 and 2.3.1. Compared to ZAP70, SYK has a 5- to 10-fold lower association with the TCR complex and is associated with decreased LCK recruitment, thus implying ZAP70 as the critical SYK kinase family member in T-cells or alternatively postulating a differential role of SYK and ZAP70 in the modulation of TCR activity.208 Either way, the finding that aberrantly activated SYK is expressed in more than 90% of PTCL cases indicates that SYK can play a key role in PTCL development. 209 Intriguingly, a recent study discovered an additional ITK fusion protein comprised of the N-terminal part of ITK and the kinase domain of the proto-oncogene tyrosine kinase FER in PTCL-NOS. Expression of this kinase fusion in human embryonic kidney (HEK)293 cells resulted in increased colony formation capacity. 27
2.3.2 ITK-SYK mouse models After the detection of the ITK-SYK fusion in PTCL-NOS, several mouse models have been developed to analyze the effects of ITK-SYK expression in vivo .155,185,210 Expression of ITK- SYK in CD4 +CD8 + and single positive CD4 + and CD8 + T-cells mediated by CD4-Cre mimicked constitutively activated T-cell receptor (TCR) signaling in the absence of antigens and resulted in the development of clonal PTCL-NOS with 100% penetrance resembling human disease. Spleens were infiltrated with highly proliferative neoplastic T-cells, predominantly CD4 + in 61% of mice, CD8 + in 23% of mice and mixed in the remaining mice. The malignant cells furthermore infiltrated the bone marrow as well as distant organs such as kidneys, liver and lung. Interestingly, ITK-SYK could only mimic an activated TCR signal, whereas, consistent with the selective role of ITK in TCR signaling, its expression in CD19 + B-cells had no oncogenic effects. As described earlier, CD4 +CD8 + T-cells are subject to negative selection and are driven into apoptosis upon strong TCR signals to prevent Introduction 14 autoimmunity. 119 ITK-SYK in this model was expressed starting at the CD4 +CD8 + stage. Constitutive TCR signaling within these cells resulted in increased negative selection and culminated in strongly reduced overall thymocyte numbers and eventually in decreased naïve peripheral T-cell numbers.155 A closely related mouse model using LCK -Cre and CD4 - Cre driven expression of ITK-SYK confirmed these observations and emphasized the importance of CD4 + T-cells as the primary drivers of ITK-SYK driven PTCL. Interestingly, the investigators could also detect a systemic inflammatory phenotype with increased serum levels of inflammatory cytokines such as IFNγ, IL-6 and tumor necrosis factor α (TNFα). 210 A different mouse model of ITK-SYK driven PTCL-NOS was established by retrovirally transducing total bone marrow cells enriched for stem and transit-amplifying cells by 5-fluorouracil (5-FU) treatment with ITK-SYK and subsequently retransplanting them into lethally irradiated recipient mice. Animals developed PTCL with infiltration of several organs with malignant ITK-SYK + CD4 + or CD4 -CD8 - but not CD8 + T-lymphocytes. Intriguingly, these mice also exhibited a massive inflammatory phenotype with strong skin, ear and tail infiltrates of inflammatory cell types, resulting in encrustations, necrosis and increased serum levels of the inflammatory cytokines IL-5 and IFNγ. As has been shown previously, an intact kinase domain was essential for PTCL induction. But contradictory to prior investigations 184 , abolished membrane localization enhanced the disease phenotype and markedly reduced survival. SYK inhibitor treatment resulted in reduced T-cell infiltration and improvement of the inflammatory phenotype suggesting SYK inhibition as a possible treatment approach for ITK-SYK driven PTCL-NOS. 185 Further investigations using the same mouse model additionally revealed a massive expansion of activated myeloid cells, especially granulocytes and of Lineage(Lin) -cKit +Sca1 + (LKS) cells which resemble the stem cell population. Interestingly, this was not dependent on ITK-SYK expression of the respective cells, but rather appeared to be driven by non-cell-autonomous processes such as cytokine stimulation, thus being a secondary effect of the emerging PTCL. 186
2.4 Janus kinase (JAK) signaling pathway
2.4.1 JAK / signal transducer and activator of transcription (STAT) signaling overview After intense research on the signaling cascades of IFN induced cellular responses, the JAK/STAT signaling pathway was first described by Darnell Jr., Kerr and Stark in 1994. 211 Today, JAK/STAT signaling is known to regulate membrane to nucleus signals derived from various soluble extracellular factors such as cytokines and hormones and to coordinate their transcriptional responses. 212 It is active in virtually all tissues and controls embryonic development, homeostasis and tissue growth by regulating proliferation, differentiation, survival and apoptosis in various organs such as lung, bone, colon, heart, the central Introduction 15 nervous system and the skin.213–221 Furthermore, the JAK/STAT pathway has emerged as one of the major signaling cascades involved in innate and adaptive immunity and thus plays an important role in inflammatory responses. 212,222 The aberrant activation of JAK/STAT signaling has been described as a recurrent event in autoimmune disease 223 and solid tumors 221 as well as hematopoietic neoplasias. 224,225 The JAK/STAT signaling cascade is one of the simplest and most direct pathways described. Figure 2.3 schematically shows the canonical JAK/STAT signaling. Upon binding of an extracellular ligand, e.g. a cytokine or hormone to its respective receptor, two receptor subunits dimerize 226 , thus bringing their constitutively associated JAK molecules into close proximity. Hereby activated, they phosphorylate each other resulting in further activation which eventually allows them to phosphorylate specific tyrosine residues on the intracellular domain of the receptor. 227 These phosphorylated tyrosines serve as binding sites for STAT molecules which are subsequently recruited, phosphorylated and hence activated by the JAKs. 228 Two phosphorylated STATs bind to the phosphorylation sites of one another and hereby form an active STAT dimer. 229 In its activated transcription factor form, the dimer is now transported into the nucleus where it binds specific DNA sequences, regulating the expression of the specific target genes of the respective receptor stimulating factor. 227
Figure 2.3: Schematic overview of the canonical JAK/STAT signaling cascade. Upon ligand binding to its extracellular binding domains, the cytokine or growth factor receptor subunits dimerize, thus bringing their associated JAK tyrosine kinase molecules in close proximity. This results in an activation of the kinase domain and mutual phosphorylation. Phosphorylation further activates JAKs, resulting in the phosphorylation of the receptor. The resulting phosphotyrosine residues of the receptor serve as binding sites for the STAT proteins which are subsequently phosphorylated by the JAKs. The hereby activated STATs in turn dimerize, rendering them active transcription factors and allowing their transport into the nucleus where they bind to specific DNA Introduction 16
sequences. This induces the expression of target genes to implement cellular responses. P, phosphotyrosine residue (adapted from Dodington et al.). 230
In non-canonical JAK/STAT signaling which has been explored in Drosophila melanogaster , unphosphorylated Stat molecules are associated with heterochromatin protein 1 (Hp1) and together, they bind heterochromatin regions of the genome, thereby repressing gene transcription. Upon Jak activation and increased levels of phosphorylated Stat proteins, unphosphorylated Stat levels localized on the heterochromatin are reduced, thus leading to Hp1 dissociation and destabilization of the heterochromatin. This in turn results in transcription of genes silenced by Stats and Hp1.231–233 Studies on JAK1 dependent chromatin remodeling at the INFγ locus have implied that non-canonical JAK/STAT signaling also occurs in mammalian systems.234 To terminate JAK/STAT activation after receptor stimulation, various regulatory mechanisms have evolved. Upon cytokine stimulation, the expression of suppressor of cytokine signaling (SOCS) proteins is massively upregulated, hence representing a classical negative feedback loop.235,236 SOCS proteins can bind phosphorylated JAKs or the receptor itself and thus inhibit their activity. 237–239 Some SOCS family members directly bind to the phosphorylated receptor tyrosine residues, therefore competing with STATs for their binding sites which results in a diminished recruitment of STAT proteins. 240 A third proposed mechanism through which SOCS proteins potentially regulate JAK/STAT activity is the induction of JAK ubiquitination and subsequent proteasomal degradation. 241 In contrast to SOCS, protein inhibitor of STAT (PIAS) proteins inhibit STATs. Each PIAS family member interacts with its respective STAT protein only upon cytokine stimulation. 242 The mechanisms of inhibition differ between PIAS family members and range from directly blocking the DNA-binding of STAT dimers 243,244 over transcriptional co-repressor functions 245 to mediating the conjugation of small-ubiquitin-related modifier (SUMO) to STAT 246 which most likely results in impaired DNA-binding. 247 The dephosphorylation and deactivation of JAK and/or STAT proteins by protein tyrosine phosphatases (PTPs) including SHP2 and CD45 has also been implicated in the regulation of JAK/STAT signaling. 248–250 The non-receptor tyrosine kinases of the JAK family are associated with various transmembrane receptors such as growth hormone receptors251 and cytokine receptors lacking intrinsic tyrosine kinase activity, thus relying on associated tyrosine kinase molecules for signal transduction. 252 In mammals, three JAK kinase family members, namely JAK1, JAK2 and TYK2 are ubiquitously expressed 253 , whereas the fourth family member, JAK3, is predominantly expressed in the hematopoietic system. 254 Seven different STAT family members have been identified in mammals, namely STAT1, STAT2, STAT3, STAT4, STAT5A and STAT5B (referred to as STAT5) and STAT6.255 Receptor dimerization upon ligand binding results in the trans-phosphorylation of the same JAK family kinases or Introduction 17 alternatively involves the activation of two different family members. 256 The subsequent STAT phosphorylation leads to the formation of STAT homo- or heterodimers which enter the nucleus to engage in the transcriptional regulation of specific target genes.257–260 Each cytokine receptor selectively binds to a specific JAK kinase and signals via a different combination of JAKs and STATs, hence resulting in different cellular responses. 255 Table 2.1 shows the predominant activation pattern of JAK/STAT signaling after stimulation with various cytokines. However, cell-type specific variation can occur. 261
Table 2.1: Activation of JAKs and STATs in response to stimulation with different cytokines (adapted from Silvennoinen et al.) 261 CYTOKINE JAK STAT IFNα JAK1,TYK2 STAT1, STAT2 IFNγ JAK1, JAK2 STAT1 IL-10 JAK1, TYK2 STAT1, STAT3 IL-2, IL-7, IL-15 JAK1, JAK3 STAT5 IL-4 JAK1, JAK3 STAT6 IL-6 family JAK1, JAK2, TYK2 STAT3, STAT1 IL-3, GM-CSF JAK2 STAT5 IL-5 JAK2 STAT3, STAT1 EPO, TPO, GH, PRL JAK2 STAT5 G-CSF JAK2 STAT3 IL-12 JAK2, TYK2 STAT4 EGF, PDGF JAK1 STAT1, STAT3, STAT5 EGF, epidermal growth factor; EPO, erythropoietin; G-CSF, granulocyte colony-stimulating factor; GH, growth hormone; GM-CSF, granulocyte-macrophage colony-stimulating factor; PDGF, platelet-derived growth factor; PRL, prolactin; TPO, thrombopoietin.
2.4.2 JAK/STAT signaling in normal CD4 + T-helper cell differentiation The JAK/STAT signaling pathway plays an important role in physiological T-cell immunity and regulates differentiation and T-cell function. It enables the cytokine stimulated T-cell to upregulate the transcription of ligand-specific genes, thus inducing a T-cell response. 262,263 The role of JAK/STAT signaling in T-cell differentiation is best understood in the development of CD4 Th-cell subsets. Different JAKs and STATs induced by various extracellular stimuli in + CD4 T-cells lead to differentiation into multiple Th subtypes including Th1, T h2 and Th17 and the subsequent release of distinct cytokines characteristic for the respective T-cell functions (Figure 2.4).264 Peptide-MHC complex stimulation and simultaneous IL-12 binding to the IL-12 receptor of a naïve CD4 + T-cells leads to the trans-activation of receptor-bound JAK2 and TYK2. These then phosphorylate and thus activate STAT4 and to a lesser extent STAT1 which, in turn, induce the transcription of T-box transcription factor (T-bet), a T h1 specific transcription factor. T-bet directly stimulates the transcription of T h1 specific cytokines such as IFNγ and IL-12. T h1 effector cells play a major role in the elimination of intracellular 262,264–266 pathogens. Th2 effector cells are important players in combating parasite infections Introduction 18
and have been associated with allergic reactions. Differentiation into T h2-cells is dependent on IL-4 binding to its respective receptor which leads to the activation of JAK1 and JAK3 and subsequently STAT6. The latter then induces transcription of the GATA-binding protein 3 (Gata-3) transcription factor which ultimately drives the expression of IL-4, IL-13 and IL-5 resulting in B-cell and eosinophil recruitment and activation. 262,264,266,267 Additionally, STAT6 268 + inhibits T h1 differentiation. IL-6, IL-23 and IL1β stimulation of naïve CD4 T-cells results in activation of JAK1 and JAK2 and ultimately in phosphorylation of STAT3. The activated STAT3 dimer then drives the expression of the retinoic acid-related orphan receptor gamma transcription factor (RORγt). As a consequence, the cells secrete the T h17 hallmark cytokine
IL-17. T h17-cells play a major role in neutrophil enriched inflammation, resulting in the elimination of extracellular bacteria and fungi. 262,264,266,269
Figure 2.4: The role of JAK/STAT signaling in T-helper cell differentiation. Naïve T-cells differentiate into distinct functional subtypes upon stimulation with specific cytokines. IL-12 induces the differentiation into IFNγ and
IL-12 producing T h1-cells via the JAK2/TYK2 STAT4 axis. IL-4 stimulation and subsequent JAK1/JAK3 and
STAT6 activation result in the differentiation of T h2-cells, secreting predominantly IL-4, IL-13 and IL-5. Finally IL-6, IL-23 as well as IL-1β cytokines induce JAK1/JAK2 and consecutive STAT3 activation, ultimately leading to differentiation into T h17-cells and the secretion of the characteristic IL-17a and IL-17f cytokines. T-bet, Gata-3 and RORγt are transcription factors induced by the respective STATs and responsible for the expression of 262 270 Th-subtype specific cytokines (adapted from Benveniste et al. and modified according to O’Shea and Paul and Tamiya et al. 266 ).
Introduction 19
Thus, JAK/STAT signaling is a critical player of T h dependent immune responses and a pivotal mediator of the adequate reaction to distinct types of pathogenic infection.
2.4.3 Aberrant JAK/STAT signaling in TCL The JAK/STAT signaling pathway as assessed by STAT3 and STAT5 phosphorylation and nuclear localization is frequently over-activated in TCL. 271 Aberrant activation has been observed in most disease entities including the PTCL subtypes ALCL 272–274 , AITL 275 and PTCL-NOS.276 This constitutive signaling can be caused by various mutations in the genes encoding JAK and STAT proteins. Table 2.2 shows such mutations detected in the most common forms of PTCL.
Table 2.2: JAK and STAT mutations in PTCL subtypes (adapted from Waldman and Chen) 271 LYMPHOMA TYPE JAK MUTATIONS STAT MUTATIONS JAK2 V617F STAT3 S614? AITL JAK2 G511S STAT3 D661?
STAT3 S614R STAT3 G618R JAK1 G1097D/S/V STAT3 Y640F ALK --ALCL JAK1 Y640F STAT3 N647I JAK1 L910P STAT3 D661H/Y STAT3 A662V
PTCL-NOS JAK3 L1073F STAT5B Q743H ?, unknown amino acid; A, alanine; D, aspartic acid; F, phenylalanine; G, glycine; H, histidine; I, isoleucine; L, leucine; N, asparagine; P, proline; Q, glutamine; R, arginine; S, serine; V, valine; Y, tyrosine; V617F; valine at position 617 is replaced by phenylalanine.
Interestingly, all JAK mutations found in AITL as well as the JAK1 Y640F mutation in ALK --ALCL are located in the pseudokinase domain. This part of the JAK kinases has been reported to exert inhibitory functions by inducing the phosphorylation of two residues, down-regulating tyrosine kinase activity in the absence of ligand stimulation. 277–279 The other JAK mutants in ALK --ALCL and PTCL-NOS occur in the actual tyrosine kinase domain rendering it constitutively active. 271 The mutations in the STAT3 gene observed in AITL and ALK --ALCL affect the SH2-domain which is involved in recruitment to the cytokine receptor, its dimerization and thus STAT activation. 271,280 The STAT5B mutation detected in PTCL- NOS affects its transactivation domain (TAD). 271 This part of the STAT protein undergoes serine phosphorylation upon activation and subsequently recruits additional transcription factors, resulting in increased transcription of target genes. 281 However, mutations in the genes encoding for JAK/STAT pathway components are not sufficient to initiate oncogenic cell proliferation, but rather augment cytokine receptor signals upon ligand binding and prolong pathway activation.282–284 In line with these findings, JAK/STAT over-activation in TCL is not always associated with mutations in the pathway Introduction 20 itself, but can also be caused by various alternative routes. These include mutations of the cytokine receptors themselves 285,286 , increased or aberrant cytokine production 271,287–292 and aberrations concerning the molecules normally involved in the negative regulation of JAK/STAT signaling. 293,294 Furthermore, kinase fusions inducing STAT activation have been discovered in PTCLs. The NPM-ALK fusion was shown to activate STAT3 in ALCL.295,296 The PTCL-NOS oncogene ITK-SYK also led to an induction of STAT3 phosphorylation. The mechanism behind this activation however remains to be elucidated. 210,297
2.4.4 Aberrant JAK/STAT signaling in myeloid malignancies Apart from its importance in adaptive immunity and T-cell responses, JAK/STAT signaling also plays a pivotal role in innate immunity and inflammation. Differentiation, activation and proliferation of myeloid effector cells like neutrophil granulocytes and monocytes after cytokine stimulation are strongly JAK/STAT dependent. 298–302 Interestingly, JAK/STAT signaling has been shown to be over-activated in many myeloid malignancies. These hematologic disorders include acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) and myelo-proliferative neoplasms (MPNs) with its major sub-entities being CML, polycythemia vera (PV), essential thrombocythemia (ET) and primary myelofibrosis (PMF). 5 As shown for TCL, aberrant pathway activation in myeloid malignancies can be driven by mutations in genes directly involved in the JAK/STAT signaling cascade or by alterations of upstream effector molecules such as cytokine receptors. 303 The most well-known mutation found in myeloid malignancies is a JAK2 mutant harboring a V617F substitution in its pseudokinase domain, rendering the kinase constitutively active and subsequently leading to phosphorylation of STAT5. It was first described in 2005 and has since been discovered to be occurring in 95% of patients presenting with PV and 50-60% of those suffering from ET and PMF, thus providing a valuable tool for routine diagnostics.304–307 A smaller fraction of MDS patients (5%) also harbors this mutation in their JAK2 gene. Interestingly, JAK2 V617F negative PV cases often exhibit other mutations in the JAK2 gene, mainly affecting exon 12. 308 AML in contrast to MPN derives from primitive blasts rather than from terminally differentiated cells. It has been associated with JAK2 fusion proteins such as human autoantigen pericentriolar material 1 (PCM1)-JAK2 309 or BCR-JAK2.310 Just as other JAK2 fusions described in acute lymphoblastic leukemias, they lead to homodimerization mediated by the fusion partner and subsequent trans-phosphorylation resulting in active JAK2. 303 Though JAK2 mutations are the most frequent JAK aberrations in myeloid diseases, 2% of AMLs not developing from progressing MPNs harbor point mutations in the JAK1 gene. 311 STAT3 and STAT5 phosphorylation is frequently upregulated in myeloid malignancies such as MPNs. 312 However, this activation does not seem to be conferred by mutated STATs themselves, but rather by increased upstream signaling. STAT5 for example is known to be the key mediator of JAK2 V617F downstream signaling313 . Despite frequent over-activation of Introduction 21
STAT3 314 , the role of the JAK STAT3 axis in myeloid malignancies is still unclear. 303 Several studies have implied that, as holds true for JAK/STAT aberrations in TCL, intact cytokine receptors are required for JAK/STAT mutants to constitutively activate downstream signaling 284,313 Mutations not directly involving JAK/STAT pathway components but activating downstream signaling via JAKs and STATs, have also been found in myeloid malignancies. These include mutations in the gene encoding thrombopoietin receptor ( MPL ) as has been shown for ET and MF 315,316 and internal tandem duplications in the fms-like tyrosine kinase 3 (FLT3-ITD) in AML. The latter induce activation of multiple signaling pathways, including phosphorylation and activation of STAT5 leading to cytokine independent cell proliferation. 317–319
2.4.5 JAK inhibitors in the treatment of TCL and MPN Aberrant JAK/STAT signaling has proven to be a promising target for therapeutic intervention in TCL and myeloid malignancies. Various JAK inhibitors have made it to the clinic or are in clinical trials for the treatment of MPN.320,321 One of them is Ruxolitinib, a potent JAK1/JAK2 inhibitor, which has been shown to be a reliable therapeutic agent to target the malignant cells in these hematologic diseases.322 It was the first and so far the only JAK inhibitor approved by the FDA for the treatment of myeloid disorders. Other pathway inhibitors, namely Gandotinib (JAK2), Lestaurtinib (JAK2), Momelotinib (JAK1/JAK2), Pacritinib (JAK2) and Fedratinib (JAK2) however are currently in clinical trials for application in these diseases. 323 Inhibitors directly targeting STATs have also been introduced in recent years. Though not yet in clinical trials, several experimental studies have implicated the functionality of STAT inhibitors in the treatment of myeloid malignancies, especially CML and AML. 324–327 In lymphoid malignancies and more particularly in TCL, no JAK/STAT inhibitors have been FDA-approved until this day. Pacritinib and Ruxolitinib are currently undergoing clinical trials assessing their potential in the treatment of lymphoid disorders like relapsed B-cell lymphoma and PTCL.328,329 Furthermore, JAK kinase and STAT3 inhibitors have been used on the experimental level, implying these pathway modulators as promising treatment options for patients suffering from various types of T-cell lymphoma. 330–333
Aims of the study 22
3 Aims of the study Peripheral T-cell lymphomas are a heterogeneous group of malignant diseases arising from the mature T-cell compartment. Most subtypes carry a dismal prognosis with high relapse rates and mortality due to the lack of targeted therapies and resistance to classical chemotherapies. 8,78–81 At diagnosis of TCL, patients often present with a strong inflammatory phenotype including massive granulocytosis correlating with even worse prognosis. 17,71,76,334 Targeting both, the malignant T-cells and the inflammatory phenotype, is a challenge for the development of new therapeutic strategies for TCL.
The ITK-SYK kinase was the first recurrent gene fusion identified in PTCL-NOS and can be detected in 17% of these malignancies. 25 In mouse models, ITK-SYK constitutively engaged in TCR signaling and its expression led to PTCL with 100% penetrance resembling human disease. 155 Malignant CD4 + T-cell infiltration was accompanied by massive inflammation and myeloid cell expansion. 185,186,210 Furthermore, ITK-SYK expression was shown to activate the JAK/STAT signaling pathway which is often aberrantly upregulated in T-cell lymphomas and MPN. 210,297
In the first part of this study, the effects of the inflammatory phenotype on TCL development was evaluated in an ITK-SYK driven TCL mouse model. Therefore, antibody-mediated depletion of neutrophil granulocytes was performed and T-cell distribution and infiltration as well as mouse survival was assessed. In the second part, the work focused on possible mechanisms to target the malignant T-cells and the inflammatory myeloid cell expansion simultaneously in murine and human TCLs by inhibiting the JAK/STAT signaling pathway which was shown to be activated in T-cells and inflammation associated myeloid cells. Thus, performance of different JAK inhibitors on the malignant T-cells and the inflammatory phenotype was determined. Finally, it was investigated, whether JAK/STAT inhibition in a human AITL xenograft showed beneficial effects on T-cell proliferation and inflammation to ascertain if JAK/STAT inhibition could be a new treatment strategy for patients presenting with different subtypes of TCL accompanied by an inflammatory phenotype.
Materials 23
4 Materials
4.1 Laboratory equipment and disposables
4.1.1 Equipment NAME MANUFACTURER 2100 Antigen Retriever aptum Animal blood counter Scil Autoclave MMM Vakulab Blotting system (Tank Blot) Bio-Rad Camera for mouse photography (iPhone 5S, iPhone SE) Apple Cell sorter (BD FACSAria TM Fusion) BD Biosciences Centrifuge (5417R) Eppendorf Centrifuge (Pico 21) Heraeus Centrifuge (Multifuge X3R) Heraeus Centrifuge (Megafuge 1.0R) Heraeus Centrifuge (Megafuge 3.0R) Heraeus Centrifuge (Varifuge 3.0) Heraeus ECL chemocam imager Intas Science Imaging Flow cytometer (CyAn ADP 9 Color) Beckman Coulter Flow cytometer (LSR Fortessa™) BD Biosciences Freezer -20°C Bosch Freezer -20°C Siemens Freezer -20°C Liebherr Freezer -80°C Heraeus Freezer -80°C Thermo Fisher Scientific Freezing container Mr Frosty Nalgene Fume hood (Secuflow) Waldner Ice machine Ziegra IHC wet chamber University Hospital Freiburg Incubator cell culture (Heracell 240i) Thermo Fisher Scientific Incubator cell culture (Heraeus BB6220) Heraeus Incubator IHC slides New Brunswick Scientific Irradiation box for mice University Hospital Freiburg Irradiation source for mice – X-Ray (RS 2000) Rad Source Isuflurane anaesthesia unit Dräger Liquid nitrogen tank Air Liquide Liquid nitrogen tank Cryotherm Magnetic stirrer Heidolph Magnetic stirrer with heater Heidolph Manual counting device Nickel Microplate reader Berthold Technologies Microplate reader Tecan Microscope Axiocam Zeiss Microscope Axiovert Zeiss Microscope Axioplan 2 Zeiss Microscope AxioImager Zeiss Microscope Zeiss Materials 24
Microwave Panasonic Mouse dissecting set Aesculap Multi-channel pipets Eppendorf Neubauer cell counting chamber Marienfeld pH-meter SI Analytics Pipettes Gilson Pipette controller Integra Biosciences Platform shaker Heidolph Polyacrylamide gel electrophoresis system Bio-Rad Power supply Pharmacia Power supply Bio-Rad Refrigerator Heraeus Refrigerator Liebherr Scale (Scout Pro) Ohaus Scale (XL 600) DIPSE Scale (EMB) Kern Scale (PFB) Kern Scale (Quintix) sartorius Spectrophotometer NanoDrop PEQLAB – Life Science Spectrophotometer NanoDrop Thermo Fisher Scientific Staining jar Roth Steamer (plus FS 20 Multi Gourmet) Braun Sterile laminar flow Heraeus Sterile laminar flow Waldner Sterile laminar flow NuAire Thermal cycler PEQLAB – Life Science Thermomixer Eppendorf Timer Roth Timer New England BioLabs Ultrasonificator (Sonorex RK31) Bandelin Vortex Heidolph Vortex IKA Labortechnik Vortex Janke & Kunkel Water bath MGW Lauda Water bath Julabo Water bath HAAKE
4.1.2 Disposables NAME MANUFACTURER Canules Braun Cell scraper Greiner Bio-One Cell strainers (100 µl) Greiner Bio-One Cryogenic tube Corning Cover slips (cell counting chamber) Knittel Glaeser Cover slips (immunohistochemistry) R. Langenbrinck Culture dishes (6 cm, 10 cm) Sarstedt Culture flask (T25, T75, T175) Sarstedt EDTA coated tubes for mouse blood Sarstedt Erlenmeyer flasks Schott Materials 25
Filter papers (western blot) Whatman Filter papers (for flasks) Whatman Heparin coated capillaries Hirschmann Microscopic slides R. Langenbrinck Monovette EDTA Sarstedt Multiwell plates, sterile (6-well, 12-well, 24-well, 96-well) Sarstedt Multiwell plates, sterile (96-well round-bottom/flat-bottom) Falcon Nitrile gloves Ansell Nitrocellulose membrane GE Healthcare Parafilm American National Can Pasteur pipettes (glas) WU Mainz Pasteur pipettes (plastic) Sarstedt PCR Single Cap Strips (0.2 ml) Biozym Pipet tips (20/200 µl, 1000 µl) STARLAB Pipet tips (2/10 µl) Sarstedt Polypropylene tubes (15 ml, 50 ml) Greiner Bio-One Polypropylene tubes (5 ml, 14 ml, round-bottom) Falcon Polystyrene tubes (5 ml, round-bottom) Falcon Reaction tubes (1.5 ml, 2 ml) Sarstedt Scalpels Feather Serum tubes for mouse blood Sarstedt Sterile stripettes Corning Syringe (2 ml, 5 ml, 10 ml, 20 ml) Braun Syringe strainers (0.22 µm, 0.45 µm) Merck
4.2 Chemicals and reagents NAME MANUFACTURER 2-propanol Sigma-Aldrich 5-fluorouracil medac Aqua ad iniectabilia Braun Acetic acid Merck Acrylamide/Bisacrylamide 30% (w/v): 0.8% (w/v) Roth Albumin fraction V, bovine (BSA) Roth
Ammonium chloride (NH 4Cl) Roth Ammonium persulfate Sigma-Aldrich ß-Mercaptoethanol Sigma-Aldrich Baytril (Enrofloxacin) Bayer
Calcium chloride (CaCl 2) Sigma-Aldrich Ciprofloxacin Bayer Complete protease inhibitor cocktail Roche Dimethylsulfoxide Sigma-Aldrich
Disodium phosphate (Na 2HPO 4•7H 2O) Roth Dulbecco’s modified eagle medium (DMEM) + 4.5 g/l Gibco Thermo Fisher Scientific Glucose + 4 mM L-glutamine D-Glucose AppliChem Dulbecco’s phosphate buffered saline (DPBS, 1 x) Gibco Thermo Fisher Scientific Eosin Thermo Fisher Scientific Ethanol pure Sigma-Aldrich Ethanol denatured SAV Liquid Production Materials 26
Ethylenediaminetetraacetic acid (EDTA) Merck Fetal bovine serum (FBS) Sigma-Aldrich Fetal bovine serum, embryonic stem cell qualified Gibco Thermo Fisher Scientific (ES-FBS) Ficoll PAN Biotech FuGENE HD transfection reagent Promega Formalin solution, 10% Sigma-Aldrich Glycine AppliChem Haematoxylin Solution, Mayer’s Merck Hank’s balanced salt solution (HBSS) Gibco Thermo Fisher Scientific HEPES Buffer 1 M Gibco Thermo Fisher Scientific Histoclear National diagnostic Hydrochloric acid (HCl), 37% Sigma-Aldrich
Hydrogen peroxide (H 2O2) 30% Roth Isoflurane Abbott LIVE/DEAD™ Fixable Aqua Dead Cell Stain Kit Thermo Fisher Scientific
Magnesium chloride (MgCl 2•6H 2O) AppliChem
Magnesium sulfate (MgSO 4•7H 2O) Merck Mayer’s hemalum solution Merck Methanol Honeywell Research Chemicals
Monopotassium phosphate (KH 2PO 4) Roth Nonfat dried milk powder AppliChem NuPAGE LDS sample buffer (4 x) Thermo Fisher Scientific NuPAGE sample reducing agent Thermo Fisher Scientific PageRuler prestained protein ladder Thermo Fisher Scientific Penicillin-Streptomycin 10,000 U/ml (P/S) Gibco Thermo Fisher Scientific Phenol red Sigma-Aldrich PhosStop phosphatase inhibitor cocktail Roche Polybrene Sigma-Aldrich Polyethylene glycol (PEG) 300 Sigma-Aldrich Polyethylenimine (PEI) Sigma-Aldrich Ponceau S Sigma-Aldrich Potassium chloride (KCl) Roth Protein A sepharose beads BioVision Protein G sepharose beads GE Healthcare Recombinant murine IL-1α (mIL-1α) Miltenyi Biotec Recombinant murine IL-3 (mIL-3) PeproTech Recombinant murine IL-6 (mIL-6) PeproTech Recombinant murine stem cell factor (mSCF) PeproTech
RNAse/DNAse free H 2O Roche Roswell Park Memorial Institute 1640 medium (RPMI) Gibco Thermo Fisher Scientific
Sodium bicarbonate (NaHCO 3) Sigma-Aldrich Sodium chloride VWR Sodium dodecyl sulfate (SDS) Roth
Sodium orthovanadate (Na 3VO 4) MP Biomedicals Target retrieval solution DAKO T-Cell Culture Supplement with ConA (T-STIM) Corning Tetramethylethylenediamine (TEMED) Roth Tris-(hydroxymethyl)-aminomethane (Tris) HCl Sigma-Aldrich Tris base Sigma-Aldrich Materials 27
Triton X-100 Fluka Trypane blue Gibco Thermo Fisher Scientific Trypsin-EDTA (0.05%, 1 x) Gibco Thermo Fisher Scientific Tween 20 AppliChem
4.3 Buffers and solutions NAME COMPOSITION Blocking buffer IHC DAKO EnVision+ Kit TBS 1 x 3% BSA (w/v) 3% serum (v/v)
Blocking buffer western blot TBS-T 1 x 5% BSA (w/v)
Blocking buffer IHC DAKO CSA Kit TBS 1 x 1% BSA (w/v)
Buffer IHC Vectastain ABC HRP Kit PBS 1 x 1% BSA
FACS-buffer PBS 1 x 1 % FBS
GEY’s solution for erythrocyte lysis 70% H 2O 20% Solution A 5% Solution B 5% Solution C Solution A (autoclaved) 0.66 M NH 4Cl 25 mM KCL 4.2 mM Na 2HPO 4•7H 2O 0.88 mM KH 2PO 4 28 mM Glucose 0.005% Phenol red in dH 2O Solution B (autoclaved) 21 mM MgCl 2 • 6H 2O 5.7 mM MgSO 4 • 7H 2O 31 mM CaCl 2 in dH 2O Solution C (autoclaved) 0.27 M NaHCO 3 in dH 2O autoclaved
Ponceau solution 0.1% Ponceau S (w/v) 5% acetic acid (v/v) in dH 2O
PBS-Tween (PBS-T) PBS 1 x 0.05% Tween 20 (v/v)
Materials 28
Reinhard lysis buffer 0.5% Triton X-100 (v/v) 50 mM Tris, pH 7.6 150 mM NaCl 5 mM EDTA 1 mM Na 3VO 4 PhosStop (1 tablet/10 ml) Complete (1 tablet/10 ml) in dH 2O
Resolving gel buffer 1.5 M Tris-HCl in dH 2O adjust pH to 8.8
SDS-resolving gel (10%) 0.375 M Tris-HCl, pH 8.8 0.1% SDS (w/v) 10% Acrylamide (w/v) 0.27% Bisacrylamide (w/v) 0.05% APS (w/v) 0.05% TEMED (v/v) in dH 2O
SDS-running buffer (10 x) 1.9 M glycine 0.25 M Tris base 35 mM SDS in dH 2O
SDS-stacking gel 0.125 M Tris-HCl, pH 6.8 0.1% SDS (w/v) 4% Acrylamide (w/v) 0.107% Bisacrylamide (w/v) 0.05% APS (w/v) 0.1% TEMED (v/v) in dH2O
Skim milk solution TBS-T 1 x 5% Nonfat dried milk powder (w/v)
Stacking gel buffer 0.5 M Tris-HCl in dH 2O adjust pH to 6.8
Stripping Solution 62.5 mM Tris-HCl, pH 6.5 2% SDS (w/v) 0.1 M (β-ME) in dH 2O
TBS-buffer (10 x) 1.5 M NaCl 0.5 M Tris base in dH 2O adjust pH to 7.4
TBS-buffer high salt (10 x) 3 M NaCl 0.65 M Tris-HCl in dH 2O adjust pH to 7.6
Materials 29
TBS-Triton (TBS-Tr) TBS 1 x 0.05% Triton X-100 (v/v)
TBS-Tween (TBS-T) TBS 1 x 0.1% Tween 20 (v/v)
Transfer buffer SDS-running buffer 1 x 20% methanol in dH 2O
Vehicle 3.3% D-glucose (w/v) 33% PEG 300 (v/v) in dH 2O
4.4 Media MEDIUM COMPONENT Culture medium for HEK293T/Preparation medium 10% FBS (v/v) 1% P/S (v/v) in DMEM
Culture medium for D10.G4.1 10% FBS (v/v) 1% P/S (v/v) 10% T-STIM (v/v) 0.05 M β-ME 10 pg/ml mIL-1α in RPMI 1640
Cryopreservation medium 10% DMSO in FBS
Prestimulation medium 10% ES-FBS (v/v) 1% P/S (v/v) 1 µg/ml Ciprofloxacin 10 ng/ml mIL-3 10 ng/ml mIL-6 100 ng/ml mSCF in DMEM
Starvation Medium 0.7% FBS (v/v) 1% P/S (v/v) in RPMI1640
4.5 Kits NAME MANUFACTURER AllPrep DNA/RNA Mini Kit QIAGEN Clarity™ Western ECL Substrate Bio-Rad CSA, Catalyzed Signal Amplification System DAKO Cytofix/Cytoperm TM Fixation/Permeabilization Kit BD Biosciences Cytomation EnVision + System-HPR (DAB) DAKO Cytometric Bead Array (CBA) Human Flex Sets (IL-5, BD Biosciences IL-6, IFNγ)
Materials 30
Cytometric Bead Array (CBA) Mouse Flex Sets (IFNγ, BD Biosciences IL-5, IL-6, IL-10, IL-13, IL-17A, GM-CSF) Human Soluble Protein Master Buffer Kit BD Biosciences Mouse/Rat Soluble Protein Master Buffer Kit BD Biosciences Pierce™ BCA Protein Assay Kit Thermo Fisher Scientific VECTASTAIN ABC HRP Kit (Peroxidase, Rabbit IgG ) Vector Laboratories WesternBright Sirius Biozym
4.6 Cell lines
4.6.1 Human cell lines NAME ORIGIN VENDOR ATCC® # HEK293T Human embryonic kidney ATCC® CRL-3216™
4.6.2 Murine cell lines NAME ORIGIN VENDOR DSMZ # D10.G4.1 Murine T-helper cell (CD4 +) DSMZ ACC-45
4.7 Primary human TCL specimen The peripheral blood sample was obtained with informed consent from a patient with AITL who was untreated until day of blood sampling.
4.8 Antibodies
4.8.1 Cell depletion IMMUNOGEN /USE REACTIVITY SOURCE PURIFICATION MANUFACT. Ly-6G mouse rat Ultra-LEAF™ BioLegend IgG Isotype Control keyhole limpet rat Ultra-LEAF™ BioLegend
4.8.2 Flow cytometry IMMUNOGEN REACTIVITY FLUOROCHROME CLONE MANUFACT. CD3 mouse BV510 17A2 BioLegend CD3 mouse PE/Cy7 17A2 BioLegend CD3 human V450 UCHT1 BD Biosciences CD4 mouse APC GK1.5 BioLegend CD4 mouse PaB RM4-5 BD Biosciences CD4 human BV510 OKT4 BioLegend CD7 human PE/Cy7 CD7-6B7 BioLegend CD8a mouse eFluor450 53-6.7 eBiosciences CD8a mouse PaB 53-6.7 BioLegend CD8a human PE HIT8a BioLegend CD11b human/mouse PE M1/70 BioLegend CD11b human/mouse PE/Cy7 M1/70 BD Biosciences CD16/32 mouse PE 2.4G2 BD Biosciences Materials 31
CD19 mouse PE/Cy7 6D5 BioLegend CD34 mouse PE/Cy5 MEC14.7 BioLegend CD45 human FITC HI30 BioLegend CD45.1 mouse APC A20 BioLegend CD45.2 mouse APC 104 BioLegend CD45R (B220) human/mouse PE/Cy5 RA3-6B2 BioLegend CD90.2 mouse PE/Cy7 30-H12 BioLegend CD117 (c-kit) mouse APC 2B8 BioLegend CD117 (c-kit) mouse PE 2B8 BioLegend CD127 (IL-7RA) mouse PE/Cy7 A7R34 BioLegend F4/80 mouse APC BM8 BioLegend Ly-6A/E (Sca-1) mouse PaB E13-161.7 BioLegend Ly-6G mouse PaB 1A8 BioLegend Ly-6G/Ly-6C mouse PE/Cy7 RB6-8C5 BioLegend (Gr-1) Ly-6G/Ly-6C mouse APC RB6-8C5 BioLegend (Gr-1) STAT3 pY795 human/mouse AF647 4/P-STAT3 BD Biosciences STAT5 pY694 human/mouse AF647 47/STAT5 BD Biosciences Ter119 mouse PE/Cy7 Ter-119 Biolegend
4.8.3 Co-Immunoprecipitation and western blot
4.8.3.1 Primary antibodies IMMUNOGEN REACTIVITY SOURCE DILUTION MANUFACT. -Actin human/mouse mouse 1: 50,000 Sigma Aldrich ITK human/mouse mouse 1:1000 Cell Signaling JAK1 human/mouse rabbit 1:1000 Santa Cruz JAK1pY1034/1035 human/mouse rabbit, polyclonal 1:500 Cell Signaling JAK2 human/mouse rabbit, monoclonal 1:1000 Cell Signaling JAK2pY1008 human/mouse rabbit, monoclonal 1:1000 Cell Signaling JAK3 human/mouse rabbit, monoclonal 1:1000 Cell Signaling JAK3pY980/981 human/mouse rabbit, monoclonal 1:500 Cell Signaling STAT3 human/mouse rabbit, monoclonal 1:1000 Cell Signaling STAT3 pY705 human/mouse rabbit, polyclonal 1:1000 Cell Signaling STAT4 human/mouse rabbit, monoclonal 1:1000 Cell Signaling STAT4 pY693 human/mouse rabbit, polyclonal 1:1000 Cell Signaling STAT5 human/mouse rabbit, polyclonal 1:1000 Cell Signaling STAT5 pY694 human/mouse rabbit, monoclonal 1:1000 Cell Signaling STAT6 human/mouse rabbit, monoclonal 1:1000 Cell Signaling STAT6 pY641 human rabbit, polyclonal 1:1000 Cell Signaling
4.8.3.2 Secondary antibodies IMMUNOGEN REACTIVITY SOURCE DILUTION MANUFACT. IgG mouse goat 1:20,000 Santa Cruz IgG rabbit goat 1:20,000 Cell Signaling Materials 32
4.8.4 Immunohistochemistry
4.8.4.1 Primary antibodies IMMUNOGEN REACTIVITY SOURCE DILUTION MANUFACT. CD3 human/mouse rabbit, monoclonal 1:50 abcam CD11b mouse rabbit, polyclonal 1:400 abcam CD11b human/mouse rabbit, monoclonal 1:100,000 abcam
4.8.4.2 Secondary antibodies IMMUNOGEN REACTIVITY SOURCE DILUTION MANUFACT. DAKO IgG rabbit goat premixed (EnVision +) Vector IgG rabbit goat 1:200 Laboratories Reactivities against species are only indicated for human and mouse. STAT5 antibodies recognize both isoforms of STAT5 (STAT5A and STAT5B).
4.9 Plasmids PLASMID FUNCTION mammalian retroviral vector for expression of reporter protein pMI-empty-GFP GFP mammalian retroviral vector for expression of human ITK-SYK pMI-ITK-SYK-GFP oncogene and reporter protein GFP mammalian retroviral vector for expression of human pMI-myr. SYK-GFP myristoylated SYK gene and reporter protein GFP mammalian retroviral vector for expression of human SYK pMI-SYK WT-GFP gene and reporter protein GFP mammalian retroviral vector for expression of human pMI-SYK Y325H-GFP constitutively active SYK Y325H oncogene gene and reporter protein GFP EcoPack retroviral packaging system
4.10 Inhibitors AGENT TRADENAME MECHANISM MANUFACTURER Pacritinib none Tyrosin-kinase inhibitor CTI BioPharma Ruxolitinib JAKAVI Tyrosin-kinase inhibitor Novartis Pharma
4.11 Mouse strains and husbandry NAME NOMENCLATURE Model # VENDOR The Jackson Balb/c Balb/cJ 000651 Laboratory Balb/c Balb/cJ Balb/cJRJ Janvier NOG NOD.Cg-Prkdc scid Il2rg tm1Sug /JicTac NOG-F/M TACONIC Animal experiments were authorized by the Regierungspräsidium Freiburg and performed in concordance with the Tierschutzgesetz . Materials 33
Mouse proposals #: G13/071, G12/097, G15/085 Balb/cJ and NOG mice were bred and raised by the Center for Experimental Models and Transgenic Services (CEMT) under SPF-conditions. Upon abandonment of breeding of Balb/cJ in the CEMT-facilities, Balb/cJRJ were ordered directly from Janvier. Mice were kept appropriately for the species and veterinarily checked. Water ad libitum, Baytril (0.0125‰) at all times for transplanted NOG mice, Baytril (0.0125‰) for Balb/c until two weeks after transplantation (tx), then untreated Food ad libitum, autoclaved Litter autoclaved Cages IVC (four animals per cage max.) at all times for transplanted NOG mice, IVC for Balb/c until two weeks after tx, then standard cages (five animals per cage max.) Room temperature 21 2°C Relative humidity 55 10% Light-dark-cycle 12 h Treatment bid 10 µl/g body weight (bw) Vehicle bid 30 mg/kg bw Ruxolitinib (3 mg/ml) bid 150 mg/kg bw Pacritinib (15 mg/ml) for eleven days, then reduction to 75 mg/kg bw (7.5 mg/ml) due to toxicity Schematic mouse and equipment images in Figure 6.2 A, Figure 6.3 A, Figure 6.4 and 6.25 were obtained from Pixabay Website.
4.12 Databases NAME URL Ensembl www.ensembl.org ExPASy Proteomics Server www.expasy.ch/sprot/ NCBI www.ncbi.nlm.nih.gov/ PubMed www.pubmed.gov UniProt www.uniprot.org
4.13 Software and tools NAME MANUFACTURER Acrobat Reader Adobe A plasmid Editor v2_0_29d M. Wayne Davis AxioVision Zeiss Diva BD Biosciences Expasy Translate Tool www.web.expasy.org/translate/ FACSDIVA™ BD Biosciences FCAP Array v3.0 BD Biosciences Materials 34
FloJo v7.6.5, v10.4.2 FlowJo LLC EndNote X7 Clarivate Analytics Graph Pad Prism 5.02 GraphPad Microsoft Office (Excel, PowerPoint, Word, OneNote) Microsoft Paint v4.3 Microsoft SparkControl TECAN Summit DAKO ChemoStar Intas Science Imaging ZEN Zeiss
Methods 35
5 Methods
5.1 In vitro experiments
5.1.1 Cell culture
5.1.1.1 Thawing, cultivating and freezing of cells Cryopreserved HEK293T cells or D10.G4.1 cells were thawed in a 37°C waterbath and transferred to 9 ml of HEK293T medium. After centrifugation (1500 rpm, 5 min), the supernatant was removed and the cells were resuspended in their respective culture medium. The cells were then transferred to cell culture flasks and kept at 37°C and 5% CO 2. Adherent HEK293T cells were cultivated until approximately 70% confluency. For cell splitting or seeding, the supernatant was removed, the cells were washed once with PBS and detached from the culture flask by the addition of 0.05% trypsin-EDTA (1 ml, 2 ml or 4 ml for T25-, T75- or T175-flask respectively). The trypsin reaction was stopped by resuspending the cells in HEK293T medium and the appropriate volume of cells for a splitting ratio of 1:8 to 1:12 or a definite cell number was transferred to a new flask or culture dish and filled up with the appropriate volume of medium. Suspension D10.G4.1 cells were cultivated in D10.G4.1 medium to a density of approximately 1 x 10 6/ml. The appropriate volume of cells for a splitting ratio of 1:5 to 1:8 or a definite cell number was transferred to a new flask and filled up with the appropriate volume of D10.G4.1 medium. For cryopreservation, the appropriate number of cells was centrifuged at 1500 rpm for 5 min and the supernatant was discarded. The pellet was resuspended in 1 ml cryopreservation medium and transferred to a 1.2 ml cryogenic tube. To ensure homogeneous freezing, tubes were kept at -80°C in isopropanol filled Mr Frosty freezing containers overnight and subsequently transferred to liquid nitrogen for long-term storage.
5.1.1.2 Cell counting To determine absolute cell counts, 10 µl of the cell suspension were mixed with 10 µl of trypane blue (1:10 diluted solution) which stains dead cells. 10 µl thereof were then added to a Neubauer counting chamber with coverslip. All living cells were counted in the four major quadrants and the cell number per ml and the absolute count were determined as follows: count/ml = (counted cells / 4) x 10 4 x 2 (dilution in trypane blue) total count = counted cells/ml x total volume of cell suspension
5.1.1.3 Serum and growth factor starvation To inhibit cell signaling mediated by the growth factors and FBS present in the culture medium, D10.G4.1 cells pre-seeded at 5 x 10 5/ml the previous day were starved for 2 h. After Methods 36 removing the supernatant by centrifugation at 1500 rpm for 5 min, cells were washed twice with PBS. Each wash was followed by centrifugation at 1500 rpm for 5 min and removal of the supernatant. Finally, cells were resuspended in 7-10 ml starvation medium and kept at
37°C and 5% CO 2 for 2 h.
5.1.2 Retroviral transduction of non-adherent cell line D10.G4.1
5.1.2.1 Production of retrovirus HEK293T cells were seeded at 7 x 10 6/ml in 6-well plates (2 ml/plate) and kept in HEK293T medium o/n at 37°C and 5% CO 2. At a cell density of approximately 70%, cells were transfected with EcoPack (1.3 µg/well) and pMI vector encoding the desired oncogene and/or GFP (2.7 µg/well). For this purpose, plasmid DNA was mixed with 150 µl of DMEM medium without additives and 10 µl PEI was added. The samples were mixed well by vortexing and kept at room temperature (RT) for 10 min. During incubation, medium on HEK293T cells was replaced by fresh HEK293T medium and the DNA complex was added to the cells dropwise. After 6 h of cultivation, the medium was replaced once again and after an additional 18 h, virus supernatant was filtered through a sterile 0.2 µm filter. 2 ml of fresh HEK293T medium was added to each well and after 24 h, virus harvest was repeated. To assess transfection efficacy, cells were trypsinated as described above and analyzed for expression levels of the reporter protein GFP by flow cytometry (FACS).
Figure 5.1: FACS analysis of HEK293T cells after transfection with pMIG vector. The number above the desired gate indicates the percentage of GFP + cells within total cells in this dotplot (frequent of parent).
PE
GFP
5.1.2.2 Retroviral transduction of a murine T-cell line D10.G4.1 cells were seeded at 7 x 10 4/ml in 12-well plates (1 ml/plate) and kept in D10.G4.1 medium o/n at 37°C and 5% CO 2. For retroviral infection, 1 ml virus supernatant/well was mixed with 10 µl of 1 µg/µl polybrene and kept at RT for 5 min. Subsequently, virus supernatant was added to the cultivated D10.G4.1 cells and cells were centrifuged at 2500 rpm and 32°C for 90 min, before being cultivated as described above. After 8 h, switchback was performed. For this purpose, 1 ml of supernatant was removed from the cells and centrifuged at 1500 rpm for 5 min to pellet any remaining cells. These were then Methods 37 resuspended in 1 ml fresh D10.G4.1 medium and added to the respective well. After removal of 1 ml of cell supernatant, retroviral infection and switchback were repeated after 24 h with the same D10.G4.1 cells. To expand the cells for FACS sorting and freezing, they were cultivated and split as described above. Cells were then analyzed for transduction efficacy by measuring expression levels of the reporter protein GFP by flow cytometry.
Figure 5.2: FACS analysis of D10.G4.1 cell line after transduction with pMIG vector. The number within the desired gate indicates the percentage of GFP + cells within total cells in this dotplot (frequent of parent).
PE
GFP
5.1.2.3 Cell sorting To ensure that all D10.G4.1 cells expressed the desired human gene, cells were FACS sorted by the expression of GFP. The corresponding gene was encoded on the same plasmid as the chosen human gene and the protein could therefore be used as a reporter for successful transduction. Cells were sorted using BD FACSAria TM Fusion cell sorter with the help of Klaus Geiger and Dieter Herchenbach. Only GFP expressing cells were cultivated further and used for subsequent analysis.
5.1.3 Protein analysis To assess the expression or activity of specific proteins of interest in cell lines, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and subsequent transfer by western blot (WB) and immunodetection of total and phosphorylated antigens was performed.
5.1.3.1 Isolation of total protein and determination of protein concentration Cells were seeded at 0.5 x 10 6/ml and cultivated for 22 h or 24 h respectively. Former were then growth factor and serum starved for an additional 2 h. Next, cells were pelleted and washed once with PBS (centrifugation at 1500 rpm for 5 min) and the cells were resuspended in the respective volume of Reinhard lysis buffer (depending on pellet size 75 - 200 µl) and kept on ice for 10 min. After centrifugation at 10,000 rpm for 10 min at 4°C, the purified protein lysate (= supernatant) was transferred to a new tube. Protein concentration was determined using Pierce bicinchoninic acid (BCA) protein assay according to manufacturer’s protocol and lysates were stored at -20°C. Methods 38
5.1.3.2 SDS-PAGE 50 µg of protein was mixed with the appropriate volume of 4 x LDS Sample Buffer and 10 x reducing agent and the total volume was adjusted to 25 µl with dH 2O. Samples were heated to 75°C for 10 min and subsequently loaded onto a 10% resolving SDS polyacrylamide gel overlaid by a 4% stacking gel together with a pre-stained protein marker. Separation was achieved by applying a voltage of 70 V until samples had passed through the stacking gel followed by an increase to 140 V.
5.1.3.3 Western blot and detection After the gel run, proteins were transferred to a nitrocellulose membrane using a tank blotting system by applying an electric current of 400 mA for 1 h 45 min. To verify successful protein transfer, a Ponceau S solution was added to the membrane, incubated for 5 min at RT on a platform shaker and rinsed with water to visualize the protein bands. After removing leftover Ponceau S staining from the membrane by washing in TBS-T, the membrane was blocked in 5% BSA in TBS-T for 1 h and subsequently incubated o/n in primary antibody directed against the protein of interest diluted in 5% BSA in TBS-T under constant agitation. After three wash steps in TBS-T, a horseradish peroxidase (HRP)-linked secondary antibody directed against the primary antibody was added to the membrane and incubated for at least 1 h before washing was repeated. Eventually, the protein-antibody complex was visualized by adding enhanced chemiluminescence (ECL) substrate to the membrane and exposing it for up to 20 min using an ECL chemocam imager. In case of the detection a phosphorylated antigen, the membrane was used again to detect the total amounts of the respective protein. Therefore, membranes were kept in stripping solution for 5 to 7 min at 50 °C, followed by three washing steps with TBS-T. Then blocking and immunodetecting procedures were repeated for the total protein binding primary antibody.
5.1.3.4 Co-Immunoprecipitation To determine which proteins interact with one another in the D10.G4.1 cell line, co-immunoprecipitation (co-IP) experiments were performed. Cells were starved for 2 h (see 5.1.1.3), protein lysates were prepared and protein concentration was assessed as described in 5.1.3.1. SDS-PAGE and Western Blots were performed for whole protein lysates as described in 5.1.3.2 and 5.1.3.3 to obtain input controls. 500 µg of protein were then used for the co-IP. Sepharose beads were selected according to the species from which the precipitating antibody was derived (protein A sepharose beads for rabbit antibodies, protein G sepharose beads for murine antibodies). 300 µl of beads were washed twice with 500 µl PBS (13,000 rpm for 1 min at 4°C) and were then resuspended in 300 µl ice-cold PBS. In order to reduce unspecific binding to the beads, pre-clearing of the lysates was performed by adding 20 µl of the respective beads to 500 µg whole protein lysate. The samples were then Methods 39 rotated for 60 min at 4°C and subsequently centrifuged at 13,000 rpm for 12 min at 4°C. The supernatant was transferred to a new tube and the beads were discarded. For the co-IP, the precipitating antibody (2 µl) was added to the pre-cleared protein lysate and rotated o/n at 4°C. The next day, 30 µl of the respective beads were added to the sample in order to bind the antibody-antigen complex and hence to any proteins bound to the protein of interest. The mix was rotated for 90 min at 4°C followed by centrifugation at 13,000 for 1 min at 4°C. The supernatant was removed and the antibody-bound beads were washed 3 x with Reinhard lysis buffer (13,000 rpm for 1 min at 4°C). The bead pellet now only contained the precipitating antibody with its antigen and any proteins directly interacting with it. Finally, to visualize the binding partners of the desired protein, the pellet was resuspended in 15 µl 4 x LDS Sample Buffer and 7 µl 10 x reducing agent and heated to 75°C for 10 min. SDS-PAGE and Western Blot were performed as described in 5.1.3.2 and 5.1.3.3.
5.2 In vivo experiments
5.2.1 Bone marrow transplantation (ITK-SYK mouse model)
5.2.1.1 Enrichment, isolation and cultivation of primary murine BM cells Male Balb/c donor mice were injected intraperitoneally (ip) with 10 mg/kg bw 5-FU to enrich for hematopoietic stem and progenitor cells in the bone marrow. After four days, mice were killed by cervical dislocation and femurs, tibias and hip bones were excised. Bones were flushed with HEK293T-medium using a syringe canule and filtered through a 100 µm cell strainer. After pelleting (1500 rpm for 5 min), bone marrow cells were lysed for 10 min at RT in GEY’s solution. After two washing steps in HEK293-T medium (1500 rpm for 5 min each), cells were counted as described in 5.1.1.2 and resuspended in an appropriate volume of prestimulation medium to obtain cell suspension of 3-5 x 10 6/10 ml and kept on 10 cm dishes o/n at 37°C and 5% CO 2 for subsequent retroviral transduction.
5.2.1.2 Production of retrovirus HEK293T cells were seeded at 3 x 10 5/ml in 10 cm dishes (10 ml/dish) and kept in HEK293T medium o/n at 37°C and 5% CO 2. At a cell density of approximately 70%, cells were transfected with EcoPack (2 µg/dish) and pMI vector encoding the ITK-SYK and/or GFP (8 µg/dish). For this purpose, plasmid DNA was mixed with 500 µl of DMEM medium without additives and 30 µl FuGENE HD transfection reagent was added. The samples were mixed by snipping and kept at RT for 15 min. During incubation, medium on HEK293T cells was replaced by 3 ml fresh HEK293T medium and the DNA complex was added to the cells dropwise. 8 h and 24 h after transfection, 5 ml fresh HEK293T medium were added and after another 24 h, virus supernatant was filtered through a sterile 0.2 µm filter. To assess transfection efficacy, cells were trypsinated as described in 5.1.1.1 and analyzed for Methods 40 expression levels of the reporter protein GFP by flow cytometry (similar to transduction with PEI, see Figure 5.1).
5.2.1.3 Retroviral transduction of primary murine BM cells For retroviral transduction, bone marrow cells were seeded at 3-5 x 10 6/3 ml prestimulation medium in 6-well plates. 3 ml virus supernatant were mixed with 270 µl HEPES and 5.4 µl 10 mg/ml polybrene and added to the pre-seeded BM cells (final concentration: 45 mM HEPES, 9 µg/ml polybrene). Spininfection was performed at 2400 rpm for 90 min at 32 °C and cells were subsequently kept at 37°C and 5% CO 2 for 6 h. For switchback, 3 ml of supernatant was removed from the cells and centrifuged at 1500 rpm for 5 min to pellet any remaining cells. These cells were then resuspended in 3 ml fresh prestimulation medium and added to the respective well. The second spininfection was performed similarly 24 h after the first and after removal of 3 ml of cell supernatant. 6 h later, BM cells were harvested, washed once with 1 x HBSS, filtered again through a 100 µm cell strainer and counted. Cell concentration was adjusted to 5 x 10 5/150 µl in 1 x HBSS. 24 h after the second spininfection, leftover BM cells were analyzed for transduction efficacy by measuring expression levels of the reporter protein GFP by flow cytometry.
Figure 5.3: FACS analysis of primary murine BM cells after transduction with pMIG vector. The number above the desired gate indicates the percentage of GFP + cells within total cells in this dotplot (frequent of parent).
PE
GFP
5.2.1.4 Irradiation of recipients Female Balb/c recipient mice were lethally irradiated with 4.5 Gray (Gy) 24 h prior to transplantation using an X-ray irradiation source. Irradiation was repeated 6 h prior to transplantation. To minimize infection risk, mice received Baytril in their drinking water for at least 2 weeks after irradiation.
5.2.1.5 BM transplantation Mice were narcotized using isoflurane and retroorbitally injected with 150 µl 1 x HBSS containing 5 x 10 5 transduced BM cells. Methods 41
5.2.2 Bone marrow retransplantation (ITK-SYK mouse model) For retransplantation (retx) experiments, CD3 +CD90 + thymus and spleen cells from ITK-SYK transplanted mice were sorted for CD4 +CD8 -, CD4 -CD8 +, CD4 +CD8 + and CD4 -CD8 - by FACS (see 5.2.10). Sorted cells were mixed with 1 x 10 6 Balb/c WT bone marrow cells per recipient mouse, resuspended in 150 µl 1 x HBSS and retroorbitally injected into narcotized lethally irradiated Balb/c recipients (see 5.2.1.4 and 5.2.1.5).
5.2.3 Bone marrow transplantation (xenograft model)
5.2.3.1 Isolation of primary patient PBMCs by Pancoll 1 monovette-EDTA with approximately 10 ml of peripheral blood (PB) from an AITL patient was mixed with 20 ml of PBS and the mixture was carefully layered over 15 ml Pancoll solution with a density of 1.077 g/ml. To obtain a peripheral blood mononuclear cell (PBMC) phase, the sample was centrifuged at 400 x g and RT for 30 min without a break. The white intermediate layer contained the PBMCs and was carefully removed and transferred to a new tube. Cells were washed twice in 50 ml PBS (200 – 300 x g, RT, 10 min), counted (see 5.1.1.2) and frozen in FBS + 10% DMSO as described for in vitro freezing procedures (5.1.1.1).
5.2.3.2 Transplantation Cells were thawed as described for in vitro thawing procedures (5.1.1.1), washed twice with 10 ml PBS (1500 rpm, 5 min), counted (5.1.1.2) and resuspended at 6 x 10 6/ml in 1 x HBSS. 1 NOG mouse was narcotized with isoflurane and cells were injected ½ ip and ½ iv retroorbitally.
5.2.4 Bone marrow retransplantation (xenograft model) For retransplantation experiments, total spleen cells from primary or secondary xenografts were harvested. After erythrocyte lysis and washing with HEK293T medium (for procedures see 5.2.9), cells were counted (5.1.1.2), analyzed for human (h) CD45 by FACS (5.2.10) and resuspended in the appropriate volume of 1 x HBSS to obtain 400 µl cell suspension for each recipient mouse to be transplanted. Cells were then injected into NOG recipients according to 5.2.3.2.
5.2.5 Treatment experiments
5.2.5.1 Treatment with granulocyte-depleting antibody For granulocyte depletion experiments, GFP- and ITK-SYK-mice were split into equal groups by weight. In order to assess the influence of neutrophil granulocytes on the ITK-SYK phenotype, this cell type was depleted using an anti-Ly-6G antibody as has been described before.335 For single treatment experiments, mice were injected ip with 250 µg of either anti- Methods 42
Ly-6G antibody or IgG isotype control antibody which harbors a variable region that is not directed against any mouse antigens but hosts the same fragment crystallizable region (Fc-region) on day 14 after GFP or ITK-SYK transplantation. For repetitive treatment experiments, antibody injection was repeated on day 28 after transplantation. Mice were sacrificed and analyzed 42 days after transplantation (5.2.8) or kept for survival studies (5.2.7).
5.2.5.2 Treatment with Pacritinib or Ruxolitinib in ITK-SYK mouse model For JAK inhibitor treatment experiments, GFP- and ITK-SYK-transplanted mice were split into equal groups by weight. Ruxolitinib was administered at 30 mg/kg bw in Vehicle at a concentration of 3 mg/ml. Pacritinib was administered at 150 mg/kg bw in Vehicle at a concentration of 15 mg/ml and after 11 days of treatment reduced to 75 mg/kg bw at 7.5 mg/ml due to toxicity. Active agents and vehicle (10 µl/g bw) were orally administered twice daily for 32 days starting on day 14 after transplantation. Mice were subsequently sacrificed and analyzed (5.2.8). For survival experiments, mice were treated until Vehicle control group died.
5.2.5.3 Treatment with Ruxolitinib in xenograft mouse model Tertiary recipients were transplanted retroorbitally with 27 x 10 6 cells. On day 5 after transplantation treatment with Vehicle (10 µl/g bw) twice daily or 30 mg/kg bw Ruxolitinib (3 mg/ml in Vehicle) twice daily was started and carried out for 16 days. Mice were euthanized on day 21 after transplantation and subsequently analyzed (5.2.8).
5.2.6 Blood withdrawal and processing In order to assess disease progression or successful granulocyte depletion, peripheral blood samples were collected retroorbitally from anaesthetized mice. To obtain total cell counts as well as blood pictures, blood samples were measured using Scil Animal Blood Counter. For flow cytometry, 40 µl of each blood sample were lysed in GEY’s solution for 10 min at RT with two subsequent washing steps with FACS-buffer (1500 rpm, 5 min). Finally, cells were stained for 30 min at 4°C with 0.5 µl fluorochrome-labeled antibodies in 100 µl FACS-buffer followed by another washing step. Data was acquired using CyAn ADP flow cytometer.
5.2.7 Mouse follow-up, determination of phenotypic score and survival analysis After transplantation, mice were monitored for general signs of disease such as ruffled fur, hunched back or clotted eyes and weighed two to three times per week. During Ruxolitinib and Pacritinib treatment periods, mice were monitored and weighed daily. GFP- and ITK- SYK-transplanted mice were sacrificed between day 42 and day 46 after transplantation, xenograft mice were euthanized on day 21 after transplantation when the Vehicle group was Methods 43 moribund (≥ 20% weight loss, severe deterioration of general health). Phenotypic score (ps) was assessed by visual examination and weighing as shown in Table 5.1. To determine the total ps, score points in all 4 categories were summed up. For survival analysis, mice were monitored daily until termination criteria were reached and then denoted as dead. Table 5.1 Phenotypic score (ps) points for weight loss and skin lesions POINTS WEIGHT LOSS TAIL EAR BODY strong/extensive 3 > 15% necrotic necrotic encrustation strong strong intermediate 2 > 10-15% encrustation encrustation encrustation weak weak weak 1 5-10% encrustation encrustation encrustation 0 < 5% no encrustation no encrustation no encrustation
5.2.8 Mouse sacrifice For serum extraction, mice were exsanguinated by retroorbital blood withdrawal. Blood was collected in serum tubes, allowed to clot for 30 min and then centrifuged for 5 min at 10,000 x g. Supernatant (= serum) was transferred to a 1.5 ml reaction tube and frozen at -80°C and subsequently transferred to liquid nitrogen. Mice not exsanguinated were sacrificed by cervical dislocation.
5.2.9 Mouse organ preparation and processing After sacrifice, mice were dissected and organs were extracted. For GFP- and ITK-SYK- transplanted mice, spleen, lung, liver, colon, thymus, femur, tibia, hip bone, ear, tail and a small patch of shaved skin from the back were obtained, of which lung, liver and spleens were weighed. ½ spleen, lung, liver, colon, ear and the skin patch were stored in 10% formaldehyde o/n and then rebuffered into PBS. These organ samples were then taken to the Pathology Department of the University Hospital Freiburg to be embedded into paraffin and sectioned into 5 µm thin slides by Sabine Speier. Histology slides were then mounted on microscopic slides. ½ spleen, ½ thymus and the remaining bones were used for cell purification. Spleen and thymus cells were obtained by mashing the organ with a syringe plunger through a 100 µm cell strainer. Bone marrow cells were obtained by flushing the bones with preparation medium using a syringe canule and subsequent filtering through a 100 µm cell strainer. Cells from one femur were collected separately to assess total cell numbers per femur. Purified primary cells were submitted to erythrocyte lysis using GEY’s solution (10 min RT) and then washed twice with FACS-buffer (1500 rpm, 5 min). For flow cytometry, cells were stained for 30 min at 4°C with 0.5 µl fluorochrome-labeled antibodies in 100 µl FACS-buffer followed by another washing step. Data was acquired using CyAn ADP flow cytometer. Analysis was performed using FlowJo7.6 or FlowJo10.4 software (FlowJo LLC). Methods 44
5.2.10 Flow cytometry Using the CyAn ADP 9 Color Flow Cytometer, it is possible to measure up to 9 different fluorochromes meaning 9 different markers at once. 3 lasers with excitation wavelengths of 405 nm, 488 nm and 633 nm enable measurement of 9 colors using 9 photomultipliers. For laser voltage set-up, unstained samples were used. Compensation was performed using single color stainings. Exclusion of debris/dead cells and duplets was achieved using forward scatter (FS) against side scatter (SS) and FS against pulse width (PW) dotplots respectively.
5.2.10.1 Extracellular stainings Cell surface markers were stained for 30 min at 4°C followed by a single wash step with FACS-buffer (1500 rpm, 5 min). The pellet was then resuspended in approximately 300 µl of FACS buffer and data was acquired using CyAn ADP 9 Color Flow Cytometer. Analysis was performed using FlowJo7.6 or FlowJo10.4 software (FlowJo LLC). The following staining mixes were used for extracellular antigens.
Table 5.2: Mixes for extracellular antigen staining for flow cytometric analysis STAINING ORGAN SURFACE MARKERS Granulocyte/macrophage PB F4/80, Gr-1 depletion Monocyte depletion PB CD11b, Gr-1 Blood lineage PB B220, CD3, CD11b, CD90.2, Ly-6G Lineage Spleen B220, CD3, CD11b, Ly-6G, Ter119 Lineage (for intrac. staining) Spleen CD11b, Ly-6G h/murine (m) B220, h/mCD11b, hCD45, Murine lineage (xenograft) PB, Spleen mLy-6G Lineage (Lin) mix , CD16/32, CD34, cKit, Myeloid progenitors Spleen Sca-1 T-Cells Thymus CD3, CD4, CD8, CD90.2 hCD4, hCD8, hCD7, hCD45, mCD45.1, T-Cells (xenograft) PB, Spleen mCD45.2, CD3, CD11b, CD19, CD127, Gr-1, Lin consists of Ter119
CD90.2 is expressed on murine thymocytes, mature T-cells and neurons. Staining of neurons is not expected in thymus, spleen and blood of Balb/c mice. Therefore CD90.2 was used as a marker for total T-lymphocytes. CD3 is a well-known pan T-cell marker. As in our hands, some anti-CD3 antibodies did not bind their target well or the used fluorophores were not bright enough in some staining mixtures, anti-CD90.2 and/or anti-CD3 antibodies were used for total T-cell detection depending on the staining mix and the fluorophores used. Analyzed cells should be positive for both markers. CD90.2 is abbreviated CD90 in graphs of results section due to space constraints.
Methods 45
Gating strategies for all staining panels are shown in the following figures.
all cells alive singlets
SS PW count
FS FS GFP
Figure 5.4: Gating strategy for alive, singlet and GFP + or GFP - cell populations. Alive cells were separated from debris using FS versus SS dotplot. Singlet cells were determined by FS versus PW distribution. Cells were then separated into GFP + and GFP - populations. The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent).
PB singlets PB singlets
1 - Gr CD11b
F4/80 Gr -1 Figure 5.5: Gating strategy for detection of efficient neutrophil granulocyte, macrophage and monocyte depletion in PB. PB singlet cells were subdivided into F4/80 +Gr-1- macrophages and F4/80 -Gr-1+ neutrophil granulocytes. They were also analyzed for Gr-1+CD11b + monocytes. The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent).
Methods 46
GFP +/ - PB singlets monocytes + granulocytes
CD11b CD11b
B220 Ly -6G
non-monocytes, non- granulocytes, non-B-cells
CD90.2
CD3 Figure 5.6: Gating strategy for analyzing lineage determination of PB cells. GFP + or GFP - singlet PB cells were subdivided into B220 + B-cells and CD11b + cells of myeloid lineage. These myeloid cells were further split into Ly-6G + granulocytes and Ly-6G - monocytes. B220 -CD11b - cells were then separated into CD90.2 + T-cells which co-expressed CD3+ and other cells. Due to low anti-CD3 antibody binding efficiencies, all CD90.2 + cells were labeled T-cells. The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent).
Methods 47
GFP +/ - singlets non-erythrocytes
CD11b CD11b
Ter119 Ly -6G
non-monocytes, non- granulocytes
B220
CD3 Figure 5.7: Gating strategy for analyzing lineage determination of spleen cells and for splenic granulocyte and monocyte staining with subsequent staining of phosphorylated intracellular antigens. GFP + or GFP - singlet cells were depleted of Ter119 + erythrocyte progenitor cells. Non-erythrocyte cells were then subdivided into CD11b +Ly-6G - monocytes and CD11b +Ly-6G + granulocytes. Cells that did not fit into either of these categories were separated into B220 + B-cells and CD3 + T-cells. Cells stained for intracellular antigens were not stained for Ter119, CD3 and CD90, but were divided into monocytes and granulocytes as shown here for non- erythrocytes (upper right image). The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent).
Methods 48
singlets murine non-B
h/mB220 h/mCD11
hCD45 mLy -6G
Figure 5.8: Gating strategy for murine lineage determination of xenograft PB and spleen cells. Singlet cells were subdivided into hCD45 + cells and mB220 + B-cells. NOG mice are not expected to show any B220 expression since they are depleted of all lymphoid cells. The anti-B220 antibody was only used for gating without expecting any noticeable B-cell populations. Non-human and non-mB220 + were further split into CD11b +Ly-6G - monocytes and CD11b +Ly-6G + granulocytes. T-cell levels were not assessed since NOG mice do not harbor any murine T-cells. The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent).
- GFP +/ - singlets Lin
cKit cKit
Lin Sca -1
LK
CD16/32
CD34 Methods 49
Figure 5.9: Gating strategy for analyzing myeloid progenitor populations. GFP + or GFP - singlet spleen cells were depleted of lineage determinated (Lin +) cells. These Lin - cells were divided into cKit +Sca-1+ (LKS) and cKit +Sca-1- (LK) cells. LK cells could then be further separated into CD16/32 - megakaryocyte-erythroid progenitors (MEPs), CD16/32 low common myeloid progenitors (CMPs) and CD16/32 high granulocyte-macrophage progenitors (GMPs). Normally, the MEP compartment would show no expression and the CMP and GMP compartment low expression of CD34, but this antibody clone was found to not bind properly to its target. Discrimination between the progenitor cell types was still possible using only CD16/32 marker expression. The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent). Balb/c spleen cells in general have very low LK and LKS counts. Therefore analyzing the myeloid progenitor pool from spleen cells was very difficult. To improve gating strategies, gatings were optimized using BM cells as shown here and subsequently transferred to equally stained spleen cell samples. LKS cell counts in Balb/c spleens and BM are so low that distinguishing between different hematopoietic stem cell (HSC) such as short-term and long-term HSCs and multipotent progenitors (MPPs) was not feasible.
GFP +/ - singlets T-cells
CD90.2 CD8
CD3 CD4 Figure 5.10: Gating strategy for analyzing T-cells for extracellular only staining methods and for T-cell marker staining with subsequent staining of phosphorylated intracellular antigens. GFP + or GFP - singlet cells were analyzed for CD3 +CD90.2 + T-cells. Thymus cells in anti-Ly-6G antibody treatment experiments were stained using CD90.2 only as a pan-T-cell marker. CD3 +CD90.2 + or CD90.2 + cells respectively were then further divided into CD4 + T-helper cells and CD8 + cytotoxic T-cells as well as the immature T-cell subgroups expressing both (CD4 +CD8 +) or none (CD4 -CD8 -) of these two markers. The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent).
Methods 50
singlets hCD45
mCD45.1/mCD45.2 hCD8
hCD45 hCD4
hCD4 +/hCD8 +/hCD4 +hCD8 +
SS
hCD7 Figure 5.11: Gating strategy for human T-cell subpopulations of xenograft PB and spleen cells. Singlet cells were subdivided into human (h)CD45 + cells and murine (m)CD45 + cells. Human cells were then further divided into CD4 + T-helper cells and CD8 + cytotoxic T-cells as well as the immature T-cell subgroups expressing both of these two markers. All T-cell subpopulations were then analyzed for the expression of CD7. The number below the name of the desired gate indicates the percentage of gated cells within total cells in this dotplot (frequent of parent).
5.2.10.2 Intracellular stainings For intracellular staining of phosphorylated and therefore activated STAT3 and STAT5, extracellular lineage and T-cell stainings were performed as described in 5.2.10.1. After an additional washing step in FACS-buffer (1500 rpm, 5 min), cells were fixed and permeabilized in 250 µl Fixation/Permeabilization Solution obtained with the BD Fixation/Permeabilization Solution Kit for 20 min at 4°C. After a centrifugation step (1500 rpm, 5 min), the supernatant was discarded and the fixated cells were washed twice in 1 ml 1 x BD Perm/Wash Buffer (1500 rpm, 5 min). Intracellular antigens were stained with 1 µl fluorochrome-labeled antibody in 50 µl 1 x BD Perm/Wash Buffer for 30 min at 4°C. Finally, cells were washed twice in 1 ml 1 x BD Perm/Wash Buffer (1500 rpm, 5 min) and the pellet then resuspended in 300 µl of 1 x BD Perm/Wash Buffer. Flow cytometry data was acquired using CyAn ADP 9 Color Flow Cytometer. FACS analysis and calculation of mean Methods 51 fluorescence intensity (MFI) of the respective intracellular antigen for each desired cell type was performed using FlowJo7.6 or FlowJo10.4 software (FlowJo LLC).
5.2.10.3 Cell sorting For T-cell retransplantation experiments, thymus and spleen cells were harvested as described in 5.2.9 and cells were stained using T-cells staining panel. CD3 +CD90 + cells of each organ were subdivided into CD4 +CD8 -, CD4 -CD8 +, CD4 +CD8 + and CD4 -CD8 - cells and all cell populations were sorted using BD FACSAria TM Fusion with the help of Klaus Geiger and Dieter Herchenbach.
5.2.11 Cytokine arrays To determine serum cytokine levels, serum samples were thawed and diluted 1:4 in assay diluent obtained from the respective CBA Master Buffer Kit. The cytokine assay was performed using the mouse or human CBA Master Buffer Kit and the CBA Flex Sets for mIFN-γ, mIL-5, mIL-6, mIL-10, mIL-13, mIL-17A and mGM-CSF or hIFN-γ, hIL-5 and hIL-6 respectively according to manufacturer’s protocol. Data was acquired on BD LSRFortessa flow cytometer and analysed using BD FCAP Array v4.0.
5.2.12 Histopathology and immunohistochemistry Organs were fixated, embedded and sectioned as described in 5.2.9. Slides were kept at 56°C o/n prior to immunohistochemical staining.
5.2.12.1 Immunohistochemistry staining using anti-CD3 antibody with VECTASTAIN ABC HRP Kit Deparaffinisation was achieved by incubating the slides as follows: 5 x 6 min in Histoclear 4 x 3 min Ethanol 100% 1 x 2 min Ethanol 96% 1 x 2 min Ethanol 70%
1 x 3 min dH 2O Antigen retrieval was performed by heating the slides for 15 min in 1 x DAKO Target Retrieval Solution in a steamer followed by cooling on ice for 7 min. Immunohistochemical staining was performed using an antibody directed against CD3 (1:300 dilution in 1% BSA in PBS) according to VECTASTAIN ABC HRP Kit protocol. The primary antibody was incubated o/n at 4°C, the secondary antibody was incubated for 30 min at RT. Counterstain was done with Mayer’s hemalum for 30 seconds (sec) followed by a 1 sec wash in 0.1% HCl. Pictures were taken using the AxioImager microscope by Zeiss. Methods 52
5.2.12.2 Immunohistochemistry staining using anti-CD11b antibody with Cytomation EnVision + System-HPR Deparaffinisation and antigen retrieval was performed similarly to 5.2.12.1. Immunohistochemical staining was performed using an antibody directed against murine CD11b (1:400 dilution in 3% BSA in TBS) according to Cytomation EnVision + System-HPR protocol. The primary antibody was incubated o/n at 4°C, the secondary antibody was incubated for 30 min at RT. Counterstain was done with Mayer’s hemalum for 30 sec followed by a 1 sec wash in 0.1 % HCl. Pictures were taken using the Axioplan2 microscope by Zeiss.
5.2.12.3 Immunohistochemistry staining using anti-CD11b antibody with CSA, Catalyzed Signal Amplification System Deparaffinisation was achieved by incubating the slides as follows: 2 x 5 min in Histoclear 2 x 5 min Ethanol 100% 2 x 5 min Ethanol 95% 1 x 5 min Ethanol 70% 1 x 5 min PBS + 0.3% Triton X-100 Antigen retrieval was performed by heating the slides for one heating cycle in 1 x DAKO Target Retrieval Solution in 2100 Antigen Retriever followed by cooling at RT for 2 h. Immunohistochemical staining was performed using an antibody directed against CD11b (1:100,000 dilution in 1% BSA in TBS) according to BD CSA, Catalyzed Signal Amplification System protocol. Avidin and biotin block were performed using the Avidin/Biotin Blocking Kit by Vector Labs. The primary antibody was incubated for 48 h at 4°C. The secondary antibody was used from the VECTASTAIN ABC HRP Kit, diluted 1:200 in 1% BSA in TBS and incubated for 15 min at RT. Counterstain was done with hemalaun for 30 sec followed by a 1 sec wash in 0.1 % HCl. Pictures were taken using the AxioImager microscope by Zeiss.
5.3 Statistical analysis Data is shown as mean values + standard error of the mean (SEM, error bars). To determine significant differences between groups or parameters, two-tailed unpaired Student’s t-test was performed. Survival studies were tested using the Log-rank Mantel-Cox test. A p-value (p) < 0.05 was considered statistically significant.
Results 53
6 Results
6.1 ITK-SYK expression in primary bone marrow cells causes T-cell lymphoma in mice The gene encoding the kinase/kinase fusion ITK-SYK is expressed in 17% of all PTCL-NOS cases 25 and is comprised of the N-terminal PH- and TH-domains of ITK and the C-terminal TK-domain of SYK (Figure 6.1 A). To assess the effects of this oncogene in a murine PTCL model, primary Balb/c BM cells were transduced with pMIG vector expressing GFP or pMIG-ITK-SYK vector expressing ITK-SYK coupled to GFP as a reporter and subsequently transplanted into lethally irradiated recipient mice (GFP mice and ITK-SYK mice). Within seven weeks, strong infiltration of peripheral organs such as skin with CD3 positive T-cells could be observed in ITK-SYK mice. This resulted in alterations in organ structure e.g. in complete destruction of the subcutaneous adipose tissue (Figure 6.1 B). Furthermore, ITK- SYK mice developed massive granulocytosis (Figure 6.1 C). Interestingly, GFP + cells which harbored the ITK-SYK gene as well as GFP - cells with a wild-type (WT) genotype expanded in equal proportions. This indicates that granulocyte proliferation is not dependent on ITK- SYK expression in the granulocytes themselves. It is rather likely to be driven by extracellular stimuli e.g. by growth factors or cytokines secreted by other cells as a response to ITK-SYK expression.
A ITK SYK B Skin CD3 PH TH Kinase GFP ITK-SYK
C PB Granulocytes GFP+ 80 *** GFP- cells *** + PB cells PB
- 60 Ly-6G
+ 40 /GFP +
20 ** 0 % of CD11b
within GFP within GFP ITK-SYK
Figure 6.1: ITK-SYK expression in primary bone marrow cells causes T-cell lymphoma in mice. (A) Schematic representation of ITK-SYK. (B) Immunohistochemical HRP-DAB staining of paraffin-embedded skin tissue of control Balb/c mice transplanted with BM transduced with empty pMIG-vector (GFP mice, left) and Balb/c mice transplanted with BM transduced with pMIG-ITK-SYK-vector (ITK-SYK mice, right) with anti-CD3 antibody on day (d) 46 after transplantation (tx) after treatment for 32 days with Vehicle (Veh) without bioactive compound (original magnification x 100). Shown are representative images for skin-stainings of at least 3 different mice per group. (C) Percentage of CD11b +Ly-6G + cells within GFP + or GFP - peripheral blood (PB) cells of GFP and ITK-SYK mice after treatment for 29 days with Veh without bioactive compound (n=5 per group). Blood samples were taken on d43 after tx and analyzed by FACS. Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP + and GFP - populations within the same mice. Results 54
6.2 Depletion of granulocytes in ITK-SYK mice improves survival, but does not alter T-cell phenotype To investigate which features of the ITK-SYK phenotype are mediated by granulocytosis and whether depletion of this cell type could improve disease development, anti-Ly-6G antibody (ab) treatment experiments were performed.
6.2.1 Single injection of granulocyte depleting antibody in ITK-SYK mice improves phenotypic score For the first experiment, the mice were injected intraperitoneally (ip) with a single dose of 250 µg immunoglobulin G (IgG) isotype control ab or anti-Ly-6G ab on d14 after tx (Figure 6.2 A). FACS analysis of PB levels of myeloid cells revealed a specific and effective depletion of the granulocytic cell compartment within 24 h, whereas macrophage and monocyte levels remained unchanged (Figure 6.2 B). The mice were monitored until d37 after tx and then assessed for their macroscopic phenotype. As described, calculation of a phenotypic score was achieved by distributing score points for weight loss as well as ear, tail and skin encrustations and necrosis as they occur in this mouse model (Table 5.1, page 43). Single dose anti-Ly-6G ab treatment was able to significantly improve this phenotypic score (Figure 6.2 C)
A
d0 d14 d15 d37 GFP/ITK-SYK tx 1st ip PB ps IgG/ assessment Ly-6G ab B C Myeloid Cell Compartment (d15) Phenotypic Score (d37) 20 8 ** IgG * Ly-6G 15 6
10 4
5 2 phenotypic score phenotypic 0 0 % of myeloid cells in PB in %of cells myeloid granulocytes macroph. monocytes IgG Ly-6G (Gr-1 +F4/80 -) (Gr-1 -F4/80 +)(Gr-1 -CD11b +)
Figure 6.2: Single injection of granulocyte depleting antibody in ITK-SYK mice improves phenotypic score. (A) Workflow of experimental procedure. ps, phenotypic score. Mice were injected ip with 250 µg of the respective ab. (B) Percentage of granulocytes (Gr-1+F4/80 -), macrophages (macroph. Gr-1-F4/80 +) and monocytes (Gr-1-CD11b +) in PB of ITK-SYK mice on d1 after single ip injection with IgG isotype control ab or anti- Results 55
Ly-6G. Blood samples were taken on d15 after tx and analyzed by FACS. (C) Phenotypic score of ITK-SYK mice 23 days after single ip injection with IgG isotype control ab or anti-Ly-6G ab on d37 after tx. (B, C) n=6 per group. Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Parts of this experiment were performed and analyzed by T. Mack.
6.2.2 Repeated injection of granulocyte depleting antibody in ITK-SYK mice improves survival, but does not alter T-cell phenotype To investigate the effects of extended granulocytic depletion, two doses of 250 µg of IgG isotype control ab or anti-Ly-6G ab were administered on d14 and d28 after tx. Analysis of myeloid cell levels in PB on d15 after tx revealed similar results as shown before (Figure 6.2 B, not shown). Mice were sacrificed on d42 after transplantation which corresponds to d14 after the second ab administration or monitored for survival studies (Figure 6.3 A).
A
d0 d14 d15 d28 d42 survival GFP/ITK-SYK tx 1st ip PB 2nd ip sacrifice IgG/ IgG/ Ly-6G Ly-6G ab ab B C IgG Ly-6G Thymus T-Cell Subgroups (d42) GFP + IgG GFP + Ly-6G 100 CD4 + CD8 + CD4 +CD8 + CD4 -CD8 - GFP - 80
60 cells within cells + thymus cells thymus - 40 /GFP
+ 20 *** *** *** **
%of CD90 0 GFP IgG Ly-6G IgG Ly-6G IgG Ly-6G IgG Ly-6G
D E Mouse Survival Spleen CD3 1st + 2 nd treatment IgG Ly-6G (d14/d28) 100 IgG 80 Ly-6G
60
40
% survival % p = 0,0016 20
0 0 20 40 60 80 100 days post tx
Figure 6.3: Repeated injection of granulocyte depleting antibody in ITK-SYK mice improves survival, but does not alter T-cell phenotype. (A) Workflow of experimental procedure. Mice were injected ip with 250 µg of the respective ab per injection. (B) Encrustation of ears and tails in ITK-SYK mice on d28 after first and d14 after second ip injection with IgG isotype control ab or anti-Ly-6G ab on d42 after tx. Shown are representative images for 6 mice per group. (C) Percentage of CD90 +CD4 +CD8 - (CD4 +), CD90 +CD4 +CD8 +, CD90 +CD4 -CD8 + (CD8 +) and Results 56
CD90 +CD4 -CD8 - cells within GFP + and GFP - thymus cells of ITK-SYK mice on d28 after first and d14 after second ip injection with IgG isotype control ab or anti-Ly-6G ab analyzed by FACS (n=6 per group). Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice. (D) Immunohistochemical HRP-DAB staining of paraffin-embedded spleen tissue of ITK-SYK mice with anti-CD3 ab on d28 after first and d14 after second ip injection with IgG isotype control ab or anti-Ly-6G ab (original magnification x 200). Shown are representative images for spleen stainings of at least 6 different mice per group. (E) Kaplan-Meier survival curve representing the survival of ITK-SYK mice after two ip injections with IgG isotype control ab or anti-Ly-6G ab (d14 and d28 after tx, n=6 per group). Statistical analysis was performed using the Log-rank Mantel-Cox test. (C, D) Organs were extracted on d42 after tx. Parts of this experiment were performed and analyzed by T. Mack.
As shown in Figure 6.3 B, anti-Ly-6G antibody treatment ameliorated ear and tail lesions compared to IgG isotype control ab. No effect of the granulocyte depletion could however be observed on the distribution of T-cell subgroups in the thymus (Figure 6.3 C) or on the splenic T-cell infiltration (Figure 6.3 D) of these mice, suggesting that granulocytosis is a downstream effect of the TCL. Still, anti-Ly-6G ab treatment could significantly extend overall mouse survival (Figure 6.3 E) which is most likely achieved by inhibiting the extensive inflammation which is partially mediated by neutrophil granulocytes. Thus, this data proposes granulocyte depletion as a symptomatic treatment option for PTCL.
6.3 Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves ITK-SYK phenotype in vivo Ruxolitinib is a selective JAK1/2 inhibitor used in the clinic to deplete malignant myeloid cells and reduce granulocytic expansion in MPNs such as polycythemia vera. 323 Due to the fact that phenotypic score and overall survival were improved upon granulocyte depletion in the ITK-SYK model and that ITK-SYK is known to drive JAK/STAT activation in T-cells 210,297 , a common feature of various forms of TCL, it appeared prudent to test whether Ruxolitinib treatment could improve TCL development and inflammation simultaneously in the ITK-SYK mouse model. In order to distinguish between JAK1 and JAK2 effects, it was decided to additionally treat another group of mice with the selective JAK2 inhibitor Pacritinib. Table 6.1 shows the IC50 values of both inhibitors for the different JAK kinase family members.
Table 6.1: IC50 levels of Ruxolitinib and Pacritinib for JAK family kinases KINASE RUXOLITINIB PACRITINIB JAK1 3.2 nM 1280 nM JAK2 2.8 nM 23 nM JAK3 428 nM 520 nM TYK2 19 nM 50 nM
Results 57
To assess whether JAK1/2 inhibition could improve the phenotype in ITK-SYK mice, Vehicle only, Ruxolitinib or Pacritinib was administered orally twice daily for 32 days or, for survival experiments, until control group had died, starting on d14 after tx (Figure 6.4).
d0 d14 d43 d46 survival GFP/ITK-SYK tx start treatment PB cytokines (Veh vs Ruxo) sacrifice (Veh vs Pac)
d14-d62 Ruxo 30 mg/kg bw orally bid d14-d24 Pac 150 mg/kg bw orally bid d25-d56 Pac 75 mg/kg bw orally bid
Figure 6.4: Workflow of experimental procedure for Ruxolitinib and Pacritinib treatment of GFP vs ITK- SYK mice. GFP or ITK-SYK mice were treated with Veh (PEG 300 + 5 % Dextrose 1:3, 10 µl/g body weight (bw) twice daily, 30 mg/kg bw Ruxolitinib (Ruxo, 3 mg/ml in Veh) twice daily or 150 mg/kg bw Pacritinib (Pac, 15 mg/ml in Veh) twice daily with reduction to 75 mg/kg Pac (7.5 mg/kg in Veh) on d25 due to toxicity, starting on d14 after tx. For analysis, mice were treated for 32 consecutive days and then sacrificed. For survival, mice were treated until ITK-SYK Veh group had died.
6.3.1 Ruxolitinib but not Pacritinib treatment improves external ITK-SYK TCL phenotype Ruxolitinib treatment of ITK-SYK transplanted Balb/c mice almost completely reversed encrustations, whereas JAK2 inhibition alone by Pacritinib showed no beneficial effects on these skin alterations (Figure 6.5 A). Furthermore, Ruxolitinib treatment resulted in a highly significant improvement of the phenotypic score compared to Vehicle control, while Pacritinib only showed very mild effects on the external disease phenotype (Figure 6.5 B).
A GFP ITK-SYK B Phenotypic Score (d43) Veh 10 ** 10 8 8
6 6
Ruxo 4 4
2 2 phenotypic score phenotypic phenotypic score phenotypic 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac Pac GFP ITK-SYK GFP ITK-SYK
Figure 6.5: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves external ITK-SYK TCL phenotype. (A) Infiltration of skin in GFP and ITK-SYK mice on d46 after tx after treatment with Veh, Ruxo or Pac. Shown are representative images for at least 3 mice per group. (B) ps of GFP and ITK-SYK mice on d43 after tx after treatment with Veh, Ruxo or Pac (left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; right: GFP Veh n=4; GFP Pac n=3; ITK-SYK Veh, ITK-SYK Pac n=8). Bars represent mean values Results 58
with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001.
6.3.2 Ruxolitinib but not Pacritinib improves body and lung weight of ITK-SYK mice ITK-SYK mice developed TCL within seven weeks after tx. Disease progression was accompanied by massive weight loss and an increase in spleen size and weight (Figure 6.6 A, B, C). Additionally, liver and lung weights were also found to be increased in ITK-SYK mice compared to GFP controls (Figure 6.6 D, E). The combined inhibition of JAK1 and JAK2 but not of JAK2 alone rescued weight loss (Figure 6.6 A) as is shown here for the relative weight loss compared to the starting weight prior to tx. Notably, long-term administration of neither of the two compounds seemed to have any severe side-effects since neither Ruxolitinib nor Pacritinib treated GFP mice showed any signs of weight loss or malaise when treated with either compound.
A Weight Loss start treatment start treatment
110 110 GFP Veh GFP Veh GFP Ruxo GFP Pac 100 100 ITK-SYK Veh ITK-SYK Veh ITK-SYK Ruxo ITK-SYK Pac 90 ** 90
80 80 weight loss (%) loss weight loss(%) weight
70 70 0 4 7 1 4 1 2 2 0 4 7 4 1 8 5 2 1 1 18 2 25 28 3 35 39 4 46 11 1 18 2 25 2 32 3 39 4 46 days post tx days post tx
B Veh Ruxo Pac
GFP
ITK-SYK
1 cm 1 cm 1 cm
CDESpleen Liver Lung * * 1.5 *** 8 * 2.0 ** * ** 6 1.5 1.0 4 1.0 0.5 2 0.5 rel. lung weight lung rel. rel. liver weight liver rel. rel. spleen weight spleen rel. (% of (% weight) body (% of (% weight) body (% of (% weight) body 0.0 0 0.0 Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo GFP ITK-SYK GFP ITK-SYK GFP ITK-SYK Spleen Liver Lung 1.5 8 2.0 ** ** * ** 6 1.5 1.0 4 1.0 0.5 2 0.5 rel. lung weight lung rel. rel. liver weight liver rel. rel. spleen weight spleen rel. (% of (% weight) body (% of (% weight) body (% of (% bodyweight) 0.0 0 0.0 Veh Pac Veh Pac Veh Pac Veh Pac Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK GFP ITK-SYK
Results 59
Figure 6.6: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves body and lung weight of ITK-SYK mice. (A) Percentage of weight after treatment with Veh, Ruxo or Pac compared to starting weight measured on d0 after tx of GFP and ITK-SYK mice. Statistical significance was calculated for the values on d46 (left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; right: GFP Veh n=4; GFP Pac n=3; ITK-SYK Veh, ITK-SYK Pac n=8). (B) Spleen sizes of GFP and ITK-SYK mice on d46 after tx after treatment with Veh, Ruxo or Pac. Shown are representative images for at least 3 mice per group. (C,D,E) Relative (rel.) spleen (C), liver (D) and lung (E) weight calculated as percentage of bw of GFP and ITK-SYK mice on d46 after tx after treatment with Veh, Ruxo or Pac (top: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; bottom: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK-SYK Pac n=3). Bars represent mean values with error bars showing the SEM. (A,C,D,E) Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001.
Spleen size (Figure 6.6 B) and weight (Figure 6.6 C) as well as liver weight (Figure 6.6 D) were not altered by either agent, but interestingly, lung weight relative to body weight was significantly reduced with Ruxolitinib, whereas Pacritinib had no effects on the increased lung weight (Figure 6.6 E). Table 6.2 and Table 6.3 show the mean total spleen, liver and lung weight in each treatment group with the respective standard deviation (SD).
Table 6.2: Mean organ weights ± standard deviation of GFP and ITK-SYK mice after Veh vs Ruxo treatment SPLEEN, g ± SD LIVER, g ± SD LUNG, g ± SD GFP Vehicle 0.1074 ± 0.0154 1.0978 ± 0.1460 0.1880 ± 0.0288 GFP Ruxolitinib 0.0948 ± 0.0109 0.9918 ± 0.0675 0.1748 ± 0.0138 ITK -SYK Vehicle 0.2242 ± 0.0569 1.2372 ± 0.2558 0.3028 ± 0.0581 ITK -SYK Ruxolitinib 0.2136 ± 0.0281 1.2814 ± 0.1549 0.2232 ± 0.0378 g, gram; SD, standard deviation; vs, versus
Table 6.3: Mean organ weights ± standard deviation of GFP and ITK-SYK mice after Veh vs Pac treatment SPLEEN, g ± SD LIVER, g ± SD LUNG, g ± SD GFP Vehicle 0.0970 ± 0.0111 1.1075 ± 0.1147 0.1643 ± 0.0134 GFP Pacritinib 0.0893 ± 0.0072 1.0193 ± 0.0190 0.1460 ± 0.0144 ITK -SYK Vehicle 0.1910 ± 0.0440 1.0760 ± 0.0362 0.1790 ± 0.0317 ITK -SYK Pacritinib 0.1530 ± 0.0229 1.1623 ± 0.1060 0.1813 ± 0.0323 g, gram; SD, standard deviation; vs, versus
6.3.3 Ruxolitinib but not Pacritinib reduces elevated cytokine levels in ITK- SYK mice It was shown in section 6.1 that granulocytosis in ITK-SYK mice is most likely mediated by factors secreted by ITK-SYK expressing cells outside of the granulocytic cell pool. In accordance with that, ITK-SYK expression in this murine model was seen to result in an increase in certain inflammatory cytokines such as IFNγ which could possibly mediate these effects 185 . Therefore, the effects of Ruxolitinib and Pacritinib on the serum levels of certain cytokines were assessed. As expected, IFNγ serum levels as well as those of the T-cell stimulatory cytokine IL-6 were increased in ITK-SYK mice compared to GFP control. Another Results 60 cytokine which was found to be upregulated was IL-5 which is secreted among others by activated T h2-cells and stimulates B-cells and eosinophils. Interestingly, IL-6 and IFNγ serum levels were significantly downregulated by Ruxolitinib but not by Pacritinib (Figure 6.7 A, B). IL-5 levels remained high even after treatment with either compound (Figure 6.7 C). Other cytokines and growth factors such as the anti-inflammatory IL-10 (Figure 6.7 D), the allergy- associated IL-13 (Figure 6.7 E), the pro-inflammatory IL-17A (Figure 6.7 F) and the granulocyte-macrophage colony-stimulating factor (GM-CSF, Figure 6.7 G) failed to show increased serum levels in ITK-SYK mice and were therefore also not targetable with Ruxolitinib or Pacritinib.
A B C IL-6 IFN IL-5
100 100 ns 150 * 80 80 ns 100 60 ** 60
40 40 50 pg/ml serum pg/ml pg/ml serum pg/ml 20 20 serum pg/ml
0 0 0 Ctrl Veh Ruxo Pac Ctrl Veh Ruxo Pac Ctrl Veh Ruxo Pac ITK-SYK ITK-SYK ITK-SYK D E FG IL-10 IL-13 IL-17A GM-CSF 100 100 100 100
80 80 80 80
60 60 60 60
40 40 40 40 pg/ml serum pg/ml pg/ml serum pg/ml 20 20 serum pg/ml 20 serum pg/ml 20
0 0 0 0 Ctrl Veh Ruxo Pac Ctrl Veh Ruxo Pac Ctrl Veh Ruxo Pac Ctrl Veh Ruxo Pac ITK-SYK ITK-SYK ITK-SYK ITK-SYK
Figure 6.7: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces elevated serum cytokine levels in ITK-SYK mice. Serum cytokine levels of murine IL-6 (A), IFNγ (B), IL-5 (C), IL-10 (D), IL-13 (E), IL-17A (F) and GM-CSF (G) of GFP Veh (Control, Ctrl) and ITK-SYK mice after treatment with Veh, Ruxo or Pac on d46 after tx as were determined using BD CBA Flex Sets with subsequent FACS analysis (GFP Veh n=4, GFP Ruxo, ITK-SYK Veh, ITK-SYK Ruxo n=3 per group); Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001, ns non-significant.
This data shows that ITK-SYK expression increases pro-inflammatory and T-cell stimulatory cytokines which could possibly drive TCL expansion and granulocytosis in this mouse model. JAK1/2 co-inhibition is sufficient to reduce levels of some of these cytokines. Particularly the effects on IFNγ, which is normally secreted by T-lymphocytes, suggest that JAK1/2 inhibition does not only act on the expanding granulocytes and through that improves the inflammatory phenotype, but it also hints that Ruxolitinib might directly target the malignant T-cells. Results 61
6.3.4 Ruxolitinib improves survival in ITK-SYK mice to a higher extent than Pacritinib ITK-SYK expression in primary bone marrow cells and subsequent transplantation into Balb/c mice led to TCL development with 100% lethality within 60 days after transplantation (Figure 6.8). To determine whether Ruxolitinib and Pacritinib are able to increase mouse survival of ITK-SYK mice, the drugs were administered as shown in Figure 6.4, but treatment was continued until the Vehicle treated control group had died. Upon treatment, survival was significantly extended by both inhibitors, but overall survival with Ruxolitinib was longer than with Pacritinib treatment (Figure 6.8). This once again shows the beneficial effects of JAK1/2 co-inhibition over JAK2 inhibition alone.
Mouse Survival
start treatment end treatment start treatment end treatment 100 (d14) (d58) 100 (d14) (d59) Veh Veh 80 Ruxo 80 Pac
60 60
40 40 p = 0,0018 % survival % survival 20 20 p=0,002 0 0 0 20 40 60 80 100 0 20 40 60 80 100 days post tx days post tx
Figure 6.8: Simultaneous JAK1/2 inhibition improves survival in ITK-SYK mice to a higher extent than JAK2 inhibition alone. Kaplan-Meier survival curve representing the survival of ITK-SYK mice after treatment with Veh vs Ruxo (left) or Veh vs Pac (right) until Veh group had died (left: n=5 per group, right: ITK-SYK Veh n=7; ITK-SYK Pac n=5). Statistical analysis was performed using the Log-rank Mantel-Cox test.
6.3.5 Ruxolinitib but not Pacritinib decreases ITK-SYK expressing cell percentages in ITK-SYK mice To investigate whether JAK inhibitor treatment could decrease the percentage of ITK-SYK expressing cells in PB, BM, spleen and thymus of ITK-SYK mice, the respective organs were extracted after treatment with Ruxolitinib and Pacritinib and assessed for GFP + cells by FACS. Figure 6.9 shows that in all organs, ITK-SYK mice displayed a much lower GFP + cell proportion than the respective GFP controls, hinting at lower engraftment efficacy of ITK-SYK positive cells. In PB, neither Ruxolitinib nor Pacritinib had any effect on ITK-SYK expressing cell percentages (Figure 6.9 A), while in BM (Figure 6.9 B), spleen (Figure 6.9 C) and thymus (Figure 6.9 D) only simultaneous inhibition of JAK1 and JAK2 with Ruxolitinib significantly reduced the fraction of ITK-SYK expressing cells. These findings yet again indicate that Ruxolitinib exerts its function by directly inhibiting JAK signaling in the ITK-SYK expressing malignant cell compartment. Results 62
A PB 100 100
80 80 cells cells + 60 + 60
40 40
20 20 within total cells total within cells total within % of % GFP of % GFP 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK B BM 100 100
80 80 cells cells + 60 + 60
40 40 ** ns 20 20 within total cells total within cells total within %of GFP %of GFP 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK C Spleen 100 100
80 80 cells cells + 60 + 60
40 40 ** ns 20
within total cells total within 20 within total cells total within % of% GFP %of GFP 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK
D Thymus 100 100
80 80 cells cells + 60 + 60
40 40 ** ns 20 20 within total cells total within cells total within % of GFP of % % of GFP of % 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK
Figure 6.9: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone decreases ITK-SYK expressing cell percentages in ITK-SYK mice. Percentage of GFP + cells within total PB (A), total BM (B), total spleen (C) and total thymus (D) cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. PB was taken on d43 and organs on d46 after tx and analyzed by FACS. (PB left: GFP Veh n=5; GFP Ruxo n=4; ITK-SYK Veh, ITK- SYK Ruxo n=10; PB right: GFP Veh n=4; GFP Pac n=3; ITK SYK Veh: n=10 per group; ITK-SYK Ruxo n=8; organs left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; organs right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK-SYK Pac n=3 per group). (A, B, C, D) Horizontal bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001, ns non-significant.
Results 63
6.3.6 Ruxolitinib but not Pacritinib reduces myeloid cell infiltration To assess the effects of the different JAK inhibitors on elevated myeloid cell levels in ITK- SYK mice, CD11b +Ly-6G + granulocytes and CD11b +Ly-6G - monocytes were analyzed in PB and spleens using FACS. As expected, a significant increase in the granulocyte percentage in both organs could be observed in ITK-SYK mice vs GFP controls, although the granulocyte fraction in spleens (Figure 6.10 B) was much more elevated compared to peripheral blood (Figure 6.10 A). As seen before, this cell expansion was largely independent of the GFP status and therefore of ITK-SYK expression. In some cases, significant differences between GFP + and GFP - cell populations could be detected, but these differences could also be found in the GFP control mice and should therefore be regarded as engraftment artifacts. Nevertheless, both, the GFP + and GFP - granulocyte percentages were increased in ITK-SYK mice treated with Vehicle. Upon treatment with Ruxolitinib, granulocyte levels were reduced in both organs, whereas Pacritinib administration had no effect on granulocytic expansion in PB or spleen of ITK-SYK mice (Figure 6.10).
A PB Granulocytes
* *** *** *** *** 80 *** *** 80 ** ***
cells GFP+ * cells ** *** + + GFP- PB cells PB cells PB
- 60 60
+ *** Ly-6G Ly-6G + 40 + 40 /GFP *** /GFP + * - 20 20 ** ** 0 0 %of CD11b %of CD11b within GFP within Veh Ruxo Veh Ruxo GFP within Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK B Spleen Granulocytes
** ** ** GFP+ 40 *** * 40 ** GFP- cells *** cells *** ***
+ + ** 30 30 ** spleen cells spleen spleen cells spleen - -
Ly-6G * Ly-6G + + 20 20 /GFP /GFP + ** + 10 10
0 * 0 ** %of CD11b %of CD11b Veh Ruxo Veh Ruxo Veh Pac Veh Pac within GFP within GFP ITK-SYK GFP within GFP ITK-SYK
Figure 6.10: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone decreases elevated granulocyte counts in PB and spleens of ITK-SYK mice. Percentage of CD11b +Ly-6G + cells within GFP + or GFP - PB (A) and spleen (B) cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. Blood samples were taken on d43 and spleens on d46 after tx and analyzed by FACS. (PB left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; PB right: GFP Veh n=4; GFP Pac n=3; ITK SYK Veh: n=10 per group; ITK-SYK Ruxo n=8; spleen left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; spleen right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK-SYK Pac n=3 per group). (A, B) Bars represent mean Results 64
values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice.
Another myeloid cell type which was found to show increased percentages in PB and spleens of ITK-SYK mice was the monocytic cell compartment. As was seen for granulocytes, monocyte levels in the spleen (Figure 6.11 B) were increased to a much higher extent than in PB (Figure 6.11 A) and their expansion was once again independent of the ITK-SYK expression status. Interestingly, the beneficial effects of Ruxolitinib in reducing the monocytic cell levels could only be seen in the spleen, whereas they could not be ameliorated in the PB. JAK2 inhibition alone with Pacritinib failed to reduce monocytic expansion in both organs (Figure 6.11).
A PB Monocytes
** ** * ** GFP+ 40 ** 40 * GFP- cells *
cells ** - - PB cells PB PB cells PB
- 30 30 + Ly-6G Ly-6G + 20 + 20 /GFP /GFP + -
10 10
0 0 %of CD11b %of CD11b within GFP within Veh Ruxo Veh Ruxo GFP within Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK B Spleen Monocytes
** ** GFP+ 50 *** 50 ** GFP-
cells ** cells ** - - ** 40 *** * 40 spleen cells spleen cells spleen - - Ly-6G Ly-6G 30 30 + + /GFP /GFP 20 20 + + 10 10 * ** 0 0 %of CD11b %of CD11b Veh Ruxo Veh Ruxo Veh Pac Veh Pac within GFP within within GFP within GFP ITK-SYK GFP ITK-SYK
Figure 6.11: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone decreases elevated monocyte counts in spleens of ITK-SYK mice. Percentage of CD11b +Ly-6G - cells within GFP + or GFP - PB (A) and spleen (B) cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. Blood samples were taken on d43 and spleens on d46 after tx and analyzed by FACS. (PB left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; PB right: GFP Veh n=4; GFP Pac n=3; ITK SYK Veh: n=10 per group; ITK-SYK Ruxo n=8; spleen left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; spleen right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK-SYK Pac n=3 per group). (A, B) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice.
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To assess whether JAK inhibition could also reduce myeloid cell infiltrates in peripheral organs, immunohistochemistry stainings for the myeloid marker CD11b were performed on paraffin-embedded tissue sections from liver, skin, colon, lung and ear samples of ITK-SYK mice treated with Vehicle, Ruxolitinib or Pacritinib (Figure 6.12). Unfortunately, the antibody used for Vehicle and Ruxolitinib tissue sections was not available anymore when the Pacritinib experiments were performed and the new antibody did not work properly with the previously used Cytomation EnVision + System-HPR (DAB) kit. Thus for the Pacritinib slides, it was inevitable to switch to the CSA, Catalyzed Signal Amplification System, manufactured by the same company (DAKO). Specificity of either antibody was tested using GFP mouse tissue samples in which no myeloid infiltration was expected (not shown). As was shown for PB and spleen before, ITK-SYK mice showed high infiltration rates of CD11b + myeloid cells in all of the tested organs. CD11b
ITK-SYK Veh ITK-SYK Ruxo ITK-SYK Pac
Liver
Skin
Colon
Lung
Ear
Figure 6.12: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces myeloid cell infiltration of peripheral organs in ITK-SYK mice. Immunohistochemical HRP-DAB staining of paraffin-embedded organs Results 66
of ITK-SYK mice after treatment with Veh, Ruxo or Pac with anti-CD11b ab on d46 after tx (original magnification x 100). Shown are representative images for organ-stainings of at least 3 different mice per group.
Liver stainings revealed defined regions of myeloid cell infiltration in close proximity of blood vessels. This infiltration could be strongly reduced by administration of JAK1/2 inhibitor Ruxolitinib, whereas Pacritinib treatment showed only minor effects on CD11b + cell infiltration (Figure 6.12 top row). As already shown in Figure 6.1 B, skin structure was completely destroyed in ITK-SYK mice and it presented with strong infiltration of CD11b + cells and a complete loss of the subcutaneous adipose fat layer. In Ruxolitinib treated mice, these effects were completely abrogated, whereas the skin of Pacritinib treated mice was comparable to that of Vehicle controls (Figure 6.12 second row). Similar CD11b + infiltration patterns could be obtained for colon (Figure 6.12 third row), lung (Figure 6.12 fourth row) and ear (Figure 6.12 bottom row) samples from ITK-SYK mice. For every organ tested, Ruxolitinib but not Pacritinib was able to impede myeloid cell infiltration. This data implicates that JAK2 inhibition alone is not sufficient to inhibit expansion of the myeloid cell compartment and infiltration of peripheral organs with CD11b + cells. It rather suggests that either simultaneous inhibition of JAK1 and JAK2 is required or that JAK1 is the main mediator of ITK-SYK driven myeloid expansion and infiltration and therefore the major Ruxolitinib target in this disease setting.
6.3.7 JAK1/2 inhibition has no effect on STAT3 and STAT5 activation in splenic granulocytes of ITK-SYK mice The next step was to investigate whether Ruxolitinib exerts its function in the downregulation of granulocyte levels by direct inhibition of the JAK/STAT signaling pathway in these cells. Since more profound effects of ITK-SYK expression alone and of subsequent Ruxolitinib treatment on granulocytic expansion were observed in the spleen rather than in PB (Figure 6.10), these experiments were performed on splenic cells. JAK kinases are normally activated by extracellular stimuli and forward these signals by phosphorylating and hereby activating their downstream targets, the STAT proteins. The phosphorylated STATs then enter the nucleus and directly participate in transcriptional regulation of JAK/STAT target genes. As JAK phosphorylation is not measurable by flow cytometry due to lack of antibodies, the activation of the signaling pathway was assessed by measuring phosphorylation and therefore activation of the most common JAK downstream mediators STAT3 and STAT5. In total spleen cells of ITK-SYK mice, Ruxolitinib led to a mild reduction in the phosphorylation levels of STAT3 (Figure 6.13 A) and STAT5 (Figure 6.13 B) as can be seen in the histograms. FACS analysis of the mean fluorescence intensity (MFI) of pSTAT3 (Figure 6.13 C) and pSTAT5 (Figure 6.13 D) in splenic granulocytes revealed a higher MFI in GFP + cells compared to GFP - cells, regardless of whether the cells expressed GFP only or Results 67 the ITK-SYK oncogene. This hints at a partial spill-over of the GFP fluorescence into the APC detector. Interestingly, phosphorylation levels of STAT3 in GFP - cells of ITK-SYK mice compared to GFP controls were significantly reduced even in Vehicle treated mice, and JAK inhibition with neither Ruxolitinib nor Pacritinib showed any further decrease of pSTAT3 MFI. No change of STAT3 phosphorylation could be observed in GFP + splenic granulocytes upon ITK-SYK expression compared to GFP controls and these MFIs remained constant after treatment. Surprisingly, Ruxolitinib and Pacritinib treatment of GFP control mice seemed to cause an increase in STAT3 phosphorylation of GFP + cells (Figure 6.13 C). STAT5 phosphorylation of GFP - cells of GFP and ITK-SYK mice remained unaltered in any case, whereas ITK-SYK expressing GFP + cells seemed to show a slight increase of STAT5 activation compared to GFP control mice (Figure 6.13 D). Yet, phosphorylation levels of STAT5 were not altered by either JAK inhibitor.
A C pSTAT3 Total Spleen Cells pSTAT3 Spleen Granulocytes ** GFP+ * ** 40 40 * GFP- ** * 30 30 ** spleen cells spleen spleen cells spleen + + ** 20 20 ** ** ** ** Ly-6G 10 Ly-6G
+ *** 10
+ *** ** pSTAT3of MFI pSTAT3of MFI count 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac CD11b CD11b GFP ITK-SYK GFP ITK-SYK pSTAT3 B D pSTAT5 Total Spleen Cells pSTAT5 Spleen Granulocytes
GFP+ * ** 30 30 * GFP-
20 cells spleen 20 spleen cells spleen + + * *** ** *** *** *** *** 10 10 ** Ly-6G Ly-6G + + pSTAT5 of MFI pSTAT5of MFI
count 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac CD11b CD11b GFP ITK-SYK GFP ITK-SYK pSTAT5 Veh Ruxo Pac
Figure 6.13: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces STAT3 and STAT5 phosphorylation in total spleen cells, but has no effect on splenic granulocytes of ITK-SYK mice. Representative histograms of MFI of intracellular FACS staining of phosphorylated STAT3 (A) and STAT5 (B) in total spleen cells of ITK-SYK mice after treatment with Veh, Ruxo or Pac. Data was acquired for at least 3 mice per group. MFI of intracellular FACS staining of phosphorylated STAT3 (C) and STAT5 (D) in CD11b +Ly-6G + cells within GFP + or GFP - spleen cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. (left: GFP Veh n=4, GFP Ruxo, ITK-SYK Veh, ITK-SYK Ruxo n=3 per group; right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK- SYK Pac n=3 per group). Spleens were taken on d46 after tx. (C, D) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice.
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These results indicate that the inhibition of granulocytic expansion and infiltration is not mediated by direct inhibition of the JAK/STAT signaling cascade in the granulocytes themselves. A more likely hypothesis would be that the secretion of certain molecules such as cytokines from other cell types harboring the ITK-SYK translocation is inhibited by Ruxolitinib which then impairs granulocytosis and myeloid infiltration in ITK-SYK mice. This fits in well with previous data showing decreased levels of the pro-inflammatory IFNγ (Figure 6.7 B) and the fact that granulocytosis is mediated independently of the respective ITK-SYK status (Figure 6.1 C).
6.3.8 Ruxolitinib but not Pacritinib reduces elevated GMP and CMP but not MEP levels in spleens of ITK-SYK mice To dissect whether granulocytic and monocytic expansion is triggered at the mature cell stage or in earlier myeloid lineage progenitors, the distribution of myeloid cell progenitors in GFP and ITK-SYK mice treated with Vehicle, Ruxolitinib or Pacritinib was analyzed. All myeloid progenitor cell type percentages were significantly elevated in spleens of ITK-SYK mice compared to GFP controls (Figure 6.14). As was shown for the mature granulocytes and monocytes, this increase was independent of the ITK-SYK expression status since GFP + and GFP - cells were equally exalted. Granulocyte-macrophage progenitor (GMP, Figure 6.14 A) and common myeloid progenitor (CMP, Figure 6.14 B) cell levels could be reduced by simultaneous inhibition of JAK1 and JAK2 kinases, whereas JAK2 inhibition alone had no beneficial effect. No effect of either inhibitor could be observed on the elevated megakaryocyte-erythroid progenitor (MEP, Figure 6.14 C) percentages. These observations imply that granulocyte and monocyte expansion is already triggered in common immature progenitors and that JAK1/2 co-inhibition already targets their expansion at these early differentiation stages. Interestingly, the progenitor compartment of megakaryocytes and erythrocytes is not altered by JAK inhibitors, showing that the treatment selectively targets myeloid cell expansion which causes the underlying infiltration of peripheral organs with myeloid cells leading to the excessive inflammation visible in ITK-SYK harboring PTCL mice. Results 69
A Spleen GMP
cells * ** ** cells ** high *** 0.8 GFP+
high ** 0.8 * GFP- 0.6
spleen cells spleen 0.6 - spleen cells spleen CD16/32 - - CD16/32 0.4 - 0.4 /GFP /GFP + Sca-1 + Sca-1 + 0.2 + 0.2 cKit cKit - 0.0 - 0.0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac within GFP within GFP ITK-SYK GFP within GFP ITK-SYK % of% Lin %of Lin
B Spleen CMP cells cells *** ** *** low low * GFP+ 0.4 ** ** 0.4 * GFP-
0.3 0.3 * spleen cells spleen thymus cells thymus - CD16/32 CD16/32 - - - 0.2 0.2 /GFP /GFP + + Sca-1 Sca-1 + + 0.1 * 0.1 cKit cKit - - 0.0 0.0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac within GFP within GFP ITK-SYK GFP within GFP ITK-SYK %of Lin %of Lin
C Spleen MEP cells cells -
- * * GFP+ ** 1.5 1.5 * * GFP- * *** spleen cells spleen CD16/32 CD16/32 spleen cells spleen - -
- 1.0 - 1.0 /GFP /GFP Sca-1 Sca-1 * + + + + 0.5 0.5 cKit cKit - - 0.0 0.0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac within GFP within within GFP within GFP ITK-SYK GFP ITK-SYK %of Lin %of Lin Figure 6.14: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces elevated GMP and CMP but not MEP levels in spleens of ITK-SYK mice. Percentage of LK CD16/32 high GMP (A) LK CD16/32 low CMP (B) and LK CD16/32 - MEP (C) cells within GFP + or GFP - spleen cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. Spleens were taken on d46 after tx and analyzed by FACS. (left: GFP Veh, ITK- SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK-SYK Pac n=3 per group). (A, B, C) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice. Results 70
6.3.9 Ruxolitinib improves T-cell infiltration of skin in ITK-SYK mice to a higher extent than Pacritinib To delineate the effects of JAK inhibition on the skin infiltration of T-cells in the ITK-SYK driven TCL model, immunohistochemistry stainings for the T-cell marker CD3 were performed on paraffin-embedded tissue sections from skins of GFP and ITK-SYK mice treated with Vehicle, Ruxolitinib or Pacritinib. GFP mice showed normal skin architecture with an epidermal, dermal and subcutaneous adipose tissue layer and no signs of abnormally infiltrating T-cells. Skin structure was not altered by administration of either JAK inhibitor (Figure 6.15 top row). In ITK-SYK mice treated with Vehicle, a complete loss of subcutaneous adipose tissue and a high number of infiltrating CD3 + T-cells were observed. JAK2 inhibition with Pacritinib showed reduced T-cell infiltration, but the abnormal absence of the subcutaneous fatty tissue could not be rescued. Skin sections of Ruxolitinib in comparison presented with virtually no infiltration of T-cells and normal distribution of skin tissue layers (Figure 6.15 bottom row). This means that JAK1/2 co-inhibition in contrast to JAK2 inhibition alone is able to protect the skin of ITK-SYK mice from massive T-cell infiltration and structural degradation, once again pointing to JAK1 as the major Ruxolitinib target in ITK-SYK driven TCL. Skin CD3 Veh Ruxo Pac
GFP
ITK -SYK
Figure 6.15: Simultaneous JAK1/2 inhibition improves T-cell infiltration of skin in ITK-SYK mice to a higher extent than JAK2 inhibition alone. Immunohistochemical HRP-DAB staining of paraffin-embedded skin tissue of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac with anti-CD3 ab on d46 after tx (original magnification x 100). Shown are representative images for skin-stainings of at least 3 different mice per group.
Results 71
6.3.10 Retransplantation of CD4 + T-cells of ITK-SYK mice causes a similar phenotype in secondary recipients Previous investigations in ITK-SYK driven PTCL-NOS mouse models, including the one used in this study, have shown that CD4 + cells are the primary malignant T-cells in the developing disease with rarer cases having been described to show a malignant CD4 -CD8 - phenotype.155,185,210 To confirm these results, the different GFP + T-cell subsets (CD3 +CD90 +CD4 +CD8 - (CD4 +), CD3 +CD90 +CD4 -CD8 + (CD8 +), CD3 +CD90 +CD4 +CD8 + (CD4 +CD8 +), CD3 +CD90 +CD4 -CD8 - (CD4 -CD8 -) obtained from thymi and spleens of ITK-SYK mice were transplanted at indicated numbers into secondary recipients and monitored for progression-free survival (PFS, Figure 6.16 A). Disease development for each subtype was independent of the transplanted cell number. Of transplanted thymic T-cells, 57% of CD4 + T- cell recipients developed PTCL, whereas none of the other transplanted thymic T-cell subtypes caused any disease phenotype within one year after transplantation. In spleen cell recipients, the penetrance of PTCL in CD4 + secondary recipients reached 100% with the second highest incidence occurring after transplantation with CD4 -CD8 - (40%) followed by CD8 + for which only two out of nine mice developed PTCL (22%). This fits in well with previous data suggesting CD4 + T-cells as the main driver of ITK-SYK harboring PTCL.
A Retransplantability of Thymic T-cells Retransplantability of Splenic T-cells
+ 100 + 100 CD4 CD4 CD8 + CD8 + CD4 +CD8 + CD4 +CD8 + CD4 CD4 -CD8 - CD4 -CD8 - 50 50 % PFS % % PFS % CD4
0 0 0 100 200 300 400 0 100 200 300 400 days post tx days post tx B Thymus CD4+ Retx Spleen CD4+ Retx
CD Spleen Weight CD4+ Retx Phenotypic Score CD4+ Retx
1.0 10
0.8 8
0.6 6
0.4 4
0.2 2 phenotypic score phenotypic rel. spleen weight spleen rel. (% of (% weight) body 0.0 0 thymus spleen thymus spleen
Results 72
Figure 6.16: Retransplantation of thymic and splenic CD4 + T-cells of ITK-SYK mice causes a similar phenotype in secondary recipients. (A) PFS of lethally irradiated Balb/c mice transplanted with thymic or splenic GFP + CD3 +CD90 +CD4 +CD8 -, CD3 +CD90 +CD4 -CD8 +, CD3 +CD90 +CD4 +CD8 + or CD3 +CD90 +CD4 -CD8 - cells harvested and sorted from ITK-SYK mice mixed with 1 x 10 6 untreated Balb/c BM support. Transplanted were 11,000 – 21,000 thymic (n=9) and 67,000 – 500,000 splenic (n=4) CD4 +CD8 -; 4,000 – 13,000 thymic (n=7) and 15,000 – 49,000 splenic (n=9) CD4 -CD8 +; 2,000 – 6,500 thymic (n=2) and 1,000 – 7,500 splenic (n=2) CD4 +CD8 +; 1,300 – 5,200 thymic (n=2) and 11,000 – 37,000 splenic (n=5) CD4 -CD8 - cells. Engraftment was independent of transplanted cell number and PFS was monitored over 12 months. All mice surviving > 1 month after tx were included into the analysis. Lines representing thymic CD8 + and CD4 +CD8 + are hidden behind the line representing thymic CD4 -CD8 - cells. (B) Infiltration of ears and tails of Balb/c mice retransplanted with thymic or splenic CD4 + ITK-SYK cells. Shown are representative images for at least 4 mice per group. Spleen weight (C) and phenotypic score (D) of Balb/c mice retransplanted with thymic or splenic CD4 + ITK-SYK cells at time of death (thymus CD4 + cells: n=5, spleen CD4 + cells: n=4). Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Dashed line indicates baseline levels (mean of 5 primary recipient GFP mice treated with Veh).
Both, thymic and splenic ITK-SYK expressing CD4 + T-cells caused ear and tail encrustation and necrosis (Figure 6.16 B) as could be seen in primary recipients. Furthermore, an increase in relative spleen weight compared to control spleens could be noted (Figure 6.16 C). The phenotypic score was even higher in mice which received thymic CD4 + T-cells compared to splenic CD4 + T-cell recipients (Figure 6.16 D, baseline = 0). This data shows that ITK-SYK expressing CD4 + T-cells cause TCL development in secondary recipients resembling the primary disease phenotype. As a higher impact on the phenotypic score was demonstrated for retransplanted thymic CD4 + T-cells compared to splenic cells, further investigations were focused on JAK inhibitory effects on T-cells extracted from the thymus.
6.3.11 Ruxolitinib but not Pacritinib normalizes malignant CD4 + T-cell levels in thymi of ITK-SYK mice To assess whether JAK inhibition exerts its effects also on the primary malignant T-cells, the distribution of GFP + ITK-SYK expressing total CD3 +CD90 + T-cells and of each subpopulation (CD3 +CD90 +CD4 +CD8 -, CD3 +CD90 +CD4 -CD8 +, CD3 +CD90 +CD4 +CD8 +, CD3 +CD90 +CD4 - CD8 -) was analyzed within total GFP + thymus cells by FACS. ITK-SYK expression led to a significant decrease of total T-cell levels as well as primary malignant CD4 + T-cell and CD4 +CD8 + T-cell levels. All of these T-cell subpopulation levels could be restored by JAK1/2 co-inhibition with Ruxolitinib, while JAK2 inhibition alone by Pacritinib had no effect on either cell type (Figure 6.17 A, B, D). The impact of ITK-SYK expression and the subsequent effects of the JAK inhibitors on the distribution of CD8 + and CD4 -CD8 - T-cells were quite adverse in the two experiments. Due to the fact that CD8 + and CD4 -CD8 - T-cell levels are generally much lower than those of the other T-cell subtypes (app. 5% of all thymus cells each in the GFP control mice), small variations in malignant CD4 + cell levels and CD4 +CD8 + Results 73 cell levels could cause dramatic shifts within the distribution of these subgroups (Figure 6.17 C, E), thus resulting in the observed variability.
A Thymus Total T-Cells *** 150 *** *** 150 *** cells cells + + 100 100 thymus cells thymus thymus cells thymus CD90 CD90 + + + + 50 50
% of% CD3 0 % of CD3 0 within GFP within within GFP within Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK B Thymus CD4 + T-Cells cells cells -
- * 50 ** * 50 *** CD8 CD8 + 40 + 40 CD4 30 CD4 30 thymus cells thymus thymus cells thymus + + + + 20 20 CD90 CD90
+ 10 + 10
0 0 within GFP within Veh Ruxo Veh Ruxo GFP within Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK C %of CD3 %of CD3 Thymus CD8 + T-Cells cells cells + 15 ** + 15 *** * CD8 CD8 - - 10 10 CD4 CD4 thymus cells thymus cells thymus + + + + 5 5 CD90 CD90 + +
0 0 within GFP within within GFP within Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK D %of CD3 %of CD3 Thymus CD4 +CD8 + T-Cells cells cells *** + + 80 ** * 80 *** CD8 CD8 + 60 + 60 CD4 CD4 thymus cells thymus cells thymus + 40 + 40 + +
CD90 20 CD90 20 + +
0 0 within GFP within Veh Ruxo Veh Ruxo GFP within Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK E %of CD3 %of CD3 Thymus CD4 -CD8 - T-Cells cells cells - - 20 20 ** CD8 CD8 - - 15 15 CD4 CD4 + + thymus cells thymus 10 cells thymus 10 + +
CD90 5 CD90 5 + +
0 0 within GFP within within GFP within Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK %of CD3 %of CD3
Results 74
Figure 6.17: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone normalizes malignant CD4 + T-cell levels in thymi of ITK-SYK mice. Percentage of CD3 +CD90 + (A), CD3 +CD90 +CD4 +CD8 - (B), CD3 +CD90 +CD4 -CD8 + (C), CD3 +CD90 +CD4 +CD8 + (D) and CD3 +CD90 +CD4 -CD8 - (E) cells within GFP + thymus cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac measured by FACS. (left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK- SYK Pac n=3 per group). Thymi were taken on d46 after tx. (A, B, C, D, E) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001.
These results indicate that JAK1/2 co-inhibition, but not JAK2 inhibition alone, does not only target the granulocytic compartment but exerts its effects also on the malignant ITK-SYK expressing CD4 + T-cell population.
6.3.12 Ruxolitinib reduces activation of JAK downstream signaling mediators in malignant T-cells to a higher extent than Pacritinib To examine whether Ruxolitinib exerts its function by directly inhibiting JAK1 and JAK2 in the malignant T-cells, intracellular flow cytometry was used to determine the MFI of phosphorylated and therefore activated JAK downstream targets STAT3 and STAT5. In total GFP + thymus cells of ITK-SYK mice, Ruxolitinib led to a massive reduction in the phosphorylation levels of STAT3 (Figure 6.18 A) and STAT5 (Figure 6.18 B) as can be seen in the histograms.
A B + + pSTAT3 ITK-SYK Thymus Cells pSTAT5 ITK-SYK Thymus Cells
count count
pSTAT3 pSTAT5 Veh Ruxo Pac
Figure 6.18: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces activation of STAT3 and STAT5 in total GFP + thymus cells of ITK-SYK mice. Representative histograms of mean fluorescence intensity (MFI) of intracellular FACS staining of phosphorylated STAT3 (A) and STAT5 (B) in total GFP + thymus cells of ITK-SYK mice after treatment with Veh, Ruxo or Pac on d46 after tx. Data was acquired for at least 3 mice per group.
Results 75
A pSTAT3 Thymus Total T-Cells
* * GFP+ 40 40 GFP-
30 30 thymus cells thymus cells thymus + 20 + 20
CD90 10 CD90 10 pSTAT3MFI pSTAT3MFI + ** + ** * *** 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac ofCD3 ofCD3 GFP ITK-SYK GFP ITK-SYK B pSTAT3 Thymus CD4 + T-Cells + + *** GFP+ 25 25 GFP- CD90 CD90 + 20 + 20
15 15 thymus cells thymus thymus cells thymus - 10 - 10 *** *** CD8 CD8
+ 5 * + 5
CD4 0 CD4 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac pSTAT3 ofMFI CD3 GFP ITK-SYK pSTAT3of MFI CD3 GFP ITK-SYK C pSTAT3 Thymus CD8 + T-Cells + + * GFP+ 30 30 GFP- CD90 CD90 + +
20 20 thymus cells thymus cells + + 10 * 10 * CD8 CD8 - -
CD4 0 CD4 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac pSTAT3of MFI CD3 GFP ITK-SYK pSTAT3of MFI CD3 GFP ITK-SYK D pSTAT3 Thymus CD4 +CD8 + T-Cells + + GFP+ * *** 50 50 GFP- CD90 CD90 + + 40 40
30 30 thymus cell thymus cell + + 20 20 CD8 CD8 + + 10 ** 10 ** ***
CD4 0 CD4 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac pSTAT3of MFI CD3 GFP ITK-SYK pSTAT3ofMFI CD3 GFP ITK-SYK E pSTAT3 Thymus CD4 -CD8 - T-Cells + + GFP+ * 40 40 GFP- CD90 CD90 + + 30 30 thymus cells thymus 20 cells thymus 20 - -
* *
CD8 10 CD8 10 - * -
CD4 0 CD4 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac pSTAT3ofMFI CD3 GFP ITK-SYK pSTAT3of MFI CD3 GFP ITK-SYK
Figure 6.19: Simultaneous JAK1/2 inhibition reduces activation of STAT3 in thymic T-cell subpopulations of ITK-SYK mice to a higher extent than JAK2 inhibition alone. MFI of intracellular FACS staining of phosphorylated STAT3 in CD3 +CD90 + (A), CD3 +CD90 +CD4 +CD8 - (B), CD3 +CD90 +CD4 -CD8 + (C), Results 76
CD3 +CD90 +CD4 +CD8 + (D) and CD3 +CD90 +CD4 -CD8 - (E) cells within GFP + or GFP - thymus cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. (GFP Veh n=4, GFP Ruxo, GFP Pac, ITK-SYK Veh, ITK-SYK Ruxo, ITK-SYK Pac n=3 per group). Thymi were taken on d46 after tx. (A, B, C, D, E) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice.
FACS analysis in the different T-cell subpopulations (CD3 +CD90 +CD4 +CD8 -, CD3 +CD90 +CD4 -CD8 +, CD3 +CD90 +CD4 +CD8 +, CD3 +CD90 +CD4 -CD8 -) revealed an increased MFI of pSTAT3 in all T-cell subtypes of ITK-SYK mice compared to GFP controls with the exception of CD4 -CD8 - T-cells (Figure 6.19). Interestingly, this gain of STAT3 activity only occurred in the GFP + cells of ITK-SYK mice. In all T-cell subsets, STAT3 activation was significantly reduced by Ruxolitinib with the most profound effects in the malignant CD4 + cells (Figure 6.19 B). JAK1/2 co-inhibition in all T-cell subgroups resulted in MFIs comparable to those in Ruxolitinib treated GFP mice. Pacritinib only achieved minor inhibition of STAT3 phosphorylation which was still significantly higher in total and CD4 +CD8 + T-cells than the MFI in the respective control mice (Figure 6.19 A, D). STAT3 activation levels remained constant in all GFP - cells independent of the transplanted gene. This implies that ITK-SYK expression in murine T-cells directly activates JAK signaling and subsequent STAT3 phosphorylation. As a consequence, Ruxolitinib directly acts on the malignant T-cells by inhibiting JAK1/2 activation and subsequent STAT3 phosphorylation, whereas a JAK2 only inhibitor exhibits a much more attenuated effect. A similar increase of phosphorylation could be observed for STAT5 in thymic T-cell subpopulations (Figure 6.20) of ITK-SYK mice compared to GFP controls. Interestingly, the reduction of STAT5 phosphorylation in the malignant CD4 + T-cells (Figure 6.20 B) by Ruxolitinib was comparable to that of Pacritinib, indicating STAT3 as the major mediator of Ruxolitinib in improving the T-cell phenotype in ITK-SYK mice rather than STAT5. No alteration of STAT5 phosphorylation could be observed in CD4 -CD8 - T-cells (Figure 6.20 E). The significantly reduced STAT5 activation in GFP + and GFP - cells in Pacritinib treated GFP mice compared to Vehicle control however clearly demonstrated that the sparse effects of Pacritinib treatment were not caused by a lack of bioavailability. Therefore, it can be assumed that in fact, JAK2 inhibition itself was successful but not sufficient to impair TCL formation in ITK-SYK mice as strongly as simultaneous JAK1/2 inhibition with Ruxolitinib. In summary, this data shows that ITK-SYK directly drives JAK/STAT pathway activation in thymic T-cells. Moreover, it reveals that the administered doses of Ruxolitinib and Pacritinib were suitable to inhibit JAK kinases in normal thymic T-cells. However, only the simultaneous inhibition of JAK1 and JAK2 could achieve a profound impairment of ITK-SYK driven activation of the JAK/STAT pathway in ITK-SYK mice. This once again hints at JAK1 as the Results 77 major Ruxolitinib target responsible for disease formation and progression in murine ITK- SYK driven TCL.
A pSTAT5 Thymus Total T-Cells ** GFP+ 40 40 * GFP-
30 30 thymus cells thymus cells thymus + 20 + 20
CD90 10 ** CD90 10 pSTAT5MFI pSTAT5MFI + * + * **
0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac ofCD3 ofCD3 GFP ITK-SYK GFP ITK-SYK B pSTAT5 Thymus CD4 + T-Cells + + GFP+ 25 25 GFP- CD90 CD90 + + 20 20
15 15 thymus cells thymus thymus cells thymus - - 10 10 * * CD8 CD8
+ 5 + 5
0
CD4 0 CD4 Veh Ruxo Veh Ruxo Veh Pac Veh Pac pSTAT5of MFI CD3 GFP ITK-SYK pSTAT5ofMFI CD3 GFP ITK-SYK C pSTAT5 Thymus CD8 + T-Cells + + GFP+ 40 40 * GFP- CD90 CD90 + + 30 30
thymus cells 20 thymus cells 20 + +
CD8 10 * CD8 10 * - -
CD4 0 CD4 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac pSTAT5of MFI CD3 pSTAT5of MFI CD3 GFP ITK-SYK GFP ITK-SYK D pSTAT5 Thymus CD4 +CD8 + T-Cells + + GFP+ 50 * 50 *** GFP-
CD90 CD90 * + + * 40 40
30 30 thymus cell thymus cell + + 20 20 CD8 CD8 + + 10 ** 10 ** ***
CD4 0 CD4 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac E ofpSTAT5 MFI CD3 GFP ITK-SYK pSTAT5of MFI CD3 GFP ITK-SYK pSTAT5 Thymus CD4 -CD8 - T-Cells + + GFP+ 25 25 * GFP- CD90 CD90 + + 20 20
15 15 thymus cells thymus thymus cells thymus - 10 - 10 CD8 CD8 - - 5 5
CD4 0 CD4 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac pSTAT5of MFI CD3 pSTAT5of MFI CD3 GFP ITK-SYK GFP ITK-SYK
Results 78
Figure 6.20: Simultaneous JAK1/2 inhibition reduces activation of STAT5 in thymic T-cell subpopulations of ITK-SYK mice to a higher extent than JAK2 inhibition alone. MFI of intracellular FACS staining of phosphorylated STAT5 in CD3 +CD90 + (A), CD3 +CD90 +CD4 +CD8 - (B), CD3 +CD90 +CD4 -CD8 + (C), CD3 +CD90 +CD4 +CD8 + (D) and CD3 +CD90 +CD4 -CD8 - (E) cells within GFP + or GFP - thymus cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. (GFP Veh n=4, GFP Ruxo, GFP Pac, ITK-SYK Veh, ITK-SYK Ruxo, ITK-SYK Pac n=3 per group). Thymi were taken on d46 after tx. (A, B, C, D, E) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice.
6.3.13 Ruxolitinib but not Pacritinib improves the B-cell phenotype in PB and spleens of ITK-SYK mice
A PB B-Cells *** ** *** * GFP+ *** *** ** 60 *** ** 60 ** *** GFP- PB cells PB cells -
+ 40 40 PB cells PB cells within cells + + /GFP + 20 20 /GFP ** -
%of B220 ** GFP
0 %of B220 0
within GFP within Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK B Spleen B-Cells
* ** *** GFP+ 80 80 * *** ** * GFP- ** ** ** 60 60 cells cells spleen cells spleen cells spleen + + - - * * 40 40 /GFP /GFP + + 20 20 %of B220 %of B220 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac within GFP within within GFP within GFP ITK-SYK GFP ITK-SYK
Figure 6.21: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves B-cell phenotype in PB and spleen cells of ITK-SYK mice. Percentage of B220 + cells within GFP + or GFP - PB (A) and spleen (B) cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. Blood samples were taken on d43 and spleens on d46 after tx and analyzed by FACS. (PB left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; PB right: GFP Veh n=4; GFP Pac n=3; ITK SYK Veh: n=10 per group; ITK-SYK Ruxo n=8; spleen left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; spleen right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK-SYK Pac n=3 per group). (A, B) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice.
Results 79
To further analyze the cellular distribution in ITK-SYK mice under JAK inhibitor treatment, PB (Figure 6.21 A) and splenic (Figure 6.21 B) B-cell levels were assessed by FACS. B-cell percentages in both organs were significantly reduced in ITK-SYK mice compared to GFP controls. This reduction was independent of the ITK-SYK expression status of the respective B-cells and was therefore likely to be a secondary effect of the infiltration of these organs with other cells such as myeloid cells. Interestingly, B-cell levels in PB and spleen were slightly reduced by both inhibitors in GFP control mice, pointing at a direct effect of JAK2 inhibition on this cell type independent of ITK-SYK expression. In ITK-SYK TCL mice, only Ruxolitinib significantly elevated B-cell percentages whereas Pacritinib further reduced them, indicating that lack of JAK1 inhibition combined with JAK2 inhibition confers a disadvantageous effect in this setting. Thus, these observations serve as further evidence that Ruxolitinib exerts its major effects on ITK-SYK driven TCL via JAK1 inhibition.
6.3.14 Ruxolitinib but not Pacritinib improves T-cell levels in PB but not in spleens of ITK-SYK mice Next, the distribution of total T-cells in PB (Figure 6.22 A) and spleens (Figure 6.22 B) of GFP and ITK-SYK mice was assessed by FACS.
A PB T-Cells
** *** *** * *** GFP+ 40 *** ** 40 * *** GFP- * PB cells PB cells
- 30 30 ** +
PB cells PB *** cells within cells + 20 + 20 /GFP + * /GFP 10 - 10 *** %of CD90 GFP
0 %of CD90 0
within GFP within Veh Ruxo Veh Ruxo Veh Pac Veh Pac GFP ITK-SYK GFP ITK-SYK B Spleen T-Cells ** ** ** *** *** GFP+ 40 ** 40 ** GFP- ** ** 30 30 * cells cells spleen cells spleen cells spleen + - - + ** 20 20 /GFP /GFP + + 10 10 %of CD3 %of CD3 0 0 Veh Ruxo Veh Ruxo Veh Pac Veh Pac within GFP within GFP ITK-SYK GFP within GFP ITK-SYK
Figure 6.22: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves T-cell levels in PB but not in spleens of ITK-SYK mice. (A) Percentage of CD90 + cells within GFP + or GFP - PB cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. (B) Percentage of CD3 + cells within GFP + or GFP - spleen cells of GFP and ITK-SYK mice after treatment with Veh, Ruxo or Pac. Blood samples were taken on d43 and spleens on d46 after tx and analyzed by FACS. (PB left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; Results 80
GFP Ruxo n=4; PB right: GFP Veh n=4; GFP Pac n=3; ITK SYK Veh: n=10 per group; ITK-SYK Ruxo n=8; spleen left: GFP Veh, ITK-SYK Veh, ITK-SYK Ruxo n=5 per group; GFP Ruxo n=4; spleen right: GFP Veh n=4; GFP Pac, ITK-SYK Veh, ITK-SYK Pac n=3 per group). (A, B) Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001. Asterisks above the white bars represent the significance of the difference between GFP+ and GFP- populations within the same mice.
The analysis revealed a significant reduction of T-cell levels in both organs after transplantation with ITK-SYK compared to GFP independently of the ITK-SYK expression status. Simultaneous inhibition of the JAK1 and JAK2 kinases but not of JAK2 only resulted in a complete rescue of the T-cell distribution in the PB, whereas the splenic effects could not be omitted by either inhibitor. These findings once more underline the eligibility of the assumption that JAK1 is the major Ruxolitinib target in our TCL model.
6.4 ITK-SYK drives the activation of JAK1 but not JAK2 in vitro To better understand the underlying mechanisms of ITK-SYK driven JAK activation, phosphorylation of several JAK/STAT signaling molecules was assessed in a murine benign CD4 + T-cell line in vitro . The IL-2 and IL-1α dependent T-cell line D10.G4.1 was retrovirally transduced with the same GFP and ITK-SYK expressing vectors used in the described ITK-SYK mouse model. Cells were then sorted for GFP+ cells and seeded for 24 h in D10.G4.1 cultivation medium. After protein extraction, SDS-PAGE and subsequent blotting to nitrocellulose membranes, phosphorylated and total protein levels of JAK/STAT pathway mediators were visualized by immunodetection (Figure 6.23). Functionality of all antibodies was affirmed using protein lysates of other cell lines or interleukin stimulated cells (not shown). Intriguingly, ITK-SYK expression in normal CD4 + cells led to a strong activation of JAK1 and JAK3, whereas JAK2 was not phosphorylated upon ITK-SYK expression. This fits in well with the previous observations that JAK1/2 inhibition almost completely abolished ITK-SYK driven effects on malignant CD4 + cells in the murine TCL mouse model and confirms JAK1 as the major mediator of ITK-SYK driven disease. STAT3 activation was, in accordance with findings in the murine model, also increased compared to GFP transduced D10.G4.1 cells. Western Blot (WB) analysis also proposed STAT6 as an additional potential JAK target activated by ITK-SYK. STAT5 phosphorylation was rather decreased upon ITK- SYK expression, thus further underlining the assumption that STAT5 is not a critical player in JAK/STAT signaling induced by ITK-SYK. The same holds true for STAT4 which remained entirely unphosphorylated. Taken together, this data confirms before-mentioned results showing that JAK1 is likely to be the main driver of ITK-SYK driven murine TCL and thus the major target of Ruxolitinib. These results also explain why the JAK2 only inhibitor Pacritinib was not sufficient to block TCL development in the ITK-SYK mouse model. Results 81
D10.G4.1
MW MW
SYK SYK - [kDa] - [kDa] GFP ITK GFP ITK pJAK1 JAK1 130 130
130 pJAK2 130 JAK2
pJAK3 JAK3 130 130
100 pSTAT3 100 STAT3
100 pSTAT4 STAT4 100
pSTAT5 STAT5 100 100
100 pSTAT6 STAT6 100
ß-Actin 40
Figure 6.23: ITK-SYK drives the activation of JAK1 but not JAK2 in a murine CD4 + T-cell line. WB of murine CD4 + T-cell line D10.G4.1 after transduction with pMIG or pMIG-ITK-SYK and sort for GFP. Abs directed against phosphorylated and total JAK1, JAK2, JAK3, STAT3, STAT4, STAT5 and STAT6 and against total β-Actin were used. Left panel shows the phosphorylated protein, right panel the total protein. MW, molecular weight; kDa, kilodaltons.
To further delineate whether ITK-SYK mediated activation of the JAK signaling pathway in CD4 + T-cells is dependent on its kinase activity or rather on its cellular location, D10.G4.1 cells were transduced with the described pMIG vector encoding different SYK constructs and WB experiments were repeated. To ensure that the activation of JAK1 was not mediated by the growth factors present in D10.G4.1 culture medium, cells were starved for 2 h before isolation of total protein. Longer starvation times led to massive apoptosis in these cells and were therefore not applicable. ITK-SYK is located at the cellular membrane via the PH-domain of the N-terminal part of ITK.184 To analyze whether membrane localization is the critical part of JAK activation, the cell line was transduced with a plasmid expressing myristoylated (myr) SYK which is a variant of WT SYK with an addition of a myristoyl group compelling membrane-binding. Furthermore, WT D10.G4.1 cells (naïve) and those transduced with WT SYK or a construct with a point mutation rendering SYK constitutively active (SYK(Y325H)) were also analyzed. These WB experiments showed that none of these constructs besides ITK-SYK were able to activate JAK1 in a murine CD4 + T-cell line (Figure 6.24). This means that neither membrane localization nor constitutive activation of SYK alone is sufficient to mediate JAK/STAT pathway activation. Results 82
D10.G4.1
MW SYK [kDa] - naïve SYK WT SYK myr ITK SYK (Y325H)
130 pJAK1
130 JAK1
ß-Actin 40
Figure 6.24: ITK-SYK activation of JAK1 in a murine CD4 + T-cell line does neither depend on localization nor on kinase activation alone. WB of D10.G4.1 after transduction with pMIG-SYK WT, pMIG-myristoylated (myr) SYK, pMIG-ITK-SYK and pMIG-SYK (Y325H) and sort for GFP or untransduced (naïve). Abs directed against phosphorylated (top) and total (middle) JAK1 and against total β-Actin (bottom) were used.
6.5 Simultaneous inhibition of JAK1 and JAK2 is an effective treatment strategy in a human angioimmunoblastic TCL xenograft PTCLs present a rare disease entity making up only 9.4% of all NHLs.4 Of these PTCL cases, only 25.9% are PTCL-NOS 8 and of these, only 17% (= 0.4% of all NHLs) harbor an ITK-SYK translocation.25 Due to this disease rarity, finding a suitable patient sample with an ITK-SYK mutation for generating an ITK-SYK driven PTCL-NOS xenograft is close to impossible. To circumvent this problem, a PB sample from a patient suffering from AITL was used. This lymphoma subtype makes up 18.5% of all PTCL cases.8 As is true for ITK-SYK + PTCL-NOS, it is usually driven by malignant CD4 + T-cells 160 , shows inflammatory properties 64,67,73,74 and skin lesions are often observed.336 To investigate the effects of JAK1/2 inhibition also in a human PTCL disease context, this lymphoma subtype appeared to be a promising option. The workflow for the generation of the xenograft model is shown in Figure 6.25. Due to limited patient material, only 6 x 10 6 PB cells of the AITL patient were transplanted into a single NOG mouse. This corresponded to 0.34 x 10 6 CD4 + and 0.36 x 10 6 CD8 + T-lymphocytes. To expand the patient cells into more recipients in order to be able to generate groups large enough for Ruxolitinib treatment, spleen cells of this mouse were analyzed and via two secondary recipients finally transplanted into eight tertiary recipients. Interestingly, approximately 87% of all hCD45 + cells of the primary xenograft mouse (= 72.1% of all spleen cells) were CD4 + and only a minority of cells were CD8 +. This indicates that the phenotype was TCL driven rather than being caused by graft-versus-host disease (GvHD), since in GvHD NOG mouse models, CD8 + T-cells rapidly proliferate when transplanted together with CD4 + cells.337 Secondary recipients showed a similar CD4 + accumulation. Due to rapid disease formation and progression, tertiary recipients received treatment starting on d5 after transplantation. Treatment dose and administration was equal Results 83 to that in the ITK-SYK mouse model. After 16 days of treatment on d21 after transplantation, the mice had to be sacrificed due to massive reduction in the general state of health of the Vehicle control group.
start treatment: d5
Vehicle 40 days 23 days 16 days
Ruxo 16 days 6 x 10 6 prim. PB
0.9 x 10 6 lymphocytes (15% of PB) 43.8 x 10 6 spleen cells 37.33 x 10 6 spleen cells = 37.4% CD4 = 0.34 x 10 6 CD4 cells = 82.5% hCD45 = 36.1 x 10 6 hCD45 cells = 72.4% hCD45 = 27.0 x 10 6 hCD45 cells = 39.5% CD8 = 0.36 x 10 6 CD8 cells = 72.1% hCD4 = 31.6 x 10 6 hCD4 cells = 67.5% hCD4 = 25.2 x 10 6 hCD4 cells CD4/CD8 = 0.9 (ref: 1.0 – 3.3)
Figure 6.25: Workflow of experimental procedure for Ruxolitinib treatment of TCL xenograft mice. One PB sample from an AITL patient was serially transplanted into NOG mice until a sufficient number xenograft mice were generated to perform treatment experiments (n=4 per group). NOG mice were treated with Veh (PEG 300 + 5% Dextrose 1:3, 10 µl/g bw) twice daily or 30 mg/kg bw Ruxo (3 mg/ml in Vehicle) twice daily for 16 days starting on d5 after treatment. Organs were then harvested on d21 after tx and analyzed.
6.5.1 Ruxolitinib reduces organ weight and cell counts in AITL xenograft mice Ruxolitinib treatment of AITL xenograft NOG mice resulted in a significant deceleration of body weight loss (Figure 6.26 A). Furthermore, it impaired spleen growth (Figure 6.26 B) and significantly reduced spleen weight by more than half compared to Vehicle control treated mice (Figure 6.26 C). Additionally, the total cell count in the spleens was significantly diminished upon JAK1/2 inhibition. The same tendency could be observed for the BM for which one femur per mouse was counted (Figure 6.26 D).
Results 84
A Weight Loss start treatment
110 Veh Ruxo 100 * 90 weight loss (%) loss weight
80 0 5 7 9 2 9 1 14 16 1 21 days post tx
BC Spleen Weight 1.5 ** Veh. 1.0
Ruxo 0.5 rel. spleen weight spleen rel. (% of weight) (% body 1 cm 0.0 Veh Ruxo
D Spleen Count Femur Count
) ns ) 6 15 6 200 *
150 10
100 5 50
total femur cells (x10 cells femur total 0
total spleen cells (x10 cells spleen total 0 Veh Ruxo Veh Ruxo
Figure 6.26: Ruxolitinib impairs weight loss and reduces spleen size, weight and cell counts of human xenograft lymphomas. (A) Percentage of bw of AITL xenograft mice after treatment with Veh or Ruxo compared to starting weight measured on d0 after tx. Statistical significance was calculated for the values on d19. (B) Spleen sizes of Veh and Ruxo treated xenograft mice on d21 after tx. Shown are representative images for 4 mice per group. (C) Rel. spleen weight calculated as percentage of bw of Veh and Ruxo treated xenograft mice. (D) Total spleen (left) and femur (right) cell counts of Veh and Ruxo treated xenograft mice. (A, C, D) n=4 per group. Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01, ***p < 0.001, ns non-significant.
6.5.2 Ruxolitinib reduces inflammatory responses in AITL xenograft mice To determine whether Ruxolitinib can inhibit inflammatory responses in the used AITL xenograft model, PB was assessed for the distribution of white blood cells with a special focus on myeloid cells by blood counter analysis and FACS. In addition to Vehicle and Ruxolitinib treated xenograft mice, cell counts were also determined for non-transplanted NOG mice to obtain baseline levels, indicated by dashed lines in Figure 6.27 A, B, C, D, E. Results 85
Tertiary xenograft recipients treated with Vehicle control showed a massively increased white blood cell count (WBC, Figure 6.27 A) as well as elevated lymphocyte (Figure 6.27 C), monocyte (Figure 6.27 D) and granulocyte (Figure 6.27 E) counts in the PB. Intriguingly, these effects could be almost completely abrogated through Ruxolitinib treatment. Red blood cell counts (RBCs) in the xenograft mice were slightly lower than in WT littermates which could not be reversed by JAK1/2 inhibition. Percentages of PB granulocytes and monocytes, as were determined by FACS analysis, showed increased cell levels in the PB (Figure 6.27 F), but the effect on total cells was comparable to that obtained with the blood counter (Figure 6.27 D, E, G). Although the granulocytic counts were strikingly different between the two methods, the overall tendency was similar. These numeric variations could have been caused either by inaccuracies of the blood counter or by increased apoptosis of granulocytes during cell lysis and preparation for FACS analysis. FACS analysis hardly showed any hCD45 +hCD11b + cells in the PB of these mice (Supplementary Figure 9.1). Therefore, it is highly unlikely that the presence of human granulocytes was responsible for these aberrations. The percentagewise increase of myeloid cells in the PB of Ruxolitinib treated xenograft mice could be explained by the general decrease in the WBC and decreased malignant T-cell levels (Figure 6.29), resulting in higher cell levels of myeloid cells though total numbers were diminished.
ABCD E WBC RBC PB Lymphocytes PB Monocytes PB Granulocytes 40 ** 10 10 * 5 * 25 ** /µl] /µl] /µl] 3 3
8 3 30 8 4 20 cells/µl] cells/µl] 6 6 3 6 3 15 20 4 4 2 10 10 2 2 1 5 RBC [x10 RBC WBC[x10 monocytes [x10 monocytes lymphocytes [x10 lymphocytes 0 0 0 0 [x10 granulocytes 0 Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo F G
PB Granulocytes PB Monocytes l) PB Granulocytes
l) PB Monocytes - + / / ** 3 ** 3 100 100 * 10 5 ** 80 80 8 (x 10 (x 4 (x 10 (x + - mLy-6G mLy-6G + + 60 60 6 3
40 40 4 2 mLy-6G mLy-6G + + 20 20 2 1 0 0 0
% ofmCD11b 0 % ofmCD11b Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo mCD11b mCD11b
Figure 6.27: Ruxolitinib inhibits inflammatory responses in the PB of human xenograft lymphomas. WBC (A, x 10 3/µl), RBC (B, x 10 6/µl) and total lymphocyte (C, x 10 3/µl), monocyte (D, x 10 3/µl) and granulocyte (E x 10 3/µl) counts of Veh and Ruxo treated xenograft mice analyzed by scil Vet ab blood counter. Dashed lines indicate baseline levels (mean of 3 non-transplanted NOG mice). Percentage of (F) and total amount (G, x 10 3/µl) of murine mCD11b +mLy-6G + granulocytes (left) and mCD11b +mLy-6G - monocytes (right) in PB of Veh and Ruxo treated xenograft mice measured by FACS. Blood samples were taken on d21 after tx. (A, B, C, D, E, F, G) n=4 Results 86
per group. Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01.
FACS analysis was also performed to determine myeloid cell levels and counts in spleens of human AITL xenograft mice (Figure 6.28). NOG mice are depleted of all lymphoid cells. Still, myeloid cell levels in this organ were quite low in the xenograft mice, suggesting a massive infiltration of the spleen with cells that are neither of murine myeloid nor of murine lymphoid origin. This already points to a massive infiltration of the spleens with human cells. The effects of Ruxolitinib on myeloid cell levels and cell counts were comparable to those observed in the PB with a significant decrease in numbers of either cell type upon JAK1/2 co- inhibition. The significant percentagewise increase in monocyte levels (Figure 6.28 A) could again be explained by decreased total cell numbers as was shown in Figure 6.26 D.
A B Spleen Granulocytes Spleen Monocytes Spleen Granulocytes
) Spleen Monocytes ) - 6 + * 6 100 100 * 10 10 * (x 10 (x
80 80 10 (x
+ 8 - 8 mLy-6G mLy-6G + + 60 60 6 6 mLy-6G 40 40 4 mLy-6G 4 + + 20 20 2 2
0 0 0 0 % of mCD11b %of mCD11b mCD11b Veh Ruxo Veh Ruxo mCD11b Veh Ruxo Veh Ruxo
Figure 6.28: Ruxolitinib inhibits myeloid expansion and infiltration in spleens of human xenograft lymphomas. Percentage of (A) and total amount (B, x 10 6/spleen) of mCD11b +mLy-6G + granulocytes (left) and mCD11b +mLy-6G - monocytes (right) in spleens of Veh and Ruxo treated xenograft mice measured by FACS. Spleens were taken on d21 after tx. (A, B) n=4 per group. Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05.
These results show that Ruxolitinib treatment strongly reduces the inflammatory expansion of myeloid cells in the PB and spleens of human AITL xenograft mice and therefore achieves similar effects as were seen in the primary ITK-SYK mouse model. This allows the presumption that Ruxolitinib might be an effective treatment strategy in all PTCL cases accompanied by massive inflammatory reactions.
6.5.3 Ruxolitinib reduces T-cell lymphoma burden in AITL xenograft mice To delineate whether Ruxolitinib also has effects on engraftment and proliferation of primary human T-cells in the PB and spleen of human AITL xenograft mice, FACS analysis was performed. Figure 6.29 A shows the percentages of human T-cells in the PB of the xenograft NOG mice. Interestingly, the engrafted human cells were almost exclusively CD4 +, indicating that the mice indeed suffered from TCL and not from GvHD. It has been shown that malignant T-cells in AITL often loose CD7 expression.162,163 Therefore, the CD4 + T-cells were Results 87 also analyzed for this putative malignancy marker. Distribution of human CD4 +CD7 + and CD4 +CD7 - cells was almost equal in PB of xenograft NOG mice, showing a large population of abnormal CD7 - T-lymphocytes. Notably, Ruxolitinib treatment of human AITL xenograft NOG mice resulted in a significant decrease not only in percentage (Figure 6.29 A) but also in total counts (Figure 6.29 B) of human CD4 + T-cells in the PB effectively depleting the malignant cells.
A PB CD4 + + + PB CD4 + CD7 - + PB CD4 +CD8 +
PB CD4 CD7 - PB CD8 + +
+ 60 ** 60 ** 60 ** 60 + 60 hCD7 hCD8 hCD7 + + + hCD4 hCD8
+ 40 40 40 40 + 40 hCD4 hCD4 hCD4 + + + 20 20 20 20 20 %of hCD45 0 0 0 %of hCD45 0 0
Veh Ruxo of% hCD45 Veh Ruxo %of hCD45 Veh Ruxo
%of hCD45 Veh Ruxo Veh Ruxo B l) l) + + + + - + l) + + PB CD4 CD7 PB CD4 CD7 PB CD4 CD8
/ PB CD8 PB CD4 / / 3 3 3 l) l) 20 * 20 * 20 / 20 20 * / 3 3 (x 10 (x (x 10 (x (x 10 (x - + 15 15 15 15 + 15 (x 10 (x (x 10 (x + + hCD7 hCD7 10 hCD8 10 10 + 10 10 + + hCD8 hCD4 + + 5 5 5 5 5 hCD4 hCD4 hCD4 + + + 0 0 0 0 hCD45 0 hCD45 Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo hCD45 hCD45 hCD45
Figure 6.29: Ruxolitinib inhibits release of human T-cells into the blood stream of xenograft lymphoma mice. Percentage of (A) and total amount (B, x 10 3/µl) of hCD45 +hCD4 + (left), hCD45 +hCD4 +hCD7 + (second from left), hCD45 +hCD4 +hCD7 - (middle), hCD45 +hCD8 + (second from right) and hCD45 +hCD4 +hCD8 + (right) cells in PB of Veh and Ruxo treated xenograft mice measured by FACS. Blood samples were taken on d21 after tx. (A, B) n=4 per group. Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01.
In accordance with PB data, FACS analysis of the spleens of these NOG mice revealed almost exclusive engraftment of human CD4 + cells with close to no detection of human CD8 + and CD4 +CD8 + T-cells. Here however, the differences in the percentage of human CD4 + T-cell populations in Ruxolitinib treated mice compared to Vehicle controls were not as profound as was seen for the PB (Figure 6.30 A, Figure 6.29 A). This indicates that the inhibitory effects do not primarily target human cell engraftment itself but rather their proliferation, seeing that the total amounts of human CD4 + T-cells were strongly reduced by JAK1/2 co-inhibition (Figure 6.30 B). CD4 +CD7 - cell percentage (Figure 6.30 A) and counts (Figure 6.30 B) were both significantly decreased, thus implying a small effect of Ruxolitinib on engraftment and/or survival of these cells. Taken together, this data illustrates that JAK1/2 co-inhibition has only mild effects on engraftment of the presumably malignant primary human CD4 +CD7 - T-cell population in AITL xenograft mice. It rather inhibits proliferation of these cells in the spleen as well as Results 88 subsequent mobilization and release into the blood stream, leading to a strongly diminished TCL burden in the transplanted NOG mice. This underlines the potential of Ruxolitinib treatment as a therapeutic approach in AITL patients.
A + + + + Spleen CD4 + Spleen CD4 CD7 Spleen CD4 + CD7 - + Spleen CD4 CD8 -
+ Spleen CD8 + 100 100 * 100 **
+ 100 * + 100 hCD7 hCD7 hCD8 + + 80 80 80 80 + 80 hCD4 hCD8 + 60 60 60 + 60 60 hCD4 hCD4 hCD4 + + + 40 40 40 40 40
20 20 20 20 20 %of hCD45 0 0 0 %of hCD45 0 0 %of hCD45
%of hCD45 Veh Ruxo Veh Ruxo
Veh Ruxo Veh Ruxo %of hCD45 Veh Ruxo
B + + + - + ) + + + ) Spleen CD4 CD7 ) Spleen CD4 6 Spleen CD4 CD7 Spleen CD8
6 Spleen CD4 CD8 6 ) 200 * ) 6 200 * 200 * 6 200 200 * (x 10 (x (x 10 (x (x 10 (x - + + 150 150 150 150 (x 10 (x
(x 10 (x 150 + + hCD7 hCD7 hCD8 + + 100 100 100 100 + 100 hCD4 hCD8 + + hCD4 hCD4 50 50 50 50 hCD4 50 + + +
hCD45 0 0 0 hCD45 0 0 Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo Veh Ruxo hCD45 hCD45 hCD45
Figure 6.30: Ruxolitinib inhibits proliferation but not engraftment of human T-cells in spleens of xenograft lymphoma mice. Percentage of (A) and total amount (B, x 10 6/spleen) of hCD45 +hCD4 + (left), hCD45 +hCD4 +hCD7 + (second from left), hCD45 +hCD4 +hCD7 - (middle), hCD45 +hCD8 + (second from right) and hCD45 +hCD4 +hCD8 + (right) cells in spleens of Veh and Ruxo treated xenograft mice measured by FACS. Spleens were taken on d21 after tx. (A, B) n=4 per group. Bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. *p < 0.05, **p < 0.01.
6.5.4 Ruxolitinib impairs increased hIFNγ and mIL-6 levels in AITL xenograft mice To examine the serum cytokine levels of human AITL xenograft NOG mice and whether Ruxolitinib has a beneficial effect on their release, cytokine arrays were performed. Specific arrays for human and murine cytokines respectively helped to distinguish between cytokines of either species. Thus, they contributed to the understanding of which cytokine is released by which cell type. For murine cytokines, serum isolated from four WT NOG mice was used as a reference and, as a comparison for human cytokine levels, assessment of cytokines in the serum of the primary AITL patient was performed. The cytokines to be analyzed were those identified as altered in the ITK-SYK mouse model compared to GFP control (Figure 6.7). Of the murine cytokines analyzed, only IL-6 levels were significantly upregulated in Vehicle treated xenograft mice compared to WT NOG mice, though the total pg/ml amounts were quite low (Figure 6.31 A). This proposes that IL-6 is primarily secreted by the expanded murine myeloid cells, since this mouse strain is depleted of all lymphoid cell types. Intriguingly, elevated IL-6 levels were normalized upon Ruxolitinib treatment. Murine IFNγ and murine IL-5 were also only present at very low levels and both showed a slight tendency Results 89 of being rather downregulated in the serum of xenograft NOG mice compared to controls (Figure 6.31 B, C). For the human cytokines, no statistical analysis could be performed between patient serum and AITL xenograft serum cytokine levels, since the former were obtained by analyzing a single sample only. However, the data shows that human IL-6 is present at lower levels in AITL xenograft mice compared to the human sample and Ruxolitinib can only increase cytokine levels to a small extent (Figure 6.31 D). Interestingly, enormous levels of human IFNγ were detected in the serum of AITL xenograft NOG mice treated with Vehicle (Figure 6.31 E). This indicates that the malignant T-cells release high amounts of this pro-inflammatory cytokine. The low amounts of IFNγ in the primary patient are most likely due to the fact that human CD4 + T-cell counts in the primary patient were quite low compared to the mice. In accordance with data obtained for the murine cytokine in the ITK-SYK TCL model, human IFNγ levels were significantly downregulated by Ruxolitinib treatment (Figure 6.31 E). Finally, human IL-5 levels in AITL xenograft mice were quite low and were not altered by treatment with Ruxolitinib (Figure 6.31 F).
A BC mIL-6 mIFN mIL-5
12 ** ** 12 12
8 8 8
4 4 4 pg/ml serum pg/ml serum pg/ml serum pg/ml
0 0 0 WT Veh Ruxo WT Veh Ruxo WT Veh Ruxo D EF hIL-6 hIFN hIL-5 12 1500 12 ***
8 1000 8
4 500 4 pg/ml serum pg/ml pg/ml serum pg/ml serum pg/ml
0 0 0 Pat Veh Ruxo Pat Veh Ruxo Pat Veh Ruxo
Figure 6.31: Ruxolitinib impairs increased IFNγ release by human T-cells and subsequent IL-6 release by murine cells in xenograft lymphoma mice. Serum cytokine levels of murine IL-6 (A), IFNγ (B) and IL-5 (C) as well as human IL-6 (D), IFNγ (E) and IL-5 (F) of Veh and Ruxo treated xenograft mice on d21 after tx were determined using BD CBA Flex Sets with subsequent FACS analysis. (A, B, C, D, E, F) n=4 per group. Horizontal bars represent mean values with error bars showing the SEM. Statistical significance was calculated using Student’s unpaired t-test. **p < 0.01, ***p < 0.001.
This data shows that not only in the ITK-SYK mouse model but also in the human AITL xenograft model, IL-6 and IFNγ levels are strongly increased and can be downregulated by Results 90 simultaneous JAK1/2 inhibition with Ruxolitinib. This indicates that elevated levels of these cytokines occur in more than one TCL subtype and are likely to play a role in disease progression and inflammation. Moreover, the results after distinction between human and murine cytokines imply that IFNγ production is facilitated by the malignant T-cells, whereas IL-6 is presumably secreted by murine myeloid cells. This provides a possible regulatory feedback mechanism in which the primary malignant T-cells produce IFNγ after JAK/STAT activation and thus induce myeloid cell expansion and secretion of IL-6 which then again further stimulates CD4 + T-cell activation. In this case, the JAK1/2 co-inhibitor Ruxolitinib would suppress the primary IFNγ secretion by the malignant cells and hence rescue the resulting inflammatory phenotype by abolishing this positive feedback loop. Therefore, Ruxolitinib might present a novel treatment strategy to decelerate disease progression and increase survival rates in PTCL associated with strong inflammatory phenotypes.
Discussion and perspectives 91
7 Discussion and perspectives PTCLs are a heterogeneous group of diseases, representing only a small fraction of malignancies arising from lymphoid cells. 1 They are associated with particularly bad prognosis due to their poor responsiveness to classical chemotherapies and the lack of targeted therapies. 8,78–81 Many patients with TCLs present with malaise caused by B-symptoms as well as inflammation and granulocytosis.17,71,76,334 These secondary effects often bestow a higher burden to the patients than the malignant T-cell expansion. This study aimed to find a therapeutic strategy to target both, the malignant T-cells and the inflammatory phenotype in a mouse model of PTCL-NOS and a human AITL xenograft model. The murine model, which was established in our laboratory, utilizes the kinase fusion ITK-SYK to induce a PTCL-NOS resembling the human disease phenotype. 185,186 It was previously shown that 17% of all PTCL-NOS cases harbor the ITK-SYK fusion25 and its expression in mice constitutively activated T-cell receptor signaling and led to infiltration of peripheral organs such as liver, lung and skin with malignant T-cells. 155,185 Furthermore, it was accompanied by a strong inflammatory phenotype with massive granulocytosis (Figure 6.1).186,210 Interestingly, the expanding granulocytes were not dependent on intrinsic ITK-SYK expression, suggesting that granulocytosis was a secondary consequence of the TCL rather than a direct effect of ITK-SYK expression (Figure 6.1). 186 This fits in well with previous data as well as the findings illustrated here that inflammatory cytokines such as IFNγ, IL-5, IL-6 and TNFα were strongly increased in the serum of ITK-SYK mice (Figure 6.7)185,210 and suggests these soluble factors as possible mediators of PTCL induced inflammation.
7.1 Effects of JAK inhibitors on the PTCL phenotype JAK/STAT signaling has been shown to be upregulated in hematopoietic malignancies. 272-275,338,339 ITK-SYK is known to drive STAT3 phosphorylation 210,297 , thus resulting in an activated JAK/STAT pathway and myeloproliferative neoplasms are often associated with JAK activating mutations 303 . Hence, JAK inhibitors were tested in the ITK-SYK mouse model to simultaneously block TCL development and impair subsequent inflammation and myeloid expansion (Figure 6.4). For this purpose, two different JAK inhibitors were introduced. Ruxolitinib blocks JAK1 and JAK2 signaling, whereas Pacritinib primarily targets JAK2 only (Table 6.1). Simultaneous inhibition of JAK1 and JAK2 with Ruxolitinib led to a very mild form of PTCL in the ITK-SYK mouse model with an improved phenotype (Figure 6.5), attenuated weight loss (Figure 6.6), abolished infiltration of CD3 + T-cells into the skin (Figure 6.15), impaired infiltration of CD11b + myeloid cells into peripheral organs (Figure 6.12) and significantly prolonged survival (Figure 6.8). JAK2 inhibition alone by Pacritinib only had minimal effects on the disease phenotype, and overall survival was only extended by half compared to Ruxolitinib treatment (Figure 6.8). Interestingly, ITK-SYK expressing cell levels in BM, spleen Discussion and perspectives 92 and thymus were decreased by Ruxolitinib but not Pacritinib (Figure 6.9), suggesting a direct effect of JAK1/JAK2 co-inhibition in contrast to JAK2 inhibition alone on ITK-SYK expressing cells and thus implying JAK1 as the major Ruxolitinib target in the primary malignant cells.
7.2 Effects of JAK inhibitors on the malignant T-cells Retransplantation experiments confirmed the ITK-SYK expressing CD4 + T-cells as the primary malignant cell type (Figure 6.16) as has been suggested before.155,185 These malignant cells showed increased levels of phosphorylated and hence activated JAK downstream targets STAT3 and STAT5 upon ITK-SYK expression compared to GFP controls and to ITK-SYK - CD4 + T-cells in ITK-SYK transplanted mice (Figure 6.19 B, Figure 6.20 B). An increase of STAT3 phosphorylation in granulocytes expressing ITK-SYK (Figure 6.13) could not be observed and STAT5 activation was only minimally enhanced by ITK-SYK expression in these cells. This underlines previous observations that ITK-SYK is dependent on TCR signaling and drives malignant transformation only in T-cells as was shown by comparison of ITK-SYK expression in T- and B-cells by Pechloff et al. 155 Interestingly, the phosphorylation of STAT3 could be entirely abrogated by JAK1 and JAK2 co-inhibition, whereas the JAK2 inhibitor Pacritinib only showed minor effects on ITK-SYK induced STAT3 phosphorylation which were not statistically significant, though STAT3 and STAT5 phosphorylation in Vehicle vs. Pacritinib treated GFP control mice proved bioavailability of the compound (Figure 6.19, Figure 6.20). This indicates JAK1 as the major player of ITK- SYK driven STAT3 activation in the malignant T-cell population. Reduction of STAT5 phosphorylation by Pacritinib was comparable to that achieved by Ruxolitinib treatment, thus implying that STAT3 is the primary mediator of Ruxolitinib mediated improval of the disease phenotype in the ITK-SYK model rather than STAT5. This fits in well with previous observations of other groups that ITK-SYK expression drives STAT3 phosphorylation.210,297 The fact that the JAK1/2 inhibitor Ruxolitinib can abrogate ITK-SYK driven STAT3 phosphorylation suggests the canonical JAK/STAT signaling as the underlying pathway rather than direct STAT phosphorylation by other upstream factors such as ITK-SYK itself as has been proposed by other groups210 , though direct phosphorylation of STAT3 by SYK kinases has been reported in B-cell leukemias/lymphomas. 340 In line with the finding that JAK1/2 co-inhibition but not JAK2 inhibition alone completely abolished STAT3 activation and strongly impaired TCL development, the in vitro cell culture system used displayed an activation of JAK1 and STAT3 but not JAK2 and STAT5 in the murine CD4 + T-cell line D10.G4.1 upon expression of the ITK-SYK oncogene (Figure 6.23). Thus further hints at JAK1 and subsequent STAT3 activation as the major Ruxolitinib target in the malignant T-cells. Interestingly, increased phosphorylation of JAK3 and STAT6 could also be observed, whereas STAT5 activation was rather diminished compared to GFP transduced control cells. This implies an additional role for JAK3 and STAT6 in ITK-SYK Discussion and perspectives 93 driven lymphomagenesis, whereas it underlines the assumption that STAT5 is not the main target of Ruxolitinib mediated JAK/STAT inhibition and subsequent improval of the TCL phenotype. STAT3 phosphorylation by JAK1 341 and JAK3 342 has been implicated to occur in solid tumors and PTCLs respectively. Furthermore, abberations of both kinases have been reported to primarily occur in T-cell lymphomas, whereas myeloid neoplasms rather depend on over-activated JAK2 signaling. 271 Another study has demonstrated that JAK1 activation has a dominant role over JAK3 activation in cytokine signal transduction. The authors showed that a kinase deficient JAK3 mutant had a less pronounced effect on subsequent downstream signaling by JAK1/JAK3 bound cytokine receptor dimers than a kinase deficient JAK1 mutant. 343 Thus, ITK-SYK expression in T-cells might lead to an activation of JAK1 and JAK3 by heterodimerization of their bound cytokine receptors. Preliminary co-immunoprecipitation experiments supported this theory by suggesting a direct interaction of JAK3 with phosphorylated JAK1 upon ITK-SYK expression in a murine CD4 + T-cell line, whereas SYK WT expression did not result in pJAK1/JAK3 association (Supplementary Figure 9.2). The JAK kinases can then phosphorylate downstream STATs, most likely STAT3 and STAT6. Due to its dominancy over JAK3, JAK1 inhibition might be sufficient to inhibit this signaling cascade, resulting in abrogated transformation of the malignant T-cells. Stimulation of CD4 + T-cells with the stimulatory cytokine IL-6 normally results in the 262,266,270 development of T h17 cells via the JAK1/JAK2 STAT3 axis (Figure 2.4). Though IL-6 serum levels in the ITK-SYK mouse model were increased (Figure 6.7) and JAK1 and STAT3 were activated upon ITK-SYK expression in a murine CD4 + T-cell line (Figure 6.23), 344 levels of IL-17A, a hallmark cytokine of T h17 cells , were not elevated in the serum of ITK- SYK mice. STAT6 is known to be phosphorylated by JAK1 and JAK3 in CD4 + T-cells 261,262 262 driving T h2 differentiation upon IL-4 binding (Figure 2.4). Though JAK1, JAK3 and STAT6 were over-activated upon ITK-SYK expression in the D10.G4.1 in vitro system, only IL-5 levels were shown to be upregulated by ITK-SYK, whereas Th2 derived IL-13 could not be detected in the serum of ITK-SYK mice (Figure 6.7). Intriguingly, though normally induced by JAK1, inhibition of this pathway mediator could not block IL-5 production. IFNγ, a cytokine normally secreted by T h1-cells upon stimulation with IL-12 via the JAK2/TYK2 and STAT4 axis 262 , was increased in the ITK-SYK model, though in vitro data showed no activation of JAK2 and STAT4 upon ITK-SYK expression (Figure 6.23). Previously published data revealed that cultivated primary murine ITK-SYK expressing CD4 + T-cells indeed secreted IFNγ, but not IL-5.185 Furthermore, serum analysis of xenograft mice transplanted with a human AITL blood sample demonstrated that the IFNγ secretion in this setting was facilitated by the malignant T-cells (Figure 6.31). Taken together, this data suggests that ITK-SYK mediated CD4 + T-cell activation and differentiation with subsequent release of T-cell subtype Discussion and perspectives 94
specific cytokines does not follow the classical pathways of T h-cell differentiation but rather uses unknown routes via JAK1/JAK3 mediated activation of STAT3 and STAT6, ultimately resulting in the massive production and secretion of the pro-inflammatory cytokine IFNγ. Since the complex interplay between JAK kinases and STAT downstream mediators, especially in malignant cells, has not been completely understood, it appears reasonable that + malignant CD4 T-cells take different roads than normal T h-cells. In fact, the process in which ITK-SYK drives JAK/STAT activation and subsequent cellular responses is likely to be quite complex and further experiments have to be performed in vivo and in vitro to assess the underlying mechanism. Extensive in vitro analysis of cell lines as well as primary murine cells taken from ITK-SYK mice will help to understand how ITK-SYK expression leads to JAK1/JAK3 phosphorylation, subsequent STAT3/STAT6 activation and the release of IFNγ. Gene expression profiling by cDNA microarray technology is currently underway to determine the transcriptional status of TCR, JAKs, STATs and other pathway mediators such as cytokines to obtain a better picture of the underlying mechanism resulting in JAK/STAT activation upon ITK-SYK expression. It will also provide an idea of the cytokine spectrum released by the malignant CD4 + T-cells, thus giving further insight into the underlying specific
Th-subtype and its signaling cascades, resulting in the complex PTCL phenotype with inflammation and myeloid expansion. The thymi of ITK-SYK mice in this study were much smaller than those of GFP controls (not shown) and the CD4 + T-cell levels were strongly reduced in this organ (Figure 6.17) which stands in line with the results obtained by Pechloff et al.. 155 The group postulated that these findings in their model were caused by TCR activation upon the expression of ITK-SYK at the CD4 +CD8 + T-cell stage and the subsequent negative selection resulting in the apoptosis of over-active lymphocytes with reduced thymocyte and naïve peripheral T-cell counts. 155 In the present study, JAK1/2 co-inhibitor Ruxolitinib was able to restore thymus size (not shown) and T-cell populations in the thymus (Figure 6.17). Since ITK directly mediates TCR signaling and therefore ITK-SYK is believed to activate TCR signaling prior to JAK/STAT activation, Ruxolitinib would not be able to interfere with TCR activation and subsequent negative selection. This implies that there must be different ways by which Ruxolitinib normalized thymus size and T-cell levels. One possible mechanism could be that T-cells upon activation in the thymus via ITK-SYK rapidly migrate into the periphery in a JAK dependent manner, hence leading to diminished T-cell levels in the thymus. After Ruxolitinib administration, this enhanced migration would be impaired, thus retaining the T-cells in the thymus. This stands in line with the finding that Ruxolitinib impairs mobilization of malignant T-cells and their release into the PB in AITL xenograft mice (Figure 6.29) as well as previous observations that the migratory potential of naïve T-lymphocytes to peripheral lymphoid organs is strongly dependent on JAKs.345 Determining the migratory potential of Vehicle vs. Discussion and perspectives 95
Ruxolitinib treated ITK-SYK expressing T-cells in cell migration assays would help to elucidate whether this is in fact the mechanism behind the reduced thymus size and the decreased T-cells in this lymphoid organ.
7.3 Ruxolitinib as a possible treatment option in PTCLs with TCR over- activation In vitro assays in a murine CD4 + T-cell line revealed that ITK-SYK expression and none of the other tested SYK constructs, including a constitutively active SYK variant and a membrane-associated SYK protein, activated JAK1 in these cells (Figure 6.24). The facts that physiologically, ITK engages in transmitting TCR signals346 whereas SYK is normally not a major player in this pathway 204 , and that ITK-SYK mimicks constitutively activated TCR signaling causing primarily CD4 + TCLs 155,185 , raised the question whether the TK domain of SYK is redundant in the ITK-SYK fusion protein and the oncogenic potential is derived from the ITK part potentially via constitutively activating TCR signaling. This would fit in well with the recent discovery of the ITK-FER fusion in TCL. 27 Functional analysis of the resulting protein in mouse models is currently ongoing. In combination with investigations regarding other ITK fusions, e.g. ITK-ALK as well as the analysis of ITK-SYK variants harboring truncated versions of the N-terminal ITK part, this will help to illuminate the actual role of ITK in mediating ITK-SYK induced PTCL development. Due to the lack of ITK-SYK + PTCL-NOS patient material, this study assessed the effects of Ruxolitinib on a human AITL derived xenograft model. As ITK-SYK driven PTCL-NOS, AITL mostly presents with a CD4 phenotype 160 and excessive inflammation 64 and is normally not associated with ITK-SYK 25 , with only one case having been described to harbor this fusion.347 The xenograft mice showed massive human T-cell infiltration in the spleens as well as high relative and absolute counts of these cells in the PB (Figure 6.29, Figure 6.30). Unlike GvHD mouse models 337 , the engrafted human cells were nearly exclusively CD4 + and a larger fraction of them displayed a loss of the T-cell marker CD7 which is a characteristic feature of AITL cells.162,163 These observations suggest that the mice were indeed suffering from AITL and not from GvHD. Nevertheless, analysis of clonal TCR -rearrangement, as is frequently observed in AITL 348 , is currently ongoing in the xenograft mice in collaboration with the pathology department to confirm the presence of T-cell clones derived from the primary malignant clones found in the patient. Interestingly, Ruxolitinib impeded proliferation and mobilization of the malignant T-cells (Figure 6.29, Figure 6.30) and strongly reduced the inflammatory phenotype (Figure 6.27, Figure 6.28), though the engraftment of the malignant cells was not altered (Figure 6.30). These findings suggest that Ruxolitinib can also be used in TCLs that normally do not harbor the ITK-SYK fusion. ITK-SYK mimicks constitutive TCR signaling when expressed in murine T-cells. 155 AITLs, like the xenograft model used in this study, are also associated with an Discussion and perspectives 96 upregulation of the TCR pathway. 154,349 Further investigations should unveil whether constitutive activation of TCR signaling in general leads to JAK/STAT activation, thus linking PTCL development to this signaling cascade in more than one PTCL entity. The observations in the AITL xenograft model as well as the fact that other kinase fusions such as ALK fusions in ALCL and ITK-FER in PTCL-NOS also mimic constitutive TCR signaling and/or induce STAT3 phosphorylation 27,295–297 strongly support this theory. The relation of TCR signaling and JAK/STAT activation has been controversely discussed. Early investigations could not show a connection between TCR activation and subsequent JAK/STAT induction.350 More recent studies however demonstrated that the TCR complex can directly interact with kinases of the JAK family and hence induce their activation in a cytokine-independent manner. 351,352 Another study revealed a direct connection of TCR induction and subsequent JAK/STAT pathway activation 353 which might be driven by increased cytokine receptor transcription upon TCR activation as was shown for the IL-12 receptor by Rogge et al.. 354 Extensive in vitro pathway analysis will help to understand the underlying mechanism of ITK-SYK driven JAK phosphorylation and whether this is mediated by TCR activation. Recent preliminary data suggest that ITK-SYK does not directly bind to JAK1 or JAK3 kinases (Supplementary Figure 9.2, Supplementary Figure 9.3), thus suggesting an alternative mechanism to induce their activation apart from direct phosphorylation and supporting the theory that TCR signaling might mediate this effect. Furthermore, analysis in ITK-SYK, ITK-FER, NPM-ALK and other oncogene expressing mouse models and cell lines and their consecutive signaling cascades will help to understand whether TCR over-activation in general leads to JAK pathway activation by a common signaling mediator, thus rendering more TCL subtypes susceptible to JAK inhibitor treatment. Previous investigations in cell lines harboring ALK fusions demonstrated that STAT3 phosphorylation can be accompanied by JAK3 phosphorylation, but does not seem to be JAK dependent, since JAK inhibition does not reduce STAT phosphorylation. These results imply that, at least in PTCLs with ALK aberrations, JAK inhibition might not be sufficient to block TCL development. 295,296 However, the cell lines used were already derived from TCLs thus likely harbored further mutations potentially leading to STAT3 activation. To better understand the underlying mechanism, non-transformed CD4 + human or murine T-cell lines like the D10.G4.1 cell line should be transduced with NPM-ALK, ITK-FER and other recurring mutations and TCR activation as well as JAK/STAT signaling upon their expression should be assessed in this system. If, however, some oncogenes in fact mediate their downstream signals via direct phosphorylation of STAT proteins, as has been shown to occur in solid tumors355 and anti-viral immunity 356 , STAT inhibitors could be a useful option in order to be able to treat more PTCL forms than with JAK inhibitors alone. Discussion and perspectives 97
7.4 Effects of granulocyte-depletion and JAK inhibition on PTCL induced inflammation Many PTCLs are accompanied by massive inflammation and myelocytosis which has been shown to correlate with worse prognosis. 73–77,334 To understand how inflammation and granulocytosis contribute to the PTCL phenotype driven by ITK-SYK expression, antibody- mediated granulocyte depletion experiments were performed. Anti-Ly-6G antibody administration led to significantly decreased granulocyte levels in the PB (Figure 6.2). Their suppression, however, was not sufficient to overcome PTCL development in the presented mouse model. It delayed disease progression, had beneficial effects on the phenotypic score and significantly improved survival (Figure 6.2 and Figure 6.3), but did not alter the malignant T-cell infiltration of the spleen and the T-cell distribution within the thymus (Figure 6.3). In the ITK-SYK mouse model and the human AITL xenograft, not only increased granulocyte levels in PB and spleen (Figure 6.10, Figure 6.27, Figure 6.28) but also elevated monocyte levels were observed (Figure 6.11, Figure 6.27, Figure 6.28). Since the used anti-Ly-6G antibody only targeted granulocytes, leaving the monocyte and macrophage counts untouched (Figure 6.2)335 , these remaining myeloid inflammatory cells might have been able to partially rescue the inflammatory phenotype normally mediated by multiple myeloid cell types. Furthermore, injection of anti-Ly-6G antibody depletes the granulocytes only momentarily. After consumption of the antibody and binding and subsequent degradation of the neutrophil- antibody complexes, newly differentiated neutrophil granulocytes replace the depleted ones, resuming their function. Thus, antibody-mediated depletion of neutrophil granulocytes only imposes some beneficial effects on the inflammation associated with PTCL development in ITK-SYK mice, hence presenting only a symptomatic treatment option. Considering that myeloid expansion was independent of ITK-SYK expression in the used mouse model (Figure 6.1, Figure 6.10, Figure 6.11)186 and that ITK-SYK expression in a myeloid cell line did not induce JAK/STAT activation, as was shown by Sprissler et al. 186 , it can be assumed that signals from the malignant T-cells, e.g. released cytokines, led to a secondary myelocytosis. Interestingly, this increase in granulocyte and monocyte levels was not only limited to the mature cells, but could also be observed at early CMP and GMP stages (Figure 6.14) as well as in the hematopoetic stem cell compartment.186 Ruxolitinib treatment impaired granulocytic expansion in PB and spleen (Figure 6.10) and monocytic expansion in the spleen (Figure 6.11). JAK mutants have been shown to induce proliferation in early progenitors such as splenic CMPs and GMPs, suggesting an important role of JAK/STAT signaling not only in mediating proliferation of mature myeloid cells but already at early developmental stages. 357 Thus, it can be assumed that cytokine-mediated proliferation and activation at all differentiation stages was abolished by the inhibitory effects of JAK1 and JAK2 blockade on the granulocytes themselves as well as by impaired malignant T-cell Discussion and perspectives 98 function and subsequent stimulation of the myeloid compartment primarily upon JAK1 inhibition. In line with this, the present study demonstrates that JAK1/2 inhibition not only restored mature myeloid cell levels but also those of immature CMPs and GMPs (Figure 6.14). For cytokine-mediated differentiation and activation, granulocytes are dependent on JAK signaling.298,299,302,358 IFNγ which is strongly increased in the serum of ITK-SYK mice (Figure 6.7) as well as AITL xenograft mice (Figure 6.31) and has been shown to be secreted by the ITK-SYK expressing CD4 + T-cells 185 , is known to stimulate cells via JAK1/JAK2 and STAT1 signaling. 359–361 Moreover, it has been verified to mediate activation of myeloid cells 362–364 . Thus, treatment with Ruxolitinib completely abolishes IFNγ induced myeloid cell activation via JAK1 and JAK2, whereas Pacritinib only inhibits one JAK kinase involved in mediating IFNγ signaling. As mentioned in section 7.2, JAK1 inhibition is dominant over JAK3 inhibition in inducing cytokine responses. 343 It is possible that JAK2 inhibition in this PTCL model is also not sufficient to block IFNγ-mediated signaling. This is supported by a study recently published by Luo et al. in which the authors have shown that JAK2, in contrast to JAK1, is largely dispensable in mediating IFNγ effects and inducing STAT1 phosphorylation in multiple melanoma cell lines.365 Another finding supporting the theory that IFNγ induced STAT1 might mediate ITK-SYK effects in myeloid cells is that activation of JAK downstream target STAT3 was not altered in splenic granulocytes of ITK-SYK mice upon ITK-SYK expression (Figure 6.13). Besides that, though STAT5 activation was minimally enhanced in these cells, it could not be impaired by Ruxolitinib treatment. This also implies other STAT family members like STAT1 as the mediators of ITK-SYK driven effects in the myeloid cell compartment, since these are strongly ameliorated under Ruxolitinib therapy. Hence, assessment of the activation of STAT1 in myeloid cells derived from ITK-SYK mice as well as analysis of commercially available IFNγ-KO mice transplanted with ITK-SYK transduced BM cells should be performed to support the theory that myeloid activation and subsequent responses are achieved by IFNγ mediated signaling.
7.5 Cytokine signaling in PTCL Analysis of serum samples from ITK-SYK mice revealed strongly increased levels of the pro- inflammatory cytokine IFNγ and the T-cell stimulating cytokine IL-6 as well as the B-cell and eosinophile stimulatory cytokine IL-5. Other tested cytokines like the anti-inflammatory IL-10, the allergy-associated T h2 cytokine IL-13, the pro-inflammatory T h17 cytokine IL-17A and granulocyte-monocyte colony-stimulating factor were not elevated (Figure 6.7). IFNγ has previsouly been shown to be secreted by in vitro cultivated primary murine ITK-SYK expressing CD4 + T-cells. 185 To get a better idea about which of the elevated cytokines were produced by what cell type in vivo, the serum levels of human and murine IFNγ, IL-6 and IL-5 were assessed in the AITL xenograft setting. These mice showed nearly no engraftment of human myeloid cells (Supplementary Figure 9.1), thus, the strong increase in hIFNγ levels Discussion and perspectives 99 could be attributed to the massively expanding human malignant T-cells. The rise in IL-6 levels, however, could only be shown for the murine cytokine, thus implying IL-6 to be released as a response of the murine system to the primary malignant T-cells (Figure 6.31). Taken together, these findings indicate that IFNγ is secreted by the the malignant T-cells and in turn stimulates other cells to upregulate their IL-6 expression. This stands in line with the facts that IFNγ secretion by T-cells can be enhanced upon the expression of a member of the Tec-kinase family to which also ITK belongs and366 and that IFNγ has been shown to be secreted by CD4 + T-cells upon ITK-SYK expression. 185 Bach et al. have demonstrated that ITK-SYK expression in murine T-cells did not only lead to an increase of serum IFNγ levels, but also induced TNFα production 210 . The latter has been shown to be secreted by CD4 + T-cells and to engage in pro-inflammatory events e.g. in the development of GvHD. 367 Another study postulated that IFNγ together with TNFα can induce the release of IL-6 by monocytic cell lines. 362 Furthermore, IL-6 has been shown to be expressed and released by neutrophil granulocytes upon stimulation with IFNγ and other soluble factors 363,368,369 and to activate STAT3 and STAT5 in CD4 + T-cells. 370–372 Taken together, these data suggest a positive feedback loop in which IFNy secretion by the malignant T-cells together with increased TNFα induces myeloid cell activation and subsequent IL-6 production. The pro-inflammatory T-cell stimulating IL-6 can then bind to IL-6 receptors on the surface of benign and malignant CD4 + T-cells, thus stimulating them further and resulting in sustained inflammation. Treatment of ITK-SYK mice with IFNγ and/or IL-6 inhibitors should be performed to determine whether the TCL development may be impaired by blocking either cytokine, thus supporting the existence of the proposed feedback loop.
IFNγ is normally produced by T h1-cells upon JAK2/TYK2 and subsequent STAT4 activation. 262,266,270 However, neither JAK2 nor STAT4 was upregulated in an ITK-SYK expressing CD4 + murine T-cell line compared to GFP control cells (Figure 6.23). This indicates that the malignant T-cells drive IFNγ secretion by an unknown mechanism, presumably involving JAK1/JAK3 and STAT3 and/or STAT6 as has been discussed in section 7.2. The fact that IFNγ secretion was reduced upon Ruxolitinib treatment, but not by JAK2 inhibition alone (Figure 6.7), supports an involvement of JAK1 in mediating IFNγ release, especially since JAK2 does not seem to be activated by ITK-SYK (Figure 6.23). JAK1/2 co-inhibition by Ruxolitinib, but not JAK2 only inhibition by Pacritinib, was also shown to significantly reduce elevated IL-6 levels (Figure 6.7). These observations could be explained by lacking effects of JAK2 inibition on IFNγ signaling as was discussed in section 7.4. Though IL-5 levels were increased in the serum of ITK-SYK mice, in vitro cultivated ITK-SYK expressing CD4 + T-cells were not shown to secrete this cytokine. 185 Thus, IL-5 secretion is likely a secondary effect of ITK-SYK driven PTCL development. The fact that serum levels of Discussion and perspectives 100 this cytokine were not reduced upon Ruxolitinib treatment, though the PTCL phenotype was strongly improved, implies that IL-5 is not a major player in the development of the observed PTCL phenotype. Previous studies have shown that JAK/STAT mutations alone are not sufficient to drive malignant cell proliferation and that they rather augment cytokine receptor signals upon ligand binding and prolong pathway activation.282–284 It is not known whether ITK-SYK mediated STAT3 activation 210,297 is dependent on intact cytokine receptors and ligand binding. Either way, the increased cytokine levels probably additionally enhance JAK/STAT activation and thus reinforce the inflammatory feedback loop.
7.6 A model of ITK-SYK induced PTCL The data obtained in this study suggest a mechanism by which ITK-SYK expression can induce PTCL formation and at the same time renders it susceptible for treatment with JAK1/2 inhibitors, whereas JAK2 inhibiton only exerts very mild beneficial effects on PTCL development. Expression of ITK-SYK in CD4 + T-cells induces the activation of JAK1 and JAK3 phosphorylation. Whether this is due to direct phosphorylation by ITK-SYK or via constitutively activated TCR signaling remains to be investigated. However, recently obtained preliminary data suggest that ITK-SYK did neither directly phosphorylate JAK1 nor JAK3 (Supplementary Figure 9.3, Supplementary Figure 9.2), thus hinting at the involvement of other mediators such as the TCR signaling pathway in JAK activation. Upon activation and co-localization of JAK1 and JAK3 (Supplementary Figure 9.2) in our proposed model, they phosphorylate STAT3 and/or STAT6 which subsequently leads to transcription of target genes involved in activation, proliferation, mobilization and cytokine production. One of these secreted cytokines is IFNγ which consecutively binds to IFNγ receptors on myeloid cells such as granulocytes and monocytes. Once activated by the cytokine, the receptors forward the signal via the classical JAK1/JAK2 and STAT1 axis to induce myeloid recruitment to the peripheral organs to which the malignant T-cells have migrated as well as proliferation, activation and cytokine secretion. IL-6 which is then secreted by the myeloid cells can in turn bind to IL-6 receptors on the surface of malignant and normal CD4 + T-cells, thus further activating them mainly via JAK1 phosphorylation, since IL-6 is known to primarily transmit its signals via JAK1. 373–375 The resulting positive feedback loop could explain the massive inflammation observed in ITK-SYK driven murine PTCLs. The proposed model would also explain the profound effects of Ruxolitinib on disease development, whereas Pacritinib treatment only showed a very mild impact. Ruxolitinib is a tyrosine kinase inhibitor targeting JAK1 and JAK2 simultaneously. In the described model, ITK-SYK expression activates mainly JAK1 and JAK3. JAK1 phosphorylation has been shown to be dominant over JAK3 phosphorylation.343 Thus, inhibition of JAK1 presumably entirely abrogates the subsequent signals, resulting in STAT3 and STAT6 phosphorylation, Discussion and perspectives 101 and reduces IFNγ secretion. Additionally, Ruxolitinib can inhibit IFNγ responses of myeloid cells by inhibiting JAK1 and JAK2 simultaneously. This then eventully abrogates IL-6 secretion and subsequent afresh stimulation of the malignant and non-malignant T-cells. Ultimately, JAK1 inhibition also results in impaired transmission of IL-6 signals via JAK1 activation. 373–375
ITK-SYK expressing malignant T-cell myeloid cell
cytokine receptor IFNγ receptor
JAK1 JAK3 JAK1 JAK2 P P P P STAT3/6 ? P P P P STAT1 IL-6 IFNγ ITK- STAT1
SYK STAT3/6 P P P P
P P STAT3/6 ? STAT1 TCR activation recruitment activation proliferation STAT1
P STAT3/6 P migration proliferation cytokine secretion cytokine secretion TCR
mainly
pathway P P
STAT3/6 via mediators gene STAT1 gene JAK1 expression expression
IL-6 STAT1
P STAT3/6 P receptor
Ruxolitinib Pacritinib
Figure 7.1: A possible mechanism by which ITK-SYK may lead to PTCL development and makes it susceptible to Ruxolitinib treatment. ITK-SYK leads to an activation of JAK1 and JAK3 kinases and subsequent activation of STAT3 and/or STAT6, either by direct phosphorylation or via other mediators such as an activated TCR pathway. STAT3 and STAT6 then induce gene expression of various target genes, leading to cell activation, proliferation, migration into distant organs and cytokine secretion. One of the secreted cytokines is IFNγ which induces the IFNγ receptor on myeloid cells. This activates JAK1 and JAK2 to phosphorylate STAT1, thus inducing gene transcription ultimately resulting in their recruitment to distant organs as well as their activation and proliferation and cytokine secretion. IL-6 is one of those secreted cytokines which in turn can induce further T-cell activation, thus forming a positive feedback loop. Ruxolitinib can inhibit virtually all steps of this “vicious circle”, hence almost completely suppress PTCL development. Pacritinib can only partially inhibit JAK2 signaling of the IFNγ receptor, but has no effect on the malignant T-cells. P, phosphorylated tyrosine.
Hence, Ruxolitinib by its ability to inhibit JAK1 and JAK2 simultaneously shows profound effects on the ITK-SYK phenotype by disrupting the proposed positive feedback loop at multiple stages. The JAK2 inhibitor Pacritinib however can only target IFNγ induced myelocyte activation in this disease model. The fact that this has not proven effective was already discussed in section 7.4. This model clearly postulates substantial benefits of JAK1/2 co-inhibition by Ruxolitinib over JAK2 inhibition by Pacritinib in ITK-SYK driven PTCL treatment. Discussion and perspectives 102
Further investigations are urgently needed to assess whether ITK-SYK in fact activates the JAK/STAT pathway in the proposed manner by constitutively engaging in TCR signaling. These would disclose to which extent this model is also applicable to other TCL entities presenting with over-activated TCR signaling and whether myeloid expansion and inflammation in PTCLs with TCR over-activation could regularly be driven by this mechanism. Ultimately, they could help to uncover whether all these PTCL cases might be susceptible to treatment with the JAK1/2 co-inhibitor Ruxolitinib.
7.7 Future perspectives PTCLs carry a dismal prognosis and many patients suffering from these diseases present with a strong inflammatory phenotype. 8,17,71,76,78–81,334 The aim of this study was to find a therapeutic strategy which targets both, the malignant T-cells as well as the myeloid cells infiltrating peripheral organs and mediating this massive inflammation. It was shown that the simultaneous inhibition of the tyrosine kinases JAK1 and JAK2 with the FDA-appoved inhibitor Ruxolitinib imposed massive beneficial effects on the development of PTCLs in an ITK-SYK driven mouse model and in a patient derived AITL xenograft. These effects were primarily mediated by the compound targeting the primary malignant CD4 + T-cells by suppressing the activation of JAK/STAT signaling which is activated upon expression of ITK-SYK. However, it remains unclear whether Ruxolitinib impairs activation and proliferation or simply inhibits migration of these aberrantly activated T-cells. Future analyses should assess the potential of the malignant cells to proliferate (cell cycle analysis) and migrate (migration assays) upon Vehicle or Ruxolitinib treatment. Furthermore, the activation status of these cells should be assessed e.g. by analysis of the activation markers CD25 and forkhead box P3 (FOXP3) 376 in this setting. Additionally, apoptosis assays would reveal the effects of Ruxolitinib on the survival of the malignant cells, since it was shown previously that primary murine CD4 + T-cells expressing ITK-SYK exhibit impaired apoptosis compared to normal murine CD4 + T-cells when cultivated in vitro .185 Further co-IP experiments are necessary to confirm the postulated ITK-SYK induced interaction of activated JAK1 and JAK3 and subsequent direct phosphorylation of STAT3 and STAT6 to delineate which STAT factor plays the pivotal role in mediating ITK-SYK driven PTCL development. Most importantly, the activation status of the TCR signaling cascade upon expression of ITK-SYK needs to be assessed to determine whether JAK/STAT signaling is activated downstream of the TCR, thus rendering more PTCL subtypes with an over-activated TCR signal susceptible to Ruxolitinib treatment. Apart from in vitro studies, these assays inevitably have to be performed also in primary cells from the ITK-SYK mouse model to take into account the versatile impacts of the surrounding microenvironment which was shown here to play a major role in disease development. Discussion and perspectives 103
The strongly impaired disease development under Ruxolitinib compared to Pacritinib treatment indicates that JAK1 is the major driver of PTCL development in ITK-SYK mice. However, the reduced CD3 + cell infiltrates and the improved mouse survival upon JAK2 inhibition by Pacritinib (Figure 6.15, Figure 6.8) suggest that JAK2 at least partially affects disease progression in the ITK-SYK mouse model. STAT5 phosphorylation was increased in the primary malignant T-cells of ITK-SYK mice, though this could not be confirmed in in vitro experiments (Figure 6.23). The fact that both inhibitors abrogated this activation similarly implies that STAT5 (Figure 6.20) is not likely to be the primary target of Ruxolitinib in the malignant T-cells and the subsequent improvement of the PTCL phenotype. Assessing the role of elevated STAT5 activation in this mouse model, however, could help to elucidate the small beneficial effects of Pacritinib on the ITK-SYK phenotype and the extended overall survival. Pacritinib treatment was also able to slightly, though not significantly, reduce STAT3 phosphorylation in the malignant T-cells. Whether this occured via the inhibition of additional JAK2 initiated STAT3 phosphorylation or partial off-target inhibition of other JAK kinases like JAK1 remains to be investigated. Off target effects have been shown to occur upon high dose treatment with either inhibitor. 377,378 Hence, ITK-SYK expression in CD4 + T-cells of conditional JAK1 KO, JAK2 KO and JAK1/2 KO mice will help to unveil the direct effects of each of these kinases on PTCL development in ITK-SYK mice. Furthermore, PTCL mouse models induced by CD4 + T-cells exhibiting constitutive JAK1 activation could be helpful to understand whether the ITK-SYK phenotype is mediated by JAK1 upregulation alone. We and other groups have previously shown that ITK-SYK driven PTCL-NOS is susceptible to SYK inhibitor treatment. 155,184,185 However, only 17% of PTCL-NOS which represent 0.4% of all NHLs harbor this specific mutation. 4,8,25 Thus, the use of SYK inhibitors in treatment of TCLs would be rather limited. The development of other therapeutic agents is urgently needed to target a broader range of TCLs. TCR signaling, as is constitutively activated by ITK-SYK expression 155 , has been shown to be upregulated in many forms of TCL. The results obtained in this study indicate that ITK-SYK induced TCR activation might mediate constitutive JAK/STAT activation. Other TCL entities also show increased phosphorylation of JAK/STAT signaling components, even in the absence of activating JAK or STAT mutants. Hence, over-activation of TCR signaling might be a general mechanism to induce JAK/STAT activation in TCL. This implies JAK inhibitors as a possible treatment option in all patients with increased TCR and JAK/STAT pathway activation. Previous studies have already assessed the efficacy of JAK/STAT inhibitors in various forms of TCL. Crescenzo et al. have shown that Ruxolitinib is a potential agent in inhibiting JAK/STAT activation in human ALK --ALCL.274 A group from Spain has shown that Ruxolitinib inhibits proliferation of CTCL cell lines by impairing STAT1, STAT3 and STAT5 phosphorylation. 330 In the same year, Maude et al. published a study providing evidence for Ruxolitinib effects in early T-cell Discussion and perspectives 104 precursor acute lymphoblastic leukemia. The present study reveals benefits of using Ruxolitinib in the treatment of PTCL-NOS and AITL. In light of the poor prognosis and high relapse rates due to the lack of targeted therapies, this FDA-approved compound presents a promising approach for future PTCL treatment. References 105
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9 Appendix
9.1 Supplementary Figures
+ hCD45 cells Figure 9.1: hCD45 + cells in PB of AITL xenograft NOG mice are not of myeloid origin. PB cells of Veh treated PB cells isolated from human AITL xenograft NOG mice on d21 after tx. The number below the name of the desired gate (CD11b +) indicates the percentage of gated cells within hCD45 + cells (frequent of parent). Representative dotplot for 4 mice.
SS
hCD11b
The following figures represent results from preliminiary co-IP experiments. Due to emerging problems with the transduced D10.G4.1 cells after these assays, new D10.G4.1 cells had to be obtained and transduced, before repetitions could be performed. However, these experiments are currently ongoing.
A B Co -IP D10.G4.1 Co -IP D10.G4.1 JAK3 Input
SYK SYK
MW - MW - ve ve ï ï
[kDa] na SYK WT ITK [kDa] na SYK WT ITK 130 pJAK1 130 pJAK3
130 JAK1 130 tJAK3 70 ITK ß-Actin 55 40
Figure 9.2: JAK3 is directly associated with phosphorylated JAK1 but not with ITK in murine CD4 + T-cells expressing ITK-SYK. (A) Co-IP of murine CD4 + T-cell line D10.G4.1 after transduction with pMIG, pMIG- SYK WT or pMIG-ITK-SYK and sort for GFP with anti-JAK3 ab followed by SDS-PAGE and subsequent WB. Abs directed against pJAK1, JAK1 and ITK were used for detection. (B) WB of lysate used for co-IP with JAK3 antibody (input). Abs directed against phosphorylated JAK3, total JAK3 and total β-Actin were used for detection. These experiments were so far only performed once due to emerging problems with the transduced cell line. Repetitions with newly transduced cell lines are currently performed.
Appendix 124
A B Co -IP D10.G4.1 Co -IP D10.G4.1 ITK Input
SYK SYK
MW - MW - ve ve ï ï
[kDa] na SYK WT ITK [kDa] na SYK WT ITK 130 pJAK1 70 ITK
130 JAK1 40 ß-Actin
Figure 9.3: ITK is not directly associated with phosphorylated JAK1 in murine CD4+ T-cells expressing ITK-SYK. (A) Co-IP of murine CD4+ T-cell line D10.G4.1 after transduction with pMIG, pMIG-SYK WT or pMIG-ITK-SYK and sort for GFP with anti-ITK ab followed by SDS-PAGE and subsequent WB. Abs directed against pJAK1 and JAK1 were used for detection. (B) WB of lysate used for co-IP with anti-ITK ab (input). Abs against ITK and β-Actin were used for detection. The band on the ITK WB at 70 kDa represents WT ITK whereas the smaller band represents ITK-SYK. These experiments were so far only performed once due to emerging problems with the transduced cell line. Repetitions with newly transduced cell lines are currently performed. Appendix 125
9.2 Abbreviations / per (mg/ml = mg per ml) # number(s) % percent °C degrees Celcius ≥ equal or more than > more than ≤ equal or lesser than 5-FU 5-fluorouracil A alanine ab antibody ABL Abelson murine leukemia viral oncogene homologue 1 ADAP adhesion and degranulation promoting adaptor protein AF Alexa Fluor TM AITL angioimmunoblastic T-cell lymphoma ALCL anaplastic large cell lyphoma ALK anaplastic lymphoma kinase AML acute myeloid leukemia AP-1 activator-protein 1 APC allophycocyanine APC antigen presenting cell APS ammonium persulfate ASCT autologous stem cell transplantation ATCC American Type Culture Collection Balb Bagg Albino BCA bicinchoninic acid BCL-6/10 B-cell lymphoma 6/10 BCR B-cell receptor BCR Breakpoint cluster region protein bid bis in die (twice daily) BM bone marrow β-ME β-Mercaptoethanol BSA Albumin fraction V, bovine BV Brilliant Violet TM bw body weight Ca 2+ calcium
CaCl 2 calcium chloride CARMA1 CARD-containing MAGUK protein 1 CCR4 CC chemokine receptor 4 CD cluster of differentiation CD90 CD90.2 cDNA complementary DNA CDC42 cell division control protein 42 homologue CEMT Center for Experimental Models and Transgenic Services CHO(E)P cyclophosphamide, doxorubicin, vincristine, (etoposide,) prednisolone CLL Chronic lymphocytic leukemia CLP common lymphoid progenitor cm centimeter(s) CML Chronic myelogenous leukemia Appendix 126
CMP common myeloid progenitor
CO 2 carbon dioxide co-IP co-immunoprecipitation CRAC calcium release-activated calcium channel CSA catalyzed signal amplification CTCL cutaneous T-cell lymphoma C-terminal carboxy-terminal Ctrl control Cy cyanine CXCL13 C-X-C motif chemokine 13 d day D aspartic acid D diversity segment DAB 3, 3-diaminobenzidine DAG diacylglycerol dH 2O distilled water DLBCL diffuse large B-cell lymphoma DMEM Dulbecco’s Modified Eagle’s Medium DMSO dimethylsulfoxid DN double negative T-cells DNA deoxyribonucleic acid DNAse deoxyribonucleic acid nuclease DP double positive T-cells DPBS Dulbecco’s phosphate buffered saline DSMZ Deutsche Sammlung von Mikroorganismen und Zellkulturen EBV Epstein-Barr virus ECL enhanced chemiluminescence E. coli Escherichia coli EDTA ethylenediaminetetraacetic acid e.g. exempli gratia (for example) EGF epidermal growth factor EPO erythropoietin ER endoplasmic reticulum ERK extracellular signal-regulated kinase ES-FBS embryonic stem cell qualified fetal bovine serum ET essential thrombocythemia et al. et alia F phenylalanine FACS fluorescence-activated cell sorting (here used as: flow cytometry) FBS fetal bovine serum Fc fragment crystallizable region FDA US Food and Drug Administration FER Proto-oncogene tyrosine kinase FER FLT3 fms-like tyrosine kinase FOS Proto-oncogene C-Fos FOXP3 forkhead box P3 FS forward scatter FYN proto-oncogene tyrosine-protein kinase FYN g gram(s) G glycine Appendix 127
GAB2 GRB2-associated binder GADS GRB2-related adaptor protein 2 Gata-3 GATA-binding protein 3 G-CSF granulocyte colony-stimulating factor GFP green fluorescent protein GH growth hormone GM-CSF granulocyte-macrophage colony-stimulating factor GMP granulocyte-macrophage progenitor Gr-1 granulocyte differentiation antigen GRB2 growth factor receptor-bound protein 2 GTPase guanosine triphosphatase GvHD graft-versus-host disease Gy Gray h hour h human H histidine
H2O water
H2O2 hydrogen peroxide HBSS Hank’s balanced salt solution HCl hydrochloric acid HDAC histone deacetylase HDACi HDAC inhibitor(s) HSC hematopoietic stem cell HEK human embryonic kidney HEPES N2-hydroxyethyl-piperazine-N'-2-ethane sulfonic acid Hp1 Heterochromatin protein 1 HRP horseradish peroxidase I isoleucine IC50 half maximal inhibitory concentration ICOS inducible T-cell co-stimulator IFN interferon IgG immunoglobulin G IHC immunohistochemistry IL interleukin IL-7RA IL-7 receptor subunit alpha InsP3 inositol triphosphate intrac. intracellular ip intraperitoneal IP3R1 type I inositol 1,4,5-trisphosphate receptor IRES internal ribosomal entry site ITAM immunoreceptor tyrosine-based activation motifs ITD internal tandem duplications ITK IL-2 inducible T-Cell kinase iv intravenous IVC individually ventilated cage J joining segment JAK Janus kinase JNK Jun N-terminal kinase JUN JUN protein kb kilobase(s) Appendix 128
KCl potassium chloride kDa kilodalton(s) kg kilogram(s)
KH 2PO 4 monopotassium phosphate KO knockout l liter(s) L leucine LAT linker for activation of T-cells LCK lymphocyte-specific protein tyrosine kinase LDS lithium dodecyl sulfate Lin lineage determinated cells/ lineage determinated cell staining pre-mix LK Lin -cKit +Sca-1- cell population LKS Lin -cKit +Sca-1+ cell population Ly-6A/C/E/G lymphocyte antigen 6 locus A/C/E/G m murine M molar mA miliampere MALT1 mucosa-associated lymphoid tissue lymphoma translocation protein 1 MAPK mitogen activated protein kinase Manufact. manufacturer MDS myelodysplastic syndrome MEKK MAP/ERK kinase kinase MEP megakaryocyte-erythroid progenitor MF mycosis fungoides MFI mean fluorescence intensity mg milligram(s) µg microgram(s)
MgCl 2 magnesium chloride
MgSO 4 magnesium sulfate MHC major histocompatibility receptor min minute(s) MKK MAPK kinase ml milliliter(s) µl microliter(s) mM millimolar µm micrometer(s) µM micromolar MPL thrombopoietin receptor MPN myeloproliferative neoplasm MPP multipotent progenitor mRNA messenger ribonucleic acid MSCV murine stem cell virus myr myristoylated MW molecular weight n number of replicates/mice per group N asparagine NaCl sodium chloride
NaHCO 3 sodium bicarbonate
Na 2HPO 4 disodium phosphate NaOH sodium hydroxide Appendix 129
Na 3VO 4 sodium orthovanadate NFAT nuclear factor of activated T-cells NF-κB nuclear factor kappa-light-chain-enhancer of activated B-cells ng nanogram(s)
NH 4Cl ammonium chloride NHL non-Hodgkin’s lymphoma NK natural killer nM nanomolar nm nanometer(s) NOG NOD.Cg-Prkdc scid Il2rg tm1Sug /JicTac NOS not otherwise specified NPM nucleophosmin ns non-significant N-terminal amino-terminal o/n overnight p p-value P phosphotyrosine residue P proline p38 p38 mitogen-activated protein kinase PaB pacific blue Pac Pacritinib Pat patient sample PB peripheral blood PBMC peripheral blood mononuclear cell PBS phosphate buffered saline PBS-T phosphate buffered saline + Tween 20 PCM1 pericentriolar material 1 PD-1 programmed cell death protein 1 PDGF platelet-derived growth factor PE phycoerythrin PEG polyethylene glycol PEI polyethylenimine PerCP peridinin-chlorophyll protein PFS progression-free survival pH potential of hydrogen PH pleckstrin-homology PI3K phosphoinositide 3-kinase PIAS protein inhibitor of STAT PKCθ protein kinase Cθ PLCγ1 phospholipase Cγ1 PMF primary myelofibrosis pMHC peptide bound to MHC molecules pMI pMSCV-IRES pMIG pMSCV-IRES-GFP PRL prolacti ps phenotypic score P/S penicillin-streptomycin PtdIns(4,5)P2 phosphatidylinositol 4,5-bisphosphate PtdIns(2,4,5)P3 phosphatidylinositol 3,4,5-trisphosphate PTP protein tyrosine phosphatase Appendix 130
PV polycythemia vera PW pulse width pY (e.g. pY1008) phosphorylated Tyrosine (e.g. at position 1008) Q glutamine R arginine RAC RAS-related C3 botulinum toxin substrate RASGRP1 rat sarcoma guanyl-releasing protein 1 RB retinoblastoma tumor suppressor protein RBC red blood cell count rel. relative REL proto-oncogene c-REL retx retransplantation RHOA Ras homolog gene family member A RNA ribonucleic acid RNAse ribonucleid acid nuclease RORγt retinoic acid-related orphan receptor gamma transcription factor rpm rounds per minute RPMI Roswell Park Memorial Institute 1640 medium RT room temperature Ruxo Ruxolitinib S serine Sca-1 stem cell antigen 1 SCF stem cell factor SD standard deviation SDS sodium dodecyl sulfate SDS-PAGE sodium dodecyl sulfate polyacrylamide gel electrophoresis sec second(s) SEM standard error of the mean SH Src-homology SHP2 Src-homology region 2 domain-containing phosphatase 2 SLP76 SH2-domain-containing leukocyte protein of 76 kDa SOCS suppressor of cytokine signaling SOS1 son of sevenless homologue 1 SPF specific-pathogen-free SS Sézary syndrome SS side scatter STAT signal transducer and activator of transcription SUMO small-ubiquitin-related modifier SYK spleen tyrosine kinase TAD transactivation domain T-bet T-box transcription factor TBS tris buffered saline TBS-T tris buffered saline + Tween 20 TBS-Tr tris buffered saline + Triton X-100 (P)TCL (peripheral) T-cell lymphoma TCR T-cell receptor TEMED tetramethylethylenediamine TH tec-homology
Th T-helper cell TK tyrosine kinase (domain) Appendix 131
TNFα tumor necrosis factor α TPO thrombopoietin
Treg regulatory T-cell Tris tris (-hydroxymethyl)-aminomethane T-STIM T-Cell Culture Supplement with ConA tx transplantation TYK2 non-receptor tyrosine-protein kinase TYK2 U unit US United States of America V valine V variable segment V Volts VAV1 VAV guanine nucleotide exchange factor 1 Veh Vehicle vs versus v/v volume percent WB western blot WBC white blood cell count WHO World Health Organization WT wild-type w/v weight percent x x-fold x g acceleration of gravity Y tyrosine Y325H tyrosine residue at position 325 is replaced by histidine (example) ZAP70 Ζ-associated protein of 70kDa
Appendix 132
9.3 List of figures Figure 2.1: T-cell receptor signaling overview...... 8 Figure 2.2: Schematic view of the ITK-SYK kinase resulting from a fusion of the N-terminal part of ITK and the C-terminal part of SYK...... 11 Figure 2.3: Schematic overview of the canonical JAK/STAT signaling cascade...... 15 Figure 2.4: The role of JAK/STAT signaling in T-helper cell differentiation...... 18 Figure 5.1: FACS analysis of HEK293T cells after transfection with pMIG vector...... 36 Figure 5.2: FACS analysis of D10.G4.1 cell line after transduction with pMIG vector...... 37 Figure 5.3: FACS analysis of primary murine BM cells after transduction with pMIG vector..40 Figure 5.4: Gating strategy for alive, singlet and GFP + or GFP - cell populations...... 45 Figure 5.5: Gating strategy for detection of efficient neutrophil granulocyte, macrophage and monocyte depletion in PB...... 45 Figure 5.6: Gating strategy for analyzing lineage determination of PB cells...... 46 Figure 5.7: Gating strategy for analyzing lineage determination of spleen cells and for splenic granulocyte and monocyte staining with subsequent staining of phosphorylated intracellular antigens...... 47 Figure 5.8: Gating strategy for murine lineage determination of xenograft PB and spleen cells...... 48 Figure 5.9: Gating strategy for analyzing myeloid progenitor populations...... 49 Figure 5.10: Gating strategy for analyzing T-cells for extracellular only staining methods and for T-cell marker staining with subsequent staining of phosphorylated intracellular antigens...... 49 Figure 5.11: Gating strategy for human T-cell subpopulations of xenograft PB and spleen cells...... 50 Figure 6.1: ITK-SYK expression in primary bone marrow cells causes T-cell lymphoma in mice...... 53 Figure 6.2: Single injection of granulocyte depleting antibody in ITK-SYK mice improves phenotypic score...... 54 Figure 6.3: Repeated injection of granulocyte depleting antibody in ITK-SYK mice improves survival, but does not alter T-cell phenotype...... 55 Figure 6.4: Workflow of experimental procedure for Ruxolitinib and Pacritinib treatment of GFP vs ITK-SYK mice...... 57 Figure 6.5: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves external ITK-SYK TCL phenotype...... 57 Figure 6.6: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves body and lung weight of ITK-SYK mice...... 59 Appendix 133
Figure 6.7: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces elevated serum cytokine levels in ITK-SYK mice...... 60 Figure 6.8: Simultaneous JAK1/2 inhibition improves survival in ITK-SYK mice to a higher extent than JAK2 inhibition alone...... 61 Figure 6.9: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone decreases ITK-SYK expressing cell percentages in ITK-SYK mice...... 62 Figure 6.10: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone decreases elevated granulocyte counts in PB and spleens of ITK-SYK mice...... 63 Figure 6.11: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone decreases elevated monocyte counts in spleens of ITK-SYK mice...... 64 Figure 6.12: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces myeloid cell infiltration of peripheral organs in ITK-SYK mice...... 65 Figure 6.13: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces STAT3 and STAT5 phosphorylation in total spleen cells, but has no effect on splenic granulocytes of ITK-SYK mice...... 67 Figure 6.14: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces elevated GMP and CMP but not MEP levels in spleens of ITK-SYK mice...... 69 Figure 6.15: Simultaneous JAK1/2 inhibition improves T-cell infiltration of skin in ITK-SYK mice to a higher extent than JAK2 inhibition alone...... 70 Figure 6.16: Retransplantation of thymic and splenic CD4 + T-cells of ITK-SYK mice causes a similar phenotype in secondary recipients...... 72 Figure 6.17: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone normalizes malignant CD4 + T-cell levels in thymi of ITK-SYK mice...... 74 Figure 6.18: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone reduces activation of STAT3 and STAT5 in total GFP + thymus cells of ITK-SYK mice...... 74 Figure 6.19: Simultaneous JAK1/2 inhibition reduces activation of STAT3 in thymic T-cell subpopulations of ITK-SYK mice to a higher extent than JAK2 inhibition alone...... 75 Figure 6.20: Simultaneous JAK1/2 inhibition reduces activation of STAT5 in thymic T-cell subpopulations of ITK-SYK mice to a higher extent than JAK2 inhibition alone...... 78 Figure 6.21: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves B-cell phenotype in PB and spleen cells of ITK-SYK mice...... 78 Figure 6.22: Simultaneous JAK1/2 inhibition but not JAK2 inhibition alone improves T-cell levels in PB but not in spleens of ITK-SYK mice...... 79 Figure 6.23: ITK-SYK drives the activation of JAK1 but not JAK2 in a murine CD4 + T-cell line...... 81 Figure 6.24: ITK-SYK activation of JAK1 in a murine CD4 + T-cell line does neither depend on localization nor on kinase activation alone...... 82 Appendix 134
Figure 6.25: Workflow of experimental procedure for Ruxolitinib treatment of TCL xenograft mice...... 83 Figure 6.26: Ruxolitinib impairs weight loss and reduces spleen size, weight and cell counts of human xenograft lymphomas...... 84 Figure 6.27: Ruxolitinib inhibits inflammatory responses in the PB of human xenograft lymphomas...... 85 Figure 6.28: Ruxolitinib inhibits myeloid expansion and infiltration in spleens of human xenograft lymphomas...... 86 Figure 6.29: Ruxolitinib inhibits release of human T-cells into the blood stream of xenograft lymphoma mice...... 87 Figure 6.30: Ruxolitinib inhibits proliferation but not engraftment of human T-cells in spleens of xenograft lymphoma mice...... 88 Figure 6.31: Ruxolitinib impairs increased IFNγ release by human T-cells and subsequent IL- 6 release by murine cells in xenograft lymphoma mice...... 89 Figure 7.1: A possible mechanism by which ITK-SYK may lead to PTCL development and makes it susceptible to Ruxolitinib treatment...... 101 Figure 9.1: hCD45 + cells in PB of AITL xenograft NOG mice are not of myeloid origin...... 123 Figure 9.2: JAK3 is directly associated with phosphorylated JAK1 but not with ITK in murine CD4 + T-cells expressing ITK-SYK...... 123 Figure 9.3: ITK is not directly associated with phosphorylated JAK1 in murine CD4+ T-cells expressing ITK-SYK...... 124
Appendix 135
9.4 List of tables Table 2.1: Activation of JAKs and STATs in response to stimulation with different cytokines17 Table 2.2: JAK and STAT mutations in PTCL subtypes ...... 19 Table 5.1 Phenotypic score (ps) points for weight loss and skin lesions ...... 43 Table 5.2: Mixes for extracellular antigen staining for flow cytometric analysis ...... 44 Table 6.1: IC50 levels of Ruxolitinib and Pacritinib for JAK family kinases ...... 56 Table 6.2: Mean organ weights ± standard deviation of GFP and ITK-SYK mice after Veh vs Ruxo treatment ...... 59 Table 6.3: Mean organ weights ± standard deviation of GFP and ITK-SYK mice after Veh vs Pac treatment...... 59
Appendix 136
9.5 Publications Jägle, S., Rönsch, K., Timme, S., Andrlová, H., Bertrand, M., Jäger, M., Proske, A. , Schrempp, M., Yousaf, A., Michoel, T., Zeiser, R., Werner, M., Lassmann, S., Hecht, A., 2014. Silencing of the EPHB3 tumor-suppressor gene in human colorectal cancer through decommissioning of a transcriptional enhancer. Proc. Natl. Acad. Sci. U. S. A. 111, 4886– 4891. https://doi.org/10.1073/pnas.1314523111
Haug, S., Schnerch, D., Halbach, S., Mastroianni, J., Dumit, V.I., Follo, M., Hasenburg, A., Köhler, M., Dierbach, H., Herzog, S., Proske, A. , Werner, M., Dengjel, J., Brummer, T., Laßmann, S., Wäsch, R., Zeiser, R., 2015. Metadherin exon 11 skipping variant enhances metastatic spread of ovarian cancer. Int. J. Cancer 136, 2328–2340. https://doi.org/10.1002/ijc.29289
Dafflon, C., Craig, V.J., Méreau, H., Gräsel, J., Schacher Engstler, B., Hoffman, G., Nigsch, F., Gaulis, S., Barys, L., Ito, M., Aguadé-Gorgorió, J., Bornhauser, B., Bourquin, J.-P., Proske, A. , Stork-Fux, C., Murakami, M., Sellers, W.R., Hofmann, F., Schwaller, J., Tiedt, R., 2017. Complementary activities of DOT1L and Menin inhibitors in MLL-rearranged leukemia. Leukemia 31, 1269–1277. https://doi.org/10.1038/leu.2016.327
Metzger, E., Stepputtis, S.S., Strietz, J., Preca, B.-T., Urban, S., Willmann, D., Allen, A., Zenk, F., Iovino, N., Bronsert, P., Proske, A. , Follo, M., Boerries, M., Stickeler, E., Xu, J., Wallace, M.B., Stafford, J.A., Kanouni, T., Maurer, J., Schüle, R., 2017. KDM4 Inhibition Targets Breast Cancer Stem-like Cells. Cancer Res. 77, 5900–5912. https://doi.org/10.1158/0008-5472.CAN-17-1754