THE NATURAL HISTORY OF TRANSIENT ABNORMAL MYELOPOIESIS IN NEONATES AND CHILDREN WITH DOWN SYNDROME
By Neha Bhatnagar
A thesis submitted for the degree of Doctorate of Medicine April 2015
Centre for Haematology Imperial College London
1 ABSTRACT
Children with Down syndrome (DS) have a markedly increased risk of acute myeloid leukaemia (ML-DS) during the first 5 years of life compared to children without DS. Many children with ML-DS have a preceding history of a neonatal pre-leukaemic disorder known as Transient Abnormal Myelopoiesis (TAM). Both TAM and ML-DS harbour the same acquired N-terminal GATA1 mutation(s) indicating they are clonally-linked conditions. Currently, there is a lack of clear clinical, haematological and molecular diagnostic criteria for TAM. My project aimed to (i) precisely define TAM (ii) document the natural history of TAM and identify the population at risk of developing ML-DS and
(iii) characterise blast cells in TAM in order to establish whether particular blast cell sub-populations might be associated with a higher frequency of subsequent transformation to ML-DS and whether it is possible to distinguish between blast cells which do and do not carry GATA1 mutations.
To address these aims I analysed data from 382 DS neonates recruited to the Oxford Imperial Down Syndrome Cohort
Study (OIDSCS); a prospective, population-based study to systematically examine clinical findings, haematological indices, blood cell morphology and GATA1 mutation status in neonates with DS. Using standard methods (PCR of
GATA1 exons 2/3 followed by dHPLC and direct sequencing) GATA1 mutation(s) were detected in 45/382 neonates
(11.8%). Of these 35/45 neonates (77.8%) had clinical and/or haematological evidence of TAM (blasts >10%) and
10/45 (22.2%) were clinically and haematologically 'silent'. Neonates with clinically and haematologically silent TAM could not be distinguished from DS neonates where no GATA1 mutation(s) were detectable by standard methods.
Using next-generation-sequencing (NGS) an additional 27/337 (8.0%) DS neonates had one or more small mutant
GATA1 clones. These 27 neonates were clinically, haematologically and molecularly 'silent' and would be missed unless highly sensitive methodology is employed.
To investigate the natural history of the evolution of TAM and both types of silent TAM to ML-DS, I studied all of the DS children in the cohort who have progressed to ML-DS (n=5). Four of these children had overt TAM and one had clinically and haematologically silent TAM. Compared to DS children who did not progress to ML-DS, these 5 children were more likely to have persistent hepatomegaly, thrombocytopenia and additional cytogenetic abnormalities at time of disease progression.
2 I studied the immunophenotypic profile of blasts in TAM and was unable to identify a TAM-specific immunophenotypic population which DS neonates without GATA1 mutation(s) did not have. However, in neonates with GATA1 mutation(s) the CD45dimCD34+/-CD33+/-CD36+CD7+ blast sub-population was significantly expanded as compared to neonates without GATA1 mutation(s).
These studies describe for the first time the full range of clinical and haematological features associated with a mutant
GATA1 clone in DS neonates. As there were no reliable clinical, haematological or biological features (such as blast cell properties) which can identify neonates with GATA1 mutation, TAM is accurately defined as a neonate with DS and the presence of one or more GATA1 mutation(s) determined by a sensitive screening method such as NGS. This definition of TAM would identify all neonates at risk of transformation to ML-DS... Follow up of the whole cohort until the age of 5 years will be necessary to fully evaluate the significance of very small mutant GATA1 clones. A precise diagnosis of TAM may help plan treatment to better manage TAM and prevent ML-DS by eradicating mutant
GATA1 clones.
3 TABLE OF CONTENTS
ACKNOWLEDGMENTS...... 7 DECLARATION ...... 8 FIGURES ...... 9 TABLES ...... 12 ABBREVIATIONS ...... 14 CHAPTER 1 - Introduction ...... 17 1.1 Down syndrome ...... 18 1.1.1 Incidence and prevalence of DS ...... 18 1.1.2 Clinical features of DS ...... 21 1.1.3 Haematological abnormalities in DS ...... 21 1.2 Transient abnormal myelopoiesis (TAM) in DS ...... 24 1.2.1 Clinical features of TAM ...... 24 1.2.2 Haematological features of TAM ...... 26 1.2.3 Molecular pathogenesis of TAM ...... 27 1.2.4 Natural history of TAM ...... 33 1.2.5 Management of TAM ...... 34 1.3 Myeloid Leukaemia of Down syndrome (ML-DS) ...... 35 1.3.1 Clinical and haematological features of ML-DS ...... 35 1.3.2 Molecular pathogenesis of TAM evolution to ML-DS ...... 36 1.3.3 Management of ML-DS ...... 36 1.4 Acute lymphoblastic leukaemia (ALL) in DS ...... 37 1.5 Aims...... 39 1.5.1 To determine the clinical and haematological features of TAM in order to accurately define TAM: ...... 39 1.5.2 To determine the natural history of TAM evolution to ML-DS thereby describing the population at risk of leukaemia: ...... 39 1.5.3 To characterise blast cells in TAM: ...... 39 CHAPTER 2 - Methods ...... 40 2.1 Study population, ethics and consent ...... 41 2.2 Sample collection and processing...... 43 2.2.1 Samples ...... 43 2.2.2 Sample processing ...... 44 2.3 Flow cytometric analysis and sorting ...... 44 2.3.1 Surface antibody staining ...... 44 2.3.2 Flow cytometric analysis...... 45 2.3.3 Flow cytometric sorting ...... 45 2.3.4 Analysis of flow cytometric data ...... 45 2.4 Clonogenic assays ...... 45 2.4.1 Methocult medium and cytokines ...... 45 2.4.2 Plating, counting and colony identification ...... 46
4 2.4.3 Colony assays of specific TAM blast populations ...... 47 2.5 Cytospins...... 47 2.6 GATA1 gene mutation analysis ...... 47 2.7 Statistics ...... 48 CHAPTER 3 - The clinical and haematological features of TAM ...... 49 3.1 Background ...... 50 3.1.1 Clinical and haematological features of TAM based on retrospective studies ...... 50 3.1.2 Molecular features of TAM ...... 50 3.2 Aim ...... 50 3.3 Experimental approach ...... 51 3.3.1 Oxford Imperial Down Syndrome Cohort Study (OIDSCS) ...... 51 3.3.2 Definition of TAM ...... 51 3.3.3 Clinical and haematological data ...... 53 3.4 Clinical features in DS neonates with and without GATA1 mutation(s) ...... 54 3.4.1 Demographic details ...... 54 3.4.2 Pregnancy-related complications in neonates with and without GATA1 mutation(s) ...... 58 3.4.3 Clinical features of neonates with and without GATA1 mutation(s) ...... 60 3.4.4 Congenital anomalies in DS neonates with and without GATA1 mutation(s) ...... 67 3.4.5 Cytogenetic features of DS neonates with and without GATA1 mutation(s) ...... 69 3.5 Haematological features of DS neonates with GATA1 mutation(s) ...... 72 3.5.1 Haematological features at birth in DS neonates with and without GATA1 mutation(s) ...... 72 3.5.2 Haematological features during the first 5 years of life in DS infants with & without GATA1 mutation ..77 3.5.3 Peripheral blood blast count and GATA1 clone size in DS neonates with GATA1 mutation(s) ...... 84 3.5.4 Peripheral blood film morphological features in DS neonates with and without GATA1 mutation(s) ...... 89 3.6 The natural history of TAM during the first 5 years of life ...... 94 3.7 Summary and Discussion ...... 101 CHAPTER 4 - The natural history of TAM evolution to ML-DS ...... 104 4.1 TAM and ML-DS as a model of myeloid leukaemogenesis ...... 105 4.2 Aim ...... 105 4.3 Experimental approach ...... 106 4.4 Defining the natural history of TAM evolution to ML-DS ...... 106 4.4.1 Clinical features in neonates with TAM evolution to ML-DS at birth & time of progression to ML-DS 106 4.4.2 Haematological features of neonates with TAM evolution to ML-DS ...... 111 4.4.3 Molecular features of neonates with TAM evolution to ML-DS ...... 117 4.4.4 Cytogenetic features of neonates with TAM evolution to ML-DS ...... 119 4.5 Summary and Discussion ...... 120 CHAPTER 5 - Immunophenotypic and functional properties of blast cells in neonates with TAM ...... 122 5.1 Background ...... 123 5.2 Aim ...... 124 5.3 Experimental Approach ...... 125
5 5.4 Defining the TAM blast population(s) carrying the mutant GATA1 clone(s) ...... 126 5.5 Clonogenicity of TAM blast population(-s) carrying the mutant GATA1 clone(-s) ...... 133 5.6 The impact of GATA1 mutation(s) on haematopoietic stem cell differentiation ...... 141 5.7 Summary and Discussion ...... 143 CHAPTER 6 - Discussion ...... 146 6.1 Background ...... 147 6.2 The clinical and haematological features of TAM ...... 148 The natural history of TAM during the first five years of life ...... 150 6.4 Immunophenotypic and functional properties of blast cells in neonates with TAM ...... 151 6.5 Future work ...... 152 6.6 Conclusion ...... 154 REFERENCES ...... 155 Appendix 1: List of OIDSCS recruiting centres ...... 162 Appendix 2: OIDSCS Clinical Proforma ...... 163 Appendix 3: OIDSCS Full blood count review form ...... 165 Appendix 4: OIDSCS Morphology Review form ...... 166 Appendix 5: Peripheral blood blast cell frequency in healthy term neonates and healthy and sick pre-term neonates 167 Appendix 6: Flurochrome conjugated antibodies used in flow cytometry ...... 168
6 ACKNOWLEDGMENTS
I would like to express my utmost thanks to Professor Irene Roberts for her constant support, encouragement, patience and dedicated supervision during my fellowship. I am also grateful to Professor Tassos Karadimitris and Professor
Paresh Vyas for their helpful advice.
I am extremely thankful to Helen Richmond for her help and support during my fellowship.
Many thanks go to various members of the Roberts and Karadimitris laboratory for their practical support and advice, particularly Anindita Roy, Kelly Perkins, Natalina Elliott, Bethan Psaila, David O’Connor, Katerina Goudevenou,
Deena Iskander, Georg Bohn and Sarah Filippi.
My thanks go to Richard Szydlo at the Department of Medicine, Imperial College London for his help with medical statistics.
I am grateful to Professor Joan Morris, Anna Springett at the Queen Mary University of London and Lorna Crawford at the Southern General Hospital, Glasgow as well as Eddy Maher at Western General Hospital, Edinburgh for their help in retrieving karyotype data via the National Down syndrome cytogenetic register and regional centres.
I would like to thank Kay Kendall Leukaemia Fund and Leuka for providing generous funding for this project and my
Clinical Research Fellowship.
Lastly, I am extremely grateful to my family and friends who have consistently supported me and given me strength and reassurance during my fellowship.
7 DECLARATION
I have designed and performed all the experiments described in this thesis unless otherwise stated. Contributions from other people have been acknowledged in the appropriate sections. I analysed the data, produced graphs and figures and wrote the text with guidance from my supervisor, Professor Irene Roberts.
Prior to beginning my project, consent and sampling of participants to the Oxford Imperial Down Syndrome Cohort
Study has been approved by the Berkshire Research Ethics committee, reference 06MRE/12/10; NIHR Portfolio No.
6362.
The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-
Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it.
For any reuse or redistribution, researchers must make clear to others the licence terms of this work.
Neha Bhatnagar
April 2015
8 FIGURES
Figure 1.1 G-banded karyotype of a trisomy 21 female showing three copies of human chromosome
21
Figure 1.2 Prevalence of Down syndrome diagnoses and live births (per 1,000 live births) in England
and Wales from 1989- 2012
Figure 1.3 Diagram of GATA1 gene mutation showing N-terminal truncating mutation at exon 2
resulting in production of GATA1s isoform
Figure 1.4 Schematic representation of the GATA-1 protein
Figure 1.5 The Down Syndrome Critical Region on human chromosome 21
Figure 1.6 Schematic representation of GATA1 mutation(s) and clinical phenotype of TAM and ML-
DS
Figure 3.1 Frequency of GATA1 mutation(s) in DS neonates enrolled into the Oxford Imperial Down
Syndrome Cohort Study
Figure 3.2 Demographic features of DS neonates with and without GATA1 mutation(s)
Figure 3.3 Ethnicity of DS neonates with and without GATA1 mutation(s)
Figure 3.4 Intrauterine growth restriction at birth was higher in DS neonates with GATA1 mutation(s)
compared to those without GATA1 mutation(s)
Figure 3.5 Perinatal complications at birth in DS neonates with and without GATA1 mutation(s)
Figure 3.6 Clinical features at birth in DS neonates with and without GATA1 mutation(s)
Figure 3.7 Frequency of congenital anomalies in DS neonates with and without GATA1 mutation(s)
Figure 3.8 Karyotype at birth in DS neonates with and without GATA1 mutation(s)
Figure 3.9 Haematological features at birth in DS neonates with and without GATA1 mutation(s)
Figure 3.10 Full blood count at birth in DS neonates with and without GATA1 mutation(s)
Figure 3.11 Platelet counts during the first five years of life in DS infants with and without GATA1
mutation(s)
Figure 3.12 White blood cell counts during the first five years of life in DS infants with and without
GATA1 mutation(s)
Figure 3.13 Haemoglobin concentrations during the first five years of life in DS infants with and
without GATA1 mutation(s)
Figure 3.14 Peripheral blood blasts at birth in DS neonates with and without GATA1 mutation(s)
9 Figure 3.15 Mutant GATA1 clone size in DS neonates with GATA1 mutation(s)
Figure 3.16 Correlation of mutant GATA1 clone size with haematological variables in DS neonates
with GATA1 mutation(s)
Figure 3.17 Correlation of mutant GATA1 clone size with clinical variables in DS neonates with
GATA1 mutation(s)
Figure 3.18 Peripheral blood film morphological features at birth in DS neonates with GATA1
mutation(s)
Figure 3.19 Representative plots showing the natural history of neonates with GATA1 mutation(s)
during the first five years of life
Figure 3.20 Representative plots of haemoglobin, white blood cell count and platelets in two neonates
with TAM who received treatment with cytosine arabinoside and underwent remission
Figure 4.1 Demographic features at birth of neonates with GATA1 mutation(s) progressing to
Myeloid Leukaemia of Down Syndrome (ML-DS) compared to those without later ML-
DS
Figure 4.2 Clinical features of neonates with GATA1 mutation(s) at time of evolution to ML-DS
Figure 4.3 Haematological features of neonates with GATA1 mutation(s) progressing to ML-DS
Figure 5.1 Gating strategy for blast sub-populations based on cell surface antigen expression
Figure 5.2 Higher frequency of CD34+ cells within the ‘blast’ gate in DS neonates with GATA1
mutation(s)
Figure 5.3 Mutant GATA1 clones were present in all TAM blast sub-populations
Figure 5.4 Blasts were present in DS neonates without GATA1 mutation(s) and non-DS neonates
Figure 5.5 DS neonates with GATA1 mutation(s) had increased CD34+33+ cells and CD34-33+ cells
within the ‘blast’ gate
Figure 5.6 Higher frequency of CD36+CD7+ cells in all blast cell sub-populations in DS neonates
with GATA1 mutation(s)
Figure 5.7 TAM blast sub-populations in DS neonates with GATA1 mutation(s) were less clonogenic
than DS and non-DS neonates without GATA1 mutations
Figure 5.8 Representative colonies from DS neonates with and without GATA1 mutation(s) and non-
DS neonates
10 Figure 5.9 TAM blast sub-populations in DS neonates with GATA1 mutation(s) gave rise to BFU-E
and CFU-GM colonies
Figure 5.10 Gating strategy to identify mature cells from DS neonates with GATA1 mutation(s)
11 TABLES
Table 1.1 Down syndrome cases diagnosed and notified to the National Down Syndrome
Cytognetic Register (England and Wales, 2012)
Table 1.2 Frequency of medical problems common in Down syndrome (DS)
Table 1.3 The spectrum of haematological abnormalities in Down syndrome
Table 1.4 Clinical features of Transient abnormal myelopoiesis (TAM)
Table 1.5 Haematological features of Transient abnormal myelopoiesis (TAM)
Table 1.6 Haematological abnormalities in mouse models of Down syndrome
Table 2.1 Cytokine cocktail added to Methocult medium
Table 3.1 Demographic features of DS neonates with and without GATA1 mutation(s)
Table 3.2 Ethnicity of DS neonates with and without GATA1 mutation(s)
Table 3.3 Pregnancy related complications in DS neonates with and without GATA1 mutation(s)
Table 3.4 Perinatal complications at birth in DS neonates with and without GATA1 mutation(s)
Table 3.5 Clinical features at birth in DS neonates with and without GATA1 mutation(s)
Table 3.6 Frequency of congenital anomalies in DS neonates with and without GATA1
mutation(s)
Table 3.7 Karyotype at birth in DS neonates with and without GATA1 mutation(s)
Table 3.8 Haematological features at birth in DS neonates with and without GATA1 mutation(s)
Table 3.9 Haematological features at birth in DS neonates with TAM and Silent TAM
Table 3.10 Platelet counts during the first five years of life in DS infants with and without GATA1
mutation(s)
Table 3.11 White blood cell counts during the first five years of life in DS infants with and without
GATA1 mutation(s)
Table 3.12 Haemoglobin concentrations during the first five years of life in DS infants with and
without GATA1 mutation(s)
Table 3.13 Peripheral blood blasts at birth in DS neonates with and without GATA1 mutation(s)
Table 3.14 Mutant GATA1 clone size in DS neonates with GATA1 mutation(s)
Table 3.15 Peripheral blood film morphological features at birth in DS neonates with GATA1
mutation(s)
Table 3.16 Clinical features of four neonates with TAM who received treatment with cytosine
12 arabinoside
Table 3.17 The impact of treatment with cytosine arabinoside (Ara-C) on TAM progression to ML-
DS
Table 4.1 Demographic and clinical features of neonates with GATA1 mutation(s) progressing to
Myeloid Leukaemia of Down Syndrome (ML-DS) compared to those without later ML-
DS
Table 4.2 GATA1 mutation(s), additional genetic events and cytogenetics in neonates with TAM
evolution to ML-DS
Table 4.3 Frequency of mutated genes other than GATA1 in ML-DS samples in whole-exome
sequencing identified by Yoshida et al, 2013
Table 5.1 Frequency of CD34+ cells within the ‘blast’ gate in DS neonates with and without
GATA1 mutation(s) and non-DS neonates
Table 5.2 Frequency of CD36+CD7+ cells in all blast cell sub-populations in DS neonates with
and without GATA1 mutation(s) and non-DS neonates
Table 5.3 Clonogenicity of blast cell populations in DS neonates with and without GATA1
mutation(s) and non-DS neonates
Table 5.4 GATA1 mutation(s) were present in circulating normoblasts and granulocytes from
neonates with TAM
13 ABBREVIATIONS
ALL Acute lymphoblastic leukaemia
AM Anorectal malformation
AML Acute myeloid leukaemia
AMKL Acute megakaryoblastic leukaemia
Ara-C Cytosine arabinoside or cytarabine
ASD Atrial septal defect
AVSD Atrio-ventricular septal defect
BF Blood film
BFM Berlin-Frankfurt-Münster
BFU-E Burst forming unit-erythroid
BSA Bovine serum albumin c T21 Constitutional trisomy 21
CD Cluster differentiation (antigen)
CFU-GM Colony forming unit-granulocyte macrophage
CHD Congenital heart disease
CO2 Carbon dioxide
CoA Coarctation of Aorta
COG Children’s Oncology Group
DA Duodenal atresia
DAPI 4',6-Diamidino-2-phenylindole dHPLC Denaturing high pressure liquid chromatography
DIC Disseminated intravascular coagulopathy
DM Diabetes mellitus
DS Down syndrome
EDTA Ethylene diamine triacetic acid
EFS Event free survival
EPO Erythropoietin
EWOG-MDS European Working Group of Myelodysplastic syndromes in childhood
FACS Fluorescence activated cell sorting
14 FBC Full blood count
FBS Fetal bovine serum
FC Flow cytometry
FFP Fresh frozen plasma
FLT3 FMS-like tyrosine kinase 3
GI Gastrointestinal
GM Granulocyte monocyte
GMCSF Granulocyte macrophage colony-stimulating factor
HB Haemoglobin
HBP Haemoglobinopathy
HCT Haematocrit
HS Hepatosplenomegaly
IL Interleukin
IMDM Iscove’s modified Dulbecco’s medium
IUGR Intra-uterine growth retardation mAB Monoclonal antibody
MCH Mean corpuscular haemoglobin
MCV Mean corpuscular volume
MDS Myelodysplasia
MEP Megakaryocyte erythroid progenitor
MGG May Grünwald Giemsa stain
ML-DS Myeloid leukaemia of Down syndrome
MNC Mononuclear cells
NDSCR National Down syndrome cytogenetic register
NIHR National Institute for Health Research
NIV Non-invasive ventilation
NGS Next generation sequencing
O2 Oxygen
OA Oesophageal atresia
OIDSCS Oxford Imperial Down syndrome cohort study
15 OS Overall survival
PB Peripheral blood
PBS Phosphate-buffered saline
PCR Polymerase chain reaction
PET Pre-eclampsia
POG Paediatric Oncology Group
RBC Red blood cell
SCF Stem cell factor
SD Standard deviation
SEM Standard error of mean
Ss Sanger sequencing
ST Silent TAM
T21 Trisomy 21
TAM Transient abnormal meylopoiesis – synonomous with TMD
TMD Transient myeloproliferative disorder- – synonomous with TAM
ToF Tetralogy of Fallot
TPO Thrombopoietin
VSD Ventricular septal defect
WBC White blood cell
WHO World Health Organisation
16 CHAPTER 1 - Introduction
17 INTRODUCTION
1.1 Down syndrome
Down syndrome (DS) is a multi-system disorder resulting from the presence of trisomy of all or part of chromosome
21 (Lejuene et al., 1959). Children with DS have a markedly increased risk of developing acute leukaemia compared to individuals without DS (33-fold increase in the risk of B-cell acute lymphoblastic leukaemia and a 150-fold increase in the risk of acute myeloid leukaemia of DS, known as ML-DS) (Hasle et al2000; Whitlock et al., 2005).
ML-DS develops through a multi-step process, with a unique initial transient ‘leukaemic’ phase, known as transient abnormal myelopoiesis (TAM). The work in this thesis aimed to characterise the clinical and haematological features of TAM in order to provide an accurate definition for TAM and determine its natural history with evolution to ML-
DS.
1.1.1 Incidence and prevalence of DS
DS (MIM190685) is the commonest chromosomal abnormality in humans. Around 95% of all individuals with DS have whole-chromosome trisomies i.e. three independent copies of chromosome 21 (Figure 1.1) (Antonarakis, et al.,
2004) and the majority of these are caused by non-disjunction in meiosis, the extra copy of chromosome 21 usually deriving from the mother (Antonarakis, 1991). The remainder of cases (5%) is made up of trisomy 21 (T21) mosaics and unbalanced translocations (Antonarakis, et al., 2004).
In 2012, the National Down syndrome cytogenetic register reported 1,982 diagnoses of DS in the UK (Morris et al,
2014). Of these, 64% of diagnoses were made prenatally and 36% were post-natal diagnoses. Following a prenatal diagnosis of DS, ~80% of women underwent a termination of pregnancy. The estimated number of DS live births was
775, giving a live birth rate of 11 in 10,000 live births -Table 1.1. The prevalence of DS has increased since 1989, when the National Down syndrome cytogenetic register began data collection (Morris et al., 2014). This is primarily due to increase in maternal age and increase in number of DS pregnancies diagnosed prenatally, many of which are non-viable and therefore would have miscarried and remained undiagnosed in the absence of prenatal screening
(Figure 1.2). The percentage of prenatal diagnoses has increased from 30% in 1989 to 64% in 2012 due to improvements in first and second trimester prenatal screening for both younger and older women with combined serum tests and nuchal translucency scan and further testing with chorionic villus sampling and amniocentesis. The
18 number and prevalence of DS live births has not changed significantly over this time as over 90% of prenatal diagnosis result in termination of pregnancy (Figure 1.2).
Figure 1.1- G-banded karyotype of a trisomy 21 female showing three copies of human chromosome 21 [adapted from (Antonarakis , et al., 2004)]
Time of diagnosis Outcome Number of cases (%) Prenatal Miscarriage (20-23 weeks) 17 (0.9) Termination of pregnancy 983 (49.6) Stillbirth (≥24 weeks) 17 (0.9) Live birth 76 (3.8) Unknown outcome 166 (8.4) Total 1259 (63.5) Postnatal Miscarriage (20-23 weeks) 5 (0.3) Stillbirth (≥24 weeks) 29 (1.5) Live birth 689(34.8) Total 723 (36.5) Total 1982
Table 1.1 -Down syndrome cases diagnosed and notified to the National Down Syndrome Cytogenetic Register
(Morris et al, 2014)
19
Figure 1.2 -
Prevalence of Down syndrome diagnoses and live births (per 1,000 live births) in England and Wales from
1989- 2012.
The prevalence of DS has increased since 1989 till 2012 due to increased maternal age and increase in DS prenatal diagnosis. However, the prevalence of DS live births remained constant due to the majority of prenatal diagnoses resulting in termination of pregnancy (Morris et al., 2014).
20 1.1.2 Clinical features of DS
The clinical presentation of DS is variable. Despite this phenotypic heterogeneity, several of the characteristics are commonly shared and occur to some degree in most DS individuals such as typical facial appearance, hypotonia, small brachycephalic head, epicanthic folds, flat nasal bridge, upward-slanting palpebral fissures, small mouth and ears, excess skin at nape of neck, single transverse palmar crease, short fifth finger with clinodactyly, wide spacing, cognitive impairment and developmental delay (Roizen & Patterson, 2003; Bull, 2011). One or more additional anomalies are commonly present in 47% DS individuals (Rankin, et al., 2012)-Table 1.2. There is a significant risk of congenital heart disease (50%), visual problems (60%), hearing problems (75%), thyroid disease (4-18%), gastrointestinal disease (10-12%), cataracts (15), seizures (1-13%) and less commonly genitourinary problems (<1%), musculoskeletal and limb anomalies (<1%) (Bull, 2011; Rankinet al., 2012).
Condition Frequency (%) Neurological problems Seizures 1-13 Cataracts 15 Vision problems 60 Hearing problems 75 Congenital heart disease 40-50 Gastrointestinal disease 10-12 Respiratory problems 1 Genitourinary problems <1 Limb and musculoskeletal problems <1 Thyroid disease 4-18
Table 1.2 - Frequency of medical problems common in Down syndrome
1.1.3 Haematological abnormalities in DS
1.1.3.1 Haematological abnormalities in DS neonates
Newborns with DS are reported to have a number of benign and malignant haematological abnormalities as summarised in Table 1.3 (de Hingh et al., 2005; Henry, Walker et al, 2007; Miller & Cosgriff et al., 1983; Hord et al.,
1995; Kivivouri et al., 1996). However, these studies were retrospective and evaluated a limited data set for
21 haematological indices. Henry et al retrospectively documented the haematological abnormalities in 158 DS neonates within the first week of life (Henry et al, 2007). In this cohort 33% neonates had polycythaemia (Hb> 22 0g/L (normal range 100-215 g/L) or Hct >0.65 (normal range 0.3-0.65)), 66% neonates had thrombocytopenia (platelets <150 x109/L) and 80% of the neonates had neutrophilia (greater than upper limit of normal for post-natal age as defined by
Manroe et al., 1979). Thrombocytopenia (platelets <100 x109/L) was also reported by Hord et al in 28% of DS neonates within the first 48 hours of life (Hord et al, 1995). Kivivuori et al suggested that thrombocytopenia was short lived and resolved by the first few weeks of life (Kivivuori et al, 1996). Thereafter, they found that the platelet count increased from six weeks until the end of the first year of life when thrombocytosis, rather than thrombocytopenia was commonly seen (Kivivuori et al., 1996). However, this study was very small with few children having serial counts during the study and no other studies have reported thrombocytosis in children with DS. DS neonates have been reported to have a lower median B and T lymphocyte count at birth than non-DS neonates (p<0.01) (de Hingh, et al.,
2005).
Recent work from our laboratory has reported a much higher prevalence of haematological abnormalities than previously recognised in DS neonates (Roberts, et al., 2013). This was likely to result from the prospective nature of the study and also as it included all babies with DS born in the study hospitals. Previous studies have not included all
DS babies as a FBC is not routinely done on all newborn DS babies. These retrospective studies have only focussed on DS neonates who were hospitalised because of illness or other complications. In addition, the previous studies relied entirely on automated laboratory reports that were not validated against the clinical records. . By systematically analysing the results of full blood counts (FBC) and matching blood films, this study showed that, surprisingly, all 200
DS neonates in the study had haematological abnormalities compared to neonates without DS of the same gestational and post-natal age: 23% neonates had polycythaemia (Hct >0.65), 51% neonates had thrombocytopenia (platelets
<150 x109/L), 97.5% neonates had peripheral blood blasts (DS peripheral blood blast range 1-77%, with upper limit of blast cell frequency in normal term and preterm babies at 8%) and many had increased numbers of abnormal monocytes and/or basophils (Roberts et al., 2013).
In addition to these non-malignant haematological abnormalities, it has been clear for more than 25 years that neonates with DS may present with a unique, pre-leukaemic disorder usually known as TAM or Transient
Myeloproliferative Disorder (TMD) (Zipursky et al. 1987). The malignant nature of this disorder was recognised by
Alvin Zipursky, who provided the first clear description of the disorder, and in acknowledging the malignant nature of
22 the condition prefers to use the term Transient Leukaemia rather than TAM or TMD (Zipursky et al. 1992).
Retrospective population based studies suggest that ~10% of DS neonates have TAM which is discussed in detail in section 1.2 (Masseyet al., 2006; Klusmann et al., 2008; Zipursky, 2003)
DS neonates Polycythaemia Macrocytosis Thrombocytopenia Neutrophilia Lymphopenia Transient abnormal myelopoiesis (TAM) DS children Macrocytosis Polycythaemia Leukaemia (acute lymphoblastic leukaemia, acute megakaryoblastic leukaemia, myelodysplasia) DS adults Acute lymphoblastic leukaemia Myelodysplasia
Table 1.3 - The spectrum of haematological abnormalities in Down syndrome
1.1.3.2 Haematological abnormalities in children and adults with DS
There are limited reports on the haematology of children and adults with DS. Similar to DS neonates, children with
DS also have macrocytosis and higher haemoglobin concentrations compared to age and sex matched healthy non-DS children (Starc et al., 1992; Roizen & Amarose, 1993; David et al., 1996). Roizen and Amarose reported a mean MCV of 86.9 fl in children with DS compared to 80.6 fl in non-DS children (p<0.0001) (Roizen & Amarose, 1993). These studies found no significant difference in red cell folate, B12 and ferritin, suggesting that macrocytosis may be a result of trisomy 21. They hypothesised that the macrocytosis might be due to altered folate remethylation secondary to enhanced cystathionine beta synthase activity since this gene is situated on chromosome 21 (Taub et al., 1996; Taub, et al., 1999; Ge et al., 2005).
23 Like DS neonates, children with DS also had lower lymphocyte counts than non-DS children which is reflected in the absolute B and T-lymphocyte count (Douglas, 2005; de Hingh, 2005; Verstegen et al., 2010). Furthermore, in DS children the T-lymphocyte sub-population was reported to gradually reach those of normal children but the B- lymphocyte sub-population remains low throughout childhood in all ages with 88% of values below the 10th centile for normal and 61% of values below the 5th centile for normal (de Hinghet al., 2005). DS children are also known to have increased susceptibility to infection and autoimmune disorders (Gillespie et al., 2006; Karlsson et al, 1998; Garrison et al., 2005).
As mentioned above, the most serious haematological problem in children with DS is acute leukaemia. Population- based studies indicated that the overall risk of B-cell acute lymphoblastic leukaemia (ALL) in children with DS is around 33-fold greater than in children without DS and a 150-fold increased risk of acute myeloid leukaemia (ML-
DS), discussed in section 1.3 and 1.4 (Hasle et al., 2000;Whitlock et al., 2005;). The increased risk of ALL extends into adulthood.
There is very little information about the haematological abnormalities in adults with DS. A case series by McLean et al identified nine adults with haematological abnormalities: 7/9 adults (78%) had macrocytosis but two of these adults had vitamin B12 deficiency and another had hypothyroidism, 2/9 adults (22%) had neutropenia of which one had vitamin B12 deficiency and 1/9 adults (11%) had thrombocytopenia (McLean et al, 2009). In addition, 2/9 adults in this series, had a diagnosis of myelodysplasia (one whom later developed progressive bone marrow failure). The only large study, in 147 adults with DS (mean age 42 years) identified a higher mean cell volume (MCV 99+/-28 fl) compared to healthy controls and that almost 50% of the studied individuals had a MCV above the upper limit of the normal range (Prasher, 1994). Overall, these data suggest ongoing dysregulation in haematopoiesis in DS throughout life.
1.2 Transient abnormal myelopoiesis (TAM) in DS
1.2.1 Clinical features of TAM
TAM is a transient clonal myeloproliferative disorder characterised by circulating megakaryoblasts in the peripheral blood (Malinge et al, 2009; Zipursky, 2003). It is unique to neonates with DS or those with T21 mosaicism affecting haematopoietic cells (Hellebostad et al, 2005; Rainis et al., 2003; Cushing et al., 2006). Retrospective studies
24 suggested that TAM has a very variable clinical presentation. Approximately 6-7% of TAM were reported to present in fetal life as hydrops fetalis (Klusmannet al., 2008; Gamiset al., 2011). The outcome of TAM presenting in fetal life appeared to be poor compared with cases presenting after birth (Robertson et al, 2003; Healdet al., 2007).
Hepatosplenomegaly with hydrops in a fetus with T21 may be an indication of TAM, as 27% of such fetuses were found to have TAM in one case series (Smrcek et al., 2001). Retrospective studies suggested that the clinical presentation of TAM in the newborn may vary from asymptomatic alterations in the blood count (approximately 10-
25% neonates) to disseminated leukaemic infiltration manifesting as fulminant hepatic failure (up to 10% of neonates) at a median of 3-4 days after birth (Masseyet al., 2006; Klusmann et al., 2008; Muramatsuet al., 2008; Gamiset al.,
2011). Other clinical features most commonly included hepatomegaly, splenomegaly, jaundice and/or pericardial/pleural effusion while less common presentations include liver fibrosis, ascites and renal failure (Massey et al., 2006; Klusmannet al., 2008; Muramatsuet al., 2008)- Table 1.4. Of note, the diagnosis of TAM in these studies was uncertain and based on different criteria in each of the studies. Also, none of these studies had systematically studied either blood films or GATA1 mutation status therefore the true incidence of TAM is thus far unknown.
Common features of TAM % of cases Hepatomegaly 60 Splenomegaly 40 Jaundice 15 Pericardial/pleural effusion/Ascites 9-16 Disseminate intravascular coagulopathy 10 Uncommon features of TAM Hepatic fibrosis 7 Hydrops fetalis 7 Respiratory distress 10 Renal dysfunction 5 Rash 5
Table 1.4 - Clinical features of Transient abnormal myelopoiesis (TAM)
These data were summarised from the retrospective studies of Massey et al Klusmann et al , Muramatsu et al and
Gamis et al (Massey et al., 2006; Klusmann et al., 2008; Muramatsu et al., 2008; Gamis et al., 2011).
25 1.2.2 Haematological features of TAM
Previous retrospective studies reported the presence of several haematological abnormalities in TAM; leucocytosis and thrombocytopenia are fairly commonly reported occurring in ~20-30% and 40% of cases respectively (Klusmann et al., 2008; Gamis et al., 2011). These studies suggested that the haemoglobin may be normal, reduced or raised and that abnormal coagulation, including disseminated intravascular coagulation, may also occur- Table 1.5. A recent study by Maroz et al reported eosinophilia in some neonates with TAM (Maroz et al, 2014). Despite these interesting retrospective clinical studies the diagnostic criteria for TAM are very vague. The WHO classification defines TAM solely on the basis of ‘increased blast cells’ in a neonate with DS (Hasleet al., 2003), without specifying what constitutes ‘increased’ blast cells. These peripheral blood blasts are described to be characteristic of megakaryoblasts with cytoplasmic ‘blebbing’ (Hasle et al., 2003). Recent work in our laboratory showed that blast cells are commonly seen in neonates with DS, the vast majority of which are not given a clinical diagnosis of TAM (Roberts et al., 2013).
In addition, circulating immature blasts may also be present in the peripheral blood of healthy pre-term or sick term babies without DS, making the diagnosis of TAM potentially difficult.
Leucocytosis Thrombocytopenia Coagulopathy Haemoglobin concentration normal/raised/low Increased peripheral blood blasts Eosinophilia- in a small proportion of cases
Table 1.5 – Haematological features of Transient abnormal myelopoiesis (TAM)
These data are summarised from the retrospective studies of Klusmann et al and Gamis et al (Klusmann et al., 2008;
Gamis et al., 2011).
Previous studies have reported blasts in TAM to express variable combinations of cell surface antigens CD34, CD33,
CD7, CD36, CD38, CD117, CD56, CD71, CD42b, thrombopoietic receptor (Tpo-R, c-mpl) and interleukin 3 receptor-α (IL-3Rα) (Karandikar et al, 2001; Giordon et al., 2000; Langerbrake et al., 2005). However, these studies had a variable definition of TAM and it is clear that there was considerable heterogeneity both between studies and
26 between samples. Furthermore, these studies had evaluated the overall frequency of expression of these antigens rather
than co-expression of TAM blast cell surface antigens on sub-populations of blast cells.
1.2.3 Molecular pathogenesis of TAM
Several reports, including previous work in our laboratory, have shown that virtually all cases of TAM are uniquely
marked by the presence of an acquired mutation in exon 2 (97%) or the first part of exon 3 of the GATA1 gene on
chromosome X (Alfordet al., 2011; Wechsleret al., 2002; Xuet al., 2003; Rainis et al., 2003; Groetet al., 2003;
Hitzleret al., 2003; Ahmed, et al., 2004). In all cases, the mutation resulted in the production of an N-terminal
truncated GATA1 protein (GATA1s) -Figure 1.3 (Wechsler, Greene, McDevitt, et al., 2002). The functional
consequences of the loss of the N-terminal portion of the GATA1 protein have not yet been elucidated. However, it is
important to note that since the GATA1 gene is on the X chromosome, in cells which carry a GATA1 mutation, only
the mutant GATA1 gene will be expressed and only the mutant GATA1s protein will be produced. It is not clear
whether the lack of full length GATA1 protein is as important (or more important) than the presence of the GATA1s
protein in affected cells.
Wild type protein
Truncated protein
Figure 1.3 - Diagram of GATA1 gene mutation showing N-terminal truncating mutation at exon 2 resulting in
production of GATA1s isoform (Wechsler et al., 2002).
27 All neonates with TAM have GATA1 mutation(s) at birth indicating that these must have arisen during fetal life. It is not yet clear at what stage in fetal development GATA1 mutation(s) arise as the earliest point in gestation at which mutations have been identified is 21 weeks (Taub, et al., 2004). N-terminal truncating mutations in the GATA1 gene are also seen in all cases of ML-DS and can no longer be detected once ML-DS goes into complete remission (Ahmed et al., 2004; Wechsler et al., 2002; Yoshida et al., 2013), indicating that these mutations are essential for the development and maintenance of the leukaemia. Furthermore, paired ML-DS and TAM samples show the same
GATA1 mutation showing that they are clonally-linked conditions (Ahmed et al., 2004; Yoshida et al., 2013).
Interestingly, N-terminal truncating GATA1 mutations are not leukaemogenic in cells that are not trisomic for chromosome 21. Indeed, similar N-terminal GATA1 mutations, in the absence of T21, result in a different phenotype with anaemia and variable mild neutropenia and/or thrombocytopenia (Hollanda et al., 2006; Sankaran et al., 2012;
Klar et al., 2014). Also, GATA1 mutations are not detected in other DS and non-DS leukaemias (Wechsler et al.,
2002). These data indicate that there appears to be two distinct sets of genetic events in the pathogenesis of TAM: first, a fetal haematopoietic cell needs to be trisomic for chromosome 21 and secondly, these trisomic cells acquired one or more GATA1 mutation(s).
The detection of GATA1 mutation(s) thus requires reliable methods with adequate sensitivity. GATA1 mutation analysis performed by Sanger sequencing (Ss)/ DHPLC can identify a mutant close size of ~5%. Recent work in our laboratory has detected smaller-sized mutant GATA1 clones (~0.3%) by next-generation sequencing (Robertset al.,
2013). We have also showed that the type of mutation does not predict which neonates with TAM will later progress to ML-DS (Alford et al., 2011). Furthermore, we recently reported neonates with TAM may have more than one
GATA1 mutant clone (Roberts et al., 2013). At the same time, Yoshida et al found that ML-DS may develop from both major and minor GATA1 clones present (Yoshida et al, 2013).
Several lines of evidence indicate that GATA1 mutation(s) arise exclusively in fetal liver haematopoietic stem cells
(HSPC): (i) clinically overt TAM has involvement of the liver with progressive blast cell liver infiltration and relative sparing of bone marrow (BM) (Taub et al., 2004; Healdet al., 2007; Klusmannet al., 2008; Gamis et al., 2011), (ii) in the majority of cases TAM undergoes spontaneous remission of the mutant GATA1 clone within the first few months of birth as fetal liver haematopoiesis ceases and fully switches to BM (Klusmann et al., 2008; Massey et al., 2006;
28 Muramatsu et al., 2008; Zipursky, 2003), (iii) ML-DS develops within the first five years of life and AML in DS after five years of age is rarely due to GATA1 mutation(s) (Hasle et al., 2008).
The exact mechanism by which GATA1s contributes to the TAM phenotype is incompletely understood. It was initially suggested that the loss of the ‘transactivation’ domain reduces the activity of GATA1 in regulating the terminal differentiation of megakaryocytes leading to accumulation of poorly differentiated megakaryocytic progenitors (Wechsler et al., 2002). However, DNA binding and protein interaction at the zinc finger domain is preserved in GATA1s (Nichols et al., 2000)-Figure 1.4. This strongly suggests that trisomy 21 has a role in transforming activity of mutant GATA1.
Figure 1.4 – Schematic representation of the GATA-1 protein.
The known functional domains including the N-terminal activation domain, N-terminal zinc finger and C-terminal zinc finger are shown. Interaction partners (Friend of GATA-1 (Fog-1)) and known function of each domain is given.
Adapted from (Muntean, et al., 2006).
29 1.2.3.1 Perturbation of fetal haematopoiesis by T21
The fact that N-terminal mutations in the GATA1 gene are only leukaemogenic in trisomic cells indicates that the extra copy of chromosome 21 in some way increases the frequency of GATA1 mutations and/or that the additional chromosome 21 confers a selective growth advantage upon cells harboring GATA1 mutations. There is no evidence to date that trisomy 21 is associated with a mutator phenotype; the frequency of non-haematopoietic cancers is actually
50% lower than in individuals without DS (Hasle et al, 2000).
The possibility that the presence of trisomy 21 in some way perturbs haematopoiesis and produces a selective growth advantage was investigated by our laboratory several years ago. This showed that fetal liver haematopoiesis is abnormal in DS and that these changes precede the acquisition of GATA1 mutations (Tunstall-Pedoe et al., 2008).
Specifically, trisomy 21 causes expansion of the megakaryocyte-erythroid progenitor (MEP) and HSC compartment during the second trimester (Tunstall-Pedoe et al., 2008; Chouet al., 2008; Royet al., 2012). In addition, trisomy 21 causes marked functional changes in the HSC, MEP and lymphoid progenitor populations. Specifically clonogenicity of HSC and myeloid progenitors is increased, and the number of B-lymphoid progenitors is severely reduced.
Importantly, these abnormalities in second trimester fetal liver are evident at the HSC as well as progenitor level.
Fetal liver HSC in DS have increased megakaryocte-erythroid output and erythroid–megakaryocyte primed gene expression coupled with impaired B cell output (Roy et al., 2012). In addition, immunohistochemical studies of trisomy 21 fetal liver sections showed that megakaryocytes were both increased and morphologically abnormal (Royet al., 2012).
In order to understand more about the molecular mechanisms through which trisomy 21 perturbs fetal haematopoiesis,
MacLean et al and Chou et al studied trisomy 21 induced pluripotent stem cells (iPSC) and human trisomy 21 embryonic stem cells (ESC) (MacLean et al., 2012; Chou et al., 2012. In both cases iPSC and ES cell induced to undergo haematopoietic differentiation in vitro recapitulated many of the abnormalities seen in primary fetal haematopoietic stem and progenitor cells. It is thus clear that the presence of trisomy 21 alters the balance of HSC differentiation leading to an abnormal expansion of megakaryocyte-erythroid expansion of trisomy 21 fetal liver cells and enhanced proliferative properties in vitro. Following the acquisition of GATA1 mutation(s) there is a selective expansion of a leukaemic erythro-megakaryocytic blast cell population manifesting as TAM in late fetal/early neonatal life (Izraeli et al., 2008).
30 1.2.3.2 The role of fetal liver microenvironment in perturbation of haematopoiesis by T21
There is much evidence to suggest that fetal liver may provide a specialised microenvironment necessary for driving and maintaining abnormal haematopoiesis in DS (Klusmannet al., 2008; Gamis et al., 2011; Taub et al., 2004).
Previous work in our laboratory showed that although there were marked abnormalities in trisomy 21 fetal liver myeloid progenitors, there were no significant differences in fetal bone marrow myeloid progenitors between fetuses with and without trisomy 21 (Tunstall-Pedoe et al., 2008). In addition, there is some evidence that altered responsiveness to insulin-like growth factors (IGFs) might play a role in mediating abnormal fetal liver haematopoiesis: (i) in the mouse, fetal HSC expansion is supported by IGF2 produced by unique fetal liver stromal cells in contrast to adult bone marrow HSPC which depends on osteoblast-derived IGF1 (Zhang & Lodish, 2004;
Chou & Lodish, 2010; Garrett & Emerson, 2008), (ii) murine fetal, but not adult, megakaryocyte progenitors are dependent for their survival and proliferation on the IGF signalling pathway, as are ML-DS and TAM cells (Klusmann et al., 2010). Therefore it is possible that developmentally-regulated IGF signalling mediated by cells of the fetal liver microenvironment may contribute to the HSC megakaryocyte-erythroid bias and MEP expansion in DS fetal liver but exactly how trisomy 21 influences this is unclear.
1.2.3.3 Molecular basis for perturbation of haematopoiesis by trisomy 21
The molecular basis of perturbation of haematopoiesis in DS remains to be defined. It is plausible that trisomy 21 may exert its effects in several different ways. Human chromosome 21 (Has 21) has almost 340 short and long non-coding genes (Antonarakis et al., 2004). The functional correlation between levels of expression of Has 21 genes and phenotype is dependent on a number of factors such as tissue-specificity, cell lineage, developmental stage and inter- individual variability. The direct aetiological link between cT21 and leukaemia provides a strong rationale for investigating how an additional copy of Hsa21 specifically alters haematopoietic stem cell (HSPC) development.
Firstly, there may be a gene dosage effect of one or more chromosome 21 genes that directly influence HSPC behaviour or are important for HSPC proliferation, differentiation or survival such as DYRK1A, ERG and/or RUNX1
(Korbel et al., 2009). However, recently Letourneau et al showed that chromosome 21 (Hsa21) potentially alters the expression of multiple genes on any (or all) of the disomic chromosomes resulting in effects that are haematopoietic cell autonomous and/or mediated via other cell types, for example that may mediate the microenvironment
(Letourneau et al., 2014). Secondly, the presence of an additional chromosome may alter the epigenetic regulatory
31 mechanism such as that reported by Malinge et al in ML-DS where widespread gene methylation changes were observed resulting in altered gene expression (Malinge et al., 2013).
A number of mouse models have been developed to study the molecular mechanisms by which trisomy 21 causes the phenotypic abnormalities seen in human DS. The phenotypic characteristics of the most well-established mouse models of DS, and the extent to which they recapitulate the human phenotype, are summarised in Table 1.6. These include the only transchromosomic mouse model (Tc1) in which most of Hsa21 is present (O'Doherty et al., 2005).
Since no single mouse chromosome carries homologues of all of the genes on Hsa21, mouse models of human DS are produced through complex genomic rearrangements of Hsa21 synteneic regions (on Mmu10, Mmu16 and Mmu17)
(Liet al., 2007; Pereira et al., 2009; Yuet al., 2010; Raveau et al., 2012). The haematopoietic abnormalities have mainly been studied in the Ts65Dn mouse which showed abnormal developmental of multiple haematopoietic lineages, specifically profound thrombocytosis, macrocytic anaemia and bone marrow fibrosis (Kirsammer, et al.,
2008) and the Tc-1 mouse (Alford et al., 2010) which also showed macrocytic anaemia and thrombocytosis with splenic infiltration by abnormal megakaryocytes and erythroid cells. Unfortunately, none of these mouse models fully recapitulates the haematopoietic abnormalities seen in human DS. In particular, none of these mice developed leukaemia. However, more recently, these mouse models have been refined and by overexpressing genes associated with abnormal megakaryopiesis such as DYRK1A, MPL and ERG together with GATA1s Malinge et al and Birger et al showed a TMD-like syndrome with abnormal megakaryopoiesis and expansion of fetal mega-erythroid progenitors which then progressed to megakaryoblastic leukaemia (Malinge et al., 2012; Birger et al., 2013).
Although the majority of patients with DS have a complete additional Hsa21, a proportion of patients have partial
(segmental) trisomy of Has 21 and these patients have been pivotal in identifying limited subsets of genes on a region of Has 21 known as the ‘DS Critical Region’ (DSCR), estimated to cover a 4.3-5.4 Mb region of chromosome 21 on q22 potentially reducing the number of candidate genes involved in DS leukaemogenesis (Ronan et al., 2007; Delabar et al., 1993). However, the functional correlation between DSCR genes and clinical phenotype is uncertain (Lyle et al.,
2009)-Figure 1.5. Plausible candidate genes with roles in megakaryocyte-erythroid differentiation or leukaemogenesis include RUNX1, BACH1, ETS2 and ERG but none of these genes have been shown to definitively play a role in TMD and ML-DS (Rainis et al., 2003; Bourquin et al., 2006; Stankiewicz & Crispino, 2009). RUNX1 expression is lower in
ML-DS compared with non-DS AMKL (Bourquin, et al., 2006) and is not increased in in fetal liver CD34+ cells
(Royet al., 2012) or cT21-derived hESC or iPSC (Chou et al., 2012; Macleanet al., 2012) and similarly ERG has not
32 yet been found to be increased in human cT21 fetal haematopoietic or leukaemic cells (Bourquin et al., 2006; Royet al., 2012).
Ts65Dn (Kirsammer et al., 2008) Tc1 (O’Doherty et al., 2005; Alford et al., 2010) Macrocytic anaemia and reduced RBC Macrocytic anaemia Thrombocytosis Probable thrombocytosis Bone marrow fibrosis- megakaryocyte Extramedullary haematopoiesis – splenic infiltration with hyperplasia, granulocytic hyperplasia abnormal megakaryocytes and erythroid cells Extramedullary haematopoiesis No TAM/leukaemia No TAM/leukaemia Table 1.6- Haematological abnormalities in mouse models of Down syndrome
Figure 1.5 – The Down Syndrome Critical Region on human chromosome 21 Adapted from (Gurbuxani et al,
2004)
1.2.4 Natural history of TAM
To date there have been no prospective population based studies of TAM and therefore the exact frequency of TAM and its evolution to ML-DS is unknown. Retrospective studies suggested that most neonates with TAM (>80%)
33 undergo spontaneous resolution of both clinical and laboratory abnormalities within 3-6 months after birth with a five year overall survival of ~80% and event free survival of ~60% (Massey et al., 2006; Klusmannet al., 2008; Gamiset al., 2011). Complete remission is often characterised first by normalisation of blood counts and disappearance of peripheral blasts followed by resolution of clinical symptoms such as hepatomegaly. The overall mortality is reported to be ~20%, however, only half of the deaths are directly attributable to TAM usually due to hepatic failure secondary to fibrosis and blast cell infiltration (Masseyet al., 2006; Klusmann et al., 2008; Gamis et al., 2011).
In these clinical studies, ML-DS was reported to develop during the first 5 years of life in an estimated ~16-30% of neonates with TAM (Massey et al., 2006; Klusmannet al., 2008; Muramatsu et al., 2008; Zipursky, 2003). In some cases there was overt progression/evolution of TAM to ML-DS with persistent abnormal haematology and an indolent myelodysplastic syndrome; in other cases there was a variable apparent remission before development of ML-DS
(Klusmannet al., 2008; Masseyet al., 2006; Gamis et al., 2011; Zipursky, 2003)-Figure 1.6.
Figure 1.6 - Schematic representation of GATA1 mutation(s) and clinical phenotype of TAM and ML-DS
1.2.5 Management of TAM
Most neonates with TAM do not need treatment, however those with progressive life-threatening symptoms such as hepatic, renal and/or cardiac failure may benefit from one or more short courses of low-dose cytosine arabinoside. The
34 Pediatric/Children’s Oncology Group (POG/COG) in the USA (Massey et al., 2006) and the iBFM group in Germany
(Klusmann et al., 2008) have developed treatment guidelines for TAM, however, chemotherapy is usually given at the physician’s discretion with considerable variation in treatment policies between different centres. As there are no clear diagnostic criteria for TAM, it is difficult to identify which infants will benefit from treatment and what treatment is most effective. Moreover, no studies thus far, have demonstrated a significant impact of treatment of TAM on the likelihood of disease progression to ML-DS (Klusmannet al., 2008; Gamiset al., 2011).
1.3 Myeloid Leukaemia of Down syndrome (ML-DS)
1.3.1 Clinical and haematological features of ML-DS
ML-DS is classified as a specific sub-type of AML in the World Health Organisation (WHO) classification (Hasle et al., 2003) and has several distinct features. First, ML-DS occurs only in the first 5 years of life with a median age at presentation of 1-1.8 years (Creutzig et al., 2005; Hasle et al., 2008) and is unique to children with DS. Second, most cases of ML-DS have a clinical history consistent with preceding TAM in the neonatal period and for those that have no such history the most likely reason is the absence of appropriate diagnostic tests at birth (Robertset al., 2013).
Third, blasts in ML-DS are megakaryoblastic and most patients have a low presenting white blood cell count with no meningeal involvement (Creutziget al., 2005; Hasle et al., 2008). In contrast, in older DS children, AML is much less common and rarely megakaryoblastic (Hasle, et al., 2008). Previous studies report that there is often an indolent pre- phase characterised by myelodysplasia and bone marrow fibrosis (Creutzig,et al., 2005; Ross et al., 2005; Rao et al.,
2006; Webb et al,, 2007; Gamis, 2005).
Blasts in ML-DS are reported to be similar to blasts in TAM with respect to morphology, immunophenotype and cytochemical properties (Massey et al., 2006; Creutzig et al., 1996; Lange et al., 1998; Langerbrake et al., 2005).
Previous studies showed that ML-DS blasts co-express stem/progenitor cell markers (CD34, CD33, CD117), myeloid
(CD33), megakaryocytic (CD42b and CD41) and erythroid markers (CD36 and Glycophorin A) as well as the T cell marker, CD7 (Karandikar et al., 2001; Yumura-Yagi, Hara, Tawa, & Kawa-Ha, 1994; Langerbrake et al., 2005).
ML-DS also has a distinct cytogenetic profile compared to sporadic AML in that the favourable cytogenetic changes such as t(8;21), t(15;17), t(9;11) and inv(16), nor the acute megakaryoblastic leukaemia-associated translocations
35 t(1;22) and t(1;3)) occur in ML-DS (Forestier et al.,2008). Instead, the most frequently occurring cytogenetic abnormalities in ML-DS are reported to be trisomy 8 and/or an extra chromosome 21 (in addition to the additional copy of trisomy 21), which each occur in approximately 10–15% of cases (Forestier et al., 2008). Also, monosomy 7 and –5/5q- are found in a similar proportion of cases (Forestier et al., 2008).
1.3.2 Molecular pathogenesis of TAM evolution to ML-DS
GATA1 mutations are necessary for the initiation of clonal proliferation in TMD but are insufficient to cause ML-DS and additional mutations are needed to transform TMD blast cells to ML-DS. Additional cytogenetic events as well as mutations in several genes have been identified in a small number of cases including JAK3, JAK2, TP53, Flt3 (Rainis et al., 2003; Kiyoi, et al., 2007; Klusmann et al., 2007; Satoet al., 2008; Malinge et al,, 2009). Recent studies by
Yoshida et al and Nikolaev et al have revealed a high frequency of mutations in genes of the cohesin complex, in
CCCTC-binding factor (CTCF), epigenetic regulators (such as EZH2, KANSL1, MLL) and common signaling pathways (such as RAS, JAK-STAT and thrombopoietin receptor MPL) by exome sequencing (Yoshida et al., 2013;
Nikolaev et al., 2013). The normal function of these proteins is not yet fully characterised but they are known to play a role in the control of transcription activation/repression and/or to enhance cell growth and proliferation. It is unclear why these mutations are especially common in ML-DS but their close association with trisomy 21 indicates that trisomy 21-related changes in gene/protein expression and/or epigenetic regulation are likely to underpin this relationship in some way.
1.3.3 Management of ML-DS
Children with ML-DS have better outcomes when compared with children with sporadic AML with long-term survival of 74-91% (Nordic group 10-year OS 74%, n = 61; the Children’s Cancer Group (CCG), the CCG 2891 trial,
5-year OS 79%, n = 161; AML- BFM SG (Berlin-Frankfurt-Muenster
Study Group), 3-year OS 91%, n = 67 and the Medical Research Council (MRC) 5-year OS, 75%, n = 36)
(Ravindranath, 2003; Creutzig et al., 2005; Zeller et al., 2005; Gamis et al., 2011; Raoet al., 2006; Taub et al., 1997;
Zwaan, 2002). This has been attributed, at least in part, to hypersensitivity of ML-DS blasts to cytarabine due to overexpression of cystathionine-beta-synthase on chromosome 21 (Taub et al., 1996; Taub et al., 1999; Ge et al.,
36 2005). This drug sensitivity is suggested to be cell-lineage specific rather than simply a gene-dosage effect of chromosome 21, as the same advantage is not seen DS-ALL cells (Zwaan et al. 2002; Frost et al., 2000).
Children with ML-DS also have a significantly lower relapse rate than non-DS AML (Raoet al., 2006). Treatment failure in DS children was mostly due to chemotherapy-related toxicity (particularly related to anthracylines) and there were more induction deaths in ML-DS than non-DS AML (Raoet al., 2006). For this reason, future studies need to investigate the efficacy of reduced intensity chemotherapy treatment protocol while maintaining low rates for resistant and relapsed disease. There is no role for either autologous or allogeneic stem cell transplant (SCT) in first line therapy for ML-DS due to efficacy of chemotherapy and the increased toxicity associated with SCT (Rubin et al.,
1996; Lange et al., 1998).
1.4 Acute lymphoblastic leukaemia (ALL) in DS
Children with DS have a 33 fold increased risk of acute B-cell lymphoblastic leukaemia (B-ALL) as compared to children without DS (Hasle et al., 2000; Zipursky, 2000). This increased risk is limited to the first three decades (Hasle et al, 2000). DS-ALL also has unique clinical and haematological features contrasting with non-DS ALL.
In contrast to ML-DS, most children with DS-ALL present after the age of one year (Whitlocket al., 2005;
Dordelmann et al., 1998) with a median age of 4.5 years (range 1-23 years) (Patrick et al., 2014). Interestingly, almost all cases of DS-ALL are exclusively B-cell precursor ALL (Whitlocket al., 2005; Patricket al., 2014). T-cell ALL are very rare in DS patients but occur at higher incidence in non-DS ALL (Maloney, 2011). Recently, Buitenkamp et al
(2014) have reported 5 cases of T-ALL amongst a large series of 708 DS-ALL patients (0.7%) compared to 10-15% in non-DS ALL. Outcomes of DS-ALL children on the UKALL 2003 trial showed no significant differences by age, white cell count, National Cancer Institute (NCI) risk status or minimal residual disease (MRD) response in children with DS-ALL as compared to those without DS (Patrick et al., 2014). DS-ALL patients had worst event free survival
(EFS) (65.6% versus 87.7%, p<0.00005) and an inferior overall survival (OS) (70% versus 92.2%, p<0.0005) as compared to non-DS ALL patients (Patricket al., 2014) at a median follow up of 4.8 years, due to increased treatment related mortality and intrinsic resistance to therapy. Similar results have been reported by the Ponte di Legno study group with a EFS of 64% vs 81% at 8 years and an OS of 74% vs 89% for DS-ALL and non-DS ALL respectively
(Buitenkamp et al., 2014).
37
DS-ALL has a distinct frequency of genetic changes as compared to non-DS ALL. The common abnormalities in childhood B-ALL such as hyperdiploidy and ETV6-RUNX1are less frequent in DS-ALL occurring in 5% and 2.5%
DS-ALL patients respectively compared to 24.6% and 24% non-DS ALL patients (Whitlock et al. 2005; Maloney et al. 2010; Patrick et al. 2014; Buitenkamp et al. 2014; Forestier et al. 2008). In addition, cytogenetic abnormalities associated with a poor prognosis, such as MLL translocations and BCR:Abl fusion are rare in DS-ALL occurring in
<1% DS-ALL patients as compared to 1.2% and 2.4% non-DS ALL patients respectively (Buitenkamp et al. 2014;
Forestier et al. 2008). CRLF2 mutations which is often associated with JAK-STAT mutations occur more frequently in
DS-ALL patients than non-DS ALL patients at a frequency of up to 60% in DS-ALL patients compared to 5% in non-
DS ALL patients (Patrick et al., 2014; Buitenkamp et al., 2014; Hertzberg et al., 2010; Mullighan et al., 2010). IKZF1 deletions were detected in approximately 25-35% DS-ALL patients and associated with poor outcome (Patrick et al.,
2014; Buitenkampet al., 2014). GATA1 mutation(s) are not found in DS-ALL (Hellebostadet al., 2005).
Together these data suggest that there are intrinsic differences in the leukaemic cells and leukaemogenesis in DS-ALL compared to non-DS ALL and ML-DS.
38 1.5 Aims
1.5.1 To determine the clinical and haematological features of TAM in order to accurately define TAM:
(i) By performing a detailed analysis of the clinical findings, haematological indices, blood cell morphology for all DS neonates enrolled into the Oxford Imperial Down Syndrome Cohort Study (OIDSCS), a prospective population-based study and
(ii) By characterising GATA1 mutation status for all OIDSCS neonates and defining TAM according to whether or not their haematopoietic cells harboured an acquired GATA1 mutation(s).
1.5.2 To determine the natural history of TAM evolution to ML-DS thereby describing the population at risk
of leukaemia:
(i) By comprehensively analysing all DS infants in the OIDSCS cohort who progressed to ML-DS during the first five years of life by integrating the clinical, serial haematological, molecular and cytogenetic data of these neonates.
1.5.3 To characterise blast cells in TAM:
(i) By studying the immunophenotypic properties of blast cells in TAM and
(ii) By describing the functional properties of blast cells in TAM by a methylcellulose culture assay, in order to establish whether particular blast cell sub-populations might be associated with a higher frequency of subsequent transformation to ML-DS and whether it may be possible to distinguish between blast cells which do and do not carry
GATA1 mutations.
39 CHAPTER 2 - Methods
40 METHODS
2.1 Study population, ethics and consent
Neonates with a clinical diagnosis of Down syndrome (DS) confirmed by karyotyping prospectively enrolled from 18
UK hospitals to the Oxford Imperial Down Syndrome Cohort Study (OIDSCS) from October 2006 (Appendix 1). The original target recruitment was 400 neonates but a Substantial Amendment to extend this target to include a larger number of neonates with GATA1 mutation(s) is currently in preparation. The study had a five year follow-up to cover the period during which children with DS are at risk from ML-DS. The study was based at the University of Oxford and the Centre for Haematology, Imperial College London and had been approved by the Berkshire Research Ethics committee, reference 06MRE/12/10; NIHR Portfolio No. 6362.
Between October 2006 and June 2014, 382 DS neonates were recruited. During the period of my MD, August 2012 -
August 2014, I had estimated that I recruited approximately 50 neonates, however after close review of the consent forms; I independently recruited 20 neonates from nine hospitals within the London region. In addition, I contributed to the recruitment of 110 neonates during this time period by collecting essential clinical and laboratory data.
Furthermore, I re-recruited 85 neonates during the study period October 2006 and December 2010 and re-consented these patients for GATA1 analysis as the initial cohort of patients only consented for sample storage not analysis. This cohort was important as ML-DS may develop until the age of 5 years and this cohort of infants did not have GATA1 mutation analysis. I therefore, approached 103 families with permission from the community/general paediatrician responsible for the care of the DS infant and re-consented 83% of this study cohort.
Recruiting centres alerted Ms Helen Richmond (OIDSCS research nurse) and I when a DS neonate was born via email or telephone. We then approached the family at an appropriate time to gain written informed consent from parents/guardians with parental responsibility. We liaised with the hospital laboratory to secure the left over peripheral blood sample for GATA1 analysis and ensured that a peripheral blood film was made to meet the study inclusion criteria. Once consent was gained, the hospital laboratory was given a copy of the consent form before the blood sample and blood film were retrieved. The average rate of recruitment was 5 neonates per month. Recruitment rate was 92%; of DS neonates communicated to the study. Unfortunately, due to extensive variation between local
41 practices in the different recruiting centres and the fact that several of the recruits were not born in the recruiting hospital, it was not possible to collect data about the proportion of all DS neonates recruited compared to the total number of neonates born during the study period. However, the majority of neonates born at each recruiting centre were recruited to the study. No participating centre has a record of the total number of DS births during the study period. The National Down Syndrome cytogenetic register is also unable to provide this information until later in
2016. Reasons for non-recruitment were lack of available blood samples (n=23), parents not approached as neonate too sick or parental consent (n=7).
Detailed clinical and full blood count (FBC) data within the first 2 weeks of life was collected using the study proforma (see Appendix 2 and 3) from patient notes and laboratory reports at the time of recruitment. Comprehensive analysis of cellular composition and blood film morphology is performed using a proforma developed for the OIDSCS
(see Appendix 4). Blood films were prospectively reviewed by Dr. Georgina Hall (during October 2006 – March
2012) and Professor Irene Roberts. I independently reported blood films for the majority of neonates with TAM
(n=26) retrospectively and a representative subset of newborn DS films without GATA1 mutation(s) (n=24). I was blinded to the results of the OIDSCS morphological assessment for this latter group. Professor Irene Roberts verified my blood film reports. Results in DS neonates were compared with the normal range for neonates used at Queen
Charlotte's Neonatal Unit, Imperial College Healthcare NHS Trust. Although it is well recognised that non-leukaemic blast cells are frequently seen on the blood films of neonates, there is no normal range published for the frequency of circulating blast cells in neonates and so a normal range was established at the beginning on OIDSCS from routine blood films made on neonates admitted to the Queen Charlotte's Hospital Neonatal Unit. This is shown in Appendix 5 and shows that, even in sick preterm neonates, the frequency of blast cells in peripheral blood never exceeded 8%.
These data were used to establish the definition for TAM- see page 63.
Follow up samples (FBC and peripheral blood film) were collected for all DS neonates until the age of 5 years, during which children with DS are at risk of developing ML-DS. For neonates with a GATA1 mutation detected at birth, follow up samples were requested three monthly until the age of 2 years. If GATA1 mutation was negative at age 2 years, subsequent samples were requested every six monthly until the age of 4 years with one final test at the age of 5 years. For neonates without a GATA1 mutation detected at birth, follow up samples were requested annually until the age of 5 years. I participated in organising follow up samples for all DS neonates. Samples were requested from the
42 paediatric haematologist or community/general paediatrician responsible for the care of the infant via letter, emails and direct telephone conversation at the appropriate time points. Once the samples were taken, hospital laboratories were contacted to retrieve the sample, FBC data and peripheral blood film. If a sample was not taken at the study time point, clinicians were contacted to repeat the request for a blood sample at the next available opportunity.
Results of the GATA1 mutation analysis by Ss/DHPLC at birth were sent to the recruiting neonatal centre and community/general paediatrician or paediatric haematologist with a copy to the general practitioner if parents consented for this. Results of GATA1 mutation analysis by Ss/DHPLC for follow up samples were sent to the responsible clinician and general practitioner if originally consented for this. Results of GATA1 mutation analysis by
NGS were not reported during the time of my study as the significance of the findings was unknown.
Cytogenetic results from 16 hospitals in England were obtained from the National Down Syndrome Cytogenetic
Register, Queen Mary University of London and via the regional cytogenetic centres for 2 hospitals in Scotland: West
Scotland and South-east Scotland regional genetic service. I would like to thank Professor Joan Morris, Ms Anna
Springett at the Queen Mary University of London and Ms Lorna Crawford at the Southern General Hospital,
Glasgow as well as Mr Eddy Maher at Western General Hospital, Edinburgh for their help in retrieving these data.
2.2 Sample collection and processing
2.2.1 Samples
Peripheral blood EDTA samples and peripheral blood films were collected from neonates enrolled into the OIDSCS within the first two weeks of life. In each case the blood sample used was residual blood left over after being collected as part of routine sampling, which included a FBC. Detailed FBC data was collected from laboratory reports at time of recruitment. Blood films were made at the local hospitals on fresh blood sample and usually stained there but also stained at Oxford where unstained films were sent.
Cord blood was used to optimise cytospin methodology for flow-sorted sub-populations before using TAM samples.
Cord blood was collected at the time of elective Caesarean section and aspirated from the umbilical vein as soon as possible after the umbilical cord was cut using a 21G needle and immediately transferred to a 50ml Falcon (Beckton-
43 Dickinson, UK) containing preservative-free heparin at a concentration of 10-50IU/ml (CP Pharmaceuticals, UK).
Sampling, consent and experimental procedures on cord blood samples were already approved in the IR laboratory by
Hammersmith, Queen Charlotte’s, and Chelsea and Acton Hospitals Ethics Committee reference 04/Q0406/145.
2.2.2 Sample processing
2.2.2.1 Density gradient separation to obtain mononuclear cells
Peripheral blood samples left over from routine clinical use in neonates with and without DS were processed within 48 hours of sample collection. Peripheral blood (PB; 250 -500 μL) was diluted in 2 mL of phosphate buffered saline
(PBS) (Sigma-Aldrich, Poole, UK) and then layered onto 1.077 Histopaque (Sigma-Aldrich, Poole, UK) at a 1:2 ratio and mononuclear cells (MNC) were obtained by density gradient separation at room temperature (1800 rpm for 30 minutes).
2.2.2.2 DNA extraction for GATA1 mutation analysis
A small aliquot of left over peripheral blood sample (50 μL) was sent to Dr. Kelly Perkins and Dr. Natalina Elliott at the Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, Oxford for GATA1 mutational analysis (see section 2.6).
2.3 Flow cytometric analysis and sorting
2.3.1 Surface antibody staining
Cells were stained using PBS/fetal bovine serum 2% (FBS) (Sigma-Aldrich, Poole, UK) as a staining and washing buffer. After washing, cells were incubated with fluorophore-conjugated monoclonal antibodies (mAb) for 20-30 minutes at 4oC. These were then washed and re-suspended in 200-300 μL buffer for analysis. The antibodies used in my studies are shown in Appendix 6.
44 2.3.2 Flow cytometric analysis
Samples were analysed using a BD LSRFortessa (Beckton Dickinson, Oxford, UK). For each sample stained with antigen-specific mAb, an isotype control conjugated with the appropriate fluorophore was used. Compensation settings for 8-colour analysis were set using single-stained samples.
2.3.3 Flow cytometric sorting
Samples were sorted on FACSAria (Beckton Dickinson, Oxford, UK) machines. As above, appropriate isotype controls and single-stained samples were used to set compensation.
2.3.4 Analysis of flow cytometric data
Data were analysed on FlowJo software (Tree Star, Oregon, USA). Gating strategies are as described in the results. In all cases this involved an initial gate on viable cells identified by 4',6-Diamidino-2-phenylindole (DAPI).
2.4 Clonogenic assays
2.4.1 Methocult medium and cytokines
Methylcellulose haematopoietic progenitor assays were performed using Methocult H4230 (Stem Cell Technologies,
Vancouver, Canada) with a customised cytokine cocktail. Methocult H4230 consists of:
40 ml 2.6% methycellulose in Iscove’s modification of Dulbecco’s medium (IMDM)
30 ml FBS
10 ml 10% bovine serum albumin (BSA)
0.1ml 0.1M β-Mercaptoethanol
1ml 200mM L-glutamine
45 The cytokine cocktail used was a poly-potent cocktail from Manz et al(Manz et al, 2002). The cytokine concentrations are given below. All cytokines were from Peprotech (Peprotech Inc, Rocky Hill, NJ, USA) except erythropoietin
(EPO), which was from R&D (R&D Systems Europe, Abingdon, UK).
Cytokine Concentration (ng/ml) IL-3 20 IL-6 10 IL-11 10 SCF 10 GMCSF 50 FLT-3 10 TPO 50 EPO 4U/ml
Table 2.1. Cytokine cocktail) added to Methocult medium (Manz et al, 2002).
Cytokines, penicillin/streptomycin and IMDM (Stem Cell Technologies, Vancouver, Canada) were added to 8 ml
Methocult H4230 to make up a final volume of 10ml. 750µl aliquots of this methylcellulose mix were then transferred to 1.5ml Eppendorf tubes via a blunt end needle and syringe. TAM blast sub populations were sorted directly into
Eppendorfs containing the Methocult medium. The eppendorfs were vortexed after sorting to allow an even mix of cells within the medium.
2.4.2 Plating, counting and colony identification
The above Methocult medium was syringed into a flat bottomed 24-well plate (Beckton Dickinson, Oxford, UK) in
750µl aliquots/wells. Unused wells were filled with sterile PBS. This was then placed in an incubator at 37oC, 100% humidity and 5% CO2. Samples were plated in duplicates and triplicates when cell numbers permitted. Colonies were identified on the basis of morphology, colony size and haemoglobinisation. Colonies were counted at 7, 10 and 14 days depending on the maturity of the colonies.
46 2.4.3 Colony assays of specific TAM blast populations
To establish clonogenicity the sorted TAM blast sub-populations were plated in methylcellulose culture medium.
TAM blast sub-populations were defined as SSC intermediate and CD45 lo then (i) CD34+ CD33+, (ii) CD34+CD33-
, (iii) CD34-CD33+, (iv) CD34-CD33-.
2.5 Cytospins
Cytospins on flow sorted TAM blast populations were carried out using a Shandon Cytospin 2 (Fisher Scientific,
Loughborough, UK). Cells were suspended in 200μl Roswell Park Memorial Institute media (RPMI) (Sigma-Aldrich,
Poole, UK)/20% FBS and spun for 5 minutes at 400rpm. Cytospins were stained using May-Grunewald Giemsa Stain
(MGG) as follows. A working solution of May-Grunewald stain was made by diluting May-Grunewald Eosin Stain
(Sigma) 1:1 with pH 6.8 buffered distilled water. A working solution of Giemsa was prepared by diluting Giemsa
Stain (Sigma) 1:10 with pH 6.8 buffered distilled water. Slides were fixed by incubating in methanol (Sigma) for 30 seconds. They were then stained in May-Grunewald for 7 minutes, Giemsa for 20 minutes then washed with deionised distilled water and left to air dry.
2.6 GATA1 gene mutation analysis
Mutational analysis of exon 2 and the first part of exon 3 of the GATA1 gene was performed by PCR using the following cycling conditions: 95 0C for 10 mins; followed by 35 cycles of: 95 0C for 1 min, 62 0C for 1 min, 72 0C for
1 min; then 72 0C for 3 minutes. PCR products were visualised on agarose gel followed by direct Sanger sequencing and direct High Performance Liquid Chromatography (DHPLC). The level of sensitivity to detect mutant GATA1 clones is ~3%. In addition, neonatal samples were tested for the presence of small mutant GATA1 clones by targeted next generation sequencing (NGS) as described by Roberts et al (Roberts et al., 2013). Mutational analysis was performed by Dr. Kate Alford and Dr. Kelly Perkins in Professor Paresh Vyas’ lab and Dr Natalina Elliott in Professor
Roberts’ lab, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, OX3 9DS.
47 2.7 Statistics
Statistical analysis was performed using GraphPad Prism 6 software. Populations were compared using 2-sided T- tests, Fisher’s exact test,Chi-squared test and Pearson R correlation test; p-values <0.05 indicated statistically significant differences.
48 CHAPTER 3 - The clinical and haematological
features of TAM
49 THE CLINICAL AND HAEMATOLOGICAL FEATURES OF TAM
3.1 Background
3.1.1 Clinical and haematological features of TAM based on retrospective studies
Retrospective studies showed that there is clinical evidence of TAM in ~5-10% of neonates with DS although the presentation was very variable (Hitzleret al., 2003; Massey, et al., 2006; Klusmann et al., 2008; Muramatsu et al.,
2008; Gamiset al., 2011). Some of these studies have also reported the presence of several haematological abnormalities in TAM (Klusmann et al., 2008; Gamis et al., 2011). Of particular note, none of these studies has systematically studied either blood films or GATA1 mutation status together with clinical features and therefore, in many cases, the diagnosis of TAM is uncertain and milder cases will be missed. Thus, the true clinical spectrum of
TAM has not previously been described and is further confused by the use of different inclusion criteria in each of the studies. The WHO definition for TAM does not specify what blast percentage is abnormal in neonates with DS
(Hasleet al., 2003), thus making the diagnosis of TAM vague and potentially difficult.
3.1.2 Molecular features of TAM
Both TAM and ML-DS are uniquely marked by the presence of acquired N-terminal GATA1 mutation(s) (Wechsler et al., 2002; Xuet al., 2003; Rainiset al., 2003; Groet et al., 2003; Hitzler et al., 2003; Ahmed et al., 2004). Where paired samples have been studied, the same mutation is present both in TAM and ML-DS indicating that they are clonally- linked conditions (Ahmedet al., 2004; Yoshida et al., 2013). These studies have all relied on identifying GATA1 mutations using direct Sanger sequencing (Ss) and/or Direct high pressure liquid chromatography (DHPLC) which can identify a mutant close size of ~5% (Alford et al., 2011). Recent work in our laboratory has detected smaller-sized mutant GATA1 clones (~0.3%) by next-generation sequencing (NGS) (Robertset al., 2013).
3.2 Aim
The aim of the studies described in this chapter is to determine the specific clinical and laboratory features of TAM.
50 3.3 Experimental approach
To accurately define the clinical and laboratory features of TAM, I performed a detailed analysis of the clinical findings, haematological indices, blood cell morphology and GATA1 mutation status for all DS neonates enrolled into the Oxford Imperial Down Syndrome Cohort Study (OIDSCS).
3.3.1 Oxford Imperial Down Syndrome Cohort Study (OIDSCS)
The OIDSCS was a prospective observational study to document the frequency and spectrum of haematological abnormalities at birth in newborns with DS. Since October 2006, neonates with a clinical diagnosis of DS confirmed by karyotyping were prospectively recruited from 18 UK hospitals (see Appendix 1). The primary objective of the study was to characterise normal and abnormal haematology of children with DS for the first five years of life, specifically (i) monitoring the frequency and range of abnormalities in the full blood count (FBC) and blood film to establish range of values and define what is normal for this population, (ii) linking the FBC and blood film to clinical status and (iii) establishing the prevalence and character of the GATA1 mutation(s) in newborns and children with DS.
The secondary objective of the study was to provide greater understanding of haematopoiesis and haematological disorders associated with GATA1 mutation(s)- this was the aspect of the study which formed the work outlined in my thesis.
3.3.2 Definition of TAM
The WHO definition specifies only 'increased' blasts in a neonate with DS as sufficient for a diagnosis of TAM without defining the normal ranges for circulating blasts in neonates with and without DS. Before defining TAM, we first defined the normal ranges for circulating blasts in healthy term (n=80), healthy pre-term (n=128) and sick pre- term neonates (n=80) without DS at Imperial College Healthcare NHS Trust. These neonates had blood film reviewed for clinical suspicion of suspected sepsis. The normal range of blast cell frequency in healthy term, healthy pre-term and sick pre-term neonates without DS was 0-8% (see Appendix 5). Based on these ranges in neonates without DS, the OIDSCS used a definition for TAM which was expected to include all babies with TAM. The OIDSCS prospectively defined TAM as: a baby with DS confirmed by karyotyping and a blood film consistent with TAM
(blasts >10%) and an N-terminal GATA1 mutation(s) detected by conventional Ss/DHPLC.
51
After analysis of the first 200 babies, it was recognised that some DS babies with GATA1 mutation(s) did not meet these criteria since their blast cell frequency was <10% and/or they had a small mutant GATA1 clone detectable only by NGS (Roberts et al., 2013). To take account of this, I have used the following definitions of TAM in this thesis, although the final definition of TAM is different from the three categories described below:
Clinical TAM: blood film consistent with TAM (blasts >10%) and an N-terminal GATA1 mutation(s) detected
by conventional Ss/DHPLC
Clinically and haematologically ‘Silent’ TAM (DHPLC-positive): no clinical or haematological features of
TAM but GATA1 mutation(s) detected by Ss/DHPLC (blasts <10%)
Clinically and haematologically ‘Silent’ TAM (DHPLC-negative): no clinical or haematological features of
TAM and GATA1 mutation(s) detectable only by NGS and not detectable by Ss/DHPLC.
DS neonates without TAM: no GATA1 mutations detected by Ss/DHPLC or NGS.
In this cohort, using Ss/DHPLC, GATA1 mutation(s) were detected in 45/382 neonates (11.8%) -Figure 3.1. Of these
35/45 neonates (77.8%) had clinical and/or haematological evidence of TAM (blasts >10%) and 10/45 (22.2%) were clinically and haematologically silent with blasts <10% (Silent TAM, DHPLC +ve). Of the remaining 337 neonates,
163 (48.3%) have so far undergone NGS which revealed an additional 27 DS neonates with one or more small mutant
GATA1 clones (27/163 tested; 15.9%) (Silent TAM, DHPLC -ve)- Figure 3.1.
Through studying the clinical, haematological and molecular features of these neonates with GATA1 mutation (-s), I have accurately defined TAM for the first time. Through my work, the final definition of TAM was different from that given above and is discussed further in section 3.7.
52
Figure 3.1 Frequency of GATA1 mutation(s) in DS neonates enrolled into the OIDSCS
From October 2006-June 2014, 382 neonates were enrolled to the OIDSCS. Using Ss/DHPLC, GATA1 mutation(s) were detected in 45/382 neonates (11.8%). Of the remaining 337 neonates, 27/163 tested had a small mutant GATA1 clone (15.9%). The overall frequency of GATA1 mutation(s) thus far in the OIDSCS cohort was almost 28%, higher than previous reported studies.
3.3.3 Clinical and haematological data
Detailed clinical and FBC data within the first 2 weeks of life was collected using the study proforma (see Appendix 2 and 3) from patient notes, standardised electronic neonatal database and laboratory reports at time of recruitment.
Longitudinal clinical and haematological data was obtained through community/general paediatricians during the follow up period of 5 years. Comprehensive analysis of cellular composition and blood film morphology was performed using a proforma developed for the OIDSCS (see Appendix 4).
53 3.4 Clinical features in DS neonates with and without GATA1 mutation(s)
3.4.1 Demographic details
There was an equal distribution of male and female neonates recruited into the study and no significant difference in gender in the frequency of GATA1 mutation(s): 37/191(19.4%) male neonates had a GATA1 mutation(s) compared to
35/191 (18.3%) female neonates, p=0.9. Similarly, there was no difference in the male: female ratio in neonates with and without GATA1 mutation(s)-Figure 3.2a, Table 3.1.
The majority of neonates were born at term, with a median gestational age for neonates with and without GATA1 mutation(s) above 37 weeks (range 30-42.6 weeks). Neonates with clinically evident TAM had a lower gestational age at birth (37.1 weeks, range 31.7-39.7 weeks) than neonates with Silent TAM DHPLC-ve (38.3 weeks, range 35.7-41.9 weeks) and neonates without GATA1 mutation(s) (38.1 weeks, range 30-42.6 weeks), p<0.05 -Figure 3.2b, Table 3.1.
However, the gestational range for neonates with TAM and those without a GATA1 mutation(s) was similar and therefore although there was a statistical significance between these groups this is unlikely to be of clinical significance. The median birth weight for neonates with and without GATA1 mutation(s) was above 2.5 kg (range
1.18-3.99 kg) with no significant difference in birth weight between these groups, p=0.28 - Figure 3.2c, Table 3.1.
Clinical TAM Silent TAM Silent TAM DS Neo (No Clinical TAM (n=35) DHPLC + DHPLC - GATA1 vs DS neo (n=10) (n=27) mutation) (p-value) (n=310) Gender M:F 17:18 5:5 15:12 154:156 0.90
Median gestation 37.1 37.7 38.3 38.1 0.03 (weeks), range (31.7-39.7) (35.1-40) (35.7-41.9) (30-42.6)
Birth weight (kg), 2.72 2.95 2.90 2.86 0.29 range (1.67-3.68) (1.99-3.99) (1.84 -3.85) (1.18-2.88)
Table 3.1 Demographic features of DS neonates with and without GATA1 mutation(s)
There was no significant difference in ethnicity between neonates with and without GATA1 mutation(s), p=0.12; approximately 60% of DS neonates were of Caucasian background with approximately 20% of neonates from Asian
54 backgrounds and approximately 10% of neonates from Afro-Caribbean descent- (Figure 3.3, Table 3.2). This was in contrast to the 2011 Ethnicity and National Identity data (England and Wales) where Caucasians represented 86% of the population, Asians 7.5% and Afro-Caribbeans 3%. This difference may reflect the geographical location of the study recruiting centres, which were predominantly in inner city areas of London and Birmingham where there is a diverse ethnic population.
(A) Gender
Neonates with GATA1 mutation Neonates without GATA1 mutation
(B) Gestation (C) Birth weight
p = 0 .0 3
) 4 0 s k e e w (
3 5 n o i t a t s
e 3 0 G
2 5 T A M S T D H P L C + S T D H P L C - N o GA T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0
5 ) g
k 4 (
t h
g 3 i e w
h 2 t r i
B 1
0 T A M S T D H P L C + S T D H P L C - N o G A T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0
55 Figure 3.2A-C Demographic features of DS neonates with and without GATA1 mutation(s)
(A)Pie chart showing equal distribution of males and females in DS neonates with (n=72) and without GATA1 mutation(s)
(n=310), 48.6% vs 51.4% and 50.3% vs 49.7% respectively. (B)Dot plot showing most neonates were born at term (median gestation >37 weeks). Neonates with GATA1 mutation(s) had a significantly lower gestational age than neonates without GATA1 mutation(s) (median 37.1 weeks compared to 38.1 weeks; p=0.03) (C) Dot plots showing no difference in birth weight between neonates with and without GATA1 mutation(s), p=0.28.
56 Clinical TAM Silent TAM Silent TAM DS Neo (No (n=35) DHPLC + DHPLC - GATA1 (n=10) (n=27) mutation) (n=310) Caucasian 21 (60%) 6 (60%) 14 (51.2%) 200 (64.5%)
Asian 10 (28.6%) 0 10 (37%) 42 (13.5%)
Afro-Caribbean 3 (8.6%) 1 (10%) 1 (3.7%) 51 (16.5%)
Mixed race 0 0 2 (7.4%) 10 (3.2%)
Unknown 1 (2.8%) 3 (30%) 0 7 (2.3%)
Table 3.2 Ethnicity of DS neonates with and without GATA1 mutation(s)
1 0 0 U n k n o w n s
e M ix e d t
a 7 5
n A fr o - C a r ib b e a n o e A s ia n n
f 5 0 o
C a u c a s ia n e g a t
n 2 5 e c r e P 0 T A M S T D H P L C + S T D H P L C - N o GA T A 1
Figure 3.3 Ethnicity of DS neonates with and without GATA1 mutation(s)
Bar chart showing that the majority of neonates were of Caucasian background. There was no difference in ethnicity between these groups, p=0.12.
57 3.4.2 Pregnancy-related complications in neonates with and without GATA1 mutation(s)
As pregnancy-related complications might have an impact on the clinical presentation of TAM and/or
TAM might increase the likelihood of pregnancy-related complications, all charts were carefully reviewed for evidence of the following pregnancy-related disorders:
intrauterine growth restriction (IUGR)
maternal hypertension and/or pre-eclampsia (PET)
maternal diabetes (DM)
maternal haemoglobinopathy (HBP)
The prevalence of common pregnancy-related complications was no higher in neonates with GATA1 mutations(s) compared to those without GATA1 mutations(s)-Table 3.3. This suggests that secondary pregnancy-related complications were unlikely to explain the haematological abnormalities seen in neonates with and without GATA1 mutation(s). However, I found that neonates with clinical TAM were more likely to have IUGR than those without GATA1 mutations(s), p=0.03 – Figure 3.4, Table
3.3. The reason for this is unclear but it suggests that chronic intrauterine hypoxia may affect the haematopoietic stem/progenitor cell compartment in DS, perhaps increasing proliferation and therefore the frequency of acquired GATA1 mutations.
58 Clinical Silent TAM Silent TAM DS Neo (No Clinical TAM DHPLC + DHPLC - GATA1 TAM vs DS (n=35) (n=10) (n=27) mutation) neo (n=310) (p-value) IUGR 9 (25.7%) 1 (10%) 4 (14.8%) 37 (11.9%) 0.03
Maternal PET 0 0 0 4 (1.3%) 1.0
Maternal Diabetes 3 (8.6%) 4 (40%) 3 (11.1%) 10 (3.2%) 0.11
Maternal HBP 0 0 1 (3.7%) 3 (1%) 1.0
Table 3.3 Pregnancy related complications in DS neonates with and without GATA1 mutation(s)
Apart from IUGR, the prevalence of common pregnancy-related complications was no higher in neonates with GATA1 mutations(s) compared to those without GATA1 mutations(s).
p = 0 .0 3 * 1 0 0 7 5
R 5 0 G U I
N O 4 0 h t i Y E S w 3 0 s e t a
n 2 0 o e n 1 0 %
0 T A M S T D H P L C + S T D H P L C - N o GA T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0
Figure 3.4 The frequency of intrauterine growth restriction (IUGR) at birth was higher in DS neonates with GATA1 mutation(s) compared to those without GATA1 mutation(s)
Bar chart showing that a higher proportion of neonates with clinical TAM (26%) had IUGR compared to those without GATA1 mutations(s) (12%), p=0.03 suggesting that the haematological abnormalities seen in neonates with clinical TAM may be influenced by neonatal-related complications such as chronic intrauterine hypoxia.
There were no significant differences between any of the other groups.
59 3.4.3 Clinical features of neonates with and without GATA1 mutation(s)
Since perinatal complications might impact on the clinical (and haematological) features seen in neonates with DS, I also recorded the presence or absence of the following for all neonates with and without GATA1 mutation(s):
need for resuscitation at birth
oxygen/ non-invasive ventilation (NIV)/ intubation
sepsis (defined as blood culture positive infection or localised organ infection [Modi et al.,
2009])
bleeding (defined using a validated bleeding assessment tool (Stanworthet al., 2009)
A similar proportion of DS neonates with and without GATA1 mutation(s) required some resuscitation
(Table 3). However, neonates with GATA1 mutations(s) were more likely to require respiratory support (either NIV or intubation) than DS neonates without GATA1 mutations(s) (Figure 3.5a; Table
3.4). This may, in part, be due to pressure effect from hepatosplenomegaly, as 8 out of 9 neonates with TAM who required invasive or non-invasive respiratory support had hepatosplenomegaly.
Alternatively, it may reflect direct pulmonary or cardiac blast cell infiltration in neonates with larger mutant GATA1 clones, as discussed below.
A total of 22 babies had documented evidence of sepsis (Table 3.4). The frequency of sepsis was slightly higher in the neonates with TAM (5/35; 14%) compared to the neonates without GATA1 mutation(s) (17/310; 5%) although this just failed to reach statistical significance (p=0.06).
A total of 21 neonates had evidence of bleeding, as assessed using a validated bleeding assessment tool (Stanworth, et al., 2009). Of these 21 babies, 9 had GATA1 mutation(s) (7 with TAM and 2 with
Silent TAM) and 12 had no GATA1 mutation(s). The majority of neonates with TAM and silent TAM
60 had grade I-II bleeding related to thrombocytopenia and abnormal coagulation; the site of bleeding was gastro-intestinal and cerebral. Blood product support with platelet transfusions, fresh frozen plasma (FFP), and cryoprecipitate was required as well as vitamin K to manage symptoms in these neonates with TAM and silent TAM. In neonates without GATA1 mutation(s) bleeding was related to thrombocytopenia and sepsis; the majority of these neonates had grade I bleeding with petechiae as their main symptom but 5 out of these 12 neonates had grade III bleeding related to necrotising enterocolitis.
Neonates with TAM were more likely to have hepatosplenomegaly, skin rash and pleural/pericardial effusion and/or ascites compared to neonates without GATA1 mutation(s) (Figure 3.6a and 3.6b; Table
3.5). Fourteen neonates with TAM (40%) had hepatomegaly and 10 neonates with TAM (28.6%) had splenomegaly in contrast to no neonates with Silent TAM suggesting that the size of the GATA1 mutant clone might be responsible for the hepatosplenomegaly, presumably due to organ infiltration with blast cells with or without associated hepatic fibrosis (5 out of these14 neonates with TAM and hepatomegaly (35.6%), had abnormal liver function tests and/or fibrosis on hepatic biopsy). In support of this, the 11 DS neonates without a GATA1 mutation who had hepatosplenomegaly (3.5%) had other medical complications which were likely to explain this finding including heart failure or congenital structural malformations.
Skin rash was observed in four neonates with TAM (11.4%) and not seen in neonates with Silent
TAM (Figure 3.6 c, Table 3.5), suggesting that the size of the GATA1 mutant clone might be responsible for this presentation due to skin infiltration with blast cells.The skin rash in these 4 neonates with TAM was described as erythematous, vesiculopustular presumed to be secondary to staphylococcal or herpetic infection; however cultures for bacteria and viruses were negative. No skin biopsy was performed but the rash spontaneously resolved. Two neonates without GATA1 mutation also had skin rash (0.6%) but this was described differently as blanching and macular in nature presumed secondary to viral infection.
61
Three neonates with TAM had serous effusion (8.6%) compared to no neonates with Silent TAM-
Figure 3.6d, Table 3.5. One neonate with TAM had ascites associated with hepatosplenomegaly and liver dysfunction, another neonate with TAM had pleural and pericardial effusion associated with hepatosplenomegaly and liver fibrosis and one neonate had pericardial effusion associated with cardiomegaly, hepatosplenomegaly and atrio-ventricular septal defect thus suggesting that these features may be secondary to leukaemic blast cell infiltration. One neonate without GATA1 mutation had pleural effusion however this was secondary to congenital pneumonia.
The majority of neonates with DS were jaundiced (Table 3.5); the proportion of babies with TAM who were jaundiced were slightly higher than DS neonates without a GATA1 mutation but this did not reach statistical significance (p=0.11). However, the presence of jaundice in a neonate with DS is not a useful sign of TAM or GATA1 mutation since >50% of neonates without a GATA1 mutation were also jaundiced. The mechanism for the high frequency of jaundice is unclear. There was no evidence that the jaundice reflected a higher frequency of haemolytic anaemia (eg due to ABO incompatibility) in neonates with DS. It is possible that the jaundice reflected the highhaemoglobin concentrations in
DS neonates perhaps in combination with mild dehydration in association with poor feeding which is common in DS neonates.
In summary, no clinical features were diagnostic for TAM as the same signs could also be seen in a proportion of DS neonates without a GATA1 mutation. Three features were strongly associated with
TAM, hepatomegaly, splenomegaly and skin rash, in that they weresignificantly more common in
TAM than in neonates without GATA1 mutation. Neither of these features was seen in neonates with
Silent TAM suggesting that they may be directly related to the size of the mutant GATA1 clone.
62 Perinatal Clinical Silent TAM Silent TAM DS Neo (No Clinical complications at birth TAM DHPLC + DHPLC - GATA1 TAM vs (n=35) (n=10) (n=27) mutation) DS neo (n=310) (p-value) Resuscitation 10 (28.6%) 0 6 (22.2%) 99 (31.9%) 0.85
• Oxygen at 1 (2.9%) 0 5 18.5%) 66 (21.3%) 0.006 birth • NIV 4 (11.4%) 0 0 17 (5.5%) 0.25 • Intubation 5 (14.3%) 0 1 (3.7%) 16 (5.2%) 0.05 Sepsis 5 (14.3%) 0 0 17 (5.5%) 0.06
Bleeding/Coagulopathy 7 (20%) 1 (10%) 1 (3.7%) 12 (3.9%) 0.01
Table 3.4 Perinatal complications at birth in DS neonates with and without GATA1 mutation(s)
63 1 0 0
d O x y g e n
e 7 5 t
a 5 0 N o n -in v a s iv e v e n tila tio n t i
c In tu b a tio n s
u 4 0
s N o r e s u s c ita tio n h A e t r r
i
s 3 0 b e
t t a a
n 2 0 o e n
f 1 0 o
% 0 T A M S T D H P L C + S T D H P L C - N o GA T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0
p = 0 .0 1 * *
/ 1 0 0 g n i N O d
e 7 5 Y E S e
B l 2 5 y b
h t h t a
i 2 0 p w o
l s u
e 1 5 g t a a o n 1 0 c o e n
f 5 o
% 0 T A M S T D H P L C + S T D H P L C - N o GA T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0
Figure 3.5 Perinatal complications at birth in DS neonates with and without GATA1 mutation(s)
(A) Bar chart showing similar proportion of DS neonates with and without GATA1 mutation(s) required resuscitation at birth but neonates with clinical TAM were more likely to require invasive respiratory support than DS neonates without GATA1 mutations(s), p=0.05. (B) Bar chart showing that neonates with clinical TAM had more bleeding/coagulopathy than neonates without GATA1 mutation(s) (20% vs 3.9%), p=0.01. There were no significant differences between any other groups.
64 Clinical Silent TAM Silent TAM DS Neo (No Clinical TAM DHPLC + DHPLC - GATA1 TAM vs (n=35) (n=10) (n=27) mutation) DS Neo (n=310) (p-value) Hepatomegaly 14 (40%) 0 0 11 (3.5%) <0.0001
Splenomegaly 10 (28.6%) 0 0 0 <0.0001
Rash 4( 11.4%) 0 0 2 (0.6%) 0.001
Pleural/Pericardial 3 (1/1/1 - 0 0 1 (0.3%) 0.004 Effusion; Ascites 8.6%)
Jaundice 24 (68.6%) 8 (80%) 16 (59.3%) 166 (53.5%) 0.11
Table 3.5 Clinical features at birth in DS neonates with and without GATA1 mutation(s)
Neonates with TAM were more likely to have hepatosplenomegaly, skin rash and pleural/pericardial effusion and/or ascites compared to neonates without GATA1 mutation(s). These clinical features were not seen in neonates with Silent TAM suggesting that the size of the GATA1 mutant clone might be responsible for hepatosplenomegaly, rash, effusion/ascites due to organ infiltration by blasts.
65 p < 0 .0 0 0 1 p < 0 .0 0 0 1
y * * * * l
y * * * * l a 1 0 0 a
g 1 0 0 g e 7 5 e 7 5 m 5 0 m o t o a n N O p e 3 0 l e 4 0 N O Y E S p h
Y E S s
h h t i 3 0 t i
w 2 0
w
s s e e t 2 0 t a a n
n 1 0 o o
e 1 0 e n n
f f o o 0 0 % T A M S T D H P L C + S T D H P L C - N o GA T A 1 % T A M S T D H P L C + S T D H P L C - N o GA T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0 (A) Hepatomegaly (B) Splenomegaly
p = 0 .0 0 1 p = 0 .0 0 4 s
* * * e * * t 1 0 0 i 1 0 0 c
s 7 5 7 5 a h / s
1 5 n 1 0 a o r i
s h t u i
f N O
N O f w
e
s 1 0 Y E S Y E S h e t t i a
w 5 n
o s e e t
n 5
a f n o
o e % n
0 f 0 o T A M S T D H P L C + S T D H P L C - N o GA T A 1 T A M S T D H P L C + S T D H P L C - N o GA T A 1 % n = 3 5 n = 1 0 n = 2 7 n = 3 1 0 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0 (D) Skin rash (C) Effusion/ascites
Figure 3.6 Clinical features at birth in DS neonates with and without GATA1 mutation(s)
Bar charts showing that neonates with TAM were more likely to have (A) hepatomegaly (p<0.0001), (B) splenomegaly (p<0.0001), (C) skin rash (p<0.001) and (D) pleural/pericardial effusion and/or ascites (p<0.004) compared to neonates without GATA1 mutation(s). Neonates with Silent TAM did not have hepatosplenomegaly, skin rash, effusion/ascites suggesting that the size of the GATA1 mutant clone might be responsible for these due to organ infiltration by blasts. There were no significant differences between other groups.
66 3.4.4 Congenital anomalies in DS neonates with and without GATA1 mutation(s)
A summary of the congenital anomalies seen in the DS neonates enrolled into the OIDSCS is shown in Table 3.6. The spectrum of congenital abnormalities observed was similar to previous published reports (Bull, 2011; Rankin et al., 2012). There was no difference in the prevalence of congenital heart disease (CHD) or its various sub-types: atrial septal defects (ASD), ventricular septal defects
(VSD), atrio-ventricular septal defects (AVSD), coarctation of aorta (CoA), tetralogy of Fallot (ToF) and valvular abnormalities in neonates with and without GATA1 mutation(s) (Figure 3.7a, Table 3.6a).
Similarly, there was no difference in the frequency of congenital gastrointestinal (GI) anomalies or its most common sub-types: duodenal atresia (DA), oesophageal atresia (OA) and anorectal malformations in neonates with and without GATA1 mutation(s) (Figure 3.7b, Table 3.6b). Therefore, it is difficult to recognise neonates with GATA1 mutation(s) simply by the presence of congenital anomalies.
Clinical Silent TAM Silent TAM DS Neo Clinical TAM (n=35) DHPLC +ve DHPLC –ve (w/out TAM vs DS (n=10) (n=27) GATA1 neo (p- mutation) value) (n=310) CHD 18 (51%) 2 (20%) 14 (52%) 153 (49%) 0.79
• AVSD 7 (20%) 1 (10%) 6 (22%) 45 (15%) • ASD 4 (11%) 0 5 (18%) 47 (15%) • VSD 1 (3%) 0 1 (4%) 35 (11%) • TOF 1 (3%) 0 0 3 (1%) • COA 0 0 0 4 (1%) • Valvular 3 (9%) 1 (10%) 1 (4%) 9 (3%) defects • ASD/VSD 2 (6%) 0 1 (4%) 9 (3%)
Table 3.6a Frequency of congenital heart disease in DS neonates with and without GATA1 mutation(s)
67 l 1 0 0 a t
i N O C H D 7 5 n
e 6 0 A S D /V S D g V A L V E n e o 5 0 C O A s c
a
h T O F e t i
s 4 0
i V S D w
d
s A S D t e r 3 0 t
a A V S D a e n
h 2 0 o e n 1 0 f o
% 0 T A M S T D H P L C + S T D H P L C - N o GA T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0
Figure 3.7a Frequency of congenital heart disease in DS neonates with and without GATA1 mutation(s)
Bar chart showing no difference in the prevalence of congenital heart disease (CHD) or its various sub-types: atrial septal defects (ASD), ventricular septal defects (VSD), atrio-ventricular septal defects (AVSD), coarctation of aorta (CoA), tetralogy of Fallot (ToF) and valvular abnormalities in neonates with and without
GATA1 mutation(s) (CHD in neonates with GATA1 mutation(s) 51% vs 49% in neonates without GATA1 mutation(s)), p=0.79.
Clinical Silent TAM Silent TAM DS Neo TAM vs DS TAM (n=35) DHPLC +ve DHPLC –ve (w/out neo (n=10) (n=27) GATA1 (p-value) mutation) (n=310) GI anomalies 5 (14%) 1 (10%) 1 (4%) 20 (6%) 0.31
• OA 0 0 0 4 (1%) • DA 2 (6%) 0 1 (4%) 10 (3%) • Anorectal 3 (9%) 1 (10%) 0 6 (2%) malformations
Table 3.6b Frequency of congenital gastrointestinal (GI) anomalies in DS neonates with and without GATA1 mutation(s)
68
l 1 0 0 a t i
n N o G I a n o m a lie s e
g 7 5 A n o re c ta l m a lfo rm a tio n s s n e o i D u o d e n a l A tr e s ia t c i
l h a O e s o p h a g e a l A tr e s ia
t 2 0 i m r w
o s n e t b a a
I n 1 0 o G
e n
f o
% 0 T A M S T D H P L C + S T D H P L C - N o GA T A 1 n = 3 5 n = 1 0 n = 2 7 n = 3 1 0
Figure 3.7b Frequency of congenital gastrointestinal (GI) anomalies in DS neonates with and without GATA1 mutation(s)
Bar chart showing there was no difference in the frequency of congenital GI anomalies or its most common sub- types in neonates with and without GATA1 mutation (GI anomalies in neonates with GATA1 mutation(s) 14% compared to 6% in neonates without GATA1 mutation(s)), p=0.31.
3.4.5 Cytogenetic features of DS neonates with and without GATA1 mutation(s)
Details of karyotype analysis were available for 370/382 of the DS. The majority of neonates with and without GATA1 mutation(s) had constitutional trisomy (cT21) 47 XX/XY +21 (83% and 93% respectively, p=0.04) in keeping with previous reports (Antonarakis et al., 2004) -Figure 3.8, Table
3.7. Robertsonian translocations were found in 4% of neonates without GATA1 mutation(s), involving chromosome 14 (n=4), chromosome 21 (n=3) and chromosome 13 (n=2). None of the neonates with
GATA1 mutation(s) had a Robertsonian translocation. Mosaic translocations were present in 1% of neonates without GATA1 mutation(s). Additional abnormalities such as inv (Y) and inv (5) were found more often in neonates with than without GATA1 mutation (8% vs 0.3%, p=0.004); the
69 significance of this is unknown. Interestingly, one neonate with Silent TAM DHPLC –ve had a partial trisomy the significance of which is discussed in detail in the next chapter.
Karyotype Clinical Silent TAM Silent TAM DS Neo (No TAM vs DS TAM (n=35) DHPLC + DHPLC - GATA1 neo (p- (n=10) (n=27) mutation) value) (n=310) Constitutional T21 29 (83%) 7 (70%) 27 (100%) 290 (93%) 0.04
Robertsonian 0 0 0 9 (4%) 0.61 translocation
Mosaic T21 0 0 0 3 (1%) 1.0
Partial T21 0 1 (10%) 0 0 1.0
Other chromosomal 3 (8%) 0 0 1 (0.3%) 0.004 abnormalities (Inv Y/Inv 5) Unknown 3 (8%) 2 (20%) 0 7 (2%)
Table 3.7 Karyotype in DS neonates with and without GATA1 mutation(s)
70 8 3 % 7 0 %
C O N S T IT U T IO N A L T 2 1 C O N S T IT U T IO N A L T 2 1 T 2 1 + A D D IT IO N A L A B N O R M A L IT IE S P A R T IA L T 2 1 U N K N O W N U N K N O W N
TAM (n=35) Silent TAM DHPLC+ (n=10)
9 3 %
C O N S T IT U T IO N A L T 2 1 R O B E R T S O N IA N T R A N S L O C A T IO N M O S A IC T 2 1 T 2 1 + A D D IT IO N A L A B N O R M A L IT IE S U N K N O W N
No GATA1 mutation (n=310)
Figure 3.8 Karyotype in DS neonates with and without GATA1 mutation(s)
Pie charts showing that most DS neonates had constitutional trisomy (cT21) 47 XX/XY +21 (83% in neonates with TAM compared to 93% in neonates without GATA1 mutation(s), p=0.04). Additional abnormalities (inv
(Y) and inv (5)) were found more often in neonates with than without GATA1 mutation (8% vs 0.3%, p=0.004).
One neonate with Silent TAM DHPLC –ve had a partial trisomy (46,XX,der (21) (qter->22.1;p11.2->qter).
71 3.5 Haematological features of DS neonates with GATA1 mutation(s)
3.5.1 Haematological features at birth in DS neonates with and without GATA1 mutation(s)
Platelet count: Thrombocytopenia was shown to be a common feature in both DS neonates with and without a GATA1 mutation(s) at birth compared to healthy neonates without DS, p=0.88 (Figure
3.9a, Table 3.8). In addition, there was no significant difference in platelet count between the groups of DS neonates separated depending on their GATA1 mutational status, p=0.35 for clinical TAM vs
Silent TAM DHPLC +ve and p=0.34 for clinical TAM vs Silent TAM DHPLC –ve (Figure 3.10a,
Table 3.9). Median platelet counts were 84 x109/L (range 18-1123) in those with clinically and haematologically evident TAM (n=35), 97x109/L (range 22-182) in Silent TAM DHPLC +ve (n=10),
127 x109/L (range 41-253) in Silent TAM DHPLC -ve (n=27) and 138 x109/L (range 18-432) in those without GATA1 mutation(s) (n=310). There was a considerable overlap in platelet count between these 4 groups suggesting that thrombocytopenia results from the direct consequence of trisomy 21 on platelet production rather than the presence of GATA1 mutation(s).
White cell count: Neonates with DS had a higher white cell count than healthy neonates without DS,
(see Appendix 6 for normal reference range), p=0.01 (Figure3.9b, Table 3.8). Furthermore neonates with clinically and haematologically evident TAM (n=35) had a significantly higher WBC than those with Silent TAM DHPLC+ve (n=10) and those with Silent TAM DHPLC-ve (n=27) with a median
WBC of 22 x109/L (range 5.7-97.9 x109/L) compared to 9.1 x109/L (range 5.1-27.9 x109/L) and 13.6 x109/L (range 5.5-26.1 x109/L), p=0.03 and p=0.004 respectively - Figure 3.10b, Table 3.9. However, there was a considerable overlap between the groups and some neonates with GATA1 mutation(s) have a normal WBC. This indicates that both trisomy 21-mediated effects as well as the presence of a
GATA1 mutation(s) are likely to be responsible for these changes.
72 Haemoglobin: The haemoglobin concentration in neonates with DS is higher than healthy term neonates without DS (see Appendix 6 for normal reference range) (Figure 3.9c, Table 3.8); this implies that trisomy 21 itself results in abnormal erythropoiesis. However, the haemoglobin in neonates with GATA1 mutation(s) (n=72) is significantly lower than those without GATA1 mutation(s) (n=310) with a median of 193 g/L (range 129-240 g/L) as compared to 207 g/L (range 89-
280 g/L), p<0.0001. Similarly, neonates with clinically and haematologically evident TAM (n=35) had a significantly lower Hb than neonates with Silent TAM DHPLC –ve (n=27) with a median of
182 g/L (range 129-222 g/L) in the clinical TAM group as compared to a median of 203 g/L (range
146-240 g/L) in the Silent TAM DHPLC-ve group, p<0.0001 (Figure 3.10c, Table 3.9). However, again there was a considerable overlap between these groups.
73 (A) Platelet count (B) White blood cell count (C) Haemoglobin
p = 0 .8 8 p = 0 .0 1 p < 0 .0 0 0 1 1 2 5 0 * 3 0 0 * * * * 1 0 0 0 1 5 0 7 5 0 1 0 0 5 0 0 ) 5 0
L 2 5 0 / ) 9 4 0 0 L 0 ) / 3 0 1 9 L / 0 x 3 0 0 ( 1
2 5 g
( 2 0 0 s
x
t 2 0 0 (
2 0 e b l C H e B t 1 5 0 1 5 a l W 1 0 1 5 0 P 1 0 0 5 5 0 5 1 0 0 0 0 0 D S w ith GA T A 1 m u tn (s ) D S w /o u t GA T A 1 m u tn D S w ith GA T A 1 m u tn (s ) D S w /o u t GA T A 1 m u tn D S w ith GA T A 1 m u tn (s ) D S w /o u t GA T A 1 m u tn n = 7 2 n = 3 1 0 n = 7 2 n = 3 1 0 n = 7 2 n = 3 1 0
Figure 3.9 Haematological features at birth in DS neonates with and without GATA1 mutation(s)
Dot plots showing that (A) Thrombocytopenia was common in DS neonates with and without GATA1 mutation with a median platelet count of 115x109/L (18-1123) and 138x109/L (13-432) respectively compared to healthy non-DS neonates (reference range represented by blue lines) (B) White blood cell count (WBC) were higher in DS neonates than healthy non-DS neonates
(reference range represented by blue lines). Neonates with GATA1 mutation(s) had an even higher WBC as compared to those without GATA1 mutation(s) with a median WBC of 17.2 x109/L
(5.1-97.9) and 14.6x109/L (2.9-136.3) respectively, p=0.01, (C) Haemoglobin (Hb) concentration was higher in DS neonates as compared to healthy term neonates without DS (reference range represented by blue lines). Neonates with GATA1 mutation(s) had a lower Hb than those without GATA1 mutation with a median Hb of median 193g/L (129-240) compared to 207 g/L (89-
280) respectively, p<0.0001.
74 Full blood count DS Neo with GATA1 DS Neo without DS Neo with GATA1 median, range mutation (n=72) GATA1 mutation mutn vs DS Neo (n=310) w/out GATA1 mutn (p-value) Platelets (x109/L) 115 (18-1123) 138 (13-432) 0.88
White blood count (x109/L) 17.2 (5.1-97.9) 14.6 (2.9-136.3) 0.01
Haemoglobin (g/L) 193 (129-240) 207 (89-280) <0.0001
Table 3.8 Haematological features at birth in DS neonates with and without GATA1 mutation(s)
Median Full Clinical Silent TAM Clinical Silent TAM Clinical blood count, TAM (n=35) DHPLC +ve TAM vs DHPLC –ve TAM vs range (n=10) Silent TAM (n=27) Silent TAM DHPLC +ve DHPLC -ve (p-value) (p-value) Platelets (x109/L) 84 (18-1123) 97 (22-182) 0.35 127 (41-253) 0.34
White blood count 22 (5.7-97.9) 9.1 (5.1-27.9) 0.03 13.6 (5.5- 0.0004 (x109/L) 26.1)
Haemoglobin 182 (129- 192 (159- 0.13 203 (146- <0.0001 (g/L) 222) 239) 240)
Table 3.9 Haematological features at birth in DS neonates with TAM and Silent TAM
75 (A) Platelet count (B) White blood cell count (C) Haemoglobin
p < 0 .0 0 0 1 p = 0 .3 4 p = 0 .0 0 0 4 * * * * p = 0 .1 3 p = 0 .3 5 * * * 1 2 5 0 p = 0 .0 3 2 5 0 1 0 0 0 * 7 5 0 1 5 0 5 0 0 1 0 0 ) L / 5 0 9 4 0 0 ) ) 2 0 0 0 L 1 L /
3 0 / x
3 0 0 9 g ( 0
(
1 2 5
s
t 2 0 0 b x ( e
2 0 l H e C
t 1 5 0
B 1 5 1 5 0 a l W
P 1 0 0 1 0
5 0 5 5 1 0 0 0 0 0 T A M S T D H P L C + ve S T D H P L C -ve T A M S T D H P L C + ve S T D H P L C -ve T A M S T D H P L C + ve S T D H P L C -ve n = 3 5 n = 1 0 n = 2 7 n = 3 5 n = 1 0 n = 2 7 n = 3 5 n = 1 0 n = 2 7
Figure 3.10 Full blood counts at birth in DS neonates with and without GATA1 mutation(s)
Dot plots showing (A) no significant difference in platelet count at birth between DS neonates separated depending on their GATA1 mutational status with a median platelet counts of 84 x109/L (range 18-1123) in those with clinical TAM, 97x109/L (range 22-182) in Silent TAM DHPLC +ve and 127 x109/L (range 41-253) in Silent TAM DHPLC –ve, p=0.35 and 0.34 respectively, (B) WBC was significantly higher at birth in neonates with clinical TAM than those with Silent TAM with a median WBC of 22 x109/L (range 5.7-97.9 x109/L) in neonates with clinical TAM compared to 9.1 x109/L (range 5.1-27.9 x109/L) in Silent TAM DHPLC+ (p=0.03) and 13.6 x109/L (range 5.5-26.1 x109/L) Silent TAM DHPLC- (p=0.0004), (C) Haemoglobin
(Hb) was significantly lower at birth in neonates with clinically TAM than neonates with Silent TAM DHPLC – with a median Hb of 193g/L (129-240) compared to 207 g/L (89-280)
(p<0.0001).
76 3.5.2 Haematological features during the first 5 years of life in DS infants with and without
GATA1 mutation(s)
I analysed the serial follow-up data for all DS children enrolled in the OIDSCS to determine the haemoglobin, white blood cell and platelet counts during the first 5 years of life in children with and without a GATA1 mutation(s). As children with DS have a markedly increased risk of ML-DS during the first 5 years of life, follow up of the whole cohort is necessary to fully evaluate the significance of even very small mutant GATA1 mutant clones.
Platelets: By 12 months, the majority of neonates with and without a GATA1 mutation(s) had a platelet count within the normal range (Orkin et al, 2009) (Fig 3.11, Table 3.10). However, neonates with clinically and haematologically evident TAM had a significantly lower platelet count than those without a GATA1 mutation at 12 months (p=0.002) with a median count of 275 x109/L (range 110-
417) versus 365 x109/L (range 36-516) at 12 months. Beyond 12 months the platelet count was within the normal range for the majority of neonates with and without GATA1 mutation(s). This analysis excludes 5 neonates with TAM who progressed to ML-DS;
White cell count: Between12 months and 60 months, the WBC appeared to normalise with little difference between neonates with and without GATA1 mutation(s) (Figure 3.12, Table 3.11). At 36 months, neonates with GATA1 mutation(s) had a significantly higher WBC than those without GATA1 mutation(s) (p=0.04) with a median count of 8.0 x109/L (range 4.1-12.3) versus 6.3 x109/L (range 3.1-
12.5), however there was a considerable overlap between the two groups.
Haemoglobin: Following the first 12 months, there were no significant differences in haemoglobin value between neonates with and without GATA1 mutation (Table 3.13, Table 3.12). However, the haemoglobin concentration in many neonates with DS remained higher than healthy term neonates
77 without DS during the first five years of life suggesting that trisomy 21 mediated effects on erythropoiesis are long-lasting.
Age (months) Median Platelet count (x109/L), range TAM (n=35) Silent TAM Silent TAM DS Neo w/out DHPLC +ve DHPLC –ve GATA1 mutn (n=10) (n=27) (n=310) <1 84 (18-1123) 97 (22-182) 127 (41-253) 138 (13-432)
12 275(110-417)** 287 (215-322) 278 (204-609) 365 (36-516)
24 301 (157-412) 265 (262-268) 218 (188-471) 336 (173-615)
36 305 (136-488) - 276 (219-487) 324 (114-485)
48 329 (200-387) 421 (421-421) 481 (481-481) 337 (128-498)
60 338 (209-381) - 277 (272-460) 319 (146-567)
Table 3.10 Platelet counts during the first five years of life in DS infants with and without
GATA1 mutation(s)
Beyond 12 months the majority of infants with and without a GATA1 mutation(s) had a platelet count within the normal range. Infants with clinical TAM at birth had a significantly lower platelet count than those without a
GATA1 mutation at 12 months (p=0.002**) with a median count of 275 x109/L (range 110-417) versus 365 x109/L (range 36-516) at 12 months.
78 p = 0 .0 0 2 p = 0 .0 7 * * s 7 0 0 h s 7 0 0 t
h 5 5 0 n t 5 5 0 o n o m
5 0 0 m 4 5 0 0 2 2
1 t
t a
4 0 0 a )
4 0 0 ) L / L / 9 9 0 3 0 0 0
3 0 0 1 1 x x (
(
s
s 2 0 0 2 0 0 t t e e l l e e t t a
a 1 0 0
1 0 0 l l
P 0
P 0 T A M S T D H P L C + S T D H P L C - N o G A T A 1 T A M S T D H P L C + S T D H P L C - N o G A T A 1
p = 0 .9 6 p = 0 .3 7 s s 5 5 0 5 5 0 h h t t n n o o 4 5 0
m 4 5 0 m
8 6 4 3
t t 3 5 0 a a
3 5 0 ) ) L L / / 9 9 2 5 0 0 0 1 1 2 5 0 x x ( (
s s 1 5 0 t t e e l l 1 5 0 e e 1 0 0 t t a a 5 0 1 0 0 l l P P 0 0 T A M S T D H P L C + S T D H P L C - N o G A T A 1 T A M S T D H P L C + S T D H P L C - N o G A T A 1
p = 0 .6 0
s 6 0 0 h t n
o 5 0 0 m
0 6
t 4 0 0 a
) L /
9 3 0 0 0 1 x (
s 2 0 0 t e l e t
a 1 0 0 l
P 0 T A M S T D H P L C + S T D H P L C - N o G A T A 1
Figure 3.11 Platelet counts during the first five years of life in DS infants with and without
GATA1 mutation(s)
Dot plots showing sequential platelet counts in DS infants with and without GATA1 mutation(s) during the first five years of life. Infants with clinical TAM at birth had a significantly lower platelet count than those without a
GATA1 mutation at 12 months (p=0.002) with a median count of 275 x109/L (range 110-417) versus 365 x109/L
(range 36-516) at 12 months. Beyond 12 months the majority of infants with and without a GATA1 mutation(s) had a platelet count within the normal range (represented by blue lines).
79
Age (months) Median WBC count (x109/L), range
TAM (n=35) Silent TAM Silent TAM DS Neo w/out DHPLC +ve DHPLC –ve GATA1 mutn (n=10) (n=27) (n=310) <1 22 (5.7-97.9)**** 9.1 (5.1-27.9) 13.6 (5.5-26.1) 14.6 (2.9-136.3)
12 7.7 (2-16.5) 5.8 (4.1-12.9) 7.1 (4.7-9.8) 6..9 (3.7-18.7)
24 6.9 (3.4-16.7) 7.8 (4.4-11.3) 6.6 (4.5-13.5) 6.5 (3.9-13.8)
36 8 (4.1-12.3)* - 5.9 (4.3-8.5) 6.3 (3.1-12.5)
48 9.2 (4-11.6) 9.7 (9.7-9.7) 6.3 (6.3-6.3) 6.7 (3.8-14.9)
60 6.1 (3.3-9.1) - 6.3 (6-8.3) 5.7 (3.6-11.2)
Table 3.11 White blood cell counts during the first five years of life in DS infants with and without GATA1 mutation(s)
WBC was higher at birth in neonates with clinical TAM than those without GATA1 mutation(s), p<0.0001****. After 12 months WBC was within normal range for the majority of DS infants with and without GATA1 mutation with little difference between these groups. At 36 months, infants with
GATA1 mutation(s) at birth had a significantly higher WBC than those without GATA1 mutation(s)
(p=0.04*),
80 p = 0 .6 4 2 0 p = 0 .8 3
2 0 s h s t h n t n o 1 5
o 1 5 m
m
4 2 2
1 t 1 0 t 1 0 a
a )
) L / L / 9 9 0
0 5
5 1
1 5 5 x x ( (
C C B B W W 0 0 T A M S T D H P L C + S T D H P L C -N o G A T A 1 T A M S T D H P L C + S T D H P L C - N o G A T A 1
2 0 p = 0 .0 4 2 0 p = 0 .2 3 s s h h
t * t n n o 1 5 o 1 5 m m
6 8 3 4
t t a a
1 0 1 0 ) ) L L / / 9 9 0 0 1 1
x 5 5 x ( (
5 5 C C B B W 0 W 0 T A M S T D H P L C + S T D H P L C - N o G A T A 1 T A M S T D H P L C + S T D H P L C - N o G A T A 1
2 0 p = 0 .6 3 s h t n
o 1 5 m
0 6
t 1 0 a
) L / 9
0 5 1 5 x (
C B W 0 T A M S T D H P L C + S T D H P L C - N o G A T A 1
Figure 3.12 White blood cell counts during the first five years of life in DS infants with and without GATA1 mutation(s)
Dot plots showing sequential white blood cell (WBC) counts in DS infants with and without GATA1 mutation(s) during the first five years of life. After 12 months, WBC was within normal range (represented by blue lines) for the majority of DS infants with little difference between these groups.
81 Age (months) Median Haemoglobin (g/L), range
TAM (n=35) Silent TAM Silent TAM DS Neo w/out DHPLC +ve DHPLC –ve GATA1 mutn (n=10) (n=27) (n=310) <1 18.2 (12.9- 19.2 (15.9-23.9) 20.3 (14.6-24) 20.7(8.9-28) 22.2)**** 12 131 (115-156) 135 (121-140) 132 (114-140) 127 (72-166)
24 133 (113-148) 130 (129-131) 131 (118-137) 129 (101-161)
36 132 (105-146) - 132 (112-144) 132 (89-153)
48 132 (115-150) 115 (115-115) 130 (130-130) 131 (108-150)
60 132 (123-140) - 135 (123-140) 133 (109-145)
Table 3.12 Haemoglobin concentrations during the first five years of life in DS infants with and without GATA1 mutation(s)
At birth neonates with clinical TAM had a lower haemoglobin (Hb) concentration than those without GATA1 mutation(s), p<0.0001****. Following the first 12 months, there were no significant differences in haemoglobin concentration between infants with and without GATA1 mutation.
82 1 7 5 p = 0 .0 9 1 7 5 p = 0 .0 9 s s h h t t n n 1 5 0 1 5 0 o o m m
4 2 2 1
t t a a
1 2 5 1 2 5 ) ) L L / / g g ( (
b b H H 1 0 0 1 0 0 9 5 9 5 0 0 T A M S T D H P L C +S T D H P L C - N o G A T A 1 T A M S T D H P L C +S T D H P L C - N o G A T A 1
p = 0 .6 4 1 7 5 p = 0 .9 4 1 6 0 s s h h t t n
1 5 0 n o 1 4 0 o m m
6 8 3 4
t t a a
1 2 5
) 1 2 0 ) L L / / g g ( (
b b
H 1 0 0 H 1 0 0 9 5 9 5 0 0 T A M S T D H P L C +S T D H P L C - N o G A T A 1 T A M S T D H P L C +S T D H P L C - N o G A T A 1
1 6 0 p = 0 .6 8 s h t
n 1 4 0 o m
0 6
t a 1 2 0 ) L / g (
b
H 1 0 0 9 5 0 T A M S T D H P L C +S T D H P L C - N o G A T A 1
Figure 3.13 Haemoglobin concentrations during the first five years of life in DS infants with and without GATA1 mutation(s)
Dot plots showing sequential haemoglobin (Hb) concentrations in DS infants with and without GATA1 mutation(s) during the first five years of life. Following the first 12 months, there were no significant differences in haemoglobin concentration between infants with and without GATA1 mutation. The haemoglobin concentration in many infants with DS irrespective of the GATA1 mutation status remained higher than healthy term neonates without DS (represented by blue lines) during the first five years of life.
83 3.5.3 Peripheral blood blast count and GATA1 clone size in DS neonates with GATA1
mutation(s)
As mentioned above, there are no studies describing the relationship between peripheral blood blast percentage and GATA1 mutation status in DS neonates thus far. Automated haematology analysers often fail to identify blasts, therefore, it is vital that a manual blast count is determined by carefully evaluating the peripheral blood film. I evaluated peripheral blood blast percentages in correlation with
GATA1 analysis by Ss/DHPLC and NGS in neonates with TAM.
Clinically and haematologically evident TAM was defined as a peripheral blood blast % >10% thus it is not surprising that this group had a significantly higher blast percentage (p<0.0001) than the Silent
TAM groups, median of 31% (range 10-77%) compared to median of 4.5% (range 1-10%) for the
Silent TAM DHPLC +ve group and median of 5% (range 1-11%) for the Silent TAM DHPLC –ve group (Figure 3.14, Table 3.13). More interestingly, there was no difference in blast percentage between the two Silent TAM groups where GATA1 mutation(s) can be detected in neonates by dHPLC and where it is necessary to do NGS to detect the mutation, p=0.77. Thus, NGS is needed to identify all types of Silent TAM even when the blast percentage is low.
NGS was performed on all neonates with Silent TAM DHPLC –ve and in a total of 30 neonates with clinically and haematologically evident TAM or Silent TAM DHPLC +ve. For all of these cases the size of the mutant GATA1 clone could be calculated by comparing the number of mutant GATA1 reads with the number of total reads from GATA1 exon 2. I was then able to investigate the relationship between the % blasts and mutant GATA1 clone size. This showed that neonates with clinically and haematologically evident TAM not only had a higher peripheral blood blast % but they also had a significantly larger mutant GATA1 clone (p<0.0001) compared to neonates with Silent
TAM (Figure 3.15, Table 3.14). In neonates with Silent TAM, while the peripheral blood blast percentage was similar between the two groups, those with Silent TAM DHPLC +ve had a
84 significantly larger mutant GATA1 clone than those with Silent TAM DHPLC-ve, the latter group thus required a more sensitive method to detect the mutant GATA1 clone with NGS, p=0.03.
Furthermore, correlation analysis identified that mutant GATA1 clone size correlated with blast %
(r=+0.50, p=0.01), WBC count (r=+0.66, p<0.0001), circulating nucleated red blood cells (r=+0.51, p<0.0001), haemoglobin (r=-0.35, p=0.01) and platelet count (r=+0.25, p=0.05), suggesting that
GATA1 mutant haematopoietic stem cells retain the ability to differentiate down the erythroid and megakaryocyte lineage (Figure 3.16). Consistent with this, the clinical variables that significantly correlated with GATA1 clone size were hepatosplenomegaly (p<0.0001), rash (p=0.0005) and effusion/ascites (p=0.03) - Figure 3.17.
Peripheral Clinical TAM Silent TAM Clinical TAM Silent TAM Clinical TAM blood blast (n=35) DHPLC +ve vs Silent DHPLC –ve vs Silent (%) (n=10) TAM (n=27) TAM DHPLC +ve DHPLC -ve (p-value) (p-value) Median blast 31 4.5 <0.0001 5 <0.0001 (%) Range 10-77 1-10 1-11
Table 3.13 Peripheral blood blasts at birth in DS neonates with and without GATA1 mutation(s)
Clinical TAM had a significantly higher blast % (p<0.0001) than the Silent TAM groups with a median of 31%
(range 10-77%) compared to 4.5% (range 1-10%) for Silent TAM DHPLC +ve and 5% (range 1-11%) for Silent
TAM DHPLC –ve.
85 p < 0 .0 0 0 1 * * * * p < 0 .0 0 0 1 1 0 0 * * * * ) 8 0 % ( 6 0 s t
s 5 0 a l b
4 0 d
o 3 0 p = 0 .7 7 o l
b 2 0
l a r
e 1 0 h p i
r 5 e P 0 T A M S T D H P L C + v e S T D H P L C -v e n = 3 5 n = 1 0 n = 2 7
Figure 3.14 Peripheral blood blasts at birth in DS neonates with and without GATA1 mutation(s)
Dot plots showing that clinical TAM had a significantly higher blast % (p<0.0001) than the Silent TAM groups.
There was no difference in blast percentage between the two Silent TAM groups where GATA1 mutation(s) can be detected in neonates by dHPLC and where it is necessary to do NGS to detect the mutation, p=0.77.
GATA1 clone Clinical TAM Silent TAM Clinical TAM Silent TAM Clinical TAM size (n=35) DHPLC +ve vs Silent DHPLC –ve vs Silent (n=10) TAM (n=27) TAM DHPLC +ve DHPLC -ve (p-value) (p-value) Median 17.1 2.5 0.07 0.5 <0.0001
Range 3-82.3 0.6-11.5 0.2-7.7
Table 3.14 Mutant GATA1 clone size at birth in DS neonates with and without GATA1 mutation(s)
86
p < 0 .0 0 0 1 * * * *
1 0 0 p = 0 .0 7 8 0
6 0 5 0 e
z 4 0 i p = 0 .0 3 s
3 0
e 2 0 * n o l
C 1 0
5
0 T A M S T D H P L C + v e S T D H P L C -v e n = 3 5 n = 1 0 n = 2 7
Figure 3.15 Mutant GATA1 clone size at birth in DS neonates with and without GATA1 mutation(s)
Neonates with clinical TAM had a larger mutant GATA1 clone compared to neonates with Silent TAM with a median clone size of 17.1 (range 3-82.3) compared to 2.5 (0.6-11.5) in Silent TAM DHPLC+ve (p=0.07) and
0.5 (0.2-7.7) in Silent TAM DHPLC -ve (p<0.0001). Neonates with Silent TAM DHPLC +ve had a significantly larger mutant GATA1 clone than those with Silent TAM DHPLC-ve (p=0.03).
87 1 0 0 1 0 0
5 0 5 0 e e z z 1 0 1 0 i i s s
e e 5 5 n n o o r= 0 .6 6 l l C C p < 0 .0 0 0 1 1 .0 r= 0 .5 0 1 .0 p = 0 .0 1 0 .5 0 .5
0 .0 0 2 0 4 0 6 0 8 0 1 0 0 0 2 0 4 0 6 0 8 0 1 0 0 9 P e r ip h e ra l b lo o d b la s ts (% ) W B C x 1 0 /L
1 0 0 1 0 0
5 0 5 0 e e z z 1 0 1 0 i i s s
e e 5 r= -0 .3 5 5 n n p = 0 .0 1 o o l l C 1C .0 1 .0 r= 0 .5 1 p < 0 .0 0 0 1 0 .5 0 .5 0 .0 0 1 2 5 1 5 0 2 0 0 2 5 0 0 5 0 1 0 0 1 5 0 9 H b (g /L ) N R B C S x 1 0 /L
1 0 0
5 0 e
z 1 0 i s
e 5 n r= 0 .2 5 o l p = 0 .0 5 1C .0
0 .5
0 .0 0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 9 P la te le ts x 1 0 /L
Figure 3.16 Correlation of mutant GATA1 clone size and haematological variables in DS neonates with GATA1 mutation(s)
Correlation analysis between mutant GATA1 clone size and haematological variables identified that mutant
GATA1 clone size correlated with blast % (r=+0.50, p=0.01), WBC count (r=+0.66, p<0.0001), haemoglobin
(r=-0.35, p=0.01), circulating nucleated red blood cells (r=+0.51, p<0.0001) and platelet count (r=+0.25, p=0.05).
88 p < 0 .0 0 0 1 p = 0 .0 0 0 5 * * * * * * * 1 0 0 1 0 0
5 0 5 0 e e z z 1 0
1 0 i i s s
e e 5 5 n n o o l l C 1C .0 1 .0
0 .5 0 .5
N O H S H S N O R A S H R A S H
p = 0 .0 3 * 1 0 0
5 0 e
z 1 0 i s
e 5 n o l
1C .0
0 .5
N O EFFU S IO N /A S C IT ES EFFU S IO N /A S C IT ES
Figure 3.17 Correlation of mutant GATA1 clone size and clinical variables in DS neonates with
GATA1 mutation(s)
Correlation analysis between mutant GATA1 clone size and clinical variables identified that mutant GATA1 clone size correlated with hepatosplenomegaly (HS) (p<0.0001), rash (p=0.0005) and effusion/ascites (p=0.03).
3.5.4 Peripheral blood film morphological features in DS neonates with and without GATA1
mutation(s)
Since the WHO classification defines TAM solely on the basis of ‘increased blast cells’ in DS neonates (Hasle et al, 2003), without specifying what constitutes ‘increased’ blast cells, I carried out a comprehensive analysis of the cellular composition and morphology of peripheral blood films from
DS neonates with (n= 26) and without GATA1 mutation(s) (n=24) to identify whether there were any morphological features specific to TAM –Figure 3.18, Table 3.15 (using the OIDSCS standard proforma- Appendix 3).
89
I found that trilineage dysplasia was common in DS neonates both with and without GATA1 mutation(s) (Figure 3.18) consistent with earlier work from our laboratory, which was the first study to recognise the high frequency of dysplasia in DS neonates (Roberts et al., 2013). The most frequentfeatures of dyserythropoiesis were macrocytes, target cells and dyserythropoietic nucleated red blood cells. There were no significant differences in the frequency of each of these 3 features between DS neonates with and without GATA1 mutation(s) (p=1.0, 0.41 and 0.58 respectively).
Platelet morphology was abnormal in DS neonates with giant platelets present in almost all DS neonates and was not significantly more common in those with GATA1 mutation(s), p=0.10 (Figure
3.18). However, megakaryocyte fragments were strongly associated with the presence of GATA1 mutation(s), p<0.0001.
Dysplastic neutrophils, monocytes and basophils (EWOG-MDS criteria) were common in both neonates with and without GATA1 mutation(s) including hypogranular neutrophils, pseudo-Pelger forms, stellate monocytes and hypogranular basophils (Figure 3.18). None of these features were significantly different in DS neonates with or without GATA1 mutation(s) (p=0.34, 0.18 and 0.15 respectively). For the first time my work has shown that dysplastic eosinophils were associated with the presence of GATA1 mutation(s), found in 46.2% DS neonates with GATA1 mutation(s) and versus
16.7% DS neonates without GATA1 mutations, p=0.03.. This was an interesting novel finding since
GATA1 is not only essential for the regulation of differentiation and proliferation during erythropoiesis and megkaryopoiesis but also for the development of eosinophils (Hirasawa et al 2002;
Yu et al 2002). In addition, Maroz et alrecently showed that blasts in TAM can differentiate into the eosinophil lineage and are part of the same transient leukaemia cell clone carrying identical GATA1 mutation (Maroz et al., 2014).
90 Blast cell morphology was indistinguishable between neonates with or without GATA1 mutation(s)
(Figure 3.18b). As all DS neonates have morphological haematological abnormalities independent of their GATA1 mutation status, this suggests that trisomy 21 itself causes trilineage perturbation of haematopoiesis.
DS NEO w/out Peripheral blood film GATA1 mutn TAM vs DS NEO morphological features TAM (n=26) (n=24) (p-value) Macrocytes 26 (100%) 23 (95.8%) 1.00 Target cells 24 (92.3%) 20 (83.3%) 0.41 Dyserythropoietic nRBCs 13 (50%) 10 (41.2%) 0.58 Giant platelets 26 (100%) 21 (87.5%) 0.10 Megakaryocyte fragments 23 (88.5%) 3 (12.5%) <0.0001 Dysplastic neutrophils 25 (96.2%) 21 (87.5%) 0.34 Dysplastic monocytes 25 (96.2%) 20 (83.3%) 0.18 Dysplastic basophils 12 (46.2%) 6 (25%) 0.15 Dysplastic eosinophils 12 (46.2%) 4 (16.7%) 0.03
Table 3.15 Peripheral blood film morphological features at birth in DS neonates with and without GATA1 mutation(s)
Trilineage dysplasia (dyserythropoiesis, dysmyelopoiesis and dysmegakaryopoiesis was common in DS neonates with and without GATA1 mutation(s) at birth.
91 p < 0 .0 0 0 1 1 0 0 N o n -T A M (n = 2 4 ) * * * * T A M (n = 2 6 )
s 7 5 e t
a p = 0 .0 3 n
o *
e 5 0 n
f o
% 2 5
0
s s s s s o s ls C s t t o s te l t u o e B e n n a e y l e e o b c c R e n s o t n t m m s y r e a g s y s l y s D c g y p a D a r t fr D y a D n D M T K ia M G
Figure 3.18A Peripheral blood film morphological features at birth in DS neonates with and without GATA1 mutation(s)
Bar chart showing that trilineage dysplasia was common in DS neonates with and without GATA1 mutation(s) at birth. GATA1 mutation(s) were strongly associated with the presence of megakaryocyte fragments (p<0.0001) and dysplastic eosinophils (p=0.03).
92 Dysplastic nucleated red blood cells
Megkaryocyte fragments and giant platelets
Dysplastic neutrophils
Dysplastic monocytes
Dysplastic basophils
Dysplastic eosinophils
Blasts in DS neonates with GATA1 mutation(s)
Blasts in DS neonates w/out GATA1 mutation(s)
Figure 3.18B Peripheral blood film morphological features at birth in DS neonates with and without GATA1 mutation(s)
Peripheral blood film morphological features showing representative trilineage dysplasia.
Dyserythropoietic nucleated red blood cells showed nuclear cytoplasmic asynchrony, binucleate
93 forms and abnormal haemoglobinsation. Giant platelets were frequently seen in DS neonates with and
GATA1 mutation(s). Megakaryocyte fragments were strongly associated with the presence of GATA1 mutation(s). Dygranulopoiesis included dysplastic neutrophils with hypogranular forms and nuclear dysplasia, stellate monocytes, hypogranular basophils and hypogranular eosinophils. Blast cell morphology was indistinguishable between neonates with or without GATA1 mutation(s)
3.6 The natural history of TAM during the first 5 years of life
The OIDSCS was the first prospective study identifying 72 neonates with GATA1 mutation(s) from a total of 163+45=208 neonates who have been fully screened (ie 45 neonates with a GATA1 mutation detected by Ss/DHPLC and 27/163 (15.9%) screened by NGS where a GATA1 mutation detected only by NGS). Since 11.8% of all DS neonates had a GATA1 mutation detected by Ss/DHPLC and a further 15.9% of neonates who did not have a GATA1 mutation detected by Ss/DHPLC were subsequently found to have a small mutant GATA1 detectable only by NGS, this meant that almost
28% of all DS neonates harbour GATA1 mutation(s). Thus far, with a median follow up of 45.5 months (range 4-92 months) 5/72 (6.9%) of these neonates had progressed to ML-DS and are discussed in the next chapter.
All other neonates underwent spontaneous remission and Figure 3.19(a-c) show the natural history over the first 5 years of life in these neonates with GATA1 mutation(s).These graphs suggest that the natural history of TAM was variable. Neonates with clinically and haematologically evident TAM had leucocytosis and thrombocytopenia in the first 3 months of life which predominantly resolved by
12 months of age. Neonates with Silent TAM had normal white blood cell, platelet and haemoglobin values with little variation in these parameters.
94 In the OIDSCS, 4/35 (11.4%) neonates with clinically and haematologically evident TAM required treatment with at least one short course of low dose cytosine arabinoside (Ara-C) at a median of 22 days after birth (range 3-42 days)- (Table 3.16). The indication for treatment in each of these 4 neonates varied and was dependent on physician preference. Hepatosplenomegaly and liver dysfunction were commonly found in these neonates, indicating organ infiltration with blasts confirmed on hepatic biopsy in one neonate (TAM ARA-C 1). All four neonates had significant respiratory compromise requiring invasive ventilatory support due to pressure effect from organomegaly and presence of end-organ involvement (pleural effusion in TAM ARAC-1 and ascites in TAM ARAC-2). Of these four neonates, two neonates underwent sustained clinical and haematological remission post Ara-C treatment (Figure 3.20) and two neonates progressed to ML-DS.
One neonate (TAM ARAC-3) had persistent disease despite four courses of low dose Ara-C and another neonate (TAM ARAC-2) progressed to ML-DS after initial TAM resolution and received a seven day course of Ara-C for leukaemia treatment with good effect (further details in Chapter 4).
This compares to 2/31 neonates with TAM who did not receive Ara-C- Table 3.17. Therefore, my data suggests that treatment with Ara-C does not have an impact on TAM progression to ML-DS.
However, there were many potential confounding factors and as the number of patients in this analysis is small this data is difficult to interpret.
95 H b (g /L ) 9 / 5 0 0 7 0
W B C (x 1 0 L ) )
9 / L
4 5 0 4 5 /
) P la te le ts (x 1 0 L ) 9 6 0 L
0 4 0 0 / 4 0 9 3 7 5 1 0 W x ( 1
3 5 5 0 W B
x 3 0 0
s 3 0 0 ( t
C B s 3 0 e C
t 2 2 5 l
4 0 ( e e x
l
t 2 0 0 1 2 5 ( e x a t 0 l 1
a 3 0 1 5 0 9 l P 2 0 0 /
L
9 1 5 0 P /
/ )
) L / 1 5
) 2 0 ) 1 0 0 L / 1 0 0 L / 1 0 g ( g
( 1 0 5 0
b 5 0
b 5 H H 0 0 0 0 6 8 2 0 8 6 2 5 8 1 4 6 0 3 7 0 2 5 4 2 4 6 4 6 8 0 8 1 0 0 4 1 2 2 3 5 1 1 2 2 3 3 1 1 2 3 4 1 2 3 4 6 1 3 D D D D W W D D D M W W W W W M M M M M W W W W W M M M M M CH TAM 1 CH TAM 2
4 5 0 2 0 4 5 0 1 4 0 ) ) L L / / 9 9 1 2 0 0 0 3 7 5 3 7 5 1 1 W W x x 1 5 ( ( 1 0 0
B B s s 3 0 0 C C t t 3 0 0 e e
l l 8 0 ( ( x x e e t t
1 0 2 2 5 1 1 a a l l 0 0 2 2 5 6 0 9 9 P P
/ /
L L / / ) ) ) ) 4 0 L
L 1 5 0
/ 1 5 0 / 5 g g ( ( 1 0 0
2 0 1 0 0 b b 5 0 1 0 H
H 5 0 0 0 0 0
2 2 8 8 6 5 8 1 5 0 6 8 0 2 5 8 0 8 8 2 5 4 2 5 1 4 7 5 2 6 0 0 5 1 1 2 3 1 1 2 2 3 3 2 4 1 4 1 1 2 3 1 2 2 2 5 3 D D 1 D D W W D D W W W W W M M M M M M W M M W W W W M M M M M D CH TAM 3 CH TAM 4
Figure 3.19A Representative plots showing the natural history of clinical and haematological evident TAM during the first five years of life
Representative line graphs for four neonates with clinical and haematological evident TAM showing sequential haemoglobin (g/L), platelets (x109/L) and white blood cells
(x109/L) during the first five years of life in neonates with clinically and haematologically evident TAM (n=4). For some neonates follow up is <5 years since they presented
<5 years ago- for these neonates results from the last date of follow up are presented. Neonates with clinically and haematologically evident TAM had leucocytosis and thrombocytopenia in the first 3 months of life which resolved by 12 months of age
96 H b ( g /L ) 9 / P la te le ts (x 1 0 L ) 4 5 0 1 2 9 / ) W B C (x 1 0 L ) L / 4 0 0 9
0 1 0
1 3 5 0 W x (
B
s 3 0 0 8 t C e
l 2 5 0 ( e x t
6 1 a 0 l 2 0 0 9 P / ST DHPLC+ve 1 L
/ 4 ) )
L 1 5 0 / g
( 1 0 0
2
b 5 0 H 0 0 8 8 8 6 2 5 2 6 8 0 3 7 0 1 2 3 5 1 1 1 1 3 D D D W D W W W W M W W M
4 5 0 2 0 ) L / 4 0 0 9 0
1 3 5 0 W
x 1 5 (
B
s 3 0 0 C t e
l ST DHPLC+ve 2 (
2 5 0 x e t 1 0 1 a l 2 0 0 0 9 P
/
L / ) )
L 1 5 0
/ 5 g
( 1 0 0
b 5 0 H 0 0
8 2 5 8 1 2 0 6 4 6 8 0 2 0 0 2 5 1 1 2 1 2 3 2 3 3 D D 1 W D W W M M M W W W M M D
Figure 3.19B The natural history of Silent TAM DHPLC+ve during the first five years of life
Representative line graphs of two neonates with Silent TAM DHPLC +ve showing sequential haemoglobin (g/L), platelets (x109/L) and white blood cells (x109/L) ) during follow up- for these two neonates follow up at present is <2years. Neonates with Silent TAM DHPLC+ve had normal Hb and WBC count with little variation in these parameters. Thrombocytopenia was present at birth but resolved by 3 months age.
97 H b (g /L ) 9 / 7 0 0 2 0 P la te le ts (x 1 0 L ) ) 4 5 0 2 0 L 9 / / 6 0 0 ) W B C (x 1 0 L ) 9 L 0 / 4 0 0 5 0 0 9 1 0 W x 4 0 0 1 5 ( 1
3 5 0 W x 1 5 B s ( 3 0 0
t C B s
3 0 0 e t
l C 2 0 0 ( e e x
l t (
2 5 0 1 0 1 e x a t
1 5 0 0 l 1 0 1 a 9 0 l 2 0 0 P /
9 L P
/
/ L
) ) / 1 5 0 1 0 0 ) ) L /
L 5
/ 5 1 0 0 g ( g
( 5 0
b
b 5 0 H H 0 0 0 0
8 1 2 0 8 6 2 5 6 0 0 3 7 0 2 0 8 6 2 5 4 8 8 8 0 2 0 0 2 1 2 2 3 5 1 3 6 3 1 2 2 3 5 1 2 4 6 3 D D D D D 1 W W D D W W W W W M M M M M W W W W W M M M D ST DHPLC-ve 1 ST DHPLC-ve 2
4 5 0 2 0 4 5 0 3 0 ) ) L L / / 4 0 0 4 0 0 9 9 0 0 2 5 1 1 3 5 0 3 5 0 W W x x 1 5 ( (
B B s s 3 0 0 3 0 0 2 0 C t t C e e
l l ( 2 5 0 ( 2 5 0 x e x e t t
1 0 1 5 1 1 a a 0 l l 2 0 0 0 2 0 0 9 9 P P /
/ L
L / / 1 5 0 1 0
1 5 0 ) ) ) ) L L / / 1 0 0 5 1 0 0 g g ( (
5
b b 5 0 5 0 H H 0 0 0 0
8 2 8 4 2 0 6 5 6 8 0 3 0 8 2 0 8 6 2 5 1 6 0 3 7 0 4 2 5 1 2 1 2 3 1 3 3 1 2 2 3 5 1 2 3 3 D D 1 D D D W W D D W W M M W W W M M W W W W W M M M D ST DHPLC-ve 3 ST DHPLC-ve 4
Figure 3.19C The natural history of Silent TAM DHPLC-ve during the first five years of life
Representative line graphs for four neonates with Silent TAM DHPLC-ve showing sequential haemoglobin (g/L), platelets (x109/L) and white blood cells (x109/L) within normal parameters during the first five years of life. For some neonates follow up is <5 years since they preseted <5 years ago- for these neonates results from the last date of follow up are presented.
98
TAM ARA-C 1 TAM ARA-C 2 TAM ARA-C 3 TAM ARA-C 4 Gestation (weeks) 36.9 37.1 36.1 39.6
Birth weight (kg) 1.99 3.05 2.47 2.72
IUGR (Y/N) Y N N N
Time Ara-C treatment 6 3 38 42 given (days after birth) Multiple courses of Ara- N N N Y (4 courses) C given (Y/N) Length of Ara-C 7 9 7 5, 10, 7, 5 treatment (days) Hepatomegaly (cm) 5 3 7 6
Splenomegaly (cm) 7 4 5 5
Liver impairment (Y/N) Y Y Y N
Pleural/pericardial Y Y N N effusion +/- Ascites (Y/N) Invasive respiratory Y Y Y Y support (Y/N) Subsequent ML-DS N N Y (1.25) Y (4) Y (age-months)/N
Table 3.16 Clinical features of four neonates with TAM who received treatment with cytosine arabinoside
All four neonates had clinical features of multi-organ dysfunction. Two neonates underwent long-term remission following a single course of Ara-C and two progressed to ML-DS.
99 H b (g /L ) 9 / P la te le ts (x 1 0 L ) 9 / W B C (x 1 0 L ) 4 5 0 2 5 ) W L
/ 3 7 5 9 B
0 A ra -C
3 0 0 C
1 2 0 / x P ( 2 2 5
l s a t t e 1 5 e l
1 5 0 l e e t t a TAM ARA-C 1 s l
P 1 0 (
x
1 0 0 / 1 ) 0 L / 9 / g 5 L
( 5 0
) b H 0 0 1 4 8 2 6 0 2 6 9 4 6 8 8 2 7 1 0 1 2 2 3 3 4 5 1 1 2 3 4 2 3 D D W D D W W W W W W W M M M M M
4 5 0 7 0 ) L /
9 6 0
0 3 7 5 1 W x (
5 0 B
s 3 0 0 t C
e A ra -C
l
4 0 ( e x t
2 2 5 1 a
TAM ARA-C 2 0 l 3 0 9 P /
L
/ ) ) 2 0
L 1 5 0 / g
( 1 0 0 1 0 b 5 0 H 0 0
4 5 8 0 5 2 8 2 6 8 2 1 4 0 8 0 3 0 4 2 1 1 4 4 1 2 3 3 4 5 2 2 5 3 D D 1 W D W M M M M W W W W W W M M M D
Figure 3.20 Representative plots of haemoglobin, white blood cell count and platelets in two neonates with TAM who received treatment with cytosine arabinoside and underwent sustained remission
Representative line graphs showing sequential haemoglobin (g/L), platelets (x109/L) and white blood cells (x109/L) of two neonates with TAM who received a short course of
Cytosine Arabinoside and subsequently underwent remission. Both neonates had multi-lineage haematological abnormalities.
100
Treated with Ara-C Not treated with Ara-C
Number of patients with GATA1 4 31 mutation(s)
Death in first 3 months of life 0 0
Clone size, median (range) 13.3 (3.3-27.0) 17.2 (3.0-82.3)
Number of patients with TAM 2 2 progression to ML-DS (%) (50%) (6.6%)
Table 3.17 The impact of treatment with cytosine arabinoside (Ara-C) on TAM progression to
ML-DS
3.7 Summary and Discussion
Although retrospective studies have reported the presence of several clinical and haematological abnormalities in TAM (Masseyet al., 2006; Klusmann et al., 2008; Gamis et al., 2011) none of these studies have systematically studied either blood films or GATA1 mutation status together with clinical features. Using data from the OIDSCS, my work has for the first time described the true clinical and haematological spectrum of TAM.
In this cohort, the overall frequency of GATA1 mutation(s) was 3-fold higher than previous estimates as 11.8% (45/382 neonates) of all DS neonates have a GATA1 mutation detected by Ss/DHPLC and a further 15.9% (27/163 tested) neonates who did not have a GATA1 mutation detected by Ss/DHPLC were subsequently found to have a small mutant GATA1 detectable only by NGS, this means that almost 28% of all DS neonates harbour GATA1 mutation(s).
101 My work showed that three clinical features are strongly associated with TAM: hepatomegaly, splenomegaly and skin rash, in that they are significantly more common in TAM and may be directly related to the size of the mutant GATA1 clone and organ infiltration by blasts as they are not seen in
Silent TAM. However, no clinical features were diagnostic for TAM as the same signs could also be seen in a proportion of DS neonates without a GATA1 mutation.
I found that DS neonates with and without a GATA1 mutation(s) had several haematological abnormalities, implying that trisomy 21 has a direct consequence on haematopoiesis rather than the presence of a GATA1 mutation. Comprehensive analysis of haematological indices at birth showed that thrombocytopenia is a common feature in both DS neonates with and without a GATA1 mutation(s) compared to healthy neonates without DS with no significant difference between DS neonates separated depending on their GATA1 mutational status. Neonates with GATA1 mutation(s) had a higher white cell count than DS neonates without a GATA1 mutation suggesting that both trisomy 21-mediated effects as well as the presence of a GATA1 mutation(s) are likely to be responsible for these changes. However, no haematological features were diagnostic of TAM as there was a considerable overlap in haematologcial parameters in DS neonates with and without GATA1 mutation(s).
Similar to Roberts et al, I found that all DS neonates had morphological haematological abnormalities independent of their GATA1 mutation status suggesting that trisomy 21 itself causes trilineage perturbation of haematopoiesis (Roberts et al., 2013). I found that blast cell morphology was indistinguishable between neonates with or without GATA1 mutation(s) however megakaryocyte fragments were strongly associated with the presence of GATA1 mutation(s). In addition to this, I showed for the first time that eosinophil dysplasia was strongly associated with the presence of
GATA1 mutation(s).
102 I looked at the relationship between peripheral blood blast percentage and GATA1 mutation status in
DS neonates for the first time and found that neonates with clinically and haematologically evident
TAM not only had a higher peripheral blood blast percentage but they also had a significantly larger mutant GATA1 clone compared to neonates with Silent TAM. Neonates with Silent TAM DHPLC
+ve had a significantly larger mutant GATA1 clone than those with Silent TAM DHPLC-ve but there was no difference in blast percentage between the two Silent TAM groups thus NGS is needed to identify all types of Silent TAM even when the blast percentage is low. NGS was introduced as a sensitive method for GATA1 mutation analysis after the OIDSCS interim analysis of 200 neonates, which showed increased peripheral blood blasts in the absence of a GATA1 mutation by Ss/DHPLC
(Roberts et al., 2013). Its use is currently being evaluated only as a research tool as part of the
OIDSCS. The significance of these small mutant GATA1 clones is yet to be determined and therefore at present cannot be used to determine clinical management.
In conclusion, neonates with TAM did not have any diagnostic clinical, haematological or morphological features that were not present in neonates without TAM. The three categories of
‘clinical TAM’, ‘Silent TAM DHPLC-ve’ and ‘Silent TAM DHPLC +ve’ are inaccurate and
Ss/DHPLC methodology for GATA1 analysis are insensitive and do not identify all neonates with
GATA1 mutation(s) . For the first time, my work provides an accurate definition of TAM based on the presence of a GATA1 mutation detected by a sensitive method, NGS.
103 CHAPTER 4 - The natural history of TAM
evolution to ML-DS
104 THE NATURAL HISTORY OF TAM AND EVOLUTION TO ML-DS
4.1 TAM and ML-DS as a model of myeloid leukaemogenesis
All cases of TAM have acquired mutation(s) in exon 2 or exon 3 of the key haematopoietic transcription factor GATA1 (Wechsler et al., 2002; Mundschau et al., 2003; Hitzler, et al., 2003;
Yoshidaet al., 2013). Paired ML-DS and TAM samples show the same GATA1 mutation, indicating they are clonally-linked conditions (Ahmedet al., 2004). GATA1 mutation(s) are an early pathogenic event and ML-DS is considered to evolve from a clone of TAM cells (Hitzler et al., 2003; Yoshidaet al., 2013). The unique sequence of TAM and ML-DS as successive stages in the process of leukaemia transformation provides a platform to study the nature of events in leukaemogenesis. GATA1 mutation(s) are necessary for development of ML-DS as they are required for initiation of clonal proliferation but they alone are insufficient since the same GATA1 mutations are present in TAM and
ML-DS (Rainis et al., 2003). Recent studies have identified a large number of additional mutations needed to transform TAM blast cells to ML-DS (Nikolaevet al., 2013; Yoshida, et al., 2013).
Retrospective studies indicated that in some cases there was overt progression of TAM to ML-DS with persistent abnormal haematology and an indolent myelodysplastic phase and in other cases there was a variable apparent remission before development of ML-DS (Hitzleret al., 2003; Klusmann et al., 2008; Massey et al., 2006; Gamiset al., 2011). However, in these studies there was variable follow up of neonates with TAM and the true natural history of TAM progression to ML-DS is not known since no previous prospective studies have been performed.
4.2 Aim
The aim of the studies described in this chapter is to characterise the natural history of evolution to
ML-DS.
105
4.3 Experimental approach
To investigate the natural history of the evolution of ML-DS, I studied in detail all DS infants in the
OIDSCS cohort who progressed to ML-DS during the first 5 years of life. I comprehensively analysed and integrated the clinical, serial haematological and cytogenetic data of these 5 neonates. GATA1 gene mutational analysis was performed by Dr. Kate Alford and Dr. Kelly Perkins in Professor Paresh
Vyas’ lab and Dr Natalina Elliott in Professor Roberts’ lab, Weatherall Institute of Molecular
Medicine, John Radcliffe Hospital, University of Oxford. Otherwise I performed all the experiments and analyses described here.
4.4 Defining the natural history of TAM evolution to ML-DS
4.4.1 Clinical features in neonates with TAM evolution to ML-DS at birth and time of
progression to ML-DS
In the OIDSCS cohort 5/72 (6.9%) neonates with GATA1 mutation(s) progressed to ML-DS at a median interval of 56 weeks (range 6-72 weeks) including one neonate with Silent TAM and 4 neonates with TAM. The clinical features at birth of these 5 neonates are summarised in Table 4.1.
There was no difference in gender, gestation or birth weight between neonates with TAM evolution to
ML-DS compared to neonates with TAM who underwent spontaneous regression (Figure 4.1).
Hepatomegaly and liver dysfunction at birth were common in neonates with TAM progressing to ML-
DS suggesting hepatic infiltration by blasts with the mutant GATA1 clone(s) although none of these neonates underwent liver biopsy to formally demonstrate this. Jaundice was a common feature in both neonates with TAM that progressed to ML-DS and those that underwent spontaneous regression.
Indeed, jaundice was seen in the majority of DS neonates at birth as discussed in chapter 3. Rash was found in both groups those with TAM evolution to ML-DS and those that underwent spontaneous
106 regression. Thus, no specific clinical feature at birth can identify neonates with GATA1 mutation(s) at risk of progressing to ML-DS. Importantly, in this cohort, no neonates without GATA1 mutation at birth (detected by Ss/dHPLC) transformed to ML-DS.
At time of progression from TAM to ML-DS, all 5 neonates had hepatomegaly (Figure 4.2) suggesting that there might be hepatic infiltration by leukaemic blasts also at the ML-DS stage of the disease. While liver dysfunction at birth was common in this group, in the majority of neonates this resolved and only 1/5 (20%) had evidence of persistent liver dysfunction at time of ML-DS transformation. Petechiae and bruising was a common feature of ML-DS secondary to thrombocytopenia as discussed below.
107 Clinical features at birth Neonates with Neonates with p-value GATAT1 mutation GATAT1 progressing to ML-DS mutation without (n=5) ML-DS (n=67) Gender (M:F) 2(40%):3 (60%) 35(52%):32(48%) 0.67
Median Gestation (weeks, range) 36.9 (36.1-39.6) 38 (31.7-41.9) 0.68
Median Birth weight (kg, range) 2.72 (2.47-3.18) 2.89 (1.67-3.99) 0.99
IUGR 0 14 (21%) 0.56
Hepatomegaly 3 (60%) 11 (16%) 0.04
Liver dysfunction 3 (60%) 2 (3%) 0.001
Coagulopathy 2 (40%) 4 (6%) 0.05
Jaundice 4 (80%) 44 (66%) 0.66
Rash 1 (20%) 4 (6%) 0.31
Table 4.1 Demographic and clinical features at birth of neonates with GATA1 mutation(s) progressing to ML-DS compared to those without later ML-DS
108 1 0 0 M ale s
e F e m a le t a
n 7 5 o
e p = 0 .6 7 n
A f o
5 0 e g a t n
e 2 5 c r e P 0 M L -D S T A M n = 5 n = 6 7
4 5 p = 0 .6 8 ) s k e e w ( 4 0 h t r i
B b
t a
n 3 5 o i t a t s e G 3 0 M L -D S T AM n = 5 n = 6 7
5 p = 0 .9 9 C
) 4 g k (
t 3 h g i e w
2 h t r i
B 1
0 M L -D S T AM n = 5 n = 6 7
Figure 4.1 Demographic features of neonates with GATA1 mutation(s) progressing to ML-DS compared to those without later ML-DS
Bar char and dot plots showing no difference in (A) gender (p=0.67), (B) gestation (p=0.68) and (C) birth weight (p=0.99) between neonates with GATA1 mutation(s) progressing to ML-DS compared to those without later ML-DS.
109 1 0 0 N o s
e Y e s t a
n 7 5 o e n
f o
5 0 e g a t
A n e 2 5 c r e P 0
n ia ly io n a t e g c p e n o u t m f y o s c t y a o p d b r e e m H o iv r L h T
M L -D S 1 1 0 M L -D S 2 M L -D S 3
) M L -D S 8 M L -D S 4 m
c M L -D S 5
B (
y l 6 a g e M L -D S m M L -D S
o 4 t a
p M L -D S
e M L -D S
H 2
0 0 3 6 9 1 2 1 5 1 8 2 1 2 4 T im e (m o n th s )
Figure 4.2 Clinical features of neonates with GATA1 mutation(s) at time of evolution to ML-DS
(A) Bar chart showing that hepatomegaly was present in all neonates (n=5) with GATA1 mutation(s) at time of disease progression to ML-DS but not necessarily associated with liver dysfunction (seen in 1/5 (20%) neonates with TAM progression to ML-DS). Thrombocytopenia was common (4/5 (80%) cases) at time of TAM evolution to ML-DS.
(B) Line graph showing hepatomegaly was present at birth in 3/5 (60%) neonates with GATA1 mutation(s) and evolution to ML-DS (ML-DS2, ML-DS3, ML-DS4) and in all these neonates at time of disease transformation to ML-DS.
110 4.4.2 Haematological features of neonates with TAM evolution to ML-DS
Figure 4.3 shows plots of haemoglobin (g/L), platelet count (x109/L) and white blood cell count
(x109/L) in neonates with TAM before and during evolution to ML-DS. This shows that the sequential changes in haematological parameters during progression to ML-DS were variable.
ML-DS 1 had leucocytosis and thrombocytopenia at birth which persisted for the first 4 weeks and gradually resolved by 6 months of age. In parallel, the peripheral blood blast percentage was high at birth and was associated with the presence of a GATA1 mutation (detected by Ss/DHPLC). There was spontaneous regression of peripheral blood blasts and the mutant GATA1 clone with re-emergence of the GATA1 clone at 21 months associated with reappearance of peripheral blood blasts, leucocytosis and thrombocytopenia indicating disease transformation to ML-DS. The haemoglobin remained normal during the disease course.
ML-DS 2, had leucocytosis and a high peripheral blood blast percentage (42%) at birth associated with the presence of a GATA1 mutation which gradually resolved within the first 3 months of life.
However, there was no associated thrombocytopenia at birth and the haemoglobin was normal. A small mutant GATA1 clone was detected by NGS only at subsequent follow up at 6, 9 and 12 months though this was not associated with any haematological abnormalities apart from a fall in the platelet count from 280 x 109/L to 159 x 109/L at 12 months of age and 99 x 109/L at 14 months of age. No peripheral blood blasts were seen until 14 months of age (1%). At 15 months there was disease progression to acute leukaemia as evidenced by a marked increase in peripheral blood blasts (28%), thrombocytopenia, a rise in WBC and re-emergence of the mutant GATA1 clone detected by
Ss/DHPLC. Additional cytogenetic abnormalities were also found and these are discussed below.
This case highlights the importance of sensitive and accurate methods for detecting GATA1 mutations for monitoring disease. Following AML chemotherapy, the mutant GATA1 clone disappeared and there was normal haematopoiesis. However, there was disease relapse within six months of
111 completing chemotherapy as evidence by re-emergence of the mutant GATA1 clone, increase in peripheral blood blasts, thrombocytopenia and anaemia. Despite salvage chemotherapy the bone marrow blast percentage continued to increase and the patient was treated with palliative care.
ML-DS 3 had leucocytosis and thrombocytopenia at birth associated with a high peripheral blood blast percentage (23%) and the presence of GATA1 mutations, similar to ML-DS 1. This neonate did not undergo regression of TAM despite 4 short courses of cytosine arabinoside (Ara-C) (range 5-10 days) at age 2-3 months and instead had a rising WBC and increase in peripheral blood blasts with persistent GATA1 mutations. Additional cytogenetic abnormalities were identified at age 3 months on a bone marrow aspirate with clonal evolution at 4 months indicating progressive disease to ML-DS.
This neonate had two GATA1 clones at time of initial presentation with TAM and both these mutations were found at the time of disease progression (Table 4.2).
ML-DS 4 had leucocytosis and a high peripheral blood blast percentage (40%) associated with the presence of a GATA1 mutation at birth. The platelet count and haemoglobin were normal at birth.
Leucocytosis gradually resolved within the first 4 weeks of life, however at 6 weeks there was a rise in WBC associated with an increase in peripheral blood blasts. A GATA1 mutation was again detected, identical to one of the mutant GATA1 clones at birth.. Treatment with 7 days of Ara-C resulted in resolution of normal haematological parameters and decline of peripheral blood blasts with no GATA1 mutation detected to date (patient now aged 3 years).
For the first time, my data clearly show that ‘silent’ TAM can also progress to ML-DS: ML-DS 5 had a normal haemoglobin and WBC at birth with a low percentage of peripheral blood blasts (range 0-
5%). However, there was thrombocytopenia at birth that persisted during the first year of life and was associated with a small GATA1 mutant clone detected by NGS only. At 18 months, there was
112 worsening thrombocytopenia with a reappearance of peripheral blood blasts (22%) indicating disease progression to ML-DS.
Following AML chemotherapy in four of the above neonates, normal haematological parameters were achieved with the absence of peripheral blood blasts and no GATA1 mutation(s) detected to date, with a median follow up of 37 months (range 21- 56 months). One infant had leukaemia relapse, six months after completing AML chemotherapy with progressive disease despite salvage treatment.
113 A) ML-DS 1
4 5 G A T A 1 m u tn H b (g /L ) 9 / P la te le ts (x 1 0 L ) 5 2 5 3 0 9 / ) W B C (x 1 0 L ) L / 4 5 0 9 0 1
3 7 5 ) W x (
B % ( s 3 0 0 2 0 C
t 3 0 t
e A M L
l ( s
2 2 5 x e A M L a t
c h e m o l 1
a N o G A T A 1 l 1 5 0 0 B c h e m o 9 P
/
m u tn L / 1 0 ) ) N o G A T A 1 L
/ 1 0 0 d e te c te d
g 1 0 G A T A 1 m u tn m u tn d e te c te d ( 5 0 b H 0 0 0 8 2 6 0 4 8 2 6 0 2 5 8 1 4 8 0 3 7 0 1 1 2 2 2 3 3 4 5 1 1 2 2 4 3 D D D W 0 4 8 1 2 1 6 2 0 2 4 3 6 4 0 4 4 4 8 D W W W W W W W W W M M M M M T im e d (d a y ) w (w e e k ) m (m o n th ) T im e (m o n th s )
B) ML-DS 2
H b (g /L ) 6 0 0 9 0 9 /
) P la te le ts (x 1 0 L ) G A T A 1 9 / L
/ W B C (x 1 0 L )
5 2 5 e m u tn 9 5 0 s 0 7 5 1 4 5 0 p W x a A M L c h e m o ( l
B
3 7 5 e s 6 0 r C t
e 4 0
l L 3 0 0 ( x A M L ) e G A T A 1 m u t n t M 4 5 1 % a (
l 2 2 5 A
c h e m o 0
H ig h h y p e r d ip lo id y ( 5 3 c h r )
t G A T A 1 9 P
s /
1 5 0 L / 3 0 a 3 0 m u tn l ) ) L B A M L re la p s e / G A T A 1 m u tn
g 1 0 0 (
1 5 G A T A 1 m u tn (N G S ) b 5 0 2 0 (N G S ) G A T A 1 m u tn H 0 0 1 0 2 6 0 4 8 2 6 0 2 5 8 1 4 6 8 3 7 0 1 1 1 2 2 2 3 3 4 5 1 1 2 2 2 3 0 D D D W D W W W W W W W W W M M M M M 0 4 8 1 2 1 6 2 0 2 4 4 0 4 8 T im e d (d a y ) w (w e e k ) m (m o n th ) T im e (m o n th s )
114 C) ML-DS 3
H b (g /L ) A M L c h e m o 9 / A ra -C P la te le ts (x 1 0 L ) 9 / W B C (x 1 0 L ) G A T A 1 m u tn 1 1 0 0 1 5 0 ) 4 7 ,X Y , + 2 1 c + 2 1 (9 % ) W L
/ A ra -C 9 0 9 4 5 0 B 0 C 1 A M L c h e m o 7 5 / x P ( 3 7 5 7 5
l a s t t e e 3 0 0 l ) 3 0 l 6 0 e e t % t ( s a 2 2 5 l t
P s ( 4 5 2 0 x
a
/ G A T A 1 m u tn l
1 5 0 1 ) B 0 L 4 7 ,X Y , + 2 1 c + 2 1 (6 % ) / 9 /
g 3 0 L
( 1 0 0 1 0
)
b 5 0 N o G A T A 1 m u tn
H N o G A T A 1 m u tn 0 0 1 0 8 2 6 0 4 8 2 6 0 2 5 8 0 2 7 0 1 1 2 2 2 3 3 4 5 1 1 3 0 D D D W D W W W W W W W W W M M 0 4 8 1 2 1 6 2 0 2 4 2 8 3 2 4 0 4 8 T im e d (d a y ) w (w e e k ) m (m o n th ) T im e (m o n th s )
D) ML-DS 4
H b (g /L ) A ra -C 9 / G A T A 1 m u tn 4 5 0 3 5 P la te le ts (x 1 0 L ) 4 5
) 9 /
L W B C (x 1 0 L ) /
9 3 7 5 3 0 A M L c h e m o 0 1 W x
( 3 0 0
2 5 B G A T A 1 m u tn s
) 3 0 C t e
% l 2 2 5 2 0 ( ( x e
t t
1 a s l 1 5 0 0
1 5 a 9 l P
/
L B / ) 1 0 ) 1 5 L
/ 1 0 0
g N o G A T A 1 m u tn ( 5 0 5 b H 0 0 0 8 6 0 4 8 2 6 0 2 5 2 0 2 7 0 8 1 4 1 2 2 2 3 3 4 5 1 1 3 1 2 2 D D D W 0 4 8 1 2 1 6 2 0 2 4 3 2 4 0 4 8 D W W W W W W W W M W M M M T im e d (d a y ) w (w e e k ) m (m o n th ) T im e (m o n th s )
115 E) ML-DS 5
H b (g /L ) A M L c h e m o 9 / 4 5 0 1 0 .0 P la te le ts (x 1 0 L ) ) 9 /
L W B C (x 1 0 L ) / G A T A 1 m u tn
9 3 7 5 2 5 0 1 W
x 3 0 0 7 .5 (
B 2 0 G A T A 1 m u tn s
A M L C t 2 2 5 e
(N G S ) l (
c h e m o x ) e t 1 5 0 5 .0 1 % 1 5 a ( l 0
t 9 P
s / G A T A 1 m u tn
L / a l ) 1 0 0 ) 1 0 (N G S ) L B
/ 2 .5 g
( G A T A 1 m u tn
5 0
b 5 (N G S ) N o G A T A 1 m u tn H 0 0 .0 8 2 6 0 4 8 2 6 0 2 5 8 1 4 0 3 7 0 1 1 2 2 2 3 3 4 5 1 1 2 2 3 0 D D D W D W W W W W W W W W M M M M 0 4 8 1 2 1 6 2 0 2 4 3 2 4 0 4 8 T im e d (d a y ) w (w e e k ) m (m o n th ) T im e (m o n th s )
Figure 4.3 Haematological features of neonates with GATA1 mutation(s) progressing to ML-DS
Line graphs showing sequential haemoglobin (g/L), platelet count (x109/L), white blood cell count (x109/L) and peripheral blood blasts in five neonates with GATA1 mutation(s) before and during evolution to ML-DS (A) ML-DS1, (B) ML-DS2, (C) ML-DS3, (D) ML-DS4, (E) ML-DS5. These plots show that sequential changes in haematological parameters during progression to ML-DS were variable.
116 4.4.3 Molecular features of neonates with TAM evolution to ML-DS
GATA1 mutation(s) alone are insufficient to allow disease progression to ML-DS; additional genetic events are necessary for transformation from TAM to ML-DS. Each of the five neonates with TAM evolution to ML-DS in the OIDSCS study had detailed molecular analysis performed on paired TAM and ML-DS samples at the PV lab by Dr Kelly Perkins using whole-exome sequencing. This showed mutations in cohesion complex genes (RAD21, STAG2, SMC1), epigenetic regulators (KANSL1,
KDM6A, MLL), CTCF mutations and activating mutations in genes in common tyrosine signaling pathways such as MPL (Table 4.2). Similar mutations have also been identified by Nikolaev et al and
Yoshida et al -Table 4.3 (Nikolaev et al., 2013; Yoshida et al., 2013). The proteins encoded by these genes are involved in organising major areas of transcription along and between chromosomes.
117 GATA1 Additional genetic GATA1 mutation(s) at events at Cytogenetics at progression to mutation(s) at progression to transformation to ML-DS presentation ML-DS ML-DS RAD21 c.G185A:p.G62E GATA1 SRSF2 c.187_188ins11fs c.C284T:p.P95L ML-DS GATA1 GATA1 MLL 47,XX, +21c 1 c.187_188ins11fs c.112dupCfs c.G340A:p.A114T GATA1 KANSL1 c.59delAfs c.C934T:p.Q312X MPL c.T1475C:p.I492T ML-DS GATA1 GATA1 SMC1A 53,XY,+Y,+13,+14,+19,+21c,+22 2 c.220+1g>t:SD c.220+1g>t:SD p.R711Q STAG1 c.T671A:p.L224Q 3 months: ML-DS GATA1 GATA1 MLL 4 months: 47,XY, 47,XY, +21c 3 c.90_91delAGfs c.90_91delAGfs c.G340A:p.A114T +21c +21 (9%) +21 (6%) MLL c.4479+2T>C GATA1 ML-DS c.220+1g>a GATA1 MPL 47,XX, +21c 4 GATA1 c.220+3a>t c.T1535C:p.L512P c.220+3a>t CTCF p.Y523* ML-DS GATA1 GATA1 KDM6A 46,XX,der (21) (qter- 5 c.101_102insC c.101_102insC p.Q240R >22.1;p11.2->qter) SRSF2 c.C284T:p.P95L
Table 4.2 GATA1 mutation(s), additional genetic events and cytogenetics in neonates with TAM evolution to ML-DS
Paired TAM and ML-DS samples showed that the same GATA1 mutation is present at disease presentation and evolution to ML-DS. In addition, there were mutations in cohesion complex genes (green), CTCF mutations
(purple), epigenetic regulators (blue) and other mutations affecting common signalling pathways (pink). In one neonate there was clonal evolution at time of TAM progression to ML-DS and in another there was hyperdiploidy; 2 neonates had no cytogenetic abnormalities and one neonate had partial trisomy 21.
118 Gene Pathway Mutation frequency RAD21 STAG2 Cohesion complex 53% NIPBL SMC1/SMC3 CTCF CTCF mutation 20% EZH2 KANSL1 Epigenetic regulator 45% SUZ12 NRAS/KRAS/PTPN11/CBL RAS pathway Tyrosine kinase/cytokine receptor 47% JAK1/JAK2/JAK3/MPL mutations TP53 Common signaling pathway <1% SH2B3 SRSF2 WT1 Other <1% DCAF7
Table 4.3 Frequency of mutated genes other than GATA1 in ML-DS samples in whole-exome sequencing identified by Yoshida et al, 2013.
Recurrent mutations have been found in cohesion complex genes, CTCF mutations and epigenetic regulators and common signaling pathways similar to those found in the OIDSCS ML-DS cohort (red) (adapted from
Yoshida et al., 2013).
4.4.4 Cytogenetic features of neonates with TAM evolution to ML-DS
Previous reports suggested that karyotypic patterns in ML-DS were different from those observed in non-DS AML patients. In ML-DS, karyotypic patterns which are commonly found in non-DS AML such as t(8;21), inv (16), t(15;17) and 11q23 rearrangements were reported to be rarely seen (Sato et al. 1997; Yamaguchi et al. 1997; Kurkijan et al. 2006). A previous IBFM study by Forestier et al showed that, compared to children with AML who do not have DS, several karyotypic abnormalities are more frequent in ML-DS, including trisomy 8, trisomy 11 and trisomy 21, del (6q), del(7p), del(16q) and dup(1p) (Forestier et al. 2008).
119
In our cohort, 3 of 5 neonates with TAM evolution to ML-DS (ML-DS 1, ML-DS 4 and ML-DS 5) had no additional cytogenetic abnormalities at time of disease progression to ML-DS. Two neonates
(ML-DS 2 and ML-DS 3) had additional copies of chromosome 21 (+21c, +21); ML-DS 2 also had high hyperdiploidy with +Y, +13, +14, +19, +22 in 9/10 cells identified by FISH (fluorescence in situ hybridisation).
4.5 Summary and Discussion
My data are in keeping with previous published reports showing that all cases of TAM and ML-DS have an acquired N-terminal truncating GATA1 mutation(s) and that these mutations disappear when
TAM or ML-DS enter remission (Hitzleret al., 2003; Rainis et al., 2003; Xuet al., 2003; Ahmed et al.,
2004; Alfordet al., 2011). This has recently been confirmed using very sensitive next-generation sequencing, including exome sequencing (Yoshida et al., 2013). In my patient cohort, GATA1 mutation(s) were found in exon 2 of the GATA1 gene where the majority of mutations are found
(97%) (Alfordet al., 2011). These included insertions, deletions and point mutations as outlined in
Table 4.2, however the type of mutation does not predict which neonates will progress to ML-DS
(Alford et al., 2011). Multiple mutant GATA1 clones have been reported in neonates with TAM and were also seen in my data (Ahmedet al., 2004; Alfordet al., 2011). Recent studies of whole exome/genome sequencing of paired TAM and ML-DS samples indicated that ML-DS may develop from both major and minor GATA1 sub-clones (Yoshida et al., 2013). Importantly, my work shows that sensitive methods are necessary to detect GATA1 mutation(s) as one neonate who transformed to
ML-DS only had a GATA1 mutation detected by NGS (Ss/DHPLC negative). This is a novel finding and highlights the importance of long-term follow up (until 5 years of age) in all DS neonates with a
GATA1 mutation as they are at risk of ML-DS transformation during this period. Remarkably, my data shows that neonates without GATA1 mutation(s) (n=310) are not at risk of ML-DS transformation.
120
Therefore, the unique stepwise pathogenesis of TAM progressing to ML-DS requires three distinct genetic events: firstly, fetal haematopoietic cells need to be trisomic for chromosome 21, secondly an acquired GATA1 mutation is required and thirdly an additional genetic/epigenetic event is required for disease progression to ML-DS. This further improves our understanding of this stepwise model of leukaemogenesis and may be used for disease monitoring. Knowledge of the secondary mutations detected in children with ML-DS may be useful for identifying cases which are transforming from previous TAM or for monitoring disease after therapy for ML-DS. However, prospective studies would be needed to confirm this.
Although there were a limited number of patients in my study, my findings are similar to those of
Klusmann et al and Gamis et a who reported that neonates with persistent thrombocytopenia (platelets
<100 x109/L at 12 months age), delayed time to TAM resolution and pleural effusion had a higher risk of transformation to ML-DS (Klusmann et al., 2008; Gamis et al., 2011). In addition, my data suggests that neonates with TAM who have hepatomegaly and liver dysfunction at birth may be at higher risk of TAM evolution to ML-DS however, more patient numbers are needed to confirm this finding.
The 5-year survival following chemotherapy in ML-DS patients was similar to non-DS AML (74% vs
62%) due to excess treatment related deaths (induction deaths: 11% in ML-DS vs 4% in non-DS
AML) (Rao, et al., 2006). New treatment modalities are therefore required to decrease treatment related toxicity whilst maintaining low rates of resistant/recurrent disease. With the identification of recent genetic/epigenetic mutations in ML-DS, novel agents targeting various cellular processes in
AML such as hypomethylating agents (Estey, 2013), PARP inhibitors (Faraoni, Compagnone,
Lavorgna, et al., 2015), and JAK-inhibitors (Eghtedar et al. 2012) warrant further studies in ML-DS to determine if survival outcomes may be improved as compared to conventional chemotherapy.
121 CHAPTER 5 - Immunophenotypic and
functional properties of blast cells in
neonates with TAM
122 IMMUNOPHENOTYPIC AND FUNCTIONAL PROPERTIES OF BLAST CELLS IN
NEONATES WITH TAM
5.1 Background
A number of studies have investigated the characteristics of blast cells in TAM and in ML-DS. The two approaches taken to date have focused either on the morphological characteristics of the blast cells or their immunophenotype (Kojima et al. 1990; Yumura-Yagi et al. 1992; Karandikar et al.
2001; Coulombel et al. 1987; Litz et al. 1995; Girodon et al. 2000; Langerbrake et al . 2000). There have also been occasional small studies which have investigated their functional properties in clonogenic assays or liquid cultures (Suda et al. 1987; Miyauchi 2010; Denegri et al. 1981; Suda et al.
1985). All of these studies have limitations because the blast cell populations have not been defined, heterogeneity of the blast cell populations has not been considered ('blasts' have been viewed as a single population) and molecular analysis for the presence of GATA1 mutation(s) to demonstrate that the cell studied were actually part of the pre-leukaemic/leukaemic clone has not been performed. This is important because it is now clear that neonates with DS virtually all have circulating blast cells even if there are no GATA1 mutation(s) present (Roberts et al, 2013). In addition, several studies have shown that neonates with TAM may have more than one mutant GATA1 clone (Ahmed et al., 2004;
Alford et al., 2011; Robertset al., 2013) and how the different mutations affect the blast cell properties has not been investigated.
Most series described the blast cells in neonates with TAM as 'megakaryoblastic' on the basis of their immunophenotype and their morphology. Classically, both TAM blasts and ML-DS blasts are described as large cells with high nuclear cytoplasmic ratio, prominent nucleoli, basophilic cytoplasm with coarse basophilic granules and cytoplasmic blebbing typical of megakaryoblasts (Hasle et al.,
2003; Massey et al., 2006).
123
Studies of the blast cells in ML-DS suggested that these cells are morphologically identical and immunophenotypically similar to the blast cells in TAM (Yumura-Yagi et al. 1992; Karandikar et al.
2001; Xu et al. 2006; Langerbrake et al. 2005). It is reported that there is striking commonality between TAM and ML-DS blasts, expressing CD45, CD34, CD38, CD33, CD117, CD36, CD7,
CD41, CD61, TPO-R, IL-3R and negative for EPO-R, IL-6R, mature myeloid markers such as CD14,
CD16. However there are also some phenotypic differences between blast cells in TAM and ML-DS:
(i) TAM blasts have been reported to have higher CD34 and HLA-DR expression than blasts in ML-
DS suggesting they are more immature cells than blasts in ML-DS, (ii) TAM blasts have been reported to have less expression of CD11b and CD13 than blasts in ML-DS suggesting that TAM blasts are at a less mature differentiation stage than ML-DS blasts (Karandikar et al. 2001; Xu et al.
2006; Langerbrake et al. 2005).
It is clear that blast cells in TAM are heterogeneous and this has never been systematically studied.
The studies in this chapter sought to begin to characterise this heterogeneity at the morphological, immunophenotypic and functional level in order to establish a framework to determine, in the future, whether particular blast cell sub-populations might be associated with a higher frequency of subsequent transformation to ML-DS and whether it was possible to distinguish between blast cells which do and do not carry GATA1 mutations by any morphological, immunophenotypic or functional criteria.
5.2 Aim
The aim of the experiments described in this chapter is to investigate the immunophenotypic profile and functional properties of circulating blasts in DS neonates with and without GATA1 mutation(s).
124 5.3 Experimental Approach
Peripheral blood samples left over after clinical use from neonates with (n=6) and without (n=13)
GATA1 mutation(s) and neonates without DS (n=10) were processed to determine the TAM blast immunophenotype, looking at co-expression of CD45, CD34, CD33, CD36 and CD7 cell surface antigens. These antigens were selected for study because these are the most frequently reported in previous studies of TAM blasts (Karandikar et al. 2001; Xu et al. 2006; Massey et al. 2006; Klusmann et al. 2008; Girodon et al. 2000; Langerbrake et al. 2005).
Cord blood was initially used to optimise cytospin methodology for flow-sorted sub-populations before using TAM samples. Cord blood was collected and processed as described in section 2.2.1.
Cytospin morphology of flow-sorted sub-populations was unclear when using a 100 microns nozzle and Flow rate of 3 due to cell damage. Repeat cytospin of flow-sorted sub-populations using an 85 microns nozzle and a Flow rate of 1 obtained better morphological result. The technique was optimised within six weeks. Therefore, this methodology was used to prepare cytospins for flow- sorted TAM blast sub-populations. Cytospins for each flow-sorted blast sub-population were processed as described in section 2.5.
Putative TAM blast sub-populations were flow-sorted based on cell surface antigen expression: SSC intermediate and CD45 lo, then co-expression on CD34, CD33, CD36 and CD7 (Figure 5.1) from neonates with (n=3; designated TAM 1, TAM 2 and TAM 3) and without (n=2) GATA1 mutation(s) and neonates without DS (n=3). PCR for GATA1 mutation(s) was performed on each flow-sorted blast sub-population with protocols developed in the IR and PV labs by Dr Kelly Perkins and Dr Natalina
Elliott (see section 2.6). I performed all of the other experiments discussed in Chapter 5.
Clonogenicity of each flow-sorted blast sub-population was determined using previously published methylcellulose culture assay (Roy et al, 2012) (details in Section 2.4). Colonies were counted at day
125 14 and colony type was determined on the basis of morphology, flow cytometry and cytospin. The greatest challenge was the small starting volume of neonatal peripheral blood sample in both those with and without DS and subsequently the small cell numbers for clonogenic assays. It was therefore difficult to obtain sufficient cells from each colony type for immunophenotype and cytospin.
Similarly GATA1 mutation analysis was performed on each colony type where feasible, by PCR by Dr
Kelly Perkins and Dr Natalina Elliott (see section 2.6).
Figure 5.1 Gating strategy to identify blast cell sub-populations in DS neonates with and without GATA1 mutation(s) and non-DS neonates
Peripheral blood mononuclear cells isolated from DS and non-DS peripheral blood by Ficoll density gradient separation (see 2.2). Blast cell sub-populations were identified based on cell surface antigen expression: SSC intermediate and CD45 lo, then co-expression on CD34, CD33, CD36 and CD7.
5.4 Defining the TAM blast population(s) carrying the mutant GATA1 clone(s)
DS neonates with GATA1 mutation(s) had a higher frequency of CD34+ cells within the ‘blast’ gate in peripheral blood than DS neonates without GATA1 mutations and neonates without DS with a median
126 of 45.6% (range 20.8-92.8%) compared to 17.8% (range 0-34.5%) in DS neonates without GATA1 mutations and 18.9% (range 6.25-40.9%) in neonates without DS, p <0.0001 (Figure 5.2, Table 5.1).
Furthermore, I have shown for the first time that TAM blasts could be both CD34 positive and CD34 negative as determined by GATA1 mutation status by PCR and cytospin morphology showing large cells, with high nuclear cytoplasmic ratio, nucleoli and cytoplasmic blebs (Figure 5.3). Cytospins of peripheral blood mononuclear cells from DS neonates without GATA1 mutations and non-DS neonates also showed some blasts amongst mature neutrophils and monocytes (Figure 5.4).
More detailed analysis showed that there was a significantly higher frequency of CD34+CD33+ and
CD34-CD33+ blast cells in neonates with GATA1 mutation(s) compared to neonates without GATA1 mutations (Figure 5.5). Moreover, a proportion of CD34+/- blasts in DS neonates with GATA1 mutation(s) co-expressed CD36 and CD7 cell surface antigens (Table 5.2). This co-expression pattern was seen in all of the TAM patients and in only a small proportion of the DS neonates without TAM.
Co-expression of CD36/CD7 on CD34+/- blast cell populations was not detected in any of the non-
DS samples. This suggests that blast cells with this immunophenotype may either be unique to DS or that this population was selectively expanded in DS neonates with GATA1 mutation(s) and was present in such a low frequency in non-DS neonates that I was unable to detect any cells in the samples I investigated (Figure 5.6).
127 % CD34+ cells TAM (n=6) Non-TAM TAM vs Non- Non-DS Neo Non- TAM DS in ‘blast’ gate (n=13) TAM (n=10) vs Non-DS (p-value) (p-value) Median 45.6 17.8 <0.001 18.9 0.16 Range 20.8-92.8 0-34.5 6.25-40.9
Table 5.1 Frequency of CD34+ cells within the ‘blast’ gate in DS neonates with and without
GATA1 mutation(s) and non-DS neonates
Neonates with GATA1 mutation(s) had a significantly higher frequency of CD34+ cells with the ‘blast’ gate
(median 45.6%, range 20.8-92.8%) compared to neonates without GATA1 mutation(s) (median 17.8%, range 0-
34.5%) and non-DS neonates (median 18.8%, range 6.25-40.9%), p<0.001.
p < 0 .0 0 1 e
t 1 0 0 a g
' t
s 8 0 a l B '
n 6 0 p = 0 .1 6 i h t i w 4 0 s l l e c 2 0 + 4 3 D
C 0 T A M N O N -T A M D S N O N -D S N E O n = 6 n = 1 3 n = 1 0
Figure 5.2 Higher frequency of CD34+ cells within the ‘blast’ gate in DS neonates with GATA1 mutation(s)
Dot plots showing neonates with GATA1 mutation(s) had a higher frequency of CD34+ cells within the ‘blast’ gate in peripheral blood than DS neonates without GATA1 mutations and neonates without DS , p<0.001.
Median CD34+ve cells in the blast gate were 45.6% (range 20.8-92.8%) for neonates with GATA1 mutation(s) compared to 17.8% (range 0-34.5%) in DS neonates without GATA1 mutations and 18.9% (range 6.25-40.9%).
128 TAM blast CD34+33- CD34+33+ CD34-33+ CD34-33- sub-popn Cytospin
GATA1 Mutant Mutant Mutant Mutant mutation TAM1
TAM blast CD34+33- CD34+33+ CD34-33+ CD34-33- sub-popn Cytospin
GATA1 Mutant Mutant Mutant Mutant mutation TAM2
TAM blast CD34+33- CD34+33+ CD34-33+ CD34-33- sub-popn Cytospin
GATA1 Mutant Mutant Wild Type Mutant mutation TAM3
Figure 5.3 Mutant GATA1 clones were present in all TAM blast sub-populations
In three neonates with TAM, peripheral blood blasts were both CD34 positive and CD34 negative as determined by GATA1 mutation status by PCR and cytospin morphology showing large cells, with high nuclear cytoplasmic ratio, nucleoli and cytoplasmic blebs.
129 Blasts Mature cells and blasts (arrow) DS neonate without GATA1 mutation
Non-DS neonate
Figure 5.4 Blasts were present in DS neonates without GATA1 mutation(s) and non-DS neonates
Pre-sort cytospins of peripheral blood mononuclear cells from a DS neonate without GATA1 mutation and a non-DS neonate showed some blasts amongst mature neutrophils and monocytes.
130 8 0 p < 0 .0 0 0 5
7 0 s l
l 6 0 e c 5 0 +
3 p = 0 .7 7 3 4 0 + 4
3 3 0 D C 2 0 % 1 0
0 T A M N O N -T A M D S N O N -D S N E O n = 6 n = 1 3 n = 1 0
6 0 p = 0 .8 p = 0 .0 2
5 0 s l l e
c 4 0
+ 3 3
- 3 0 4 3
D 2 0 C
% 1 0
0 T A M N O N -T A M D S N O N -D S N E O n = 6 n = 1 3 n = 1 0
Figure 5.5 DS neonates with GATA1 mutation(s) have increased CD34+33+ cells and CD34-33+ cells within the ‘blast’ gate
Dot plots showing significantly higher frequency of CD34+CD33+ blast cells in neonates with GATA1 mutation(s) compared to neonates without GATA1 mutations and non-DS neonates, p<0.0005 and a greater frequency of CD34-CD33+ blast cells in DS neonates compared to non-DS neonates, p<0.05.
131 % cells in ‘Blast’ gate TAM (n=6) Non-TAM TAM vs Non-DS DS non-TAM (median, range) (n=13) Non-TAM Neo vs Non-DS (p-value) (n=10) (p-value) 34+33-36+7+ 0.45 (0-2.5) 0 (0-0) 0.005 0 (0-0) - 34+33+36+7+ 4.7 (0-17.8) 0 (0-1.4) 0.004 0 (0-0) 0.22 34-33+36+7+ 0.85 (0-12) 0 (0-0) 0.02 0 (0-0) - 34-33-36+7+ 1.0 (0.2-4.7) 0 (0-1.3) 0.02 0 (0-0) 0.26
Table 5.2 Frequency of CD36+CD7+ cells in blast cell sub-populations in DS neonates with and without GATA1 mutation(s) and non-DS neonates
Neonates with GATA1 mutation(s) had a higher frequency of CD36+CD7+ cells in all blast cell sub-populations compared to neonates without GATA1 mutation(s), p<0.05.
132 1 5 .0 p = 0 .0 2 2 0 .0 p = 0 .0 0 4 s
1s 2 .5 l l l
l 1 7 .5 e 1e 0 .0 c c
+ 1 5 .0 + 7 .5 7 7 1 0 + + 6 6
3 3 3 8 + + 3 3 3 3 - 2 + 6 4 4 3 3
D 4 D C C
1 2 % %
0 0 T A M N O N -T A M D S N O N -D S N E O T A M N O N -T A M D S N O N -D S N E O n = 6 n = 1 3 n = 1 0 n = 6 n = 1 3 n = 1 0
6 p = 0 .0 2 3 .0 p = 0 .0 0 5 s s
5 l l l l 2 .5 e e c c
4
+ + 7
7 2 .0
3 + + 6 6 2 3 3 - - 1 .5 3 3 3 3 - + 4 4 1 .0 3 1 3 D D C C
0 .5 % %
0 0 .0 T A M N O N -T A M D S N O N -D S N E O T A M N O N -T A M D S N O N -D S N E O n = 6 n = 1 3 n = 1 0 n = 6 n = 1 3 n = 1 0
Figure 5.6 Higher frequency of CD36+CD7+ cells in all blast cell sub-populations in DS neonates with GATA1 mutation(s)
All TAM blasts (CD34+ and/or CD34-) co-expressed CD36 and CD7 cell surface antigens. This co-expression pattern was seen in only a small proportion of the DS neonates without TAM and was not detected in any of the non-DS samples, p<0.05.
5.5 Clonogenicity of TAM blast population(-s) carrying the mutant GATA1 clone(-s)
Clonogenic cells were present in three of the four blast cell populations in the samples from patients with TAM: CD34+CD33-, CD34+CD33+ and CD34-CD33+ (Table 5.3; Figure 5.7). There were two main differences between the clonogenicity of TAM versus non-TAM samples from DS or non-DS neonates. Firstly, the clonogenicity of the CD34+ TAM sub-populations was markedly reduced
133 compared to non-TAM samples, p<0.0001 (there was no difference in clonogenicity between the non-
DS samples compared to the DS samples without TAM). Secondly, the CD34-CD33+ population from patients with TAM contained clonogenic cells (as many as in the corresponding CD34+ population) suggesting that the GATA1 mutation might confer progenitor-like properties on the CD34- population. There was no difference in the morphology of the colonies between TAM versus non-
TAM samples. It is of interest that TAM blast populations were able to generate apparently normal
BFU-E and CFU-GM (Figure 5.8).
TAM 1 showed the presence of the same GATA1 mutation in all four sorted TAM blast sub- populations (Figure 5.3). Although the CD34-CD33- population did not give rise to any colonies, the other 3 populations all gave rise to both erythroid (BFU-E) and myeloid (CFU-GM) colonies. Overall clonogenicity was more than 10-fold lower than the same cell populations sorted from DS neonates without GATA1 mutations. The CD34+CD33- population gave rise to 2 BFU-E and 1 CFU-GM/1000 cells plated (overall clonogenicity 0.3%); the CD34+CD33+ population to 8 BFU-E and 4 CFU-
GM/1000 cells plated (1.2% clonogenicity); and the CD34-CD33+ population to 6 BFU-E and 4
CFU-GM/1000 cells plated (1% clonogenicity)-Figure 5.9A. Unfortunately, no colonies yielded sufficient DNA for GATA1 mutation analysis.
TAM 2 also showed the presence of the same GATA1 mutation in all four sorted TAM blast sub- populations (Figure 5.3). As for TAM 1, the CD34-CD33- population did not give rise to any colonies; the CD34+CD33+ population gave rise to 2 CFU-GM/1000 cells plated but no BFU-E; the
CD34-CD33+ population gave rise to 1 BFU-E and 5 CFU-GM/1000 cells plated and, surprisingly, the CD34+CD33- population gave rise to no colonies- Figure 5.9B. CFU-GM colonies from both
CD34+33+ and CD34-33+ showed the same GATA1 mutant clone as the original population suggesting they were derived from a single mutant cell. Unfortunately, no BFU-E colonies yielded sufficient DNA for GATA1 mutation analysis.
134 In TAM 3, all but the CD34-33+ population showed the presence of the same GATA1 mutation
(Figure 5.3). Neither of the CD34- populations gave rise to any colonies but the CD34+ populations gave rise to 1 colony each/1000 cells plated (1 BFU-E colony from the CD34+33- population, which did not carry the mutant GATA1 clone and 1 CFU-GM from the CD34+33+ population which did not yield enough DNA for GATA1 mutation analysis- Figure 5.9C.
In summary, TAM blast cell sub-populations gave rise to heterogenous colonies that were morphologically normal and therefore unable to distinguish neonates with TAM from those without
TAM.
No. of colonies/1000 DS neonates with DS neonates without Non-DS neonates cells plated GATA1 mutation(s) GATA1 mutation (n=2) (n=3) (n=3) 34+33- 2 124 121
34+33+ 5 113 115
34-33+ 5 0 0
34-33- 0 0 0
Table 5.3 Clonogenicity of blast cell populations in DS neonates with and without GATA1 mutation(s) and non-DS neonates
Clonogenic cells were present in three of the four blast cell populations in the samples from patients with
GATA1 mutation(s): CD34+CD33-, CD34+CD33+ and CD34-CD33+, however, the clonogenicity of TAM blast sub-populations was markedly reduced compared to DS or non-DS neonates without GATA1 mutation(s).
There was no difference in clonogenicity between DS samples without TAM and non-DS samples.
135
Figure 5.7 TAM blast sub-populations in DS neonates with GATA1 mutation(s) were less clonogenic than DS and non-DS neonates without GATA1 mutations
The clonogenicity of the CD34+ TAM sub-populations was markedly reduced compared to non-TAM samples, p<0.0001. The CD34-CD33+ population from patients with TAM contained as many clonogenic cells as in the corresponding CD34+ populations suggesting that the GATA1 mutation might confer progenitor-like properties on the CD34- population. There was no difference in clonogenicity between DS samples without TAM and non-
DS sample.
136 TAM NON-TAM NON-DS
BFU-E
CFU- GM
CFU- GEMM
Figure 5.8 Representative colonies from DS neonates with and without GATA1 mutation(s) and non-DS neonates TAM blast sub-populations generated apparently normal BFU-E and CFU-GM. There was no difference in the morphology of the colonies between neonates with and without GATA1 mutation(s). Colony type was confirmed by flow cytometry.
137 TAM blast sub-popn CD34+33- CD34+33+ CD34-33+
BFU-E
GATA1 mutation status: too few cells for analysis
CFU-GM
GATA1 mutation status: too few cells for analysis
Figure 5.9A: TAM blast sub-populations in a DS neonate with GATA1 mutation(s) gave rise to BFU-E and CFU-GM colonies TAM 1 showed 0.3% clonogenicity in the CD34+CD33- population with to 2 BFU-E and 1 CFU-GM/1000 cells plated; the CD34+CD33+ population had 1.2% clonogenicity with 8 BFU-E and 4 CFU-GM/1000 cells plated; and the CD34-CD33+ population had 1% clonogenicity with 6 BFU-E and 4 CFU-GM/1000 cells plated. BFU-E and CFU-GM colonies had normal morphology. Colony types were confirmed by flow cytometry.
138 TAM blast sub-popn CD34+33+ CD34-33+
BFU-E
GATA1 mutation status: too few cells for analysis
CFU-GM
GATA1 mutation status: Mutant Mutant
Figure 5.9B: TAM blast sub-populations in a DS neonate with GATA1 mutation(s) gave rise to BFU-E and CFU-GM colonies TAM 2 showed 0.2% colongenicity in the CD34+CD33+ population with only 2 CFU-GM/1000 cells plated and the CD34-CD33+ population had 0.6% clonogenicity with 1 BFU-E and 5 CFU-GM/1000 cells plated with normal morphology. Colony types were confirmed by flow cytometry CFU-GM colonies from both CD34+33+ and CD34-33+ showed the same GATA1 mutant clone as the original population indicating they were derived from a single mutant cell.
139 TAM blast sub-popn CD34+33- CD34+33+ BFU-E
GATA1 mutation status: Wild type
CFU-GM
GATA1 mutation status: too few cells for analysis
Figure 5.9C: TAM blast sub-populations in a DS neonate with GATA1 mutation(s) gave rise to BFU-E and CFU-GM colonies TAM 3 showed CD34+ populations gave rise to 1 colony each/1000 cells plated (0.1% clonogenicity) with normal morphology. BFU-E colony from the CD34+33- population did not carry the mutant GATA1 clone. Colony types were confirmed by flow cytometry
140 5.6 The impact of GATA1 mutation(s) on haematopoietic stem cell differentiation
As another way to investigate the functional properties of the mutant GATA1 clone, I asked whether there was any evidence of the GATA1 mutation in mature peripheral blood cells in the neonates with
TAM. If the GATA1 mutation could be detected in circulating normoblasts and granulocytes, this would suggest that the mutant clone retained the ability to differentiate down these two lineages. I therefore looked for the presence of GATA1 mutation in mature cells (nucleated red blood cells, granulocytes and lymphocytes) in 3 DS neonates with GATA1 mutation(s). Mature cells were flow sorted using cell surface antigens GlyA, CD11b, CD16, CD14 and CD3 as shown in the gating strategy –Figure 5.10. I found that nucleated red cells from all 3 neonates with GATA1 mutation(s) harboured identical GATA1 mutation(s) to those in the total circulating nucleated cells (Table 5.4).
This suggests that GATA1 mutant haematopoietic stem/progenitor cells retain the ability to differentiate down the erythroid lineage. GATA1 mutation could also be detected in the granulocyte fraction of one of the three TAM samples suggesting that GATA1 mutation also permits granulocyte differentiation, however this needs to be confirmed on a larger number of cases. Unfortunately only one of the three sorted lymphocyte populations contained sufficient DNA for analysis. In this single sample GATA1 mutation could not be detected suggesting that lymphocytes are not part of the abnormal clone although further samples would need to be tested to confirm this.
GATA1 mutation status Nucleated red blood Granulocytes Lymphocytes in mature cell cells TAM 1 Mutant Mutant No result
TAM 2 Mutant Wild type Wild type
TAM 3 Mutant Wild type No result
Table 5.4 GATA1 mutations were present in circulating normoblasts and granulocytes from neonates with TAM
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Granulocytes
Lymphocytes NRBCs
Figure 5.10 Gating strategy to identify mature cells from DS neonates with GATA1 mutation(s)
Mature cells were isolated from DS peripheral blood by Ficoll density gradient separation (see 2.2).
Granulocytes, lymphocytes and nucleated red blood cells (NRBCs) were identified by cell surface antigen expression: CD34-CD33- population identified which was further analysed by GlyA and CD11b cell surface antigens: NRBCs were identified as GlyA+CD11b-, granulocytes were identified as GlyA-CD11b+ and lymphocytes were identified as GlyA-CD11b-. Lymphocytes population was further confirmed as CD14-CD16- with some CD3+ cells.
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5.7 Summary and Discussion
The aim of these experiments were firstly to determine if neonates with GATA1 mutation(s) can be diagnosed on the basis of a distinct immunophenotype for circulating blasts that is not seen in neonates without GATA1 mutation(s) and secondly to determine the functional properties of circulating blasts in DS neonates with and without GATA1 mutation(s).
For the first time, my experiments examined co-expression of cell surface antigens in order to identify whether there was more than one blast cell population in TAM and if so how many sub-populations and what their immunophenotypes were.I was unable to identify a TAM-specific immunophenotypic population that was not present in DS neonates without GATA1 mutation(s). My experiments, thus, showed that neonates with GATA1 mutation(s) cannot be diagnosed on the basis of a distinct immunophenotype for circulating blasts not seen in neonates without GATA1 mutation(s). I found that
TAM blasts were heterogeneous and for the first time my work showed that TAM blasts could be both
CD34 positive and CD34 negative. This is a novel finding and needs further investigation with more samples. Furthermore, in neonates with GATA1 mutation(s) the CD45dimCD34+/-CD33+/-CD36+CD7+ blast sub-population was significantly expanded as compared to neonates without GATA1 mutation(s) and this blast sub-population is unique to neonates with DS and not detected in non-DS samples.
Again, further work with more samples is necessary to confirm this finding.
I further looked to establish if I could discriminate blast cells from neonates with TAM and from neonates without TAM using functional studies. I found that clonogenicity of the CD34+ TAM sub- populations was markedly reduced compared to non-TAM samples. This may reflect the lack of fetal specific growth factors in the culture medium which are important for maintenance of the mutant
GATA1 clone. Indeed, there is some evidence to suggest that fetal liver provides a specialised microenvironment (Chou & Lodish, 2010) and this may be necessary for driving and maintaining abnormal haematopoiesis in neonates with TAM. The reasons for the paradoxically poor proliferation
143 in vitro versus the high proliferation in vivo are not clear. This phenomenon is also observed in cells from patients with myelodysplastic syndrome and presumably reflects an uncoupling of the mechanisms which exist in normal progenitors to balance proliferation and differentiation. It seems likely that the molecular basis for this lies with the GATA1 mutation since the studies by Yoshida et al show that very few TAM samples carry additional mutations apart from GATA1 (Yoshida et al.,
2013).
Some evidence in favour of this concept comes from the observation that the CD34-CD33+ population from only patients with TAM contained clonogenic cells suggesting that the GATA1 mutation might confer progenitor-like properties on the CD34- population. Interestingly, TAM blast populations were able to generate morphologically normal BFU-E and CFU-GM colonies therefore this does not help distinguish neonates with TAM from those without TAM. It would be interesting to investigate this further by culturing TAM blasts in a liquid culture system in order to systematically determine their lineage output and, in particular, to better assess their megakaryocytic potential since methylcellulose colony assays are not optimal for megakaryocyte differentiation. Unfortunately, there were too few cells to assess megakaryocyte output using the only avalilable alternative megakaryocyte colony-forming assay (Megacult) as this requires >1,000 CD34+ cells per assay.
Blast cell sub-populations with GATA1 mutant clone can differentiate to give heterogenous colonies.
These colonies may arise from a single cell with GATA1 mutation(s) or non-mutant cell within the sorted blast cell population. For example, in TAM 2 the CFU-GM colony from blast cell CD34+33+ and CD34-33+ populations had the same GATA1 mutant clone as the original population suggesting it was derived from a single mutant cell in each sub-population. However, in TAM 3 the CD34+33- blast cell sub-population with GATA1 mutation differentiated into BFU-E colony without GATA1 mutation suggesting that non-mutant cells are also present in this sorted population which possibly gave rise to this BFU-E colony.
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I also gained insight into the biological properties of blast cells in neonates with GATA1 mutations. I found that GATA1 mutant haematopoietic stem/progenitor cells retain the ability to differentiate down the erythroid and granulocytic lineage but perhaps not the lymphoid lineage, however further samples would need to be tested to confirm this.
My investigations have been limited due to the small number and small volume of samples available for neonates with TAM in the given time for my research. This meant there was insufficient DNA for
GATA1 mutation analysis in colonies from blast cell sub-populations.
My work provides the framework for future studies to determine a precise immunophenotypic definition of blast cell populations in neonates with GATA1 mutation(s). This needs to be investigated in a larger prospective study to determine their prognostic significance as it may help monitor disease progression and plan treatment. In addition, studies on paired samples of neonates with TAM who progress to ML-DS may help determine the biological characteristics of different blast cell populations to identify properties which may predict for disease progression.
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CHAPTER 6 - Discussion
146
DISCUSSION
6.1 Background
It has been known for many years that children with DS have an increased risk of developing ML-DS during the first 5 years of life (Hasleet al., 2008) and that this is preceded by the unique
‘preleukaemic’ condition, TAM. Furthermore, all cases of TAM and ML-DS carry the same acquired
N-terminal mutations in the GATA1 gene (Wechsleret al., 2002; Xuet al., 2003; Rainiset al., 2003;
Hitzleret al., 2003; Ahmedet al., 2004; Yoshidaet al., 2013). No studies thus far have systematically studied blood films or GATA1 mutation status together with clinical features and therefore the true clinical spectrum of TAM and the exact frequency of TAM has been unclear.
Using data from the prospective multi-centre Oxford Imperial Down Syndrome Cohort Study my project aimed to: (1)Characterise the clinical and haematological features of TAM in order to precisely define TAM, (2)Understand the natural history of TAM evolution to ML-DS and describe the population at risk of developing leukaemia, (3)Describe the immunophenotypic and functional properties of blast cells in neonates with TAM in order to establish whether particular blast cell sub- populations might be associated with a higher frequency of subsequent transformation to ML-DS and whether it was possible to distinguish between blast cells which do and do not carry GATA1 mutations by any morphological, immunophenotypic or functional criteria.
In this chapter, I will first summarise my findings then discuss their significance and limitations, how they impact on our understanding of the natural history of TAM and the opportunities for future work in this field.
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6.2 The clinical and haematological features of TAM
Before I characterised the clinical and haematological abnormalities in TAM I first had to define
TAM accurately.
Using the OIDSCS definition, I initially defined TAM into three categories for further analysis as below: (i) Clinical TAM- a neonate with DS with a peripheral blood blast percentage >10% and a N- terminal GATA1 mutation(s) detected by conventional Ss/DHPLC, (ii) Silent TAM DHPLC +ve- a neonate with DS and peripheral blood blast percentage <10% and a GATA1 mutation(s) detected by
DHPLC and (iii) Silent TAM DHPLC-ve- a neonate with DS and a GATA1 mutation(s) detected only by NGS.
I found that TAM had a very variable clinical presentation, confirming the observations made in the three large retrospective studies (Massey et al., 2006; Klusmann et al., 2008; Gamis et al., 2011). I identified three clinical features that are strongly associated with TAM: hepatomegaly, splenomegaly and skin rash (p<0.01). These features correlated with the size of the mutant GATA1 clone suggesting that they are directly due to organ infiltration with leukaemic blasts carrying the GATA1 mutation as they are not seen in Silent TAM. However, there were no diagnostic clinical features for TAM as the same signs could also be seen in a proportion of DS neonates without a GATA1 mutation.
In keeping with previous work from our lab, I found that all DS neonates independent of their GATA1 mutation status had morphological haematological abnormalities suggesting that trisomy 21 itself causes trilineage perturbation of haematopoiesis (Roberts et al, 2013). I found that thrombocytopenia was a common feature in both DS neonates with and without a GATA1 mutation(s) at birth and that there was no significant difference in the platelet count between these two groups (p=0.9). Neonates with GATA1 mutation(s) had a higher white cell counts than DS neonates without a GATA1 mutation
(p<0.05). However, there was a considerable overalp in FBC parameters in DS neonates with and
148 without GATA1 mutation(s) and no haematological features, apart from a very high blast cell frequency, was diagnostic of TAM. I confirmed that megakaryocyte fragments were strongly associated with GATA1 mutation(s) (p<0.001) and for the first time, I showed that eosinophil dysplasia was associated with GATA1 mutation(s) (p<0.05). Blast cell morphology was indistinguishable between neonates with or without GATA1 mutation(s).
Prior to my work, the relationship between the peripheral blood blast percentage and GATA1 mutation status in DS neonates was unknown. I found that neonates with clinical TAM not only had a higher peripheral blood blast percentage, but they also had a significantly larger mutant GATA1 clone compared to neonates with Silent TAM. Neonates with Silent TAM DHPLC +ve had a significantly larger mutant GATA1 clone than those with Silent TAM DHPLC-ve (p<0.05) but there was no difference in blast percentage between the two Silent TAM groups (p=0.8) thus NGS is needed to identify all types of Silent TAM even when the blast percentage is low.
As detailed analysis of the clinical and haematological features of OIDSCS neonates failed to identify any specific features that were consistently indicative, or not for TAM, this highlights the practical difficulty in defining TAM. Currently, asymptomatic neonates with GATA1 mutation(s) may be missed while in other cases TAM may be over-diagnosed by relying on non-specific clinical and haematological features. Therefore, an accurate definition of TAM should be a neonate with DS and presence of GATA1 mutation(s) detected by sensitive methodology such as NGS. Through my work, I have redefined TAM and my data showed that almost 28% of all DS neonates harbour GATA1 mutation(s). This overall frequency of GATA1 mutation(s) was 3-fold higher than previous estimates
(Massey et al., 2006; Klusmann et al., 2008; Muramatsu et al., 2008; Gamis et al., 2011; Zipursky,
2003) and is remarkable. The reasons for this high frequency of GATA1 mutations specifically in neonates with DS are not known; although the nucleotide sequence in exon 2 of the GATA1 gene
149 contains several repetitive sequences, acquired GATA1 mutations are virtually never seen in the absence of trisomy 21.
6.3The natural history of TAM during the first five years of life
With a median follow up of 45.5 months (range 4-92 months), 5/72 (6.9%) infants in the OIDSCS cohort have progressed to ML-DS this includes one neonate with Silent TAM in whom the GATA1 mutation was detected by NGS only. Therefore, all DS children with GATA1 mutation(s) at birth, even those with a small GATA1 mutation should be regularly followed up until 5 years of age as they are at risk of ML-DS. Follow-up should include FBC, blood film and monitoring for persistence of
GATA1 mutation(s) using a sensitive method such as NGS
Thus far, no neonates without a GATA1 mutation have developed ML-DS suggesting that parents of children without such mutations at birth, can be reassured that their child has little or no risk of ever developing ML-DS- provided that a sensitive method for detecting GATA1 mutations is used.
I found that TAM neonates with persistent thrombocytopenia (platelets <150 x109/L beyond 12 months age), presence of hepatomegaly and liver dysfunction at birth were more likely to transform to
ML-DS (p<0.05). However, larger patient numbers are needed to confirm this finding. My findings are similar to those of Klusmann and Gamis et al, which also reported that neonates with persistent thrombocytopenia (defined as platelets <100 x109/L) had a higher risk of transformation to ML-DS
(Klusmann et al., 2008; Gamis et al., 2011).
It is known that while GATA1 mutation(s) are necessary for development of ML-DS they alone are insufficient for the transformation to ML-DS (Rainis et al., 2003). Data on all five paired TAM and
ML-DS samples from the OIDSCS cohort identified additional mutations particularly in the cohesion
150 complex genes (RAD21, STAG1, SMC1), epigenetic regulators (KANSL1, KDM6A, MLL), CTCF mutations and mutations in genes in common tyrosine kinase signaling pathways (MPL) as has been reported by other recent studies (Nikolaev et al., 2013; Yoshida et al., 2013). Mutations in cohesion complex genes, epigenetic regulators as well as JAK family kinases occur more frequently in ML-DS than non-DS AML (Yoshidaet al., 2013). However, the reasons for this are unclear and may be related to the extra chromosome 21 which results in distinct genetic features. The normal function of the genes encoded by these proteins is also incompletely understood: cohesion complex genes are considered to be involved in defective DNA repair pathways and control gene expression (Strömet al.,
2007; Wendtet al., 2008; Rubio et al., 2008; Watrin & Peters, 2009) while epigenetic regulatory genes and CTCF mutations are believed to organise major areas of transcriptional activation/repression
(Wendt & Peters, 2009; Koolenet al., 2012; Zollinoet al., 2012). My work provides further evidence that there are three distinct genetic events in the pathogenesis of TAM evolution to ML-DS: firstly, fetal haematopoietic cells need to be trisomic for chromosome 21, secondly an acquired GATA1 mutation is required and thirdly an additional genetic/epigenetic event is required for disease progression to ML-DS.
6.4 Immunophenotypic and functional properties of blast cells in neonates with TAM
Although a major limitation to my studies was the small number of samples and small sample volume, the consistency of the results in neonates with GATA1 mutation(s) compared to neonates without
GATA1 mutation and those without DS samples suggests that the data are reliable and can be used to begin to fully characterise the immunophenotypic and functional properties of blasts in TAM. I was unable to identify a unique TAM-specific immunophenotypic population of blast cells in TAM.
However, in neonates with GATA1 mutation(s) the CD45dimCD34+/-CD33+/-CD36+CD7+ blast sub- population was significantly expanded compared to neonates without GATA1 mutation(s). Since some neonates without GATA1 mutations also had circulating blasts with this immunophenotype, expression of these antigens alone does not indicate TAM and further work will be needed to
151 determine whether there are additional antigens that are 'TAM-specific'. For the first time, my work showed that TAM blasts could be both CD34 positive and CD34 negative, however a larger sample size is necessary to confirm this finding.
I showed that clonogenicity of TAM blast sub-populations was markedly reduced compared to non-
TAM samples, however, TAM blast sub-populations were able to generate morphologically normal
BFU-E and CFU-GM colonies and therefore there were no clear functional differences between neonates with and without GATA1 mutation(s).
6.5 Future work
Given that TAM has a variable clinical presentation and there were no reliable clinical, haematological or biological features (such as blast cell properties) which can identify these neonates,
I have accurately re-defined TAM as a neonate with DS and one or more acquired N-terminal truncating GATA1 mutation(s) determined by a sensitive screening method such as NGS. This definition of TAM would identify all neonates at risk of transformation to ML-DS and for whom follow up is indicated until the age of 5 years. It is therefore essential that all neonates with DS have a blood film and FBC evaluated at birth as is recommended by the American Academy of Pediatrics
(Bull, 2011). There is a great need to develop a UK guideline for the better management of neonates with TAM and this is currently in progress with the Royal College of Paediatrics and Childhood; I am leading this writing group. The guideline will recommend that all neonates with DS should have FBC, blood film and GATA1 mutation status identified by NGS at birth.
Follow-up of all neonates at risk of ML-DS transformation is required to allow earlier identification of cytopenias and complications such as liver dysfunction that may precede ML-DS and facilitate their appropriate management. My work showed that all neonates with a GATA1 mutation(s), even those
152 where the GATA1 mutation(s) is only detected by NGS and not Ss/DHPLC are at risk of ML-DS transformation and therefore should have appropriate follow-up. It is not yet known if monitoring the
GATA1 mutant clone(s) can identify progression to ML-DS earlier than evaluating the FBC and blood film morphology and this would be an exciting area for further research. Future studies must also determine whether earlier diagnosis and treatment of TAM with a short course of low dose cytarabine and earlier diagnosis of ML-DS improves outcome for children with ML-DS. At present, there are uncertainties as to what may be the best treatment protocol and there is considerable variation in treatment policies between different centres. The British Committee for Standards in Haematology guideline on management of TAM will aim to address this; I am an active member of this writing group.
Another exciting question that is less well understood is why some neonates undergo spontaneous remission and what factors may influence this. Recent work in our laboratory looking at the role of insulin-like growth factor (IGF) pathway in leukaemia initiation in DS showed that trisomy 21 perturbs fetal haematopoiesis through both HPSC-intrinsic mechanisms (including changes in IGF responsiveness) and through alterations to the fetal liver microenvironment (unpublished work).
Further work to establish the precise mechanisms is on-going in our laboratory.
Additional genetic events detected in TAM neonates with evolution to ML-DS both in my study and recent published work (Nikolaev et al., 2013; Yoshidaet al., 2013) is beginning to unravel the role of genetic/epigenetic changes in mediating disease transformation from TAM to ML-DS. Further work is on-going with OIDSCS paired TAM and ML-DS samples to understand the exact mechanism of these genetic and epigenetic changes in TAM evolution to ML-DS.
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6.6 Conclusion
These studies for the first time provide a systemic approach to characterisation of blood counts, blood cell morphology and GATA1 mutation status in neonates with DS based on data from the prospective
OIDSC study. My work has provided an accurate definition of TAM based on sensitive methods to detect GATA1 mutation(s) by NGS. Identification of GATA1 mutation(s) in virtually all cases of TAM and ML-DS offers the potential to accurately measure minimal residual disease and prevent complications of disease by providing earlier treatment. Follow up studies are required to establish the true impact of a small GATA1 clone and if this carries the same risk of transformation to ML-DS as neonates with a larger GATA1 clone.
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Appendix 1: List of OIDSCS recruiting centres
Recruiting centre Number of DS neonates recruited (n=382)
Birmingham Heartland’s Hospital 29
Birmingham Women’s Hospital 37
Addenbrooke’s Hospital 27
Chelsea & Westminster Hospital 27
Royal Hospital for Sick Children, Edinburgh 10
Frimley Park Hospital 5
Royal Hospital for Sick Children, Glasgow 18
Hillingdon Hospital 4
St. Mary’s Hospital 10
North Middlesex Hospital 13
Northwick Park Hospital 25
John Radcliffe Hospital, Oxford 51
Queen Charlotte’s and Chelsea Hospital 26
Great Western Hospital, Swindon 10
St. Thomas’ Hospital 29
New Cross Hospital, Wolverhampton 12
Whittington Hospital 16
Whipp’s Cross Hospital 33
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Appendix 2: OIDSCS Clinical Proforma
163
164
Appendix 3: OIDSCS Full blood count review form
MORPHOLOGY REVIEW PSID No:
Oxford Imperial Down Syndrome Cohort Study
Sex: Ethnic origin:
DOB: / / Gestational age: weeks Age at testing: days
AUTOMATED FULL BLOOD COUNT RESULT
HB WCC PLT
HCT Neutrophils MPV
MCV Lymphocytes
MCH Eosinophils
RCC Basophils
NRBC Monocytes
Blasts
MANUAL DIFFERENTIAL COUNT
% % %
Neutrophils Myeloblasts Eosinophils
Metamyelocytes Lymphocytes Basophils
Myelocytes Lymphoblasts Monocytes
Promyelocytes Blasts – type unclear NRBCs
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Appendix 4: OIDSCS Morphology Review form
DEGREE OF DYSPLASIA (score) None (0) Some (1) Moderate (2) Plentiful (3)
NEUTROPHILS Hypogranular
Agranular
Hypersegmentation
Pelger forms
EOSINOPHILS Abnormal (specify below)
BASOPHILS Abnormal (specify below)
Comment:
BLASTS Cytoplasmic blebbing
Comment:
MONOCYTES Stellate forms
Other abnormalities
eg. Elongated lobes
Comment:
RED CELLS Macrocytes
Polychromasia
Targets
Basophilic stippling
Dyserythropoietic
NRBCs
Comment:
PLATELETS Giant forms
Megakaryocyte
fragments
Comment:
OTHER COMMENTS
Slide reviewed by ______Date______
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Appendix 5: Peripheral blood blast cell frequency in healthy term neonates and healthy
and sick pre-term neonates
Peripheral blood blast Healthy term neonates Healthy pre-term Sick pre-term (%) (n=80) neonates (n=128) neonates (n=80) Median 0 0 1 Range 0-2 0-4 0-8
Data from Irene Roberts
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Appendix 6: Flurochrome conjugated antibodies used in flow cytometry
All antibodies were from BD (Beckton-Dickinson, Oxford, UK) unless otherwise stated
Surface Fluorochromes marker Alexafluor APC FITC PE PE-Cy7 Pacific PerCp 700 Blue CD45 • eBioscience
CD34 • • eBioscience
CD33 • eBioscience
CD7 •
CD36 •
CD61 •
CD11b •
CD14 • BioLegend
GlyA •
CD41 •
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