Investigating the Mechanism of Bone Marrow Failure Observed in Patients with Acute Myeloid ...

389 Pages·2017·6.63 MB·English

Investigating the Mechanism of Bone Marrow Failure Observed
in Patients with Acute Myeloid Leukaemia

Katharine Ailsa Hodby

Submitted in partial fulfilment of the requirements of the Degree
of Doctor of Philosophy

August 2017
Statement of Originality
I, Katharine Ailsa Hodby, confirm that the research included within this thesis is my own, or
that where it has been carried out in collaboration with, or supported by others, that this is
duly acknowledged below and my contribution indicated. Previously published material is
also acknowledged below.
I attest that I have exercised reasonable care to ensure the work is original, and does not to
the best of my knowledge break any UK law, infringe any third party’s copyright or other
Intellectual Property Right, or contain any confidential material.
I accept the College has the right to use plagiarism detection software to check the
electronic version of the thesis.
I confirm that this thesis has not been previously submitted for the award of a degree by
this or any other university.
The copyright of this thesis rests with the authors and no quotation from it or information
derived from it may be published without the prior written consent of the author.
Signature:

Date:

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Details of Collaboration
I performed all of the experimental work described in this thesis, with the following
exceptions which are listed below.
General
Collection of AML patient samples and controls from Bart’s Hospital was done by Sameena
Iqbal and the Tissue Bank Team. Any samples which were stored prior to use were
processed as described in Section 2.2.2 by members of the Tissue Bank Team.
FISH based staining and analysis was performed by Marianne Grantham, Cytogenetics
Department, Royal London Hospital.
Whilst all sample preparation was performed by me, sequencing of DNA for the NPM1 exon
12 region was performed by the Sequencing Laboratory, London Research Institute.
Chapter 3: Study of patients with AML who present without trilineage
haematopoietic failure
A database of clinical characteristics and blood counts for all patients presenting to Bart’s
Hospital between 1997 and 2012 with AML was constructed by Janet Matthews, Data
Collection Officer, Bart’s Cancer Institute. The data were retrieved from the Bart’s Cancer
Clinical Database.
Trephine preparation and H&E staining was done by Andrew Clear, Postdoctoral Research
Assistant, Bart’s Cancer Institute.
Chapter 5: Enumerating Stem Cells in Primary Diagnostic Bone Marrow
samples from Patients Presenting with Acute Myeloid Leukaemia
Immediate analysis of fresh AML and control bone marrow samples before May 2012 was
performed by Dr F. Miraki-Moud.
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Chapter 7: Using RNA-Seq to compare the transcriptomes of normal
HSCs from AML and control bone marrow samples
Quality control of RNA samples, cDNA and prepared DNA libraries using the relevant Tape
Station kit were performed by the staff of the Genome Centre, BCI.
Library preparation, quantification and pooling were performed by me. Sequencing of the
prepared libraries was performed at the High Throughput Genome Centre, Oxford.
Bioinformatics Analysis of RNA-Seq Data was performed by Ai Nagano, Bioinformatics
Group, BCI. This included generation of the Principal Component Analysis plot shown in
Figure 7-10.

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Publications
Miraki-Moud, F; Anjos-Afonso, F; Hodby, KA; Griessinger, E; Rosignoli, G; Lillington, D; Jia, L;
Davies, JK; Cavenagh, J; Smith, M; Oakervee, H; Agrawal, S; Gribben, JG; Bonnet, D and
Taussig, DC (2013). Acute myeloid leukemia does not deplete normal hematopoietic stem
cells but induces cytopenias by impeding their differentiation. Proc Natl Acad Sci U S A 110,
13576-13581.
Miraki-Moud F, Ghazaly E, Ariza-McNaughton L, Hodby KA, Clear A, Anjos-Afonso F, Liapis
K, Grantham M, Sohrabi F, Cavenagh J, Bomalaski JS, Gribben JG, Szlosarek PW, Bonnet
D, Taussig DC (2015). Arginine deprivation using pegylated arginine deiminase has activity
against primary acute myeloid leukemia cells in vivo. Blood 125, 4060-4068.
Meeting Abstracts
Farideh Miraki-Moud, PhD, Linda Ariza-McNaughton, MSc, Essam A Ghazaly, MD, Katharine
A Hodby, Phuong Luong, Andrew Clear, PhD, Fareeda Sohrabi, John Bomalaski, John
Gribben, MD, DSc, Dominique Bonnet, PhD, Peter Szlosarek and David C Taussig, PhD,
MRCP, FRCPath (2013). Arginine Deprivation With Pegylated Arginine Deiminase Induces
Death Of Acute Myeloid Leukaemia Cells In Vivo. Abstract 1458, ASH New Orleans, 2013.
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Abstract
Patients with Acute Myeloid Leukaemia (AML) present with the signs and symptoms of
bone marrow failure. This finding spans the genetic and phenotypic diversity of the disease.
The mechanism which underlies it is poorly understood.
This thesis explores the effect of AML on the normal haematopoietic stem cell (HSC)
population, using primary human diagnostic bone marrow samples. Previous work from our
group suggested that AML induces a state of quiescence in HSCs, producing a
differentiation block responsible for the observed cytopenias1. Reversal of this process
might offer an alternative to the current treatment of patients with palliative transfusions.
I have developed a flow cytometry-based technique to differentiate normal HSCs from
leukaemia cells, selecting cells with the CD34+38-ALDHhighCLL1- expression signature.
Validation of this technique by assessment of sorted cells by FISH and PCR, suggests it is
successful in 73% of AML samples. In a further 25% of samples, it selects for a population
significantly enriched for normal HSCs.
We used this panel to investigate the concentration of HSCs at AML diagnosis, compared to
controls. We show that there is no significant difference between HSC concentration at
AML diagnosis (n=38, median [HSC] 2.5 cells/µl) and controls (n=24, median [HSC] 2.4
cells/µl). HSC concentration was not significantly affected by AML karyotype, patient age or
gender.
However, those patients presenting with a low HSC concentration at diagnosis (<0.1
HSC/µl) were found to have a significantly worse outcome both in terms of overall and
relapse-free survival, an effect apparently independent of age, gender and underlying
karyotype. HSC concentration at diagnosis with AML may therefore represent a new
independent prognostic marker.
We then studied CD33 expression patterns on HSCs within Core Binding Factor mutated
AML (n=37) at diagnosis, and found its expression to be significantly lower than on HSCs
within controls (n=9) (17% versus 58%, p=0.005). CD33 expression on HSCs from AML
samples rose significantly from diagnosis to remission (n=16) (17% to 58%, p=0.0001). This
mirrors previous findings from our group using CD34low AML samples, and is, we believe,
the first time that the antigenic signature of normal HSCs has been shown to be modified
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by the presence of AML. However, an in vitro assay to test the significance of these changes
in terms of the cytotoxicity of GO towards normal HSCs did not demonstrate a significant
difference between HSC subgroups.
Finally, we attempted to investigate the mechanism by which AML might induce HSC
quiescence by studying the comparative transcriptomes of HSCs from CD34low AML (n=6)
and controls (n=6) by RNA-Seq, using direct cell to cDNA synthesis, followed by
amplification. A first attempt resulted in poor quality data, with a significant proportion of
reads mapping to non-coding DNA regions. A repeat approach, using utilising immediate
RNA extraction post sorting resulted in significantly better quality data Bioinformatics
analysis revealed differential expression of 6 genes between the 2 datasets (GNPDA1,
ADGRG3, MIAT, WDR31, RP11-244H3.1 and RXFP1). GO enrichment studies using David
highlighted a number of pathways including the TNF signalling pathway (p=0.003; after
Benjamini-Hochberg correction p=0.51). Validation of these findings by independent qPCR,
and functional exploration of enriched signalling pathways remains outstanding.

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Acknowledgements
The work described in this thesis was undertaken whilst I was a Clinical Research Fellow at
the Centre for Haemato-Oncology at Bart’s Cancer Institute. Funding for the three year PhD
program was undertaken by Cancer Research UK.
I would like to thank David Taussig for providing the framework for this project, submitting
the initial idea to the CRUK funding body and for his support and guidance over the first
two years of my PhD. I would also like to thank Gabriella Ficz for agreeing to rescue me for
the last year of the project, and for her help and guidance in steering the project to exciting
new areas. I would also like to thank John Gribben for his wise oversight, and organisational
support.
A massive debt of thanks is owed to Farideh Miraki-Moud, for teaching me all of the
laboratory skills I know, and for her endless patience and generosity of advice when things
went wrong in the lab. In particular, she developed many of the protocols adapted for
handling small numbers of cells: without her assistance, I doubt there would be any results
at all!
To Rebecca Pike and the Flow Laboratory team for their assistance and good humour with
endless, endless sorting sessions; to Sameena Iqbal and the Tissue Bank team for their
collection of samples, and my endless requests for vials; and to Janet Matthews in the
Clinical Database team for her assistance in supplying patient information. Additional
thanks to Emily Sanderson, Robert Petty, James Heward and Jeff Davies for providing me
crash courses in Statistics and Genetics in the last year.
To CRUK and QMUL for their unquestioning support during my maternity leave, and for
easing my transition back to the world of work after 12 months of changing nappies.
Finally my thanks to all of the patients and healthy donors who donated the tissue required
for this project, and the clinical staff involved in collection and consent procedures.

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Table of Contents
Statement of Originality 1
Details of Collaboration 2
General 2
Chapter 3: Study of patients with AML who present without trilineage haematopoietic failure 2
Chapter 5: Enumerating Stem Cells in Primary Diagnostic Bone Marrow samples from Patients
Presenting with Acute Myeloid Leukaemia 2
Chapter 7: Using RNA-Seq to compare the transcriptomes of normal HSCs from AML and control
bone marrow samples 3
Publications 4
Meeting Abstracts 4
Abstract 5
Acknowledgements 7
Table of Contents 8
Table of Figures 16
Table of Tables 20
Chapter 1 Introduction 24
1.1 Background 24
1.2 Normal Haematopoiesis 24
1.2.1 Introduction 24
1.2.2 Site of Haematopoiesis 25
1.2.3 The hierarchy of haematopoietic development 25
1.3 The Haematopoietic Stem Cell 27
1.3.1 The HSC concept 27
1.3.2 Physical location of HSCs 27
1.3.3 Regulation of Stem Cell Behaviour 29
1.3.4 Stem Cell Mobilisation and Homing 31
1.3.5 Methodology for studying stem cells 33
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1.4 Acute Myeloid Leukaemia 35
1.4.1 Introduction 35
1.4.2 Incidence 36
1.4.3 Predisposing Factors to Disease Development 36
1.4.4 Clinical Presentation 36
1.4.5 Diagnosis 37
1.4.6 Classification Systems for AML 41
1.4.7 Current Therapy and Clinical Trials 41
1.4.8 Prognosis 42
1.4.9 The Leukaemia Stem Cell Model 43
1.5 Why does the development of AML lead to a failure of normal haematopoiesis? 44
1.5.1 Introduction 44
1.5.2 The interaction between HSCs and AML: summary of previous work by the group which
led to the hypothesis that acute myeloid leukemia does not deplete normal haematopoietic
stem cells but induces cytopenias by impeding their differentiation 45
1.5.3 The interaction between AML and stromal cells may affect the niche and therefore HSC
development indirectly 49
1.5.4 Caveat: How normal are the “normal” HSCs in acute myeloid leukaemia samples? The
pre-leukaemic stem cell concept 51
Chapter 2 Materials and Methods 53
2.1 Samples and Ethics 53
2.2 Sample Handling Techniques 53
2.2.1 Collection of Fresh Bone Marrow Aliquots for Immediate Analysis 53
2.2.2 Tissue Bank Processing of Samples for Delayed Analysis 54
2.2.3 Processing of G-CSF mobilised peripheral blood and cord blood 54
2.2.4 Tissue Bank storage of bone marrow serum samples 55
2.2.5 Cell Thawing 55
2.3 Cell Counting 56
2.3.1 Automated Assessment of Cell Numbers 56
2.3.2 Manual Counting of Cell Numbers 56
2.4 Flow Cytometry 56
2.4.1 Background 56
2.4.2 Fluorescence Activated Cell Sorting (FACS) 57
2.4.3 Specific Uses of Flow Cytometry in this Thesis 58
2.4.4 Fluorochrome Panel Selection 58
2.4.5 Specific Techniques 58
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