Theses - Oncology


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  • ItemEmbargo
    Characterisation of HIF2A targets identifies MYC as a key determinant of HIF2A dependency in ccRCC
    Dyas, Anna Elizabeth
    Despite advancements in ccRCC treatment, the prognosis for metastatic disease remains poor with a 5-year survival of approximately 10%. VHL loss is an early driver event in the vast majority of ccRCC cases and results in constitutive activation of HIF2A, making HIF2A an important clinical target. While HIF2A inhibitors are showing promising results in clinical trials, many patients do not respond and ultimately most patients progress. To improve our understanding of HIF2A dependency in metastatic ccRCC, I developed and thoroughly validated a comprehensive approach to identify HIF2A transcriptional targets *in vivo*. I demonstrated that HIF2A can be acutely degraded in a xenograft model of ccRCC using AID2 technology, and that combining this with RNA-seq uncouples direct targets from downstream signalling cascades. This unbiased method enabled the shortlisting of clinically relevant candidate HIF2A direct target genes which could then be functionally tested by *in vivo* CRISPR/Cas9 screening and subsequent rescue experiments. CRISPR/Cas9 screening revealed that *MYC* and *CCND1* are key dependencies in ccRCC *in vivo*, in addition to highlighting key differences between *in vitro* and *in vivo* dependencies. By leveraging a doxycycline-inducible HIF2A expression system, combined with exogenous constitutive expression of *MYC* or *CCND1*, I showed that MYC, but not CCND1, is sufficient to rescue tumour maintenance upon HIF2A loss. While both cell cycle-associated genes drive proliferative signalling, I demonstrated that only MYC protects from apoptosis, providing mechanistic insights into the role of HIF2A-dependent *MYC* expression in ccRCC. The results presented here provide a workflow for unbiased, *in vivo* characterisation of oncogenic transcription factors, and novel insights into HIF2A dependency in ccRCC.
  • ItemEmbargo
    Targeting DNA Repair in Prostate Cancer: Therapeutic Combinations & Disease Models
    Hanson, Robert
    Targeting prostate cancer cells with DNA repair inhibitors presents an opportunity to improve outcomes in patients with poor prognosis cancers. There are multiple reasons which rationalise targeting DNA repair in prostate cancer, including the enrichment of DNA repair genetic alterations in men with poor prognosis disease, as well as clinical reports of PARP inhibitor efficacy in patients with and without defective homologous recombination repair defects, when combined with standard-of-care antiandrogen therapies. However, the dominant molecular mechanisms underlying tumour cell responses to DNA repair and antiandrogen combination treatment remain unascertained. Within this thesis, I review the rationale supporting the clinical utility of DNA repair inhibitors in prostate cancer, as well as the exploration of mechanistic hypotheses behind the combinatorial efficacy of antiandrogen and DNA repair-targeted therapies. Using prostate cancer cell line models, the effect of multiple drug combinations on cell viability was profiled, highlighting synergistic interactions between the AR signalling inhibitor Enzalutamide (Enza) when combined with either PARP inhibitor Olaparib or ATM inhibition (ATMi). Olaparib and Enzalutamide combination treatment were determined to transcriptionally downregulate cell cycle progression signatures. Cell cycle analysis demonstrated G2/M accumulation, providing indications of delayed cell cycle progression due to DNA damage in the combination treatment. With regards to ATM inhibition, AR-null prostate cancer cell lines were observed to be highly sensitive to single-agent treatment. In AR-dependent prostate cancer cells, single-agent Enzalutamide or ATMi resulted in mild inductions of yH2AX levels, whereas ATMi and Enzalutamide combination treatment resulted in yH2AX suppression. This indicates an interaction between these therapies which impairs DNA damage response signalling. A whole genome CRISPR-Cas9 screen was performed to identify candidate genes that may drive sensitivity or resistance to combination treatment strategies. The findings from this work provide insights into the potential for targeting DNA repair in prostate cancer and possible mechanisms underlying the observed synergistic interactions in combination treatments. Novel groups of factors were indicated to drive exceptional sensitivity to each combination treatment. These gene sets were enriched for chromatin remodelling factors, transcriptional regulators and modulators of TGF-β signalling, presenting novel mechanisms which drive DNA repair combination therapy responses in prostate cancer. Finally, exploratory studies were conducted which leveraged patient tissue samples. This included the characterisation of *ex vivo* organoid cultures derived from high-risk localised prostate cancers, as well as preliminary tumour transcriptomic analysis for the CaNCaP03 Olaparib vs Olaparib with androgen deprivation window-of-opportunity trial. Transcriptomic analysis of patients treated with these therapies showed alignment with *in vitro*-based hypotheses. Overall, this work provides novel insight into the mechanistic underpinnings of DNA repair-targeted therapies in prostate cancer and highlights critical cell signalling pathways for further exploratory work.
  • ItemOpen Access
    The Development of the Prognostic Breast Cancer Model PREDICT
    Grootes, Isabelle
    Background: PREDICT Breast is an online prognostication and treatment benefit tool to aid clinical decision making for patients with early invasive breast cancer. Since its development in 2010, the model has shown a variety of prognostic outcomes among numerous studies. Due to improvements in breast cancer survival and advancements in cancer treatments, the model might be outdated and could lead to imprecise survival predictions. The aim of this doctoral research was to update the model and enhance its model performance in order to contribute to more accurate predictions for individual patients. The first aim was to investigate and incorporate the prognostic effect of the biomarker progesterone receptor (PR) into the model. Another objective was to address the underestimation and overestimation of breast cancer mortality by amending the prognostic tool with more recent data. Methods: The prognostic effect of PR status was based on the analysis of data from 45,088 breast cancer patients of European descent from 49 studies in the Breast Cancer Association Consortium (BCAC). Cox proportional hazards models were used to obtain estimates of the relative hazard for breast cancer-specific mortality associated with PR status after adjusting for the prognostic factors found in version 2.2. Separate models were derived for oestrogen receptor (ER)-negative cases and ER-positive cases. Data from an independent cohort of 11,365 breast cancer patients from New Zealand were utilised for external validation. Model calibration, discrimination and reclassification were used to test the model performance. Data from 34,265 ER-positive cases and 5,484 ER-negative cases diagnosed from 2000 to 2017 in the regions served by the Eastern cancer registry were used for model development of the updated version of PREDICT Breast. Various statistical fitting methods were applied to enhance the ability to capture the shape of the survival data and examine for any non-linear effects in the continuous prognostic factors, and to improve model performance relative to the previous version (v 2.2). These techniques were compared with each other based on the Akaike Information Criterion (AIC) value. Subsequently, Cox proportional hazards models with the optimal modelling method were fitted to estimate the prognostic effects of the risk factors found in PREDICT Breast and to compute the baseline hazard functions for the ER-specific cases separately. For external validation, data from West Midlands cancer registry on 32,408 breast cancer patients were used to determine the discriminative power, calibration and reclassification of the new version of PREDICT Breast. Findings: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with ER-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3×10−6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1,151 predicted. The AIC measurements showed that multiple fractional polynomials best capture the non-linear effects of the continuous risk factors and were used to estimate the non-linear transformations. The new model shows to be well-calibrated. 10-year breast cancer deaths were slightly under-predicted in the Eastern cancer registry (ER-: -2.5%, ER+: -1.4%) and over-predicted in the West Midlands data (ER: 0.1%, ER+: 6.8%). The AUC for 15-year breast cancer survival improved from 0.833 to 0.836 (p = 2.3x10−4) in the Eastern cancer registry data and from 0.810 to 0.812 (p = 0.098) in the West Midlands data. Conclusion: Incorporating the prognostic effects of PR status and year of diagnosis, updating the prognostic effects of all risk factors and amending the baseline hazard functions have led to an improvement of model performance of PREDICT Breast and resulted in more accurate absolute treatment benefit predictions for individual patients. I developed an enhanced version of the prognostic tool and successfully validated it utilising several independent data sets. The updated version will shortly be implemented online.
  • ItemEmbargo
    Elucidating TRPA1 Ion Channel Aberrations in Oesophageal Adenocarcinoma.
    Kosmidou, Kassandra; Kosmidou, Cassandra [0000-0003-2236-246X]
    Oesophageal adenocarcinoma (OAC) is the 14th most common cancer, accounting for 5% of cancer mortalities in the UK. The genomic landscape of OAC is driven by structural variations and is characterised by high mutation burden. Although recurrent mutations are observed in only few genes, we have identified TRPA1 (Transient Receptor Potential Ankyrin 1) as a novel driver gene in OAC with recurrent mutations in a sequenced cohort of 551 OAC patients. TRPA1 is a ligand-gated, Calcium (Ca2+) -permeable membrane protein, which has recently been implicated in breast and prostate cancers. This doctoral thesis aims to uncover the tumour-promoting effects of TRPA1 in OAC, by using a multi-disciplinary approach including bioinformatics, molecular modelling, biophysics, network modelling, and molecular biology techniques. Work presented in this thesis identifies missense point mutations in TRPA1. The location of these mutations along the protein, reveals a mutation cluster in the intracellular N-terminal region, namely the Ankyrin Repeat Domain (ARD). The cryo-EM structure of TRPA1 is partially resolved, and the first 445 aminoacids spanning the ARD are missing from the crystallised structure. Through homology modelling, a full-length model of TRPA1 is constructed and the protein’s dynamics are studied by Molecular Dynamics (MD) simulations. MD analyses in coarse- grain (CG) resolution reveal a flexible hinging of the otherwise rigid ARD. OAC point mutations are located on the predicted flexible loop, and I hypothesize that these mutations alter protein dynamics and flexibility. CG-MD simulations of the full-length protein embedded in a lipid bilayer show that TRPA1 mutations neither enhance nor hinder the flexibility observed in the ARD. By applying in silico methods, ten OAC point mutations are selected for downstream experimental validation, and their effect on Ca2+ flow is measured using Fura-2 Ca2+ imaging in 2D cell lines. Exogenous vectors containing mutant and wild-type TRPA1 are introduced to cells via lentiviral transduction. Missense mutations E179K, K186N, Q204K, K390N and H1018R reduce Ca2+ flow compared to WT, while L290P in the ARD, causes complete loss of Ca2+ entry following stimulation with Cinnamaldehyde, a TRPA1-specific agonist. OAC missense mutations do not cause significant changes in cell growth and proliferation, as measured by the Incucyte® platform. A network modelling approach is then employed to explore the role of TRPA1 in cellular Ca2+ signalling dynamics, and to simulate TRPA1 loss-of-function and gain-of-function scenarios in a cancer cell. First, a static disease map is built by performing a literature review on known Ca2+ effectors in OAC, using CellDesigner. The static network is then converted to an executable, dynamic network, where changes in the cell’s Ca2+ signalling apparatus are explored in silico, using the BioModel Analyser (BMA) software. This data, in combination with Gene Set Enrichment Analysis (GSEA) from OAC patient data, identify hypoxia and pro-apoptotic pathways to be dysregulated following changes in TRPA1 expression. This doctoral thesis reveals a multi-scale approach towards better understanding the complex processes by which TRPA1 can promote oncogenic processes in OAC.
  • ItemOpen Access
    Investigating the role of PTPRK in homeostasis and disease
    Young, Katherine
    Cell communication is critical in orchestrating a proportionate response to external factors, such as growth factors and during essential processes, such as junctional remodelling. Plasma membrane-localised receptor PTPs (RPTP) are well positioned to sense external environmental cues, such as cell-cell contact, and transmit signals via their intracellular domains. Using unbiased approaches we find RPTP, PTPRK binds and dephosphorylates key junctional regulators in epithelial cells. Consequently, PTPRK knockout (KO) epithelial cells exhibit impaired morphology and junctional integrity. In parallel, we find *Ptprk* KO mice are more susceptible to DSS-induced colitis and exhibit increased growth and invasion in a colorectal cancer model. These observations support its putative role as a tumour suppressor in several cancer types and its association with inflammatory bowel disease. Strikingly, we find that the ability of PTPRK to supress tumour growth in a colorectal cancer xenograft model does not require its catalytic activity. We employ the use of multi-omics to discover that this phenotype could be attributed to an enhanced susceptibility to growth factor stimulation, particularly epidermal growth factor.
  • ItemOpen Access
    Dissecting adult epithelial cell plasticity using a model of oesophageal-to-skin lineage conversion
    Jimenez Gomez, Paula; Jimenez Gomez, Paula [0000-0001-5189-3951]
    Epithelial cells possess a remarkable capacity to rapidly adapt their cell fate programme in response to changing tissue demands. Upon tissue injury or environmental perturbations, adult committed cells can reacquire stem cell properties, thereby expanding the pool of cells that contribute to tissue regeneration. Notably, this ability to rewire the cell fate programme – known as cell fate plasticity – extends beyond physiological constraints. When exposed to ectopic cues, epithelial cells can alter their identity as directed by the surrounding microenvironment. A deeper understanding of the mechanisms that govern these changes in cell identity holds great promise for regenerative medicine. However, our current knowledge of these processes is very limited. Here, I adapted an *ex vivo* regenerative model to investigate adult oesophageal cell fate in response to the ectopic microenvironment of the skin. For this, I exposed the appendage-free mouse oesophageal epithelium to the mouse skin dermis, bearing empty niches for hair follicles. Whole-mount techniques together with immunofluorescence analysis revealed that oesophageal cells re-epithelialized the skin dermis and underlying niches, forming a new epithelium with associated appendages structurally similar to hair follicles. By looking into surrogate markers of oesophageal and skin lineages, I found that oesophageal cells were instructed to change towards the skin lineage. Further investigation confirmed that the cues dictating lineage conversion emerged from the skin dermis. Yet, histological characterization and transcriptomic analysis unveiled high heterogeneity in response to dermal signals, denoting the inefficiency of the lineage conversion process. To investigate the mechanisms promoting/preventing oesophageal-to-skin lineage conversion, I made use of an in-depth single cell RNA sequencing dataset. Interestingly, cells transitioning towards skin identity showed a regenerative profile defined by a marked hypoxic signature. To further study the relevance of this signature for lineage conversion, I used gain and loss of function experiments targeting the hypoxia-inducible factor-1α (HIF1a) and its downstream target SRY-box transcription factor 9 (SOX9). These results unveiled that the HIF1a-SOX9 axis poses a barrier to oesophageal-to-skin lineage conversion. In turn, when this barrier is lifted cells respond better to the dermal signals instructing alternative fate choices. Finally, I explored the contribution of oesophageal cells to hair follicle formation following transplantation into the skin. These *in vivo* experiments confirmed that oesophageal cells have the ability to reconstitute functional hair follicles giving rise to hair. Taken together, the results of my PhD project reveal the existence of barrier mechanisms to cell fate plasticity, whereby the same cues that promote tissue regeneration prevent free-access to alternate fates. Future studies will be needed to investigate the physiological relevance of these mechanisms in the context of wound-healing and cancer, where plasticity is known to operate.
  • ItemEmbargo
    Transcriptional and Chromatin Disorientation Associated with BRCA2 Inactivation
    Gupta, Komal
    Monoallelic germline mutations in the tumour suppressor gene BRCA2 predispose to breast, ovarian, prostate and pancreatic cancer. Functionally, BRCA2 protein is involved in genome integrity maintenance via homologous recombination repair, DNA replication fork protection, and R-loop resolution. However, the mechanism by which BRCA2 inactivation causes cancer remains unclear. In this study, using RNA-seq and ATAC-seq I investigated whether BRCA2 acts as a tumour suppressor via regulating the transcriptional and chromatin organization. Using RNA seq datasets from BRCA2 mutant MCF10A cell lines and TCGA breast cancers, I report that BRCA2 inactivation leads to dysregulation of genes involved in the cell cycle, DNA repair, and replication. Strikingly, oncogene MYC targets are upregulated upon biallelic, but not monoallelic BRCA2 loss, provoking the hypothesis that MYC signalling activation is accompanied by the loss of the second BRCA2 allele. Interestingly, ATAC seq in BRCA2 WT and mutant cells to explore the effect on chromatin organization revealed that BRCA2 inactivation leads to increased heterochromatin accessibility. Further, investigating the underlying epigenetic alterations showed that BRCA2 deficient cells had a loss of repressive H3K9me3 mark which was associated with chromatin accessibility. Importantly, this chromatin de-repression was accompanied by increased expression of repetitive RNAs, which have been implicated in inducing DNA damage, genomic instability, and chromosomal segregation defects. However, the causality between chromatin changes and de-repression of repetitive RNA is not clear yet. Lastly, I explored ways to exploit the above findings to detect BRCA2 loss of heterozygosity among patients using cell-free DNA. Overall, these findings provide new insights into the tumour suppressive role of BRCA2 in maintaining global heterochromatin integrity and repetitive DNA repression which engenders novel oncogenic driver mechanisms in BRCA2 loss-associated cancers.
  • ItemOpen Access
    Integrating Epidemiological and Genomic Factors to Inform Outcomes in Barrett’s Oesophagus and Oesophageal Adenocarcinoma
    Zamani, Shahriar; Zamani, Shahriar [0000-0001-8622-5013]
    The incidence of oesophageal adenocarcinoma (OAC) has rapidly increased, and its prognosis remains poor. Barrett’s oesophagus (BO) is considered the precursor to OAC, however, BO is not apparent adjacent to tumour in nearly half of OAC patients. We have previously demonstrated that patients with BO-adjacent tumours (BO+ve OAC phenotype) have a favourable prognosis compared to those without evidence of BO adjacent to the tumour (BO-ve OAC phenotype). It has been suggested that the BO-ve OAC tumour phenotype may arise independently of BO. Recent experimental and computational studies show that all OACs likely arise from BO, even if this precursor lesion is not histologically apparent adjacent to the tumour. However, there is a lack of consolidated clinical, epidemiological and molecular data to examine this question. In this thesis, I used orthogonal approaches to examine the overlap between the BO+ve OAC and BO-ve OAC phenotypes and explain the aetiology and the observed altered prognosis. To achieve this, I assembled a large cohort (n=4,695) comprising BO+ve OAC cases (n=1,235), BO-ve OAC cases (n= 880), OAC cases with an unascertainable BO status (BO(?) OAC; n= 985), cancer-free BO cases (n=1,091) and reflux controls (n=554). A subset of the OAC cases (n=950) with available clinical, epidemiological and whole-genome sequencing data was also examined. There was little to no association between most of the 34 clinical and epidemiological factors and the OAC phenotypes. Weak associations were observed for cigarette smoking and gender with self-reported ever-smoking and female cases being more likely in the BO-ve OAC phenotype group relative to the BO+ve OAC phenotype group. However, tumour stage, lymph node spread and metastasis (TNM) was strongly associated with increased risk of BO-ve OAC. Higher TNM stage was strongly correlated with BO-ve OAC with an adjusted odds ratio of 2.4 (95\% CI:1.8-3.3), 2.9 (95\% CI:2.2-3.9) and 3.2 (95\% CI: 1.7-5.9) for stages II, III and IV, compared to stage I. The improved survival associated with BO+ve OAC persisted in survival analyses adjusted for the tumour stage and location as well as the effects of smoking, obesity and heartburn (adjusted hazard ratio=0.88, 95\% CI: 0.77-0.95, p=0.015). Of note, the BO-ve OAC phenotype was reported for 21 OAC cases with a history of undergoing endoscopic surveillance for BO. Seven different types of genomic alterations were examined in relation to the OAC phenotypes. BO+ve OAC tumours had a slightly higher tumour mutation load relative to BO-ve OAC tumours, which was not explained by the effects of ageing and cigarette smoking. There were no differences in the distribution of driver gene alterations, frequency of whole-genome doubling events, or rates of aneuploidy between the OAC phenotypes. Similarly, the prevalence of complex events such as breakage-fusion-bridges and extrachromosomal DNA did not differ according to OAC phenotype. Importantly, signature 17, which is shown to be preserved across the BO-OAC continuum, was equally enriched among the BO+ve OAC and BO-ve OAC tumours. This thesis presents the first comprehensive evaluation of epidemiological, clinical and molecular factors between the two defined OAC phenotypes. While certain epidemiological factors differ between the phenotypes, they do not explain the observed prognostic difference. The genomic landscapes of these tumour phenotypes were remarkably similar. Taken together, it is likely that all OACs arise from BO even if this precursor lesion is no longer apparent at the time of diagnosis or resection pathology. The advanced-stage tumours suggest that the precursor lesion is overgrown in BO-ve OACs. This work contributes evidence for screening strategies focused on identifying individuals with BO to reduce the public health burden of OAC.
  • ItemOpen Access
    Quantitative Analyses of Normal and Precancerous Somatic Evolution in Human Tissues
    Poon, Yeuk Pin Gladys
    Cancer arises from a single cell of origin whose lineage accumulates somatic mutations in a step-wise manner over time. The evolutionary process towards cancer development is dynamic and the earliest mutation may arise decades before the onset for some cancers. This calls for a quantitative approach for probing early cancer evolution using measurable quantities in normal and precancerous tissues. Genetic alterations under positive selection in ostensibly healthy tissues have implica tions for cancer risk. However, total levels of positive selection across the genome remain unknown. How much positive selection elsewhere in the genome is missed by gene-focused sequencing panels? Synonymous passenger mutations that hitchhike to high variant allele frequency are influenced by any driver mutation, regardless of type or location in the genome, and can therefore be used to estimate total levels of positive selection in healthy tissues. By comparing observed numbers of synonymous passengers to the numbers expected due to driver mutations in canonical cancer genes, we showed in chapter 2 and 3 that it is possible to quantify missing selection left to be explained by unobserved drivers elsewhere in the genome. We analysed the variant allele frequency spectrum of synonymous mutations from physiologically healthy blood and oesophagus to quantify levels of missing positive selection. In blood we found that only ∼ 30% of synonymous passengers can be explained by SNVs in canonical driver genes, suggesting high levels of positive selection for other mutations elsewhere in the genome. In contrast, approximately half of all synonymous passengers in the oesophagus can be explained by just the two driver genes NOTCH1 and TP53, suggesting little positive selection elsewhere. In tissues with high levels of ‘missing’ selection, we showed that our framework can be used to guide targeted driver mutation discovery. In chapter 5 we used single-cell DNA sequencing of >2000 preleukemic haematopoietic stem cells across 8 DNMT3Amut/NPM1c acute myeloid leukemia (AML) patients to reveal the patterns of driver mutation co-occurrence in ostensibly healthy stem cells. We constructed phylogenetic trees using preleukemic HSCs for all eight patients and assigned cells to tree nodes based on both single-cell and bulk sequencing information. We found that in all cases the development of AML required a single cell to acquire 3-4 key driver events. Mutation co-occurrence patterns and mutation acquisition orders were consistent with findings from other studies. Using a model developed in chapter 4, we gained power in using evolutionary histories revealed by clonal trees to separate out parametrical influence of the two major parameters µ and s in preleukemic evolution. We showed that the k-hit staircase model makes many tractable predictions regarding variation across individuals and large variations are not unexpected from the inherent stochasticity of the process. We gained important insights into precancerous evolutionary dynamics by performing quantitative analyses on genetics data obtained from both normal and preleukemic tissues. What we presented here shows that quantitative approaches combined with clear model hypotheses carry explanatory powers to explain observed patterns in genetics data with reference to the mechanisms and processes of early cancers
  • ItemOpen Access
    Characterising DNA methylation in tissue and liquid samples from patients with renal tumours
    Rossi, Sabrina Helena; Rossi, Sabrina [0000-0001-7048-7158]
    The incidence of renal cell carcinoma (RCC) and small renal masses (SRMs), defined as <4cm in diameter, is increasing dramatically. SRMs encompass a variety of potential diagnoses, including benign and malignant tumours, the most common of which is clear cell RCC (ccRCC). Current methods are unable to confidently distinguish pathological subtypes of SRMs, meaning patients with benign tumours are undergoing unnecessary invasive surgery. In addition, there are difficulties risk stratifying patients with ccRCC and predicting outcomes. Genomic alterations, such as mutational analysis, may have a role in RCC diagnosis and prognostication, but are unlikely to be sufficient alone due to low recurrence rates and significant intra-tumoral heterogeneity (ITH), which limit detection. Changes in DNA methylation are abundant and often early events in tumorigenesis, which may overcome these challenges as potential tumour markers both in tissue and liquid biopsies. To address the aforementioned diagnostic challenge, I characterised DNA methylation and gene expression in tissue from patients with benign and malignant renal tumours to elucidate similarities and differences between tumour subtypes. Subsequently, DNA methylation data were combined on over 1200 tissue samples and these were used to train and test MethylBoostER (Methylation and XGBoost for Evaluation of Renal tumours), a machine learning model to predict common pathological subtypes of renal tumours. MethylBoostER was externally validated on four independent publicly available datasets (N=518), demonstrating a high accuracy (receiver operating characteristic area under the curve; AUC >0.90). MethylBoostER predicted consistent classification of multi-region samples from the same patient in 90% of individuals, suggesting ITH does not limit model applicability in a biopsy setting. Subsequently, I undertook a systematic evaluation of methylation heterogeneity in ccRCC, exploring associations with clinical/prognostic parameters and highlighting implications for biomarker selection. I evaluated multi-region tissue samples (N=135) from ccRCC patients (N=18) and assessed heterogeneity between patients, within a patient and within a sample. Inter-patient heterogeneity dominated over intra-tumoural heterogeneity. My analysis represents the first evaluation of epipolymorphism, a measure of methylation heterogeneity within a sample, in ccRCC. Significant differential epipolymorphism was noted in ccRCC versus normal kidney at the promoter region of genes known to be implicated in kidney cancer and this finding was externally validated in an independent cohort (N=71). Although changes in epipolymorphism are believed to be a stochastic process, my results suggest that disordered methylation may accumulate in functionally relevant loci which are known to contribute to ccRCC tumorigenesis. Circulating tumour DNA (ctDNA) represents a promising target for non-invasive liquid biopsy in both diagnostic and prognostic applications. Mutational analyses of ctDNA have produced disappointing detection rates in ccRCC, possibly hampered by low ctDNA levels and high mutational ITH. I therefore performed targeted methylation analysis of ctDNA using a novel method- Nimbus (Non-destructive Integration of Methylation to Boost Underlying Signals). Targeted analysis of hypomethylated regions in plasma ctDNA distinguished ccRCC from cancer-free controls with an AUC of 0.96 and produced superior detection rates compared to mutational analysis (93% vs 50%). My results suggest that tumour signal may be enriched in post-biopsy fluid (proximal sample) compared to plasma (distal sample), a strategy that could be useful in patients with SRMs to complement the current diagnostic pathway and overcome low concentrations of plasma ctDNA. In summary, I comprehensively characterise DNA methylation in tissue and liquid samples derived from patients with renal tumours. In the future, DNA methylation analysis of renal tumour biopsy tissue and/or liquid biopsy samples could enable improved diagnosis of patients with SRMs as well as facilitating prognostic stratification.
  • ItemOpen Access
    Cellular Senescence in Non-Small Cell Lung Cancer: from mechanisms to therapeutic opportunities
    González-Gualda, Estela
    Lung cancer is the leading cause of cancer-related deaths in our society due to the inefficiency of early detection strategies and the high rate of treatment failure. Therefore, a better understanding of the mechanisms underlying its origin and the response to current treatment paradigms are crucial to improve lung cancer survival. Cellular senescence is a powerful tumour-suppressive mechanism whereby cells stably enter a cell-cycle arrest in response to oncogenic stress. However, the accumulation of senescent cells can alter the tumour microenvironment through a strong paracrine secretion of factors that can lead to detrimental and tumour-promoting effects. Intriguingly, senescence has been reported to be a defining feature of early lesions in Non-Small Cell Lung Cancer (NSCLC), a subtype that accounts for over 80% cases of lung cancer. In addition, senescence has also been reported to occur in response to the standard of treatment for this disease. It is thus conceivable that senescence may play a role in the origin and progression of this disease, despite a causal connection remains to be deciphered. Pharmacologic therapeutics that preferentially target senescent cells, known as senolytics, have been successful in preventing and even reversing senescence-driven detrimental effects in multiple pathological processes. However, their suboptimal specificity and toxicities hamper their clinical translation. Therefore, the targeting of senescent cells through the development of second-generation senolytics that can overcome these obstacles has the potential to revolutionise cancer treatment. The aim of this work is to define the role of cellular senescence at the origin and progression of lung cancer and in response to chemotherapy, and to develop safer and more effective therapeutic approaches to eliminate senescent cells in the context of lung malignancies. In this thesis, we studied the accumulation of senescent cells during the development of lung adenocarcinoma using a KrasG12V-driven lung cancer mouse model. We demonstrate that senolytic treatment of early lesions results in a significant reduction in lung tumour burden and increased survival, providing evidence of the tumour-promoting effect of senescence in early stages of NSCLC. Our research also reveals that platinum-based chemotherapy of human and murine lung adenocarcinoma cells induces senescence, which in turn promotes malignant phenotypes on untreated cancer cells in a paracrine manner in vitro, in xenografts and in orthotopic models of lung adenocarcinoma. Through high throughput unbiased transcriptomic and proteomic approaches, we show that secreted TGF-β ligands activate the Akt/mTOR pathway in untreated cells resulting in enhanced tumour growth. We further demonstrate that senolytic treatment and pharmacologic inhibition of TGFβR1 in tumours can prevent increased proliferation and enhance survival of lung tumour-bearing mice. In order to develop a novel approach for improved senolytic treatment, we show that the galacto-conjugation of senolytic ABT-263 (navitoclax) in the form of an activatable pro-drug significantly enhances cytotoxicity in combination with cisplatin, resulting in reduced lung cancer tumour growth. Importantly, our approach demonstrates decreased navitoclax-associated toxicities, including platelet apoptosis in human and murine blood treated ex vivo and decreased thrombocytopenia in mouse lung cancer models. In summary, this PhD thesis provides evidence of the incidence and role that cellular senescence plays in promoting the progression of early and advanced NSCLC and demonstrates that cisplatin chemotherapy drives pro-tumorigenic phenotypes in a paracrine fashion, which can be prevented with senolytic and TGFβR1 inhibitory treatments. Lastly, it proposes a novel second-generation therapeutic approach to mitigate senolytic toxicities and enhance the efficiency of targeting senescence in the context of lung cancer.
  • ItemOpen Access
    The evolutionary dynamics of clonal haematopoiesis and its progression to acute myeloid leukaemia
    Watson, Caroline; Watson, Caroline [0000-0002-8351-268X]
    Acute myeloid leukaemia (AML) is an aggressive blood cancer which claims the lives of 70-80% of patients within 5 years of diagnosis. Like many other cancers, AML usually develops as a consequence of serial acquisition of somatic driver mutations; a process that starts many years, or even decades, before diagnosis. This raises the prospect that early detection of ‘pre-leukaemic’ mutations could be used to identify individuals at high risk of developing AML, in whom early intervention could halt the disease before it fully develops. One of the difficulties with early detection of AML is that clonally expanded leukaemia-associated mutations are also found in the blood of healthy individuals, a phenomenon termed ‘clonal haematopoiesis’. However, most individuals with clonal haematopoiesis will never progress to AML and so a key challenge is the identification of individuals most at risk. To do this, we need a better understanding of the evolutionary dynamics of clonal haematopoiesis in the years, or decades, before AML occurs and how this differs from the dynamics of clonal haematopoiesis in individuals that remain cancer-free. We sought to understand this process by first studying the acquisition and expansion of the initial clonal haematopoiesis driver mutation. Using blood sequencing data amassed from ~50,000 individuals, combined with insights from evolutionary theory, we developed a framework to quantify the mutation rates and fitness effects of clonal haematopoiesis variants down to single nucleotide resolution. This enabled us to build a league table of the fittest and potentially most pathogenic variants in blood. We also quantified the distribution of fitness across key clonal haematopoiesis genes and found the distribution to be highly skewed, with most mutations in these genes conferring either a weak or no fitness effect. Our framework also reveals that whilst cell-extrinsic effects are likely crucial in some situations, the combined effects of chance (when a mutation arises) and cell-intrinsic fitness differences are the major forces shaping clonal haematopoiesis. Mosaic chromosomal alterations (mCAs) can also be important drivers in AML and ~3\% of individuals aged ~40-70 have a clonally expanded mCA detectable in >1% of their blood cells. We therefore adapted our framework to quantify the mutation rates and fitness effects of mCAs in blood and applied this to data generated from ~500,000 individuals in UK Biobank. We find most mCAs confer growth rates of ~10-20\% per year and find correlation between mCA fitness and blood cancer risk. In contrast to the strong age dependence observed in single nucleotide variant prevalence in blood, we find mCA age dependence to be more variable, particularly in women, suggesting the risk of acquisition and/ or expansion of certain mCAs is non-uniform throughout life and is influenced by gender-specific factors. To determine how the dynamics of clonal haematopoiesis differs in individuals who progress to AML, we identified longitudinal blood samples that had been collected annually at multiple timepoints from individuals who subsequently developed AML, as well as age-matched controls who remained cancer free. We developed a custom error-corrected duplex sequencing platform to detect mutations in 34 clonal haematopoiesis/AML-associated genes, genome-wide mCAs and AML-associated translocations and used this to perform an integrative assessment of the genetic changes in these samples. We find there are four main evolutionary patterns in the years preceding AML diagnosis: linear evolution, evolution with clonal interference, static evolution and late evolution. We calculate the age at acquisition of the first and second mutations and, whilst the initial driver mutation is often acquired early in life, there are some very fit ‘uber drivers' which appear to occur as the initial event just ~4 years pre-diagnosis. We find that the variants we identified as ‘highly fit' in clonal haematopoiesis are significantly enriched pre-AML and we were able to determine how fitness effects changed with the acquisition of subsequent mutations. NPM1 mutations, which characteristically occur late in AML development and have never been seen in individuals who do not progress to AML, can be detected as early as 2 years pre-AML diagnosis, highlighting the benefit afforded by low VAF variant calling, particularly in high-risk individuals. This quantitative analysis of clonal haematopoiesis, combined with an integrated assessment of genetic changes in longitudinal blood samples from individuals who progress to AML, reveals important insights into the evolutionary dynamics of mutations in the years preceding AML. Understanding which features distinguish pre-malignant from benign clonal evolution is key for risk stratification of clonal haematopoiesis and will aid in the development of rational monitoring approaches and identification of those who may benefit from early intervention studies.
  • ItemOpen Access
    The Role of the Proneural Transcription Factor ASCL1 in Neuroblastoma Cell Division and Differentiation
    Parkinson, Lydia
    Neuroblastoma is the most common solid childhood cancer and typically has a very poor prognosis. Neuroblastoma is a ‘cancer of improper development’ and is thought to arise from sympathetic neuroblast precursors that fail to engage the neuronal differentiation programme; instead they are locked in a pro-proliferative developmental state. Neuroblastomas are epigenetically regulated, a core regulatory circuit (CRC) of transcription factors maintaining their highly proliferative, developmental state. In subtype MS neuroblastoma, tumours can spontaneously regress, in which case children are cured for life. The mechanisms behind spontaneous regression are poorly understood, but the main hypothesis is that the cells enter a terminal differentiation programme. Thus, harnessing the latent differentiation capacity of neuroblasts provides an exciting therapeutic avenue for drug induced cell differentiation and tumour clearance in neuroblastoma. ASCL1 is a master transcriptional regulator which modulates both proliferation and differentiation of sympathetic neuroblast precursor cells. During development, ASCL1 is transiently expressed and is downregulated as cells differentiate into mature sympathetic neurones. In high-risk neuroblastomas, the levels of ASCL1 remain high, supporting proliferation. The aim of this project was to understand the effect of ASCL1 deletion on neuroblastoma cell behaviour. CRISPR technology was used to remove ASCL1 from three different neuroblastoma cell lines to study the effect of losing ASCL1 in different cellular contexts. It was found that ASCL1 deletion results in slower cell growth, a phenotype consistent in all neuroblastoma cell lines tested. Studies show no difference in the transcription and expression of the CRC transcription factors, but instead their ability to bind to regulatory regions of chromatin is compromised. RIME analysis shows that ASCL1 binds components of the CRC on the chromatin suggesting ASCL1 could be directly recruiting targets. ASCL1 is considered a pioneer factor and ATAC-Seq analysis shows that chromatin accessibility is reduced in the ASCL1 knock-out lines, suggesting ASCL1 could be limiting both chromatin accessibility and directly recruiting transcription factors to the chromatin. In addition to these findings, when analysing RNA-Seq and ATAC-Seq data it appears ASCL1 maintains neuroblastoma cells in a state which is primed for differentiation. Taken together these results suggest ASCL1 has a dual role in neuroblastoma, supporting both the proliferative state and also poising cells for differentiation.
  • ItemOpen Access
    Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer with Gene Expression and Computational Pathology
    Cope, Wei; Cope, Wei [0000-0002-5661-3522]
    Many breast cancer patients are treated with chemotherapy before surgery for the removal of the tumour, which is known as neoadjuvant chemotherapy (NAT). It improves outcome for many patients, and their response to the treatment is prognostic for their overall outcome. However, not all patients who receive NAT respond to the treatment, and, as a result, many suffer unnecessarily from side effects and delays to surgery. In this thesis, I designed and evaluated two potentially independent and complementary strategies for predicting an individual patient’s response to treatment based on gene expression and computational pathology. Firstly, I attempted to develop a clinically practical approach for classifying breast tumours using RNA from routine formalin fixed paraffin embedded (FFPE) histopathological samples. Breast cancers can be classified into distinct groups, 'integrative clusters' (IntClusts), with different outcomes and potentially different response to NAT. The published classification is based on RNA expression from fresh frozen tissue, which is impractical in a clinical setting. Initially, I attempted to build an accurate classifier for IntClusts based on RNA expression from widely available FFPE tissue, using a user-friendly NanoString technique. Unfortunately, it was not possible to achieve reliable classification with this method using the gene probe set pre-selected based on fresh frozen tissue. Next, I sought to identify the genes whose expression was not affected by the fixative process by comparing paired FFPE and fresh frozen tissue with RNA sequencing, a method that allows the quantification of all genes. There was poor agreement in measured gene expression between the two types of tissue sample, FFPE versus frozen, and between the assessment methods on the same tissue type, RNA-sequencing versus Illumina microarray, resulting in unreliable classification of tumours into integrative clusters. These findings represent a challenge to the adoption of the integrative clusters in real-world precision medicine. Secondly, I developed quantitative computational methods for the assessment of digitized H&E slides, which are routinely produced clinically. I developed and validated two machine learning methods for cell classification, where cells on an image can be automatically detected and identified as tumour cells, lymphocytes, or stromal cells. I also show that my method can be effectively generalised to immunohistochemistry slides. In a novel dataset, using a new method, I replicate the previous finding that the presence of immune infiltrate in pre-treatment biopsies is predictive of NAT response. I then used this cell classification to demonstrate that the spatial profiles of tumour clusters and their relationship to immune cells are associated with treatment outcome. Specifically, I found that larger tumour clusters, more heterogeneous tumour clusters, and more lymphocytes in the region immediately bordering tumour clusters are all correlated with pathological complete response to NAT. The spatial features of the peri-tumour region were more predictive than the features of the tumour itself, suggesting a particularly important role for the interface between tumour clusters and their immune microenvironment. To conclude, I review the large number of further studies spawned by the work I present in this thesis, and explain how they might improve our ability to understand tumour biology, and translate this understanding to the clinical setting. In summary, I have explored the real-world applicability of gene expression profiling and computational pathology methods in widely available clinical samples. These approaches have the potential for translation into adjuncts to existing stratification methods, offering patients better care. This thesis provides a step towards the translation of the molecular classification of breast cancer, and computational methods for pathology image analysis, into real-world precision medicine, predicting response to neoadjuvant chemotherapy.
  • ItemOpen Access
    The role of NEDD9 in TGFβ mediated tumour initiating cell dynamics in the Claudin-low breast cancer subtype
    Greenwood, Wendy; Greenwood, Wendy [0000-0002-2509-8695]
    Breast cancer is an extremely heterogeneous disease comprising at least ten different subtypes, each exhibiting different characteristics in progression, prognosis and response to treatment. Transforming growth factor β (TGFβ) a member of the TGF superfamily of cytokines differentially regulates breast tumour-initiating cells (BTICs). In the claudin-low breast cancer subtype, TGFβ increases the tumour initiating capacity through the ability of the scaffolding protein NEDD9 to unite the TGFβ/SMAD and Rho-Actin-SRF pathways. Previously, oncogenicity has been ascribed to the level of NEDD9 protein expression. However, my analysis indicates this mediation by NEDD9 is irrespective of NEDD9 protein expression, which is ubiquitously overexpressed in the majority of cancer types including breast cancer. In this thesis, I demonstrate how in the Claudin-low breast cancer subtype NEDD9 protein expression and post-translational modification are influenced by TGFβ pathway activation. I identify significant NEDD9 interacting proteins and their downstream effectors which contribute towards oncogenic TGFβ signalling pathways. A key TGFβ specific NEDD9 interactor identified in this subtype is the metabolic isoenzyme PKM2. Through a variety of techniques, I explore the known roles of PKM2 in the regulation of oncogenic metabolic reprogramming and demonstrate how these processes are influenced by its association with NEDD9. Finally, I investigate potential translational applications and biomarkers of TGFβ mediated, NEDD9/PKM2 dependent downstream signalling pathways, using large clinical breast cancer datasets and patient-derived tumour xenograft (PDTX) models. These data suggest a novel mechanism by which oncogenic TGFβ signalling regulates cellular proliferation and self-renewal via β-Catenin/c-Myc regulation of altered metabolism in the Claudin-low breast cancer subtype, a process which is dependent upon the scaffolding protein NEDD9 and the metabolic enzyme PKM2. Together, these data suggest that a combined biomarker of TGFβ signalling and c-Myc expression may be useful in identifying a subset of Claudin-low breast cancer patients who would be sensitive to inhibition of Wnt/β-Catenin signalling. Additionally, due to the dependence of these tumours on c-Myc driven glutamine dependent metabolic processes, metabolic magnetic resonance imaging may be useful for monitoring response in these patients.
  • ItemOpen Access
    Defining Epithelial Cell Fate Dynamics of the Oesophagus during Postnatal Development and Homeostasis
    McGinn, Jamie; McGinn, Jamie [0000-0003-2267-7437]
    Epithelial cells can respond rapidly to changing tissue demands to ensure organism survival. However, the mechanisms that finely control how cells adapt their behaviour remain largely unknown. To uncover the rules that govern epithelial cell fate, it is critical to understand their dynamic nature by exploring their response to situations away from homeostasis. Postnatal development provides an ideal physiological model of rapid but restricted tissue growth, in which cells switch from a state of expansion to the steady state of homeostasis. In this project, I investigated the cellular and molecular mechanisms that govern this transition in the mouse oesophageal epithelium. Using wholemounting techniques to explore the whole tissue at 3D single cell resolution, I investigated the postnatal-to-homeostatic transition through studies of morphological features and cell fate dynamics. Comprehensive immunofluorescence studies revealed a defined period in time when homeostatic features become established. Typical adult marker gene expression and tissue morphology, such as keratinization and cornification, were evident from P28, indicating the transition point towards homeostasis. By looking at the localisation of transcription factors associated with cell fate, I identified a temporal gradient of expression that spans postnatal development. After birth, during a period of rapid tissue expansion, a fraction of the basal population was seen to express the regenerative marker SOX9. This population progressively reduced as the tissue reached the transition point, coinciding with the emergence of a new basal population expressing KLF4, which is known to mark keratinocyte differentiation. Next, I questioned the relevance of the KLF4+ basal population by analysing proliferative capacity and the associated keratin profile. The results indicated KLF4 as a marker of commitment towards differentiation in the oesophageal basal layer, balancing progenitor cell behaviour and defining the establishment of tissue homeostasis. To investigate the molecular signature of the basal cell population throughout postnatal development, I executed an in-depth single cell RNA-sequencing analysis, revealing that the onset of homeostasis occurs simultaneously with changes in the expression of genes associated with mechanics. I was able to identify that the postnatal oesophagus is defined by a differential growth, leading to the build-up of longitudinal mechanical strain as the tissue matures. To further study the relevance of tissue strain for epithelial cell behaviour, I developed and applied an in vitro system of whole-organ stretching. This approach unveiled a mechanism whereby mechanical stress at the organ level triggers the establishment of the KLF4-expressing committed basal population in the oesophageal epithelium in a YAP dependent fashion. Together, the results of this project indicate a simple mechanism for the control of epithelial cell fate, whereby mechanical changes at the whole organ level orchestrate the establishment of tissue homeostasis at the cellular level.
  • ItemOpen Access
    Somatic evolution in normal human endometrium
    (2020-03) Moore, Luiza; Moore, Luiza [0000-0001-5315-516X]
    For decades, the primary focus of cancer research has been the cancer tissue itself. Advances in next-generation sequencing technologies have enabled identification and characterisation of driver mutations, provided insights into the tumour burdens and underlying mutational processes, sub-clonal diversification and tumour heterogeneity. However, all cancers arise from cells that were once normal. Over time, they acquired certain mutations which increased their fitness, giving them a selective advantage over their neighbours and allowing uncontrolled growth, clonal expansion and malignant transformation. Our understanding of somatic evolution occurring in normal tissues with age and in the early stages of tumourigenesis remains relatively poorly understood. In this thesis, I aimed to investigate somatic evolution in normal ageing human tissues. Firstly, I helped to establish a robust low DNA input whole-genome sequencing workflow for laser-capture micro-dissected cellular material. I then utilised this approach to explore the genomic and evolutionary landscapes of the normal human endometrium. In the first results chapter, I investigate the clonal composition of normal endometrial glands. The majority of glands are clonal cell populations that share a common recent ancestor and the monoclonality is independent of whether they have a driver mutation. In the second results chapter, I investigate the mutational landscape of normal endometrial glands. We show that somatic mutations (base substitutions, indels and genome rearrangements) accumulate with age in a more-or-less linear manner. A small number of ubiquitous mutational processes accounts for the majority of all mutations. A remarkably high proportion of normal endometrial glands carry at least one driver mutation (of the type that one is used to finding in cancers). Accumulation of drivers is negatively affected by parity. Through phylogenetic tree reconstruction of somatic mutations in endometrial glands, we show that driver mutations often occur early in life and continue to accumulate with age. This work identifies a distinct mutational landscape in the normal endometrium that is in keeping with the presence of early positive selection in this highly regenerative tissue.
  • ItemOpen Access
    Quantifying, Understanding and Predicting Differences Between Planned and Delivered Dose to Organs at Risk in Head & Neck Cancer Patients Undergoing Radical Radiotherapy to Promote Intelligently Targeted Adaptive Radiotherapy
    (2020-06-11) Noble, David; Noble, David [0000-0001-6738-2152]
    Introduction: Radical radiotherapy (RT) is an effective but toxic treatment for head and neck cancer (HNC). Contemporary radiotherapy techniques sculpt dose to target disease and avoid organs at risk (OARs), but anatomical change during treatment mean that the radiation dose delivered to the patient – delivered dose (DA), is different to that anticipated at planning – planned dose (DP). Modifying the RT plan during treatment – Adaptive Radiotherapy (ART) – could mitigate these risks by reducing dose to OARs. However, clinical data to guide patient selection for, and timing of ART, are for lacking. Methods: 337 patients with HNC were recruited to the Cancer Research UK VoxTox study. Demographic, disease and treatment data were collated, and both DP and DA to organs at risk (OARs) were computed from daily megavoltage CT image guidance scans, using an open-source deformable image registration package (Elastix). Toxicity data were prospectively collected. Relationships between DP, DA and late toxicities were investigated with univariate, and logistic regression normal tissue complication probability (NTCP) modelling approaches. A sub-study of VoxTox recruited 18 patients who had MRI scans before RT fractions 1, 6, 16, and 26. Changes in salivary gland volumes and relative apparent diffusion coefficient (ADC) values were measured and related to toxicity events. Results: Spinal cord dose differences were small, and not predicted by weight loss or shape change. Mean DA to all other OARs was higher than DP; factors predicting higher DA included primary disease site, concomitant therapy, shape change and advanced neck disease. Nine patients (3.7%) saw DA>DP by 2Gy to more than half of the OARs assessed. These patients all had received bilateral neck RT for N-stage 2b oropharyngeal cancer. Strong uni- and multivariate relationships between OAR dose and toxicity were seen. Differences between DA and DP-based dose-toxicity models were minimal, and not statistically significant. On MRI, both parotid and submandibular glands shrank during treatment, whilst relative ADC rose. Relationships with toxicity were inconclusive. Conclusions: Small differences between OAR DP and DA mean that DA-based toxicity prediction models confer negligible additional benefit at the population level. Factors such as primary disease sub-site, concomitant systemic therapy, staging and shape change may help to select the patients that do develop clinically significant dose differences, and would benefit most from ART for toxicity reduction.
  • ItemOpen Access
    Elucidating oncogenic mechanisms in human B cell malignancies
    (2018-11-24) Caeser, Rebecca
    This study consists of two pieces of work investigating haematological malignancies; Acute Lymphoblastic Leukaemia (ALL) and Diffuse Large B Cell Lymphoma (DLBCL). Firstly, Pre-B ALL represents the most common paediatric malignancy and despite increasingly improved outcomes for patients, ~ 20% of all patients diagnosed with ALL relapse. Activating mutations in the RAS pathway are common (~50%) and result in hyperactivation of the MAPK pathway. I identified Erk negative feedback control via DUSP6 to be crucial for NRASG12D-mediated pre-B cell transformation and investigated its potential as a therapeutic target. I showed that a small molecule inhibitor of DUSP6 (BCI) selectively induced cell death in patient-derived pre-B ALL cells; with a higher sensitivity observed in relapse pre-B ALL. I also discovered that a high level of Erk activity is required for proliferation of normal pre-B cells, but dispensable in leukemic pre-B ALL cells. In addition, I found that human B cell malignancies can be grouped into three categories that fundamentally differ in their ability to control Erk signalling strength. Secondly, DLBCL is the most common haematological malignancy and although potentially curable with chemotherapy, 40% of patients still succumb from their disease. Recent exome sequencing studies have identified hundreds of genetic alterations but, for most, their contribution to disease, or their importance as therapeutic targets, remains uncertain. I optimised a novel approach to screen the functional importance of these mutations. This was achieved by reconstituting non-malignant, primary, human germinal centre B cells (GC B cells) with combinations of wildtype and mutant genes to recapitulate the genetic events of DLBCL. When injected into immunodeficient mice, these oncogene-transduced GC B cells gave rise to tumours that closely resemble human DLBCL, reinforcing the biological relevance of this system. To screen potential tumour suppressor mutations in this system in a high throughput fashion, I developed a lymphoma-focused CRISPR library of 692 genes recurrently altered in B cell lymphomas. These experiments identified GNA13 as an unexpectedly potent tumour suppressor in human GC B cells and provided new understanding to its mechanism of action. These findings provide novel understanding of the complexity of oncogenic mechanisms in human B cell malignancies.
  • ItemOpen Access
    Development of computer-based algorithms for unsupervised assessment of radiotherapy contouring
    (2019-02-23) Yang, Huiqi
    INTRODUCTION: Despite the advances in radiotherapy treatment delivery, target volume delineation remains one of the greatest sources of error in the radiotherapy delivery process, which can lead to poor tumour control probability and impact clinical outcome. Contouring assessments are performed to ensure high quality of target volume definition in clinical trials but this can be subjective and labour-intensive. This project addresses the hypothesis that computational segmentation techniques, with a given prior, can be used to develop an image-based tumour delineation process for contour assessments. This thesis focuses on the exploration of the segmentation techniques to develop an automated method for generating reference delineations in the setting of advanced lung cancer. The novelty of this project is in the use of the initial clinician outline as a prior for image segmentation. METHODS: Automated segmentation processes were developed for stage II and III non-small cell lung cancer using the IDEAL-CRT clinical trial dataset. Marker-controlled watershed segmentation, two active contour approaches (edge- and region-based) and graph-cut applied on superpixels were explored. k-nearest neighbour (k-NN) classification of tumour from normal tissues based on texture features was also investigated. RESULTS: 63 cases were used for development and training. Segmentation and classification performance were evaluated on an independent test set of 16 cases. Edge-based active contour segmentation achieved highest Dice similarity coefficient of 0.80 ± 0.06, followed by graphcut at 0.76 ± 0.06, watershed at 0.72 ± 0.08 and region-based active contour at 0.71 ± 0.07, with mean computational times of 192 ± 102 sec, 834 ± 438 sec, 21 ± 5 sec and 45 ± 18 sec per case respectively. Errors in accuracy of irregularly shaped lesions and segmentation leakages at the mediastinum were observed. In the distinction of tumour and non-tumour regions, misclassification errors of 14.5% and 15.5% were achieved using 16- and 8-pixel regions of interest (ROIs) respectively. Higher misclassification errors of 24.7% and 26.9% for 16- and 8-pixel ROIs were obtained in the analysis of the tumour boundary. CONCLUSIONS: Conventional image-based segmentation techniques with the application of priors are useful in automatic segmentation of tumours, although further developments are required to improve their performance. Texture classification can be useful in distinguishing tumour from non-tumour tissue, but the segmentation task at the tumour boundary is more difficult. Future work with deep-learning segmentation approaches need to be explored.