Characterization of Mechanisms That Mediate Cancer Metastatic Colonization

Metastatic disease is the major cause of death in all solid tumor cancers. Current therapeutic strategies fail to target metastasis as the genes and mechanisms that regulate this process remain poorly understood. Metastatic colonization is the final step of the metastatic cascade whereby cancer cells form a tumor at a distant site. This final step is the culmination of clonal evolution of cancer populations that results in a highly aggressive population with enhanced metastatic capacity and often presents clinically as numerous inoperable tumor nodules that lead to mortality. Characterization of the mechanisms that govern metastatic colonization at cellular and molecular levels is necessary for the prevention and treatment of metastatic disease in patients. The first half of this thesis presents work towards understanding mechanisms that mediate colorectal cancer colonization of the liver in order to guide novel therapeutic strategies. An in vivo large-scale RNAinterference screen was performed to identify genes required for liver colonization. Liver and red blood cell pyruvate kinase (PKLR) was identified as a driver of liver metastasis in experimental models. In patients, PKLR was found to be expressed at higher levels in liver metastases relative to primary colorectal cancer tumors and also overexpressed in the primary tumors of patients with metastatic disease. PKLR was found to promote cell survival in the tumor core and enhance survival during conditions of concurrent high cell density and low oxygen availability. Molecular studies revealed that PKL negatively regulates pyruvate kinase M2 (PKM2) enzymatic activity. By inhibiting cellular pyruvate kinase activity, PKLR allows for the diversion of metabolites towards glutathione generation—allowing for the maintenance of glutathione levels. Adequate glutathione levels appears critical for metastatic colonization as GCLC, the catalytic subunit of glutamatecysteine ligase and the rate-limiting enzyme for glutathione synthesis, was found to be similarly required for effective metastasis, associated in its expression with human liver metastatic progression, and could be therapeutically targeted to reduce metastatic colonization. These findings highlight the impact of metabolic regulation on cancer cell adaptation within the metastatic niche. The robust effects on liver metastatic colonization observed upon modulating this metabolic pathway suggest clinical potential for therapeutic targeting of PKLR or cellular glutathione synthesis in colorectal cancer. The second half of this thesis presents work towards an understanding of diversity generation in clonal populations as it benefits cancer evolution and metastatic colonization. Clonal human breast cancer subpopulations were isolated to allow for the identification of subpopulations that exhibit population-level phenotypic diversity. These high variability clonal subpopulations were found to be more proficient at metastatic colonization—consistent with a positive role for diversification capacity in cancer progression. Through single-cell RNA-sequencing, cell-to-cell transcript expression variability was identified as a defining feature of these subpopulations, extending to protein-level variability. Furthermore, spliceosomal machinery was identified as a gene set with high expression variability, suggesting a means by which variation could be transmitted to a global level. Engineered variable expression of the spliceosomal gene SNRNP40 promoted metastatic fitness, and this metastatic capacity was attributable to cells with low SNRNP40 expression. Clinically, low SNRNP40 expression is associated with metastatic relapse. These findings reveal that transcriptomic variability generation may serve as a mechanism by which cancer subpopulations achieve diversification of gene expression states, which allows for enhanced fitness under changing environmental pressures encountered during metastatic progression

The characterisation of telomere dynamics in Myelodysplastic syndromes

The Myelodysplastic syndromes (MDSs) are comprised of a heterogeneous group of clonal disorders characterised by ineffective haematopoiesis. Although 30 to 35% of MDS cases progress to Acute Myeloid Leukaemia (AML), the majority of patients die from blood related ailments caused by progressive bone marrow failure. Large-scale genomic rearrangements are a key feature of MDS, with different aberrations conferring specific risks of progression. Telomere erosion, dysfunction and fusion, creating cycles of anaphase bridging breakage and fusion is a mechanism that has the potential to drive genomic instability in many tumour types including MDS. The key aim of this project was to examine the role that telomere dysfunction may play in the generation of genomic rearrangements observed in MDS/AML. High resolution Single Telomere Length Analysis (STELA) revealed telomere shortening when compared to age-matched individuals in two cohorts of MDS and AML patients; this included large-scale telomeric deletion events observed within the MDS cohort. A PCR based telomere fusion assay detected telomere-telomere fusion events at a frequency that was consistent with sporadic fusion arising as a consequence of large-scale deletion. Telomerase activity was up-regulated in AML which may contribute to the reduction of deletion and fusion events in these cells. Sequence analysis revealed that telomere fusion was associated with microhomology and sub-telomeric deletion; this profile was consistent with error-prone Ku-independent alternative end joining processes. Telomere length at diagnosis irrespective of conventional markers appeared to influence the overall survival of MDS patients, but this was not apparent in AML. More importantly, telomere length was able to refine favourable prognostic markers, specifically good risk cytogenetics, uni-lineage cytopenia and low-risk IPSS (International Prognostic Scoring System) scores of which MDS patients bearing shorter telomeres for their respective age displayed reduced overall survival. This may be a particularly important finding given the heterogeneous clinical outcomes observed within low-risk MDS patients

Development of novel software tools and methods for investigating the significance of overlapping transcription factor genomic interactions

Identifying overlapping DNA binding patterns of different transcription factors is a major objective of genomic studies, but existing methods to archive large numbers of datasets in a personalised database lack sophistication and utility. To address this need, various database systems were benchmarked and a tool BiSA (Binding Sites Analyser) was developed for archiving of genomic regions and easy identification of overlap with or proximity to other regions of interest. BiSA can also calculate statistical significance of overlapping regions and can also identify genes located near binding regions of interest or genomic features near a gene or locus of interest. BiSA was populated with >1000 datasets from previously published genomic studies describing transcription factor binding sites and histone modifications. Using BiSA, the relationships between binding sites for a range of transcription factors were analysed and a number of statistically significant relationships were identified. This included an extensive comparison of estrogen receptor alpha (ERα) and progesterone receptor (PR) in breast cancer cells, which revealed a statistically significant functional relationship at a subset of sites. In summary, the BiSA comprehensive knowledge base contains publicly available datasets describing transcription factor binding sites and epigenetic modification and provides an easy graphical interface to biologists for advanced analysis of genomic interactions

Dissecting tumor cell heterogeneity in 3D cell culture systems by combining imaging and next generation sequencing technologies

Three-dimensional (3D) in vitro cell culture systems have advanced the modeling of cellular processes in health and disease by reflecting physiological characteristics and architectural features of in vivo tissues. As a result, representative patient-derived 3D culture systems are emerging as advanced pre-clinical tumor models to support individualized therapy decisions. Beside the additional progress that has been achieved in molecular and pathological analyses towards personalized treatments, a remaining problem in both primary lesions and in vitro cultures is our limited understanding of functional tumor cell heterogeneity. This phenomenon is increasingly recognized as key driver of tumor progression and treatment resistance. Recent technological advances in next generation sequencing (NGS) have enabled unbiased identification of gene expression in low-input samples and single cells (scRNA-seq), thereby providing the basis to reveal cellular subtypes and drivers of cell state transitions. However, these methods generally require dissociation of tissues into single cell suspensions, which consequently leads to the loss of multicellular context. Thus, a direct or indirect combination of gene expression profiling with in situ microscopy is necessary for single cell analyses to precisely understand the association between complex cellular phenotypes and their underlying genetic programs. In this thesis, I will present two complementing strategies based on combinations of NGS and microscopy to dissect tumor cell heterogeneity in 3D culture systems. First, I will describe the development and application of the new method ‘pheno-seq’ for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from models of breast and colorectal cancer (CRC). By this approach, we revealed characteristic gene expression that is associated with heterogeneous invasive and proliferative behavior, identified transcriptional regulators that are missed by scRNA-seq, linked visual phenotypes and associated transcriptional signatures to inhibitor response and inferred single-cell regulatory states by deconvolution. Second, by applying scRNA-seq to 12 patient-derived CRC spheroid cultures, we identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. Taken together, we believe that our approaches provide a framework for translational research to dissect heterogeneous transcriptional programs in 3D cell culture systems which will pave the way for a deeper understanding of functional tumor cell heterogeneity