Clinical Pathology - Theses
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ItemHeritable DNA methylation marks associated with familial breast and prostate cancer( 2022)The known genetic risk factors for breast and prostate cancer account for less than 50% and 35% of the familial risk respectively. Early candidate gene studies provided evidence that DNA methylation measured in peripheral blood can mimic the effect of cancer predisposition associated with germline pathogenic variants. Key examples included the increased risk of breast cancer associated with both BRCA1 promoter hypermethylation and intragenic DNA methylation in ATM. More recently, the association between heritable DNA methylation marks and breast and/or prostate cancer risk has been reported by genome-wide studies. However, it is not clear how most of these modifications in DNA methylation mediate phenotypes resulting in increased cancer risk. In this thesis, a recently developed analytic approach, based on complex segregation analysis and family structure, was applied to identify 1,000 heritable DNA methylation marks in 57 families with multiple cases of breast and prostate cancer. Using Cox segregation analysis, we found that 229 and 140 methylation marks were associated with breast and prostate cancer respectively and 63 were associated with increased risk of both cancer types. We developed a Clustered regularly interspaced short palindromic repeats (CRISPR)-based strategy using a dCas9-DNA methyltransferase enzyme (DNMT) and a modified sgRNA containing two PP7 hairpins fused with DNMT3A in the synergistic activation mediator (SAM) system to assess whether induction of DNA methylation at these methylation sites resulted in a recognised cancer phenotype (such as DNA damage and proliferation). We first optimised CRISPR mediated DNA methylation by testing three combinations, including fusion of dCas9-DNMT3A, dCas9-DNMT3B and dCas9-DNMT1 with our modified sgRNA and found that SAM-DNMT3A which involves fusion of dCas9-DNMT3A with our modified sgRNA induced highly robust DNA methylation even compared to the previously developed approach, SunTag system, via transfection of HEK293FT cells targeting BRCA1 promoter region. In addition, we performed lentiviral transduction of human mammary breast cell lines using SAM-DNMT3A and sgRNAs targeting BRCA1, PTEN and NF1 regions and demonstrated a significant DNA methylation induction at these regions compared to GFP- sgRNA, targeting non-human genes. We found that the SAM-DNMT3A could also induce higher gene silencing in comparison with CRISPR-inhibition (CRISPRi) tool, involving dCas9-KRAB. A lentiviral delivered sgRNA pooled library, including 10 sgRNAs for each of the 1,000 heritable DNA methylation sites, was generated to perform phenotypic screens in the human mammary epithelial cells, B80-T5 and K5+/K19+ cells using SAM-DNNT3A and CRISPRi tools.We measured the effect of DNA methylation on proliferation and the DNA damage response using a PARP inhibitor synthetic lethal screen. K5+/K19+ cells, showed very low phenotypic changes. Overall, the SAM-DNMT3A tool enabled a systemic high throughput pooled screen of heritable DNA methylation sites mediating breast cancer related phenotypes including proliferation and DNA damage. The findings of this study further characterise the non-genetic component of familial risk of breast and prostate cancer, provides new opportunities to elaborate how tumorigenesis can be affected by DNA methylation and develop epigenetic therapeutics targeting these risk factors, ultimately advancing both precision prevention and medicine.
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ItemNo Preview AvailableGenetic and Epigenetic Risk Factors for Invasive Lobular Breast Cancer( 2021)Invasive lobular breast cancer (ILBC) is the second most common histological subtype of breast cancer and accounts for 10-15% of all cases. Loss of e-cadherin protein is a hallmark of ILBC and contributes to its characteristic discohesive morphology. In addition to distinct histological features, several subtype-specific molecular and clinical features have been described. However, ILBC remains understudied relative to other breast cancer subtypes, despite its frequency. In this era of precision medicine, there is a growing interest in further refining breast cancer tumour subtyping by identifying additional discriminating molecular features. However, there is limited data to pursue this for ILBC as it is often not well-represented in study samples. For instance, the seminal work on breast cancer classification based on gene-expression levels by Perou et al., (2000) included only two ILBC cases. It is important to identify ways to refine the subtyping of ILBC tumours so that women with ILBC can benefit from a more precise treatment plan, prognosis and targeted therapy options. The main objectives of this PhD project were: i) to examine the distinguishing methylation patterns between ILBC (n=151) and non-ILBC (n=341) tumours ii) to investigate the ILBC methylome to identify methylation signatures for prognostication (n=130) and iii) to subclassify ILBC into subgroups with increased homogeneity based on their genome-wide DNA methylation profiles (ILBC, n=151, non-ILBC=341) and to further characterise these subgroups by investigating their somatic mutational signatures (n=15). Three subgroups of ILBC were defined via unsupervised cluster analysis of genome-wide DNA methylation measured using the Infinium HumanMethylation450K assay. Of these, Subgroup 1 was identified as the most distinct ILBC subgroup, characterised by a predominant hypomethylation across 27,675 CpGs compared with Subgroup 2 and across 13,067 CpGs compared with Subgroup 3. Subgroup 1 showed more similarity to the TNBC (non-ILBC) cases compared with the other two methylation-defined subgroups in terms of their genome-wide methylation pattern. Survival analysis showed that women with ILBC tumours in Subgroup 1 had the poorest overall survival when compared with women in Subgroup 2 (hazard ratio (HR): 0.59, 95% confidence interval (CI): 0.19-1.79) and Subgroup 3 (HR: 0.16, 95% CI: 0.03-0.88), after adjusting for age and year of diagnosis. Subgroup 3 had an enrichment for women who had a first-degree relative with a history of any cancer. Both Subgroup 2 and Subgroup 3 were enriched with women who had a female relative with a history of breast cancer. This suggests that women in Subgroup 2 and Subgroup 3 may be genetically or epigenetically predisposed to developing breast cancer. The somatic genetic variant profiles of the ILBC DNA methylation-defined subgroups were further investigated by performing whole-exome sequencing (WES) on five ILBC tumours representing each of the three subgroups (n=15). The mismatch repair deficiency (MMRd) associated mutational signature SBS6 was the most frequently observed mutational signature in the ILBC tumours, detected in 12/15 (80%) cases. Microsatellite instability (MSI) was also predicted in 13/15 (87%) of the cases, including all 12 tumours with SBS6. Although distinct somatic (genetic) characteristics for tumours of individual subgroups were not observed, this research highlighted the potential role of MMRd in ILBC tumourigenesis and progression. DNA methylation of ILBC was also investigated as a possible prognostic biomarker. The analysis revealed 2,771 variably methylated regions within the ILBC tumours (n=130). A pooled survival analysis of the study set and TCGA data identified APC, TMEM101, HCG4P3 and CELF2 promoter methylation as potential prognostic biomarkers for women with ILBC. Comparing the DNA methylation profiles of ILBC (n=151) and non-ILBC (n=341) tumours, 13,763 genes and 8,456 intergenic regions showing statistically significant differences in DNA methylation (false discovery rate (fdr), P-value < 0.01) were identified. Gene set enrichment analysis revealed that the differentially methylated genes were found to be involved in biological pathways related to metabolism of RNA (R-HSA-8953854), mRNA processing (GO:0006397), RNA splicing (GO:0008380), cell cycle (R-HSA-1640170) and DNA repair (GO:0006281). This study brings together several lines of evidence to indicate that distinct molecular features of ILBC can enable further subtyping, identify important features for targeted therapies (e.g., MMRd) and provide additional information for prognostication. This research identified Subgroup 1 as an important subgroup with similarities to TNBC and more aggressive clinical behaviour. Further investigation of samples from Subgroup 1 may identify additional important targets for precision medicine.