Clinical Pathology - Theses
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ItemImproving the Differentiation of Inherited from Sporadic Causes of DNA Mismatch Repair Deficient Cancers( 2022)People with Lynch syndrome (LS), the most common cancer predisposition syndrome, have an increased risk of developing colorectal (CRC), endometrial (EC) and sebaceous skin (SST) tumours, among other cancer types. LS is caused by germline (likely) pathogenic variants in the DNA mismatch repair (MMR) genes, leading to a characteristic MMR-deficient (dMMR) / microsatellite unstable (MSI) tumour phenotype. However, dMMR / MSI is not only caused by LS and can also result from somatic causes of MMR gene inactivation. Identification of the dMMR / MSI tumour phenotype is of clinical significance for cancer prevention, prognosis, and response to immune checkpoint inhibitor treatment. However, diagnostic challenges still remain for accurate dMMR identification using current clinical tools. Therefore, the aim of my thesis is to address these two clinically relevant challenges: 1) can we improve detection of dMMR / MSI status in CRCs, ECs, and SSTs using next generation sequencing (NGS) derived tumour features and bioinformatic tools, and 2) can we improve differentiation of inherited (high risk) from sporadic (low risk) dMMR in CRCs, ECs, and SSTs using NGS? With the increased adoption of NGS in clinical practice for precision oncology and cancer genetics, the opportunity exists to develop a tumour-focused approach to improve the identification of LS. In Chapter 3, I investigated whether routinely collected clinicopathological tumour features could differentiate LS (inherited) from MLH1 methylated (sporadic) and suspected LS (unknown) subtypes in over 631 dMMR CRCs from the Colon Cancer Family Registry. Although age at diagnosis, sex and other variables were different between these subtypes, their power to differentiate was limited. Significantly, MLH1me tumours presented with a higher mortality rate than LS and suspected LS (SLS) tumours. These findings confirmed the need to examine new NGS-based approaches for differentiation purposes. In Chapter 4, I developed a novel model using NGS data to accurately determine dMMR from MMR-proficient (pMMR) tumour status in CRC and tested this model on EC and SST tumours. In total, 104 tumour features derived from whole exome sequencing of 300 CRCs were tested for their ability to identify dMMR with 10 features displaying >80% prediction accuracies. I established a novel model which combines the best predictive features for improved dMMR detection in CRC, EC, and SST sequenced tumours. In Chapter 5, using a custom-designed panel sequencing assay that I developed, tumour and blood-derived DNA were assessed from 134 SLS dMMR tumours (79 CRCs, 32 ECs, and 23 SSTs) in one of the largest investigations of SLS in these tumour types to date. Using the model determined in Chapter 4, I found 8.2% were not dMMR as clinically reported. The predominant cause of dMMR in SLS was biallelic somatic MMR mutations (61.9%) while only 1.5% were identified as LS that were missed by clinical testing. The findings from my thesis provide an evidence base to implement NGS-based diagnostic approaches for accurately detecting dMMR status and to resolve an SLS diagnosis in CRCs, ECs, and SSTs using a single test, which will ultimately improve utilisation of limited clinical resources for improved clinical management and cancer prevention.