Recent identity by descent in human genetic data - methods and applications

The thesis describes algorithms for detecting regions of recent identity by descent (IBD) from human genetic data and its applications in optimising resequencing studies, genomic predictions and detecting Mendelian subtypes of diseases. Firstly, we describe the algorithm ANCHAP, which scans pairs of multi-point SNP genotypes for sharing IBD of long haplotypes. A comparison with other methods shows that ANCHAP outperforms them in terms of speed or accuracy. We demonstrate the algorithm on data from population isolates - from Orcades, Croatian islands, and from a population of unrelated individuals. We compare the abundance of IBD segments between cohorts, and identify genetic regions where IBD is most common. Secondly, we verify the IBD regions detected from array data against exome sequence data. We estimate that where sharing IBD between a pair of individuals is inferred, this is confirmed by exome data in 98% of cases. Correctness of IBD detection varies with settings of ANCHAP, length of IBD segments, and position with respect to segment endpoints. We find that with sample sizes of 1000 individuals from an isolated population genotyped using a dense SNP array, and with 20% of these individuals sequenced, 65% of sequences of the un-sequenced subjects can be partially inferred. Implementation of such resequencing strategies requires an IBD-based imputation algorithm, which is outlined. Thirdly, we use recent IBD to detect carriers of Mendelian subtypes of colon cancer. We show this with the example of Lynch syndrome, which accounts for about 3% of colon cancer patients. We detect IBD sharing between known and unknown carriers around DNA mismatch-repair genes. Using the IBD relationship, we build and evaluate a model that predicts presence of Lynch Syndrome mutations. Finally, we discuss whether regions of identity by descent can be used for genomic predictions. We conclude that the utility of the inferred IBD regions depends on accuracy of detection, time to most recent common ancestors and mutation rates since

Utility of Non-rule-based Visual Matching as a Strategy to Allow Novices to Achieve Skin Lesion Diagnosis

Non-analytical reasoning is thought to play a key role in dermatology diagnosis. Considering its potential importance, surprisingly little work has been done to research whether similar identification processes can be supported in non-experts. We describe here a prototype diagnostic support software, which we have used to examine the ability of medical students (at the beginning and end of a dermatology attachment) and lay volunteers, to diagnose 12 images of common skin lesions. Overall, the non-experts using the software had a diagnostic accuracy of 98% (923/936) compared with 33% for the control group (215/648) (Wilcoxon p < 0.0001). We have demonstrated, within the constraints of a simplified clinical model, that novices’ diagnostic scores are significantly increased by the use of a structured image database coupled with matching of index and referent images. The novices achieve this high degree of accuracy without any use of explicit definitions of likeness or rule-based strategies

Short inverted repeats contribute to localized mutability in human somatic cells.

Selected repetitive sequences termed short inverted repeats (SIRs) have the propensity to form secondary DNA structures called hairpins. SIRs comprise palindromic arm sequences separated by short spacer sequences that form the hairpin stem and loop respectively. Here, we show that SIRs confer an increase in localized mutability in breast cancer, which is domain-dependent with the greatest mutability observed within spacer sequences (∼1.35-fold above background). Mutability is influenced by factors that increase the likelihood of formation of hairpins such as loop lengths (of 4-5 bp) and stem lengths (of 7-15 bp). Increased mutability is an intrinsic property of SIRs as evidenced by how almost all mutational processes demonstrate a higher rate of mutagenesis of spacer sequences. We further identified 88 spacer sequences showing enrichment from 1.8- to 90-fold of local mutability distributed across 283 sites in the genome that intriguingly, can be used to inform the biological status of a tumor

The genome as a record of environmental exposure.

Whole genome sequencing of human tumours has revealed distinct patterns of mutation that hint at the causative origins of cancer. Experimental investigations of the mutations and mutation spectra induced by environmental mutagens have traditionally focused on single genes. With the advent of faster cheaper sequencing platforms, it is now possible to assess mutation spectra in experimental models across the whole genome. As a proof of principle, we have examined the whole genome mutation profiles of mouse embryo fibroblasts immortalised following exposure to benzo[a]pyrene (BaP), ultraviolet light (UV) and aristolochic acid (AA). The results reveal that each mutagen induces a characteristic mutation signature: predominantly G→T mutations for BaP, C→T and CC→TT for UV and A→T for AA. The data are not only consistent with existing knowledge but also provide additional information at higher levels of genomic organisation. The approach holds promise for identifying agents responsible for mutations in human tumours and for shedding light on the aetiology of human cancer

Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies

The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1–10%) in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28–38%, for SNPs with a minor allele frequency in the range 1–3%

The topography of mutational processes in breast cancer genomes.

Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Furthermore, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis

A somatic-mutational process recurrently duplicates germline susceptibility loci and tissue-specific super-enhancers in breast cancers

Somatic rearrangements contribute to the mutagenized landscape of cancer genomes. Here, we systematically interrogated rearrangements in 560 breast cancers by using a piecewise constant fitting approach. We identified 33 hotspots of large (>100 kb) tandem duplications, a mutational signature associated with homologous-recombination-repair deficiency. Notably, these tandem-duplication hotspots were enriched in breast cancer germline susceptibility loci (odds ratio (OR) = 4.28) and breast-specific 'super-enhancer' regulatory elements (OR = 3.54). These hotspots may b

Process evaluation of the Bridging the Age Gap in Breast Cancer decision support intervention cluster randomized trial [abstract only]

Aims/Objectives: Shared decision making on the choice of treatment for older women with breast cancer involves many factors. Comprehensive geriatric assessment (CGA) is recognised to have a role in older patients with cancer, but how this should be utilised is still debatable. A pilot study involving older women newly diagnosed with early operable primary breast cancer was conducted aiming to explore the potential value of CGA. Methods: Decision of primary treatment followed consultation with the clinical team and was not guided by any aspect of this study. CGA, using a validated cancer-specific tool from our collaborator, A Hurria, was conducted within 6 weeks after diagnosis, regardless of date of surgery/first treatment. A total of 178 female patients aged ≥70 years with a new diagnosis of early (stage 1 or 2; cT0-2, N0-1, M0) operable primary breast cancer proven histologically, were thus far recruited from three UK centres. Results: Among these 178 patients, 149 underwent primary surgery and 29 received non-surgical treatment (primary endocrine therapy (N=28) or radiotherapy (N=1)). CGA determined that increasing age (p=0.006), reduced independence with activities of daily living (ADLs) (p=0.001) and independent activities of daily living (IADLS) (p=0.001), increased number and severity of comorbidity (p=0.043), reduced Karnofsky performance status when rated both by the patient (p=0.001) and physician (p=0.003), were significantly related to non-surgical treatment within 6 weeks after diagnosis. Other CGA parameters measured which were not significant include number of daily medications, level of social support, level of social activity, cognition, number of falls, 'Timed up and go' score. Conclusions: The pilot study has confirmed that CGA may have value in assessing this cohort of patients. Generally, it appears that patients receiving non-surgical treatment are more frail than their counterparts undergoing surgery. The study is ongoing and has expanded to include an international centre

Comprehensive molecular comparison of BRCA1 hypermethylated and BRCA1 mutated triple negative breast cancers

Funder: The Governmental Funding for Young Clinical Researchers within the National Health Service (ALF) 2017-2019Funder: Shamik Mitra is financially supported by the funding received from the European Community’s Horizon 2020 Framework Program for Research and Innovation (H2020-MSCA-ITN-2014) under Grant Agreement no. 247634Funder: Vetenskapsrådet (Swedish Research Council); doi: https://doi.org/10.13039/501100004359Funder: The Governmental Funding within the National Health Service (ALF)Funder: - The Governmental Funding of Clinical Research within the National Health Service (ALF), grant nbr 2018/40612 - The Gustav V:s Jubilee Foundation (174271 and 187041) - The research foundation at Department of Oncology in LundAbstract: Homologous recombination deficiency (HRD) is a defining characteristic in BRCA-deficient breast tumors caused by genetic or epigenetic alterations in key pathway genes. We investigated the frequency of BRCA1 promoter hypermethylation in 237 triple-negative breast cancers (TNBCs) from a population-based study using reported whole genome and RNA sequencing data, complemented with analyses of genetic, epigenetic, transcriptomic and immune infiltration phenotypes. We demonstrate that BRCA1 promoter hypermethylation is twice as frequent as BRCA1 pathogenic variants in early-stage TNBC and that hypermethylated and mutated cases have similarly improved prognosis after adjuvant chemotherapy. BRCA1 hypermethylation confers an HRD, immune cell type, genome-wide DNA methylation, and transcriptional phenotype similar to TNBC tumors with BRCA1-inactivating variants, and it can be observed in matched peripheral blood of patients with tumor hypermethylation. Hypermethylation may be an early event in tumor development that progress along a common pathway with BRCA1-mutated disease, representing a promising DNA-based biomarker for early-stage TNBC

Cancer therapy shapes the fitness landscape of clonal hematopoiesis.

Acquired mutations are pervasive across normal tissues. However, understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMNs). We find that mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response genes (TP53, PPM1D, CHEK2). Sequential sampling provides definitive evidence that DNA damage response clones outcompete other clones when exposed to certain therapies. Among cases in which CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies