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    About EMERPoliciesDerbyshire Community Health Services NHS Foundation TrustLeicester Partnership TrustNHS Nottingham and Nottinghamshire CCGNottinghamshire Healthcare NHS Foundation TrustNottingham University Hospitals NHS TrustSherwood Forest Hospitals NHS Foundation TrustUniversity Hospitals of Derby and Burton NHS Foundation TrustUniversity Hospitals Of Leicester NHS TrustOther Resources

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    Comparison of actionable events detected in cancer genomes by whole-genome sequencing, in silico whole-exome and mutation panels

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    Author
    Fennell, Dean
    Keyword
    Actionable mutations
    Cancer genomics
    Clinical genomics
    Microsatellite instability
    Precision oncology
    Tumour mutation burden (TMB)
    Whole-genome sequencing
    Date
    2022-07-15
    
    Metadata
    Show full item record
    DOI
    10.1016/j.esmoop.2022.100540
    Publisher's URL
    https://www.esmoopen.com/article/S2059-7029(22)00168-5/fulltext
    Abstract
    Background: Next-generation sequencing is used in cancer research to identify somatic and germline mutations, which can predict sensitivity or resistance to therapies, and may be a useful tool to reveal drug repurposing opportunities between tumour types. Multigene panels are used in clinical practice for detecting targetable mutations. However, the value of clinical whole-exome sequencing (WES) and whole-genome sequencing (WGS) for cancer care is less defined, specifically as the majority of variants found using these technologies are of uncertain significance. Patients and methods: We used the Cancer Genome Interpreter and WGS in 726 tumours spanning 10 cancer types to identify drug repurposing opportunities. We compare the ability of WGS to detect actionable variants, tumour mutation burden (TMB) and microsatellite instability (MSI) by using in silico down-sampled data to mimic WES, a comprehensive sequencing panel and a hotspot mutation panel. Results: We reveal drug repurposing opportunities as numerous biomarkers are shared across many solid tumour types. Comprehensive panels identify the majority of approved actionable mutations, with WGS detecting more candidate actionable mutations for biomarkers currently in clinical trials. Moreover, estimated values for TMB and MSI vary when calculated from WGS, WES and panel data, and are dependent on whether all mutations or only non-synonymous mutations were used. Our results suggest that TMB and MSI thresholds should not only be tumour-dependent, but also be sequencing platform-dependent. Conclusions: There is a large opportunity to repurpose cancer drugs, and these data suggest that comprehensive sequencing is an invaluable source of information to guide clinical decisions by facilitating precision medicine and may provide a wealth of information for future studies. Furthermore, the sequencing and analysis approach used to estimate TMB may have clinical implications if a hard threshold is used to indicate which patients may respond to immunotherapy.
    Citation
    Ramarao-Milne, P., Kondrashova, O., Patch, A. M., Nones, K., Koufariotis, L. T., Newell, F., Addala, V., Lakis, V., Holmes, O., Leonard, C., Wood, S., Xu, Q., Mukhopadhyay, P., Naeini, M. M., Steinfort, D., Williamson, J. P., Bint, M., Pahoff, C., Nguyen, P. T., Twaddell, S., … Waddell, N. (2022). Comparison of actionable events detected in cancer genomes by whole-genome sequencing, in silico whole-exome and mutation panels. ESMO open, 7(4), 100540. https://doi.org/10.1016/j.esmoop.2022.100540
    Type
    Article
    URI
    http://hdl.handle.net/20.500.12904/16368
    Collections
    Cancer

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      Shared genetic etiology of obesity-related traits and Barrett's esophagus/adenocarcinoma: Insights from genome-wide association studies.

      Jankowski, Janusz (2020-02)
      Background: Obesity is a major risk factor for esophageal adenocarcinoma (EA) and its precursor Barrett's esophagus (BE). Research suggests that individuals with high genetic risk to obesity have a higher BE/EA risk. To facilitate understanding of biological factors that lead to progression from BE to EA, the present study investigated the shared genetic background of BE/EA and obesity-related traits. Methods: Cross-trait linkage disequilibrium score regression was applied to summary statistics from genome-wide association meta-analyses on BE/EA and on obesity traits. Body mass index (BMI) was used as a proxy for general obesity, and waist-to-hip ratio (WHR) for abdominal obesity. For single marker analyses, all genome-wide significant risk alleles for BMI and WHR were compared with summary statistics of the BE/EA meta-analyses. Results: Sex-combined analyses revealed a significant genetic correlation between BMI and BE/EA ( r g = 0.13, P = 2 × 10 -04 ) and a r g of 0.12 between WHR and BE/EA ( P = 1 × 10 -02 ). Sex-specific analyses revealed a pronounced genetic correlation between BMI and EA in females ( r g = 0.17, P = 1.2 × 10 -03 ), and WHR and EA in males ( r g = 0.18, P = 1.51 × 10 -02 ). On the single marker level, significant enrichment of concordant effects was observed for BMI and BE/EA risk variants ( P = 8.45 × 10 -03 ) and WHR and BE/EA risk variants ( P = 2 × 10 -02 ). Conclusions: Our study provides evidence for sex-specific genetic correlations that might reflect specific biological mecha-nisms. The data demonstrate that shared genetic factors are particularly relevant in progression from BE to EA. Impact: Our study quantifies the genetic correlation between BE/EA and obesity. Further research is now warranted to elucidate these effects and to understand the shared pathophysiology.
    • Thumbnail

      The power of genetic diversity in genome-wide association studies of lipids

      Nelson, Christopher; Samani, Nilesh (2021-12-09)
      Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.
    • Thumbnail

      The genomics of heart failure: design and rationale of the HERMES consortium

      Nelson, Christopher; Romaine, Simon; Samani, Nilesh (2021-09-03)
      Aims: The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure. Methods and results: The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 × 10-8 under an additive genetic model. Conclusions: HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.
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