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Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

ABSTRACT: Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

SUBMITTER: Xiao W

PROVIDER: S-EPMC8506910 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Xiao Wenming W Ren Luyao L Chen Zhong Z Fang Li Tai LT Zhao Yongmei Y Lack Justin J Guan Meijian M Zhu Bin B Jaeger Erich E Kerrigan Liz L Blomquist Thomas M TM Hung Tiffany T Sultan Marc M Idler Kenneth K Lu Charles C Scherer Andreas A Kusko Rebecca R Moos Malcolm M Xiao Chunlin C Sherry Stephen T ST Abaan Ogan D OD Chen Wanqiu W Chen Xin X Nordlund Jessica J Liljedahl Ulrika U Maestro Roberta R Polano Maurizio M Drabek Jiri J Vojta Petr P Kõks Sulev S Reimann Ene E Madala Bindu Swapna BS Mercer Timothy T Miller Chris C Jacob Howard H Truong Tiffany T Moshrefi Ali A Natarajan Aparna A Granat Ana A Schroth Gary P GP Kalamegham Rasika R Peters Eric E Petitjean Virginie V Walton Ashley A Shen Tsai-Wei TW Talsania Keyur K Vera Cristobal Juan CJ Langenbach Kurt K de Mars Maryellen M Hipp Jennifer A JA Willey James C JC Wang Jing J Shetty Jyoti J Kriga Yuliya Y Raziuddin Arati A Tran Bao B Zheng Yuanting Y Yu Ying Y Cam Margaret M Jailwala Parthav P Nguyen Cu C Meerzaman Daoud D Chen Qingrong Q Yan Chunhua C Ernest Ben B Mehra Urvashi U Jensen Roderick V RV Jones Wendell W Li Jian-Liang JL Papas Brian N BN Pirooznia Mehdi M Chen Yun-Ching YC Seifuddin Fayaz F Li Zhipan Z Liu Xuelu X Resch Wolfgang W Wang Jingya J Wu Leihong L Yavas Gokhan G Miles Corey C Ning Baitang B Tong Weida W Mason Christopher E CE Donaldson Eric E Lababidi Samir S Staudt Louis M LM Tezak Zivana Z Hong Huixiao H Wang Charles C Shi Leming L

Nature biotechnology 20210909 9

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affec ...[more]

PMID: 34504346

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Project description:BackgroundLess than two percent of the human genome is protein coding, yet that small fraction harbours the majority of known disease causing mutations. Despite rapidly falling whole genome sequencing (WGS) costs, much research and increasingly the clinical use of sequence data is likely to remain focused on the protein coding exome. We set out to quantify and understand how WGS compares with the targeted capture and sequencing of the exome (exome-seq), for the specific purpose of identifying single nucleotide polymorphisms (SNPs) in exome targeted regions.ResultsWe have compared polymorphism detection sensitivity and systematic biases using a set of tissue samples that have been subject to both deep exome and whole genome sequencing. The scoring of detection sensitivity was based on sequence down sampling and reference to a set of gold-standard SNP calls for each sample. Despite evidence of incremental improvements in exome capture technology over time, whole genome sequencing has greater uniformity of sequence read coverage and reduced biases in the detection of non-reference alleles than exome-seq. Exome-seq achieves 95% SNP detection sensitivity at a mean on-target depth of 40 reads, whereas WGS only requires a mean of 14 reads. Known disease causing mutations are not biased towards easy or hard to sequence areas of the genome for either exome-seq or WGS.ConclusionsFrom an economic perspective, WGS is at parity with exome-seq for variant detection in the targeted coding regions. WGS offers benefits in uniformity of read coverage and more balanced allele ratio calls, both of which can in most cases be offset by deeper exome-seq, with the caveat that some exome-seq targets will never achieve sufficient mapped read depth for variant detection due to technical difficulties or probe failures. As WGS is intrinsically richer data that can provide insight into polymorphisms outside coding regions and reveal genomic rearrangements, it is likely to progressively replace exome-seq for many applications.

Project description:BackgroundNext-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 methodsWe 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.ResultsWe 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.ConclusionsThere 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.

Dataset Information

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Publications

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Similar Datasets

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