Comprehensive Analysis of Hypermutation in Human Cancer
By Brittany B Campbell, Nicholas Light, D. Fabrizio, M. Zatzman, F. Fuligni, Richard de Borja, S. Davidson, M. Edwards, J. Elvin, Karl Hodel and 52 more. Cell, 2017
686 citations recorded by the source corpus.
Summary We present an extensive assessment of mutation burden through sequencing analysis of >81,000 tumors from pediatric and adult patients, including tumors with hypermutation caused by chemotherapy, carcinogens, or germline alterations. Hypermutation was detected in tumor types not previously associated with high mutation burden. Replication repair deficiency was a major contributing factor. We uncovered new driver mutations in the replication-repair-associated DNA polymerases and a distinct impact of microsatellite instability and replication repair deficiency on the scale of mutation load. Unbiased clustering, based on mutational context, revealed clinically relevant subgroups regardless of the tumors' tissue of origin, highlighting similarities in evolutionary dynamics leading to hypermutation. Mutagens, such as UV light, were implicated in unexpected cancers, including sarcomas and lung tumors. The order of mutational signatures identified previous treatment and germline replication repair deficiency, which improved management of patients and families. These data will inform tumor classification, genetic testing, and clinical trial design.
Subfields: Cancer Research, Pathology and Forensic Medicine, Pulmonary and Respiratory Medicine
View Paper: https://www.semanticscholar.org/paper/db8e6571b18c5e383e708f183a85d5365bce2dda
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In Cancer Research
Citations in the corpus
- Machine learning and feature selection for drug response prediction in precision oncology applications (2018, background): “…markers typically start from unsupervised clustering of the molecular and/or genomic profiles of the patient samples, and then subsequently try to identify the treatments showing therapeutic efficacy in the distinct sample sub-clusters (Hoadley et al. 2014; Campbell et al. 2017).”
- The landscape of genomic alterations across childhood cancers (2018, neutral): “Tumours with more than 10 mutations per Mb have been referred to as ‘hypermutators’, and are often related to deficiencies in mismatch repair (MMR) 10,11 .”
- Quantitative Proteomics of the Cancer Cell Line Encyclopedia (2020, background): “A subset of cancers, hypermutated/microsatellite instable (MSI) colorectal cancers, possess orders of magnitude more mutations than other tumors (Campbell et al., 2017; Lawrence et al., 2013; The Cancer Genome Atlas Network, 2012).”