Evaluating multiple next-generation sequencing derived tumor features to accurately predict DNA mismatch repair status
- Author(s)
- Walker, R; Georgeson, P; Mahmood, K; Joo, JE; Makalic, E; Clendenning, M; Como, J; Preston, S; Joseland, S; Pope, BJ; Hutchinson, RA; Kasem, K; Walsh, MD; MACRAE, FA; Win, AK; Hopper, JL; Mouradov, D; Gibbs, P; Sieber, OM; O'Sullivan, DE; Brenner, DR; Gallinger, S; Jenkins, MA; Rosty, C; Winship, IM; Buchanan, DD;
- Journal Title
- Journal of Molecular DIagnosis
- Publication Type
- epub ahead of print
- Abstract
- Identifying tumor DNA mismatch repair deficiency (dMMR) is important for precision medicine. Tumor features, individually and in combination, derived from whole-exome sequenced (WES) colorectal cancers (CRCs) and panel sequenced CRCs, endometrial cancers (ECs) and sebaceous skin tumors (SSTs) were assessed for their accuracy in detecting dMMR. CRCs (n=300) with WES, where MMR status was determined by immunohistochemistry, were assessed for microsatellite instability (MSMuTect, MANTIS, MSIseq, MSISensor), COSMIC tumor mutational signatures (TMS) and somatic mutation counts. A 10-fold cross-validation approach (100 repeats) evaluated the dMMR prediction accuracy for 1) individual features, 2) Lasso statistical model and 3) an additive feature combination approach. Panel sequenced tumors (29 CRCs, 22 ECs, 20 SSTs) were assessed for the top performing dMMR predicting features/models using these three approaches. For WES CRCs, 10 features provided >80% dMMR prediction accuracy, with MSMuTect, MSIseq, and MANTIS achieving ≥99% accuracy. The Lasso model achieved 98.3%. The additive feature approach with ≥3/6 of MSMuTect, MANTIS, MSIseq, MSISensor, INDEL count or TMS ID2+ID7 achieved 99.7% accuracy. For the panel sequenced tumors, the additive feature combination approach of ≥3/6 achieved accuracies of 100%, 95.5% and 100%, for CRCs, ECs, and SSTs, respectively. The microsatellite instability calling tools performed well in WES CRCs, however, an approach combining tumor features may improve dMMR prediction in both WES and panel sequenced data across tissue types.
- Publisher
- Elsevier
- Keywords
- Colorectal cancer; DNA mismatch repair deficiency; Lynch syndrome; MLH1 promoter methylation; endometrial cancer; microsatellite instability; sebaceous skin tumor; tumor mutation burden; tumor mutational signatures
- Research Division(s)
- Personalised Oncology
- PubMed ID
- 36396080
- Publisher's Version
- https://doi.org/10.1016/j.jmoldx.2022.10.003
- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2022-12-13 03:13:07
Last Modified: 2022-12-14 01:13:02