Objective Germline pathogenic variants (PVs) in the DNA mismatch repair (MMR) genes and in the base excision repair gene MUTYH underlie hereditary colorectal cancer (CRC) and polyposis syndromes. We evaluated the robustness and discriminatory potential of tumour mutational signatures in CRCs for identifying germline PV carriers.
Design Whole-exome sequencing of formalin-fixed paraffin-embedded (FFPE) CRC tissue was performed on 33 MMR germline PV carriers, 12 biallelic MUTYH germline PV carriers, 25 sporadic MLH1 methylated MMR-deficient CRCs (MMRd controls) and 160 sporadic MMR-proficient CRCs (MMRp controls) and included 498 TCGA CRC tumours. COSMIC V3 single base substitution (SBS) and indel (ID) mutational signatures were assessed for their ability to differentiate CRCs that developed in carriers from non-carriers.
Results The combination of mutational signatures SBS18 and SBS36 contributing >30% of a CRC’s signature profile was able to discriminate biallelic MUTYH carriers from all other non-carrier control CRCs with 100% accuracy (area under the curve (AUC) 1.0). SBS18 and SBS36 were associated with specific MUTYH variants p.Gly396Asp (p=0.025) and p.Tyr179Cys (p=5×10-5), respectively. The combination of ID2 and ID7 could discriminate the 33 MMR PV carrier CRCs from the MMRp control CRCs (AUC 0.99); however, SBS and ID signatures, alone or in combination, could not provide complete discrimination (AUC 0.79) between CRCs from MMR PV carriers and sporadic MMRd controls.
Conclusion Assessment of SBS and ID signatures can discriminate CRCs from biallelic MUTYH carriers and MMR PV carriers from non-carriers with high accuracy, demonstrating utility as a potential diagnostic and variant classification tool.
- colorectal cancer
- colorectal cancer screening
- tumour markers
- molecular pathology
Data availability statement
Data are available upon reasonable request.
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Contributors DDB, PG, MC and IMW conceived the original study concept and design and designed the analysis. CR, FAM, IMW, AKW, JLH, MAJ, SG, DB, DOS, NM, PG, OMS, DM contributed to the acquisition of study data. The sample curation and laboratory testing was performed by MC, RW, RH, JEJ, SP, SJ, JC. PG, BJP, KM implemented the bioinformatics analysis pipeline. PG, DDB, BJP, MAJ designed and performed the statistical analyses. PG and DDB prepared the manuscript. All authors provided critical revisions to the manuscript for important intellectual content and have read and approved of the final manuscript.
Funding Funding by a National Health and Medical Research Council of Australia (NHMRC) project grant GNT1125269 (PI- Daniel Buchanan), supported the design, analysis and interpretation of data. PG is supported by an Australian Government Research Training Program Scholarship. DDB is supported by a NHMRC R.D. Wright Career Development Fellowship (GNT1125268) and funding from the University of Melbourne Research at Melbourne Accelerator Program (R@MAP). AKW is a NHMRC Career Development Fellow. MAJ is a NHMRC Senior Research Fellow. JLH is a NHMRC Senior Principal Research Fellow. O.M.S. is a NHMRC Senior Research Fellow (APP1136119). BJP is supported by a Victorian Health and Medical Research Fellowship. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number U01CA167551 and through a cooperative agreement with the Australasian Colorectal Cancer Family Registry (NCI/NIH U01 CA074778 and U01/U24 CA097735) and by the Victorian Cancer Registry, Australia and Ontario Familial Colorectal Cancer Registry (U01/U24 CA074783). This research was performed under CCFR approved projects C-AU-0818-01, C-AU-1014-02, C-AU-0312-01, C-AU-1013-02. DDB served as a consultant on the Tumour Agnostic (dMMR) Advisory Board of Merck Sharp and Dohme in 2017 and 2018 for Pembrolizumab.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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