Affiliation:
1. Department of Radiation Oncology Seoul National University Hospital Seoul Republic of Korea
2. Department of Clinical Medical Science Seoul National University College of Medicine Seoul Republic of Korea
3. Department of Radiation Oncology Seoul Metropolitan Government‐Seoul National University Boramae Medical Center Seoul Republic of Korea
4. Department of Pathology Seoul Metropolitan Government‐Seoul National University Boramae Medical Center Seoul Republic of Korea
5. Department of Radiation Oncology Seoul National University College of Medicine Seoul Republic of Korea
6. Medical Research Center, Institute of Radiation Medicine Seoul National University Seoul Republic of Korea
Abstract
AbstractPurposeTo explore genomic biomarkers in rectal cancer by performing whole‐exome sequencing.Materials and MethodsPre‐chemoradiation (CRT) biopsy and post‐CRT surgical specimens were obtained from 27 patients undergoing neoadjuvant CRT followed by definitive resection. Exomes were sequenced to a mean coverage of 30×. Somatic single‐nucleotide variants (SNVs) and insertions/deletions (indels) were identified. Tumor mutational burden was defined as the number of SNVs or indels. Mutational signatures were extracted and fitted to COSMIC reference signatures. Tumor heterogeneity was quantified with a mutant‐allele tumor heterogeneity (MATH) score. Genetic biomarkers and frequently occurred copy number alterations (CNAs) were compared between pre‐ and post‐CRT specimens. Their associations with tumor regression grade (TRG) and clinical outcomes were explored.ResultsTop five mutated genes were APC, TP53, NF1, KRAS, and NOTCH1 for pre‐CRT samples and APC, TP53, NF1, CREBBP, and ATM for post‐CRT samples. Several gene mutations including RUNX1, EGFR, and TP53 in pre‐CRT samples showed significant association with clinical outcomes, but not with TRG. However, no such association was found in post‐CRT samples. Discordance of driver mutation status was found between pre‐ and post‐CRT samples. In tumor mutational burden analysis, higher number of SNVs or indels was associated with worse treatment outcomes. Six single‐base substitution (SBS) signatures identified were SBS1, SBS30, SBS29, SBS49, SBS3, and SBS44. The MATH score decreased after CRT on paired analysis. Less than half of CNAs frequent in post‐CRT samples were present in pre‐CRT samples.ConclusionPre‐ and post‐CRT samples showed different genomic landscape. Potential genetic biomarkers of pre‐CRT samples found in the current analysis call for external validation.
Funder
Seoul National University Hospital
Subject
Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology
Cited by
3 articles.
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