Mutational signatures reveal ternary relationships between homologous recombination repair, APOBEC, and mismatch repair in gynecological cancers

Abstract

Background Revealing the impacts of endogenous and exogenous mutagenesis processes is essential for understanding the etiology of somatic genomic alterations and designing precise prognostication and treatment strategies for cancer. DNA repair deficiency is one of the main sources of endogenous mutagenesis and is increasingly recognized as a target for cancer therapeutics. The role and prevalence of mechanisms that underly different forms of DNA repair deficiencies and their interactions remain to be elucidated in gynecological malignancies. Methods We analyzed 1231 exomes and 268 whole-genomes from three major gynecological malignancies including uterine corpus endometrial carcinoma (UCEC) as well as ovarian and cervical cancers. We also analyzed data from 134 related cell lines. We extracted and compared de novo and refitted mutational signature profiles using complementary and confirmatory approaches and performed interaction analysis to detect co-occurring and mutually exclusive signatures. Results We found an inverse relationship between homologous recombination deficiency (HRd) and mismatch repair deficiency (MMRd). Moreover, APOBEC co-occurred with HRd but was mutually exclusive with MMRd. UCEC tumors were dominated by MMRd, yet a subset of them manifested the HRd and APOBEC signatures. Conversely, ovarian tumors were dominated by HRd, while a subset represented MMRd and APOBEC. In contrast to both, cervical tumors were dominated by APOBEC with a small subsets showing the POLE, HRd, and MMRd signatures. Although the type, prevalence, and heterogeneity of mutational signatures varied across the tumor types, the patterns of co-occurrence and exclusivity were consistently observed in all. Notably, mutational signatures in gynecological tumor cell lines reflected those detected in primary tumors. Conclusions Taken together, these analyses indicate that application of mutation signature analysis not only advances our understanding of mutational processes and their interactions, but also it has the potential to stratify patients that could benefit from treatments available for tumors harboring distinct mutational signatures and to improve clinical decision-making for gynecological malignancies.

Pan-cancer analysis of the interplay between mutational signatures and cellular signaling

“…Further, interactions between signatures caused by homologous recombination deficiency (HRD) and the signature associated with APOBEC family of cytidine deaminases (APOBEC) have been identified in three tissues—breast, esophageal, and pancreatic adenocarcinomas. This interaction recapitulates recent results demonstrating that dysregulated APOBEC promotes genomic instability and DNA damage, thereby further activating homologous recombination, 38 , 39 , 40 , 41 hence demonstrating the potential of our framework to detect valid interactions. In this category, we also notice that some interactions have opposing directionality across tissues.…”

Pan-cancer mutational signature analysis of 111,711 targeted sequenced tumors using SATS

“…Besides above signatures associated with endogenous mutational processes, we also detected signatures associated with environmental exposures, such as smoking (e.g., SBS4/29 in lung cancer) and UV radiation (e.g., SBS7a/b in head and neck cancer, skin cancer/melanoma or soft tissue cancer). Additionally, treatment-related signatures were identified as well, such as SBS11 caused by temozolomide in glioma 27 , and thiopurine chemotherapy treatment-induced signature SBS87 in endometrial cancer 28 , head and neck cancer 29 and lymphoid-derived hematologic cancer 30 .…”

Molecular Testing for Diagnostics, Prognostication, and Treatment Stratification in Cancers

“…However, multiple other assays are available that look at some or all of 3 markers, genome-wide loss of heterozygosity, telomeric allelic imbalance, and large state transitions. Switching from large to small, there is also underlying single-base substitution, indel, and rearrangement patterns that is associated with HRD, and assays using these have shown to have significant predictive power 53,54 . Inherently, though, all of these approaches suffer from the weakness that they are looking at the past, not current behavior of the tumor, and that they may represent a phenotype that is no longer expressed.…”

“…Switching from large to small, there is also underlying single-base substitution, indel, and rearrangement patterns that is associated with HRD, and assays using these have shown to have significant predictive power. 53,54 Inherently, though, all of these approaches suffer from the weakness that they are looking at the past, not current behavior of the tumor, and that they may represent a phenotype that is no longer expressed. To counteract this, an expression-based approach has been developed to explore the current HRD status.…”