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Pan-cancer noncoding genomic analysis identifies functional CDC20 promoter mutation hotspots.

ABSTRACT: Noncoding DNA sequences occupy more than 98% of the human genome; however, few cancer noncoding drivers have been identified compared with cancer coding drivers, probably because cancer noncoding drivers have a distinct mutation pattern due to the distinct function of noncoding DNA. Here we performed pan-cancer whole genome mutation analysis to screen for functional noncoding mutations that influence protein factor binding. Recurrent mutations were identified in the promoter of CDC20 gene. These CDC20 promoter hotspot mutations disrupt the binding of ELK4 transcription repressor, lead to the up-regulation of CDC20 transcription. Physiologically ELK4 binds to the unmutated hotspot sites and is involved in DNA damage-induced CDC20 transcriptional repression. Overall, our study not only identifies a detailed mechanism for CDC20 gene deregulation in human cancers but also finds functional noncoding genetic alterations, with implications for the further development of function-based noncoding driver discovery pipelines.

SUBMITTER: He Z

PROVIDER: S-EPMC8024666 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Pan-cancer noncoding genomic analysis identifies functional <i>CDC20</i> promoter mutation hotspots.

He Zaoke Z Wu Tao T Wang Shixiang S Zhang Jing J Sun Xiaoqin X Tao Ziyu Z Zhao Xiangyu X Li Huimin H Wu Kai K Liu Xue-Song XS

iScience 20210309 4

Noncoding DNA sequences occupy more than 98% of the human genome; however, few cancer noncoding drivers have been identified compared with cancer coding drivers, probably because cancer noncoding drivers have a distinct mutation pattern due to the distinct function of noncoding DNA. Here we performed pan-cancer whole genome mutation analysis to screen for functional noncoding mutations that influence protein factor binding. Recurrent mutations were identified in the promoter of <i>CDC20</i> gene ...[more]

PMID: 33851100

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Project description:BackgroundHigh tumor mutational burden (TMB) is one of the widely researched predictive biomarkers of immune checkpoint inhibitors and has been shown to be closely related with response to immunotherapy in multiple cancer types. However, for patients who have failed conventional therapy and are about to undergo immunotherapy, there is no consensus recommendation on the timing of tumor sampling for TMB analysis, and the effects of different therapies on TMB have not been clarified. This retrospective observational study aimed to investigate the heterogeneity of TMB and genomic mutation under the treatment pressure.Patients and methodsWe retrospectively collected the available genomic and therapeutic information from 8051 samples across 15 tumor types (>50 samples/tumor) found in 30 published studies and investigated the distribution and heterogeneity of TMB under treatment across diverse cohorts.ResultsThis integrated analysis has shown anticancer treatments increased TMB. Significant effects of treatment on TMB were more frequently observed in tumor types with lower treatment-naïve TMB, including breast, prostate, and pediatric cancers. For different cancer therapies, chemotherapy was prone to be correlated with an increased TMB in most cancer types. Meanwhile, the fraction of the TMB-high category of breast, prostate, and bladder cancers and glioma increased significantly after chemotherapy. Several actionable genes including ERS1 and NF1 in breast cancer, as well as some prognostic markers including TERT in bladder cancer and IDH1 in glioma, were significantly changed in post-chemotherapy tumors compared to treatment-naïve tumors.ConclusionOur study reveals the heterogeneity of TMB under treatment across diverse cancer types and provides evidences that chemotherapy was associated with increases in TMB as well as the fraction of TMB-high category, suggesting that resampling tumor tissues for calculating post-chemotherapy TMB could be a better option for predicting the response to immunotherapy, especially for tumors with initially low TMB.

Dataset Information

Pan-cancer noncoding genomic analysis identifies functional CDC20 promoter mutation hotspots.

Publications

Pan-cancer noncoding genomic analysis identifies functional <i>CDC20</i> promoter mutation hotspots.

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