open access publication

Article, 2018

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival

npj Genomic Medicine, ISSN 2056-7944, Volume 3, 1, Page 1, 10.1038/s41525-017-0040-5

Contributors

Hornshøj, Henrik (Corresponding author) [1] Nielsen, Morten Muhlig 0000-0002-8972-7577 [1] Sinnott-Armstrong, Nicholas A [2] Świtnicki, Michal Piotr 0000-0003-0619-9375 [1] Juul, Malene 0000-0001-9722-0461 [1] Madsen, Tobias Lynge 0000-0002-6846-4384 [1] [3] Sallari, Richard C [2] Kellis, Manolis [2] Ørntoft, Torben Falck [1] Hobolth, Asger 0000-0003-4056-1286 [3] Pedersen, Jakob Skou 0000-0002-7236-4001 (Corresponding author) [1] [3]

Affiliations

  1. [1] Aarhus University Hospital
  2. [NORA names: Central Denmark Region; Hospital; Denmark; Europe, EU; Nordic; OECD];
  3. [2] Massachusetts Institute of Technology
  4. [NORA names: United States; America, North; OECD];
  5. [3] Aarhus University
  6. [NORA names: AU Aarhus University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Cancer develops by accumulation of somatic driver mutations, which impact cellular function. Mutations in non-coding regulatory regions can now be studied genome-wide and further characterized by correlation with gene expression and clinical outcome to identify driver candidates. Using a new two-stage procedure, called ncDriver, we first screened 507 ICGC whole-genomes from 10 cancer types for non-coding elements, in which mutations are both recurrent and have elevated conservation or cancer specificity. This identified 160 significant non-coding elements, including the TERT promoter, a well-known non-coding driver element, as well as elements associated with known cancer genes and regulatory genes (e.g., PAX5, TOX3, PCF11, MAPRE3). However, in some significant elements, mutations appear to stem from localized mutational processes rather than recurrent positive selection in some cases. To further characterize the driver potential of the identified elements and shortlist candidates, we identified elements where presence of mutations correlated significantly with expression levels (e.g., TERT and CDH10) and survival (e.g., CDH9 and CDH10) in an independent set of 505 TCGA whole-genome samples. In a larger pan-cancer set of 4128 TCGA exomes with expression profiling, we identified mutational correlation with expression for additional elements (e.g., near GATA3, CDC6, ZNF217, and CTCF transcription factor binding sites). Survival analysis further pointed to MIR122, a known marker of poor prognosis in liver cancer. In conclusion, the screen for significant mutation patterns coupled with correlative mutational analysis identified new individual driver candidates and suggest that some non-coding mutations recurrently affect expression and play a role in cancer development.

Keywords

ICGC, TCGA, TERT, TERT promoter, accumulation, analysis, cancer, cancer development, cancer genes, cancer types, cancer-specific, candidates, cases, cellular functions, clinical outcomes, conservation, correlation, development, driver candidates, driver element, driver mutations, driver potentials, drivers, elements, elevated conservation, exome, expression, expression levels, expression profiles, function, gene expression, genes, genome-wide, identified elements, impact cellular function, levels, liver, liver cancer, localized mutational processes, marker of poor prognosis, markers, miR122, mutation patterns, mutational correlation, mutational processes, mutations, non-coding elements, non-coding mutations, non-coding regulatory regions, outcomes, pan-cancer screening, pan-cancer setting, patterns, poor prognosis, positive selection, potential, presence, presence of mutations, procedure, process, profile, prognosis, promoter, recurrent positive selection, region, regulatory genes, regulatory regions, samples, screening, selection, sets, significant element, somatic driver mutations, specificity, survival, survival analysis, two-stage procedure, type, whole genome, whole-genome samples

Funders

  • Danish Cancer Society

Data Provider: Digital Science