A global transcriptional network connecting noncoding mutations to changes in tumor gene expression

Area of Science:

• Genomics
• Cancer Biology
• Molecular Oncology

Background:

• Cancer genomes harbor numerous noncoding mutations.
• The functional impact of these noncoding mutations is largely uncharacterized.
• Understanding noncoding mutations is crucial for a comprehensive view of cancer development.

Purpose of the Study:

• To identify and characterize noncoding loci affected by somatic mutations in cancer.
• To investigate the impact of these mutations on gene expression and cancer pathways.
• To explore the potential of noncoding mutations for cancer subtyping.

Main Methods:

• Integrative analysis of 930 tumor whole genomes and matched transcriptomes.
• Identification of somatic expression quantitative trait loci (eQTLs) in noncoding regions.
• Validation of identified loci in an independent cohort of 3,382 tumors.
• Functional validation in cancer cell lines and assessment of cellular migration.

Main Results:

• A network of 193 noncoding loci (somatic eQTLs) was identified, where mutations disrupt target gene expression.
• These somatic eQTLs are frequently mutated in specific cancer types and validated across large cohorts.
• Noncoding mutations affecting DAAM1, MTG2, and HYI transcription were confirmed in cell lines, with increased DAAM1 expression linked to invasive cell migration.
• The identified noncoding loci converge on core cancer pathways, enabling pathway-based tumor classification.

Conclusions:

• Somatic noncoding mutations significantly impact gene expression and converge on core cancer pathways.
• The identified somatic eQTL network is disrupted in a substantial majority of tumors (88%).
• Noncoding mutations represent a widespread and critical factor in cancer etiology and progression, offering potential for novel therapeutic strategies and classifications.