Global impact of somatic structural variation on the cancer proteome

Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data with whole genome sequencing data across 1307 human tumors spanning various tissues to determine the extent somatic structural variant (SV) breakpoint patterns impact protein expression of nearby genes. We find that about 25% of the hundreds of genes with SV-associated cis-regulatory alterations at the mRNA level are similarly associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. SVs combined with altered protein levels considerably extend the numbers of patients with tumors somatically altered for critical pathways. We catalog both SV breakpoint patterns involving patient survival and genes with nearby SV breakpoints associated with increased cell dependency in cancer cell lines. Pan-cancer proteogenomics identifies targetable non-coding alterations, by virtue of the associated deregulated genes. The relevance of non-coding somatic mutations in cancer remains elusive. Here, the combination of mass spectrometry-based proteomics and whole genome sequencing data across multiple cancer types helps to assess the effects of somatic structural variant breakpoint patterns on protein expression of nearby genes.

Automated summary

This study combines mass spectrometry-based proteomics data with whole genome sequencing data to investigate the impact of non-coding somatic mutations on protein expression in cancer. The results show that about 25% of genes with SV-associated cis-regulatory alterations at the mRNA level are also associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. These findings provide insights into the importance of non-coding somatic mutations in tumors.