Systematic analysis of somatic mutations impacting gene expression in 12 tumour types

Abstract

We present a novel hierarchical Bayes statistical model, xseq, to systematically quantify the impact of somatic mutations on expression profiles. We establish the theoretical framework and robust inference characteristics of the method using computational benchmarking. We then use xseq to analyse thousands of tumour data sets available through The Cancer Genome Atlas, to systematically quantify somatic mutations impacting expression profiles. We identify 30 novel cis-effect tumour suppressor gene candidates, enriched in loss-of-function mutations and biallelic inactivation. Analysis of trans-effects of mutations and copy number alterations with xseq identifies mutations in 150 genes impacting expression networks, with 89 novel predictions. We reveal two important novel characteristics of mutation impact on expression: (1) patients harbouring known driver mutations exhibit different downstream gene expression consequences; (2) expression patterns for some mutations are stable across tumour types. These results have critical implications for identification and interpretation of mutations with consequent impact on transcription in cancer.

Cross‐species analysis of the canine and human bladder cancer transcriptome and exome

“…given the variance in the gene expression data, we hypothesize that Table S8) that is syntenic to human genome regions chromosome 3.p21 and chromosome 3.p14 (which are known to be genetically unstable in bladder cancer 59 ). A hotspot of LOH (blue bars) can be seen in chromosome 16 (at a locus coinciding with reduced gene expression, as seen in Figure 4; this region is syntenic to a region in cytogenetic bands p12 and p22 on human chromosome 8; deletions in the latter region are associated with invasive bladder tumor growth 60 and 25% of human bladder tumors have LOH on 8p 61,62 Figure 2D,E). In terms of contrasts between the 13 CNA analysis and our Figure 4, the CNA study identified a region of recurrently increased copy number in Cfa chromosome 36; in our study, we did not detect overall elevated expression of genes in this chromosome ( Figure 4).…”

“…A hotspot of somatic mutations (purple horizontal bar; significant with FDR ≤ 0.05, odds ratio = 7.5, N = 8 somatic mutations; gene‐level Fisher's Exact Test) can be seen in cytogenetic region chromosome 20.q14 (see Supporting Information Table S8) that is syntenic to human genome regions chromosome 3.p21 and chromosome 3.p14 (which are known to be genetically unstable in bladder cancer). A hotspot of LOH (blue bars) can be seen in chromosome 16 (at a locus coinciding with reduced gene expression, as seen in Figure 4; this region is syntenic to a region in cytogenetic bands p12 and p22 on human chromosome 8; deletions in the latter region are associated with invasive bladder tumor growth and 25% of human bladder tumors have LOH on 8p). In a chromosome‐level enrichment test for the frequency of mutations per Mbp, chromosome 16 had a 2.8‐fold elevated mutation rate compared to the genome‐wide average ( P < 10 −5 , Poisson test; magenta bar).…”

Effects of somatic alterations at pathway level are more mechanism‐explanatory and clinically applicable to quantity of liver metastases of colorectal cancer

“…So, evaluating the affect of alterations on cell phenotypes on pathway level is more accurate and systematic than that only on alteration itself or gene level. 50,51 The pathogenic pathways, especially type special pathogenic pathways provided important insights into molecular mechanisms. In general, for three types of CRCLM, the ability of cancer cell migration and genomic stability were gradually increased, while the immune response was gradually reduced which led to enhanced immune escape of cancer cell, but the trend of cancer cell proliferation appeared ambiguous (Table 1).…”

Functional variomics and network perturbation: connecting genotype to phenotype in cancer

“…Several approaches have been proposed to address this direction. XSeq 138 analyzes the impact of somatic mutations by incorporating gene expression, patient mutations, and a gene interaction network. PARADIGM-SHIFT 139 is another example that infers mutated gene activity from gene expression and copy number in the context of genetic pathways.…”