Differential expression analysis of clear cell renal cell carcinomas in The Cancer Genome Atlas distinguishes an aggressive subset enriched with chromosomes 7 and 12 gains

Abstract

Aims The Cancer Genome Atlas (TCGA) provides an integrated resource for investigating the genetic, phenotypical and clinical characteristics of cancer. In this study, we aimed to define distinct subsets of clear cell renal cell carcinoma (ccRCC) through differential expression and principal component analyses. Methods and results We used DESeq2 to examine the expression profiles of 472 cases in TCGA. After a process of segregation and regrouping, we compared the mutation and copy number variation landscapes to discern two major clusters: cluster 1, composed mainly of classic ccRCC, and cluster 2, which was associated with gains at chromosomes 7 and 12. Gene set enrichment analysis disclosed that cluster 2 tumours were enriched in genes involving epithelial–mesenchymal transition. Histologically, cluster 2 tumours frequently exhibited cell elongation or spindling. Patients with cluster 2 tumours or tumours harbouring chromosomes 7 or 12 gains had a significantly greater cumulative incidence of mortality. We then employed fluorescence in‐situ hybridisation with probes against chromosomes 7 and 12 in a cohort of 119 cases of ccRCC from our institute for validation. Chromosomes 7 and 12 gains were associated with lower survival rates in both univariate and multivariate analyses. Conclusions Our study demonstrates that genetic data obtained through appropriate molecular methodologies can be a useful adjunct to help predict prognosis. It also provides an example of exploring TCGA to extract meaningful information that can eventually contribute to precision medicine.

Development of a Histopathology Informatics Pipeline for Classification and Prediction of Clinical Outcomes in Subtypes of Renal Cell Carcinoma

“…Characterizing the genomic composition of a tumor can help determine optimized treatment plans for patients to improve their clinical outcomes. Previous studies suggested that CNAs were predictive of the survival and qualitative histology findings in patients with ccRCC (46). Our studies demonstrated that CNAs in several genes, including VHL, EGFR, and KRAS, can affect quantitative histopathology patterns.…”