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Updated: Mar 3, 2026

The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
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The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers

Published on: January 22, 2013

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A comprehensive analysis of cancer-driving mutations and genes in kidney cancer

Chengmei Long1, Jinbo Jian2, Xinchang Li1

  • 1Department of Organ Transplantation, Jiangxi Provincial People's Hospital, School of Medicine, Nanchang University, Nanchang, Jiangxi 330006, P.R. China.

Oncology Letters
|April 30, 2017
PubMed

Insights

This study identifies key cancer-driving genes and pathways in kidney cancer (RCC), highlighting the importance of noncoding variants and regulatory features for mutation distribution.

Area of Science:

  • Genomics
  • Cancer Biology
  • Bioinformatics

Background:

  • Driver mutations are crucial for cancer development, disrupting genes and signaling pathways.
  • Identifying these driver mutations, especially in noncoding regions, is vital for understanding cancer progression.

Purpose of the Study:

  • To identify cancer-driving mutations and genes in renal cell carcinoma (RCC).
  • To prioritize noncoding variants with high functional impact for analysis.
  • To analyze informative features influencing mutation distribution.

Main Methods:

  • Applied SIFT, Polyphen2, and MutationAssessor for coding mutation prediction.
  • Utilized OncodriveFM and OncodriveCLUST for driver gene and pathway identification.
  • Evaluated noncoding variant impact using CADD, FunSeq2, and GWAVA; analyzed feature enrichment.

Main Results:

  • Identified 1,327 deleterious coding mutations in clear cell RCC, 258 in chromophobe RCC, and 1,186 in papillary RCC.
  • Detected 77 positively selected genes (45 recurrently mutated) and 10 recurrently mutated signaling pathways with high FM bias.
  • Discovered 31 novel signaling pathways with high FM bias; found noncoding regulatory features and conserved regions enriched with high-scoring variants.

Conclusions:

  • Identified cancer-driving genes and signaling pathways in kidney cancer.
  • Regulatory elements, conserved regions, replication time, expression, GC content, and recombination rate significantly influence noncoding mutation distribution.
Keywords:
driver genedriver mutationdriver pathwayfunctional non-coding variantskidney cancer

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