Integrative bioinformatics analysis reveals new prognostic biomarkers of clear cell renal cell carcinoma

Clin Chem. 2014 Oct;60(10):1314-26. doi: 10.1373/clinchem.2014.225854. Epub 2014 Aug 19.

Abstract

Background: The outcome of clear cell renal cell carcinoma (ccRCC) is still unpredictable. Even with new targeted therapies, the average progression-free survival is dismal. Markers for early detection and progression could improve disease outcome.

Methods: To identify efficient and hitherto unrecognized pathogenic factors of the disease, we performed a uniquely comprehensive pathway analysis and built a gene interaction network based on large publicly available data sets assembled from 28 publications, comprising a 3-prong approach with high-throughput mRNA, microRNA, and protein expression profiles of 593 ccRCC and 389 normal kidney samples. We validated our results on 2 different data sets of 882 ccRCC and 152 normal tissues. Functional analyses were done by proliferation, migration, and invasion assays following siRNA (small interfering RNA) knockdown.

Results: After integration of multilevel data, we identified aryl-hydrocarbon receptor (AHR), grainyhead-like-2 (GRHL2), and KIAA0101 as new pathogenic factors. GRHL2 expression was associated with higher chances for disease relapse and retained prognostic utility after controlling for grade and stage [hazard ratio (HR), 3.47, P = 0.012]. Patients with KIAA0101-positive expression suffered worse disease-free survival (HR, 3.64, P < 0.001), and in multivariate analysis KIAA0101 retained its independent prognostic significance. Survival analysis showed that GRHL2- and KIAA0101-positive patients had significantly lower disease-free survival (P = 0.002 and P < 0.001). We also found that KIAA0101 silencing decreased kidney cancer cell migration and invasion in vitro.

Conclusions: Using an integrative system biology approach, we identified 3 novel factors as potential biomarkers (AHR, GRHL2 and KIAA0101) involved in ccRCC pathogenesis and not linked to kidney cancer before.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / genetics*
  • Carcinoma, Renal Cell / genetics*
  • Carcinoma, Renal Cell / pathology
  • Carrier Proteins / genetics
  • Cell Line, Tumor
  • Cell Movement
  • Cell Proliferation
  • Computational Biology / methods*
  • Computational Biology / statistics & numerical data
  • DNA-Binding Proteins / genetics
  • Data Interpretation, Statistical
  • Databases, Genetic
  • Early Diagnosis
  • Gene Expression Profiling
  • Gene Knockdown Techniques
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Kidney Neoplasms / genetics*
  • Kidney Neoplasms / pathology
  • MicroRNAs / genetics
  • Prognosis
  • RNA, Small Interfering / genetics
  • Receptors, Aryl Hydrocarbon / genetics
  • Reproducibility of Results
  • Transcription Factors / genetics
  • Transfection

Substances

  • Biomarkers, Tumor
  • Carrier Proteins
  • DNA-Binding Proteins
  • GRHL2 protein, human
  • MicroRNAs
  • PCLAF protein, human
  • RNA, Small Interfering
  • Receptors, Aryl Hydrocarbon
  • Transcription Factors