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

Henriett Butz, Peter M. Szabó, Roy Nofech-Mozes, Fabio Rotondo, Kalman Kovacs, Lorna Mirham, Hala Girgis, Dina Boles, A. Patócs, George M. Yousef

Research output: Contribution to journalArticle

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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), grainyheadlike-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.

Original languageEnglish
Pages (from-to)1314-1326
Number of pages13
JournalClinical Chemistry
Volume60
Issue number10
DOIs
Publication statusPublished - Oct 1 2014

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Biomarkers
Bioinformatics
Computational Biology
Renal Cell Carcinoma
Cells
Disease-Free Survival
Aryl Hydrocarbon Receptors
Kidney Neoplasms
Hazards
Systems Biology
Gene Regulatory Networks
Survival Analysis
MicroRNAs
Small Interfering RNA
Cell Movement
Publications
Multivariate Analysis
Assays
Kidney
Recurrence

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Biochemistry, medical
  • Medicine(all)

Cite this

Butz, H., Szabó, P. M., Nofech-Mozes, R., Rotondo, F., Kovacs, K., Mirham, L., ... Yousef, G. M. (2014). Integrative bioinformatics analysis reveals new prognostic biomarkers of clear cell renal cell carcinoma. Clinical Chemistry, 60(10), 1314-1326. https://doi.org/10.1373/clinchem.2014.225854

Integrative bioinformatics analysis reveals new prognostic biomarkers of clear cell renal cell carcinoma. / Butz, Henriett; Szabó, Peter M.; Nofech-Mozes, Roy; Rotondo, Fabio; Kovacs, Kalman; Mirham, Lorna; Girgis, Hala; Boles, Dina; Patócs, A.; Yousef, George M.

In: Clinical Chemistry, Vol. 60, No. 10, 01.10.2014, p. 1314-1326.

Research output: Contribution to journalArticle

Butz, H, Szabó, PM, Nofech-Mozes, R, Rotondo, F, Kovacs, K, Mirham, L, Girgis, H, Boles, D, Patócs, A & Yousef, GM 2014, 'Integrative bioinformatics analysis reveals new prognostic biomarkers of clear cell renal cell carcinoma', Clinical Chemistry, vol. 60, no. 10, pp. 1314-1326. https://doi.org/10.1373/clinchem.2014.225854
Butz, Henriett ; Szabó, Peter M. ; Nofech-Mozes, Roy ; Rotondo, Fabio ; Kovacs, Kalman ; Mirham, Lorna ; Girgis, Hala ; Boles, Dina ; Patócs, A. ; Yousef, George M. / Integrative bioinformatics analysis reveals new prognostic biomarkers of clear cell renal cell carcinoma. In: Clinical Chemistry. 2014 ; Vol. 60, No. 10. pp. 1314-1326.
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AU - Butz, Henriett

AU - Szabó, Peter M.

AU - Nofech-Mozes, Roy

AU - Rotondo, Fabio

AU - Kovacs, Kalman

AU - Mirham, Lorna

AU - Girgis, Hala

AU - Boles, Dina

AU - Patócs, A.

AU - Yousef, George M.

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N2 - 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), grainyheadlike-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.

AB - 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), grainyheadlike-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.

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