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PMID: 24367507 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer.

PloS one ·Vol. 8 ·No. 12 ·2013-00-00 ·Pages e82241

Győrffy B, Surowiak P, Budczies J, Lánczky A

Abstract

In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short. To further understand the molecular basis of the disease we have to identify biomarkers related to survival. Here we present the development of an online tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival. We searched the caBIG, GEO and TCGA repositories to identify samples with published gene expression data and survival information. Univariate and multivariate Cox regression analysis, Kaplan-Meier survival plot with hazard ratio and logrank P value are calculated and plotted in R. The complete analysis tool can be accessed online at: www.kmplot.com/lung. All together 1,715 samples of ten independent datasets were integrated into the system. As a demonstration, we used the tool to validate 21 previously published survival associated biomarkers. Of these, survival was best predicted by CDK1 (p<1E-16), CD24 (p<1E-16) and CADM1 (p = 7E-12) in adenocarcinomas and by CCNE1 (p = 2.3E-09) and VEGF (p = 3.3E-10) in all NSCLC patients. Additional genes significantly correlated to survival include RAD51, CDKN2A, OPN, EZH2, ANXA3, ADAM28 and ERCC1. In summary, we established an integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer.

MeSH Terms
Biomarkers Carcinoma, Non-Small-Cell Lung/genetics Humans Kaplan-Meier Estimate Lung Neoplasms/genetics Multivariate Analysis Proportional Hazards Models Software Transcriptome/genetics
Chemicals
Biomarkers
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Győrffy Balázs
Research Laboratory of Pediatrics and Nephrology, Hungarian Academy of Sciences, Budapest, Hungary.
Surowiak Pawel
Department of Histology and Embryology, Wroclaw Medical University, Wrocław, Poland.
Budczies Jan
Institut für Pathologie, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Lánczky András
Research Laboratory of Pediatrics and Nephrology, Hungarian Academy of Sciences, Budapest, Hungary.
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Article Info
Journal
PloS one
Abbr.
PLoS One
ISSN
1932-6203
DOI
10.1371/journal.pone.0082241
Published
2013-00-00
Epub
2013-00-18
Pages
e82241
Language
English
Region
United States
NLM ID
101285081
PMCID
PMC3867325
Subset
IM
Corrections
ErratumIn
-
External Links
PubMed source DOI: 10.1371/journal.pone.0082241 PMC Full Text View journal details
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