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DATABASE construction n=1,715 Median OS=40.0 months, age: 64+/-10 yrs PowerPoint Presentation
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An online tool for the validation of survival-predicting biomarkers in non small-cell lung cancer using microarray data of 1,329 1,715 patients.

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An online tool for the validation of survival-predicting biomarkers in non small-cell lung cancer using microarray data of 1,3291,715 patients

Balázs Győrffy and András LánczkyResearch Laboratory for Pediatrics and Nephrology, Hungarian Academy of Sciences and Semmelweis University 1st Dept. of Pediatrics, Budapest, Hungary

Background and Objective

Results

  • optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short
  • by identifying biomarkers related to survival we can further understand the molecular basis of the disease
  • OBJECTIVE: we present the development of an online available tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival
  • DATABASE construction
  • n=1,715
  • Median OS=40.0 months, age: 64+/-10 yrs
  • Histology (adeno/squamous/large): 50% / 45% / 5%
  • Stage 1/2/3/4: 63% / 27% / 10% / 1%
  • META-ANALYSIS of biomarker candidates
  • Biomarker candidates identified in Pubmed n=22
  • For each gene the exact conditions in which it was identified have been retrieved, and these have been used as filtering when selecting the patients for the survival analysis.
  • Of the 22, the best performing genes are:
  • n(1): number of patients in original study, n(2): number of patients in the KM-plotter, HR: hazard ratio, ADE: adenocarcinoma, NSCLC: all non-small-cell lung cancer patients
  • Selected KAPLAN-MEIER plots (table: *)

Materials & Methods

  • DATABASE construction
  • Repositories: GEO, TCGA, ArrayExpress, caBIG
  • Platforms: Affymetrix HGU133A, plus2 & A 2.0 arrays
  • at least 30 patients with survival information
  • MAS5 normalization + quality control
  • SURVIVAL analysis
  • Kaplan-Meier plot
  • „survival” Bioconductor package
  • Cox univariate + multivariate analysis
  • ONLINE platform
  • Apache web server on Debian Linux
  • script developed in PHP
  • Open access at: www.kmplot.com/lung
  • META-analysis
  • Pubmed search of published biomarkers
  • Best cutoff selection: each percentile (of expression) between the lower and upper quartiles are computed and the best performing threshold is used as the final cutoff in the Cox regression analysis.

Cyclin E1

CDK1

CADM1

Summary

  • we performed a meta-analysis of survival-associated genes
  • an integrated database and an online tool for future in silico validation of new candidates has been established

Web addresses

Online access: http://www.kmplot.com/lung

Group homepage: http://gyer1-6.sote.hu/gyorffy

Contact: gyorffy@kmplot.com

Grant support: OTKA PD 83154, PREDICT 259303 (EU Health.2010.2.4.1.-8), KTIA EU_BONUS_12-1-2013-0003,

Alexander von Humboldt-Foundation