Hybrid Models Identified a 12-Gene Signature for Lung Cancer Prognosis and Chemoresponse Prediction

Details

• Personal Author:
  Castranova, Vincent ; Denvir J ; Guo NL ; Luo D ; Qian Y ; Raese R ; Sabbagh E ; Vallyathan V ; Wan YW
• Description:
  Background: Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35-50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment. Methodology/Principal Findings: From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples. Conclusions/Significance: The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs. [Description provided by NIOSH]
• Subjects:
  Biomarkers Genetics Lung Lung Diseases Neoplasms Occupational Health Respiratory System Respiratory Tract Diseases Safety
• Keywords:
  Cancer Chemotherapy Genes Genetic-engineering Humans Lung-cancer Lung-disease Lung-disorders Medical-research Medical-treatment Medicinal-chemicals Respiratory-system-disorders

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• ISSN:
  1932-6203
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  OSHA Region 3 ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  HELD - Health Effects Laboratory Division
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  5
• Issue:
  8
• NIOSHTIC Number:
  nn:20037340
• Citation:
  PLoS One 2010 Aug; 5(8):e12222
• Email:
  lguo@hsc.wvu.edu
• CAS Registry Number:
  Cisplatin (CAS RN 15663-27-1) ; Paclitaxel (CAS RN 33069-62-4)
• Federal Fiscal Year:
  2010
• NORA Priority Area:
  Manufacturing
• Peer Reviewed:
  True
• Source Full Name:
  PLoS One
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:bae68069d3b4cb6a4974f40635709bd51b0c07d883eea091cc227d97935df67637a2eb4e5f4addc9c5df302b469559ed5ab126a8a560be38bd70e37ee42639c0
• Download URL:
  https://stacks.cdc.gov/view/cdc/188443/cdc_188443_DS1.pdf
• File Type:
  [PDF - 2.06 MB ]