Dataset Information

Tumor-based gene expression biomarkers to predict survival following curative intent resection for stage I lung adenocarcinoma.

ABSTRACT: BACKGROUND:Prognostic biomarkers are needed in clinical setting to predict outcome after resection for early-stage lung adenocarcinoma. The goal of this study is to validate tumor-based single-gene expression biomarkers with demonstrated prognostic value in order to move them along the clinical translation pipeline. METHODS:Prognostic genes were selected from the literature and the best candidates measured by quantitative real-time polymerase chain reaction (qPCR) in tumors of 233 patients with stage I adenocarcinoma. Significant prognostic genes were then validated in an independent set of 210 patients matching the first set in terms of histology, stage, and clinical data. RESULTS:Eleven genes with demonstrated prognostic value were selected from the literature. Complementary analyses in public databases and our own microarray dataset led to the investigation of six genes associated with good (BTG2, SELENBP1 and NFIB) or poor outcome (RRM1, EZH2 and FOXM1). In the first set of patients, EZH2 and RRM1 were significantly associated with better survival on top of age, sex and pathological stage (EZH2 p = 3.2e-02, RRM1 p = 5.9e-04). The prognostic values of EZH2 and RRM1 were not replicated in the second set of patients. A trend was observed for both genes in the joint analyses (n = 443) with higher expression associated with worse outcome. CONCLUSION:Adenocarcinoma-specific mRNA expression levels of EZH2 and RRM1 are associated with poor post-surgical survival in the first set of patients, but not replicated in a clinically and pathologically matched independent validation set. This study highlights challenges associated with clinical translation of prognostic biomarkers.

SUBMITTER: Clemenceau A

PROVIDER: S-EPMC6245750 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Tumor-based gene expression biomarkers to predict survival following curative intent resection for stage I lung adenocarcinoma.

Clemenceau Alisson A Gaudreault Nathalie N Henry Cyndi C Ugalde Paula A PA Labbé Catherine C Laviolette Michel M Joubert Philippe P Bossé Yohan Y

PloS one 20181120 11

<h4>Background</h4>Prognostic biomarkers are needed in clinical setting to predict outcome after resection for early-stage lung adenocarcinoma. The goal of this study is to validate tumor-based single-gene expression biomarkers with demonstrated prognostic value in order to move them along the clinical translation pipeline.<h4>Methods</h4>Prognostic genes were selected from the literature and the best candidates measured by quantitative real-time polymerase chain reaction (qPCR) in tumors of 233 ...[more]

PMID: 30458017

Similar Datasets

Project description:ImportancePathologic nodal stage is the most significant prognostic factor in resectable non-small cell lung cancer (NSCLC). The International Association for the Study of Lung Cancer NSCLC staging project revealed intercontinental differences in N category-stratified survival. These differences may indicate differences not only in cancer biology but also in the thoroughness of the nodal examination.ObjectiveTo determine whether survival was affected by sequentially more stringent definitions of pN staging quality in a cohort of patients with NSCLC after resection with curative intent.DesignThis observational study used the Mid-South Quality of Surgical Resection cohort, a population-based database of lung cancer resections with curative intent. A total of 2047 consecutive patients who underwent surgical resection at 11 hospitals with at least 5 annual lung cancer resections in 4 contiguous US Dartmouth hospital referral regions in northern Mississippi, eastern Arkansas, and western Tennessee (>90% of the eligible population) were included. Resections were performed from January 1, 2009, through January 25, 2016. Survival was evaluated with the Kaplan-Meier method and Cox proportional hazards models.ExposuresEight sequentially more stringent pN staging quality strata included the following: all patients (group 1); those with complete resections only (group 2); those with examination of at least 1 mediastinal lymph node (group 3); those with examination of at least 10 lymph nodes (group 4); those with examination of at least 3 hilar or intrapulmonary and at least 3 mediastinal lymph nodes (group 5); those with examination of at least 10 lymph nodes, including at least 1 mediastinal lymph node (group 6); those with examination of at least 1 hilar or intrapulmonary and at least 3 mediastinal nodal stations (group 7); and those with examination of at least 1 hilar or intrapulmonary lymph node, at least 10 total lymph nodes, and at least 3 mediastinal nodal stations (group 8).Main outcomes and measuresN category-stratified overall survival.ResultsOf the total 2047 patients (1046 men [51.1%] and 1001 women [48.9%]; mean [SD] age, 67.0 [9.6] years) included in the analysis, the eligible analysis population ranged from 541 to 2047, depending on stringency. Sequential improvement in the N category-stratified 5-year survival of pN0 and pN1 tumors was found from the least stringent group (0.63 [95% CI, 0.59-0.66] for pN0 vs 0.46 [95% CI, 0.38-0.54] for pN1) to the most stringent group (0.71 [95% CI, 0.60-0.79] for pN0 vs 0.60 [95% CI, 0.43-0.73] for pN1). The pN1 cohorts with 3 or more mediastinal nodal stations examined had the most striking survival improvements. More stringently defined mediastinal nodal examination was associated with better separation in survival curves between patients with pN1 and pN2 tumors.Conclusions and relevanceThe prognostic value of pN stratification depends on the thoroughness of examination. Differences in thoroughness of nodal staging may explain a large proportion of intercontinental survival differences. More thorough nodal examination practice must be disseminated to improve the prognostic value of the TNM staging system. Future updates of the TNM staging system should incorporate more quality restraints.

Dataset Information

Tumor-based gene expression biomarkers to predict survival following curative intent resection for stage I lung adenocarcinoma.

Publications

Tumor-based gene expression biomarkers to predict survival following curative intent resection for stage I lung adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets