Dataset Information

Validation of a proliferation-based expression signature as prognostic marker in early stage lung adenocarcinoma.

ABSTRACT: PURPOSE:New prognostic markers to guide treatment decisions in early stage non-small cell lung cancer are necessary to improve patient outcomes. In this report, we assess the utility of a predefined mRNA expression signature of cell-cycle progression genes (CCP score) to define 5-year risk of lung cancer-related death in patients with early stage lung adenocarcinoma. EXPERIMENTAL DESIGN:A CCP score was calculated from the mRNA expression levels of 31 proliferation genes in stage I and stage II tumor samples from two public microarray datasets [Director's Consortium (DC) and GSE31210]. The same gene set was tested by quantitative PCR in 381 formalin-fixed paraffin-embedded (FFPE) primary tumors. Association of the CCP score with outcome was assessed by Cox proportional hazards analysis. RESULTS:In univariate analysis, the CCP score was a strong predictor of cancer-specific survival in both the Director's Consortium cohort (P = 0.00014; HR = 2.08; 95% CI, 1.43-3.02) and GSE31210 (P = 0.0010; HR = 2.25; 95% CI, 1.42-3.56). In multivariate analysis, the CCP score remained the dominant prognostic marker in the presence of clinical variables (P = 0.0022; HR = 2.02; 95% CI, 1.29-3.17 in Director's Consortium, P = 0.0026; HR = 2.16; 95% CI, 1.32-3.53 in GSE31210). On a quantitative PCR platform, the CCP score maintained highly significant prognostic value in FFPE-derived mRNA from clinical samples in both univariate (P = 0.00033; HR = 2.10; 95% CI, 1.39-3.17) and multivariate analyses (P = 0.0071; HR = 1.92; 95% CI, 1.18-3.10). CONCLUSIONS:The CCP score is a significant predictor of lung cancer death in early stage lung adenocarcinoma treated with surgery and may be a valuable tool in selecting patients for adjuvant treatment.

SUBMITTER: Wistuba II

PROVIDER: S-EPMC3834029 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Validation of a proliferation-based expression signature as prognostic marker in early stage lung adenocarcinoma.

Wistuba Ignacio I II Behrens Carmen C Lombardi Francesca F Wagner Susanne S Fujimoto Junya J Raso M Gabriela MG Spaggiari Lorenzo L Galetta Domenico D Galetta Domenico D Riley Robyn R Hughes Elisha E Reid Julia J Sangale Zaina Z Swisher Steven G SG Kalhor Neda N Moran Cesar A CA Gutin Alexander A Lanchbury Jerry S JS Barberis Massimo M Kim Edward S ES

Clinical cancer research : an official journal of the American Association for Cancer Research 20130918 22

<h4>Purpose</h4>New prognostic markers to guide treatment decisions in early stage non-small cell lung cancer are necessary to improve patient outcomes. In this report, we assess the utility of a predefined mRNA expression signature of cell-cycle progression genes (CCP score) to define 5-year risk of lung cancer-related death in patients with early stage lung adenocarcinoma.<h4>Experimental design</h4>A CCP score was calculated from the mRNA expression levels of 31 proliferation genes in stage I ...[more]

PMID: 24048333

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Project description:BackgroundThe incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD.MethodsThe public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan-Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts.ResultsA prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29-8.11; P = 6.16E-06), GSE31210 (HR = 11.91, 95% CI 4.15-34.19; P = 4.10E-06), GSE50081 (HR = 3.63, 95% CI 1.90-6.95; P = 9.95E-05), the combined data set (HR = 3.15, 95% CI 1.98-5.02; P = 1.26E-06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49-3.13; P = 4.54E-05) and GSE72094 (HR = 2.95, 95% CI 1.86-4.70; P = 4.79E-06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design.ConclusionsOur study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.

Project description:RNA modifications implicate pathological and prognosis significance in cancer development and progression, of which, m6A and m5C are representative regulators. These RNA modifications could produce effects on the function of other RNA by regulating gene expression. Thus, in this study, we aimed to explore the correlation between m6A/m5C regulators and early-stage lung adenocarcinoma (LUAD). Only the early-stage LUAD samples were included in this investigation, and the RNA-seq dataset of The Cancer Genome Atlas (TCGA) cohort was utilized to evaluate the expression of 37 m6A/m5C regulated genes. Based on the expression level of these 37 genes, early-stage LUAD patients were divided into 2 clusters, which were performed by consensus clustering, and the m6A/m5C subtypes had significantly different prognostic outcomes (p < 0.001). Cluster1, which has a better prognosis, was characterized by the C3 (inflammatory) immune subtype, low immune infiltration, chemokine expression, major histocompatibility complex (MHC) expression, and immune checkpoint molecule expression. Furthermore, compared with cluster1, cluster2 showed a T cell exhaustion state, characterized by a high expression of immune checkpoint genes, and immune cells, such as T cells, CD8+ T cells, cytotoxic lymphocytes, NK cells, and so on. In addition, patients in cluster2 were with high tumor mutational burden (TMB) and numerous significant mutated oncogene and tumor suppressor genes, such as WNT10B, ERBB4, SMARCA4, TP53, and CDKN2A (p < 0.001). A total of 19 genes were mostly related to the prognosis of LUAD and were upregulated in cluster2 (p < 0.05), showing a positive correlation with the mRNA expression of 37 m6A/m5C regulated genes. The predictive risk model was constructed using Cox and LASSO (least absolute shrinkage and selection operator) regression analysis. Finally, a seven-gene m6A/m5C risk model, comprising of METTL3, NPLOC4, RBM15, YTHDF1, IGF2BP1, NSUN3, and NSUN7, was constructed to stratify the prognosis of early-stage LUAD (p = 0.0049, AUC = 0.791). The high-risk score was associated with a poorer prognosis. This model was also validated using two additional GEO datasets: GSE72094 (p = 0.011, AUC = 0.736) and GSE50081 (p = 0.012, AUC = 0.628). In summary, it was established that the m6A/m5C-regulated genes performed a crosstalk function in the mRNA expression of early-stage LUAD. By interacting with other mRNA genes, m6A/m5C modification disturbs DNA replication and the tumor immune microenvironment (TIME). The seven-gene risk model may be a critical tool for the prognostic assessment of early-stage LUAD.

Dataset Information

Validation of a proliferation-based expression signature as prognostic marker in early stage lung adenocarcinoma.

Publications

Validation of a proliferation-based expression signature as prognostic marker in early stage lung adenocarcinoma.

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