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An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer.

ABSTRACT: BACKGROUND: Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. METHODS: We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. RESULTS: An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. CONCLUSIONS: This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples.

SUBMITTER: Sanchez-Navarro I

PROVIDER: S-EPMC2906483 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer.

Sánchez-Navarro Iker I Gámez-Pozo Angelo A Pinto Alvaro A Hardisson David D Madero Rosario R López Rocío R San José Belén B Zamora Pilar P Redondo Andrés A Feliu Jaime J Cejas Paloma P González Barón Manuel M Angel Fresno Vara Juan J Espinosa Enrique E

BMC cancer 20100628

<h4>Background</h4>Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse.<h4>Methods</h4>We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed ...[more]

PMID: 20584321

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Project description:BackgroundGastric adenocarcinoma is an important contributor to cancer mortality and morbidity. This study aimed to explore the prognostic value of mutation patterns in gastric adenocarcinoma.Materials and methodsWe extracted somatic mutation data for 437 gastric adenocarcinoma samples from The Cancer Genome Atlas (TCGA) Stomach Adenocarcinoma (STAD) cohort. Kaplan-Meier survival in the R package maftools was used to analyze associations between mutations and survival. Multivariate Cox proportional model was used to establish risk formula. A four-gene-based risk score was developed to predict the overall survival of patients with gastric adenocarcinoma. We used the Tianjin cohort dataset with survival information to further evaluate the clinical value of this mutation signature.ResultsForty-five survival-related mutated genes were identified and verified, most of which were co-occurring in their mutation pattern and co-occurring with MLH3 and polymerase ϵ (POLE) mutations. Gastric adenocarcinoma samples with the 45 mutated genes had a significantly higher mutation count. Four-gene [UTRN, MUC16, coiled-coil domain-containing protein 178 (CCDC178), and HYDIN] mutation status was used to build a prognostic risk score that could be translated into the clinical setting. The association between the four-gene-based signature and overall survival remained statistically significant after controlling for age, sex, TNM stage, and POLE mutation status in the multivariate model [hazard ratio (HR), 1.88; 95% CI, 1.33-2.7; p < 0.001]. The prognostic significance of the four-gene-based risk score identified in TCGA cohort was validated in the Tianjin cohort.ConclusionA four-mutated gene risk formula was developed that correlated with the overall survival of patients with gastric adenocarcinoma using a multivariable Cox regression model. In two independent genomic datasets from TCGA and Tianjin cohorts, low risk scores were associated with higher tumor mutation loads and improved outcome in patients with gastric adenocarcinoma. This finding may have implications for prognostic prediction and therapeutic guidance for gastric adenocarcinoma.

Project description:Colorectal cancer (CRC) is one of the most frequently occurring malignancies worldwide. The outcomes of patients with similar clinical symptoms or at similar pathological stages remain unpredictable. This inherent clinical diversity is most likely due to the genetic heterogeneity. The present study aimed to create a predicting tool to evaluate patient survival based on genetic profile. Firstly, three Gene Expression Omnibus (GEO) datasets (GSE9348, GSE44076 and GSE44861) were utilized to identify and validate differentially expressed genes (DEGs) in CRC. The GSE14333 dataset containing survival information was then introduced in order to screen and verify prognosis-associated genes. Of the 66 DEGs, the present study screened out 46 biomarkers closely associated to patient overall survival. By Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, it was demonstrated that these genes participated in multiple biological processes which were highly associated with cancer proliferation, drug-resistance and metastasis, thus further affecting patient survival. The five most important genes, MET proto-oncogene, receptor tyrosine kinase, carboxypeptidase M, serine hydroxymethyltransferase 2, guanylate cyclase activator 2B and sodium voltage-gated channel a subunit 9 were selected by a random survival forests algorithm, and were further made up to a linear risk score formula by multivariable cox regression. Finally, the present study tested and verified this risk score within three independent GEO datasets (GSE14333, GSE17536 and GSE29621), and observed that patients with a high risk score had a lower overall survival (P<0.05). Furthermore, this risk score was the most significant compared with other predicting factors including age and American Joint Committee on Cancer stage, in the model, and was able to predict patient survival independently and directly. The findings suggest that this survival associated DEGs-based risk score is a powerful and accurate prognostic tool and is promisingly implemented in a clinical setting.

Dataset Information

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer.

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An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer.

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