Dataset Information

Three-gene predictor of clinical outcome for gastric cancer patients treated with chemotherapy.

ABSTRACT: To identify transcriptional profiles predictive of the clinical benefit of cisplatin and fluorouracil (CF) chemotherapy to gastric cancer patients, endoscopic biopsy samples from 96 CF-treated metastatic gastric cancer patients were prospectively collected before therapy and analyzed using high-throughput transcriptional profiling and array comparative genomic hybridization. Transcriptional profiling identified 917 genes that are correlated with poor patient survival after CF at P<0.05 (poor prognosis signature), in which protein synthesis and DNA replication/recombination/repair functional categories are enriched. A survival risk predictor was then constructed using genes, which are included in the poor prognosis signature and are contained within identified genomic amplicons. The combined expression of three genes-MYC, EGFR and FGFR2-was an independent predictor for overall survival of 27 CF-treated patients in the validation set (adjusted P=0.017), and also for survival of 40 chemotherapy-treated gastric cancer patients in a published data set (adjusted P=0.026). Thus, combined expression of MYC, EGFR and FGFR2 is predictive of poor survival in CF-treated metastatic gastric cancer patients.

SUBMITTER: Kim HK

PROVIDER: S-EPMC3321506 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundSecond-line therapy has consistently demonstrated survival benefit if compared with best supportive care; however, there is limited evidence whether further lines of treatment may improve the prognosis of advanced gastric cancer (AGC) patients.Materials and methodsStarting from a real-world cohort of 868 AGC patients, we retrospectively analyzed baseline parameters, tumor characteristics, and treatment data of those treated with at least three lines. Categorical features were described through cross-tables and chi-square test. We explored the impact of treatment intensity and progression-free survival (PFS) experienced in previous lines on PFS and overall survival in third-line by uni- and multivariate Cox regression models and described by Kaplan-Meier estimator plot with log-rank test.ResultsOverall, 300 patients were included in the analysis. The most common site of primary tumor was gastric body; 45.3% of cancers had an intestinal histotype, 14% were human epidermal growth receptor 2 positive. In third-line, 45.7% of patients received a single-agent chemotherapy, 49.7% a combination regimen. Patients who had experienced a first-line PFS ≥6.9 months had a better prognosis compared with those who had achieved a shorter one. Consistently, a second-line PFS ≥3.5 months positively influenced the prognosis. Patients receiving a third-line combination regimen had better outcomes compared with those treated with a single-agent chemotherapy.ConclusionOur real-world study confirms that selected AGC patients may receive third-line treatment. Longer PFS in previous lines or a more intense third-line treatment positively influenced prognosis. Further efforts are warranted to define the best therapeutic sequences, and to identify the optimal candidate for treatment beyond second-line.Implications for practiceThe benefit of third-line treatment to advanced gastric cancer patients is controversial. This study depicts a real scenario of the clinical practice in Italy, confirming that a non-negligible proportion of patients receive a third-line therapy. Longer progression-free survival in previous treatment lines or higher third-line treatment intensity positively influenced prognosis. Including a large number of real-world patients, this study provides information on third-line treatment from the daily clinical practice; moreover, its results help in defining the best therapeutic sequence and offer some hints to select the optimal candidate for treatment beyond second-line.

Project description:Identification of patients who likely will or will not benefit from cytotoxic chemotherapy through the use of biomarkers could greatly improve clinical management by better defining appropriate treatment options for patients. microRNAs may be potentially useful biomarkers that help guide individualized therapy for cancer because microRNA expression is dysregulated in cancer. In order to identify miRNA signatures for gastric cancer and for predicting clinical resistance to cisplatin/fluorouracil (CF) chemotherapy, a comprehensive miRNA microarray analysis was performed using endoscopic biopsy samples.Biopsy samples were collected prior to chemotherapy from 90 gastric cancer patients treated with CF and from 34 healthy volunteers. At the time of disease progression, post-treatment samples were additionally collected from 8 clinical responders. miRNA expression was determined using a custom-designed Agilent microarray. In order to identify a miRNA signature for chemotherapy resistance, we correlated miRNA expression levels with the time to progression (TTP) of disease after CF therapy.A miRNA signature distinguishing gastric cancer from normal stomach epithelium was identified. 30 miRNAs were significantly inversely correlated with TTP whereas 28 miRNAs were significantly positively correlated with TTP of 82 cancer patients (P<0.05). Prominent among the upregulated miRNAs associated with chemosensitivity were miRNAs known to regulate apoptosis, including let-7g, miR-342, miR-16, miR-181, miR-1, and miR-34. When this 58-miRNA predictor was applied to a separate set of pre- and post-treatment tumor samples from the 8 clinical responders, all of the 8 pre-treatment samples were correctly predicted as low-risk, whereas samples from the post-treatment tumors that developed chemoresistance were predicted to be in the high-risk category by the 58 miRNA signature, suggesting that selection for the expression of these miRNAs occurred as chemoresistance arose.We have identified 1) a miRNA expression signature that distinguishes gastric cancer from normal stomach epithelium from healthy volunteers, and 2) a chemoreresistance miRNA expression signature that is correlated with TTP after CF therapy. The chemoresistance miRNA expression signature includes several miRNAs previously shown to regulate apoptosis in vitro, and warrants further validation.

Dataset Information

Three-gene predictor of clinical outcome for gastric cancer patients treated with chemotherapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets