Dataset Information

Clinical impact of a novel microRNA chemo-sensitivity predictor in gastroesophageal cancer

ABSTRACT: Background: miRNAs might be potentially useful biomarkers for prediction of response to chemotherapeutic agents, radiotherapy and survival. The aim of this retrospective study was to validate miRNA response predictors in a cohort of patients with gastroesophageal cancer in order to predict overall survival (OS) and disease-specific survival (DSS). Material and methods: The study population encompassed 53 patients treated with curative intended for loco-regional gastroesophageal cancer. miRNA expression was quantified from pre-therapeutic and diagnostic, formalin-fixed, paraffin embedded tumor specimens using Affymetrix GeneChip miRNA 1.0 Array. Based on growth inhibition of the NCI60 panel in the presence of cisplatin, epirubicine and capecitabine, a miRNA based response predictor was developed. The Cox proportional hazards model was applied to assess the correlations of the response predictor with OS and DSS. Results: A univariate analysis demonstrated a statistical significant improvement of OS for patients who had undergone surgical resection with prediction scores above the median prediction score (HR: 0.41 (95% CI: 0.17-0.96). Adjusting for surgery and stage, this predictor was identified to be independently associated with both OS (HR: 0.37 (95% CI: 0.16-0.87)) and DSS (HR: 0.32 (0.12-0.87)). Conclusion: The miRNA profile predictive for sensitivity to cisplatin, epirubicine and capecitabine was shown to be independently associated with OS and DSS in patients with gastroesophageal cancer.

ORGANISM(S): synthetic construct Homo sapiens

PROVIDER: GSE78049 | GEO | 2016/02/18

SECONDARY ACCESSION(S): PRJNA312443

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Introduction: Effective predictive biomarkers for selection of patients benefiting from adjuvant platinum-based chemotherapy in non-small cell lung cancer (NSCLC) are needed. Based on a previously validated methodology, molecular profiles of predicted sensitivity in two patient cohorts are presented. Methods: The profiles are correlations between in vitro sensitivity to cisplatin and vinorelbine and baseline mRNA expression of the 60 cell lines in the National Cancer Institute panel. An applied clinical samples filter focused the profiles to clinically relevant genes. The profiles were tested on 1) snap-frozen tumors from 133 patients with completely resected stage 1B-2 NSCLC randomized to adjuvant cisplatin and vinorelbine (ACV, n=71) or no adjuvant treatment (OBS, n=62) [GSE14814] and 2) formalin-fixed paraffin-embedded (FFPE) pre-treatment tumors from 95 patients with completely resected stage 1A-3B NSCLC receiving adjuvant cisplatin and vinorelbine. Results: The combined cisplatin and vinorelbine profiles showed: 1) univariate Hazard Ratio (HR) for sensitive versus resistant of 0.265 (95% CI:0.079-0.889, p=0.032) in the ACV cohort and a HR of 0.28 in a multivariate model (95% CI:0.08-1.04, p=0.0573); 2) significant prediction at 3 year survival from surgery in univariate (HR=0.138 (95% CI:0.035-0.537), p=0.004) and multivariate analysis (HR=0.14 (95% CI:0.030-0.6), p=0.0081). No discrimination was found in the OBS cohort (HR=1.328, p=0.60). The cisplatin predictor alone had similar figures with 1) univariate HR of 0.37 (95% CI:0.12-1.15, p=0.09) in the ACV cohort and 2) univariate HR of 0.14 (95% CI:0.03-0.59, p=0.0076) to three years. Functional analysis on the cisplatin profile revealed a group of upregulated genes related to RNA splicing as a part of DNA damage repair and apoptosis. Conclusions: Profiles derived from snap-frozen and FFPE NSCLC tissue were prognostic and predictive in the patients that received cisplatin and vinorelbine but not in the cohort that did not receive adjuvant treatment.

Dataset Information

Clinical impact of a novel microRNA chemo-sensitivity predictor in gastroesophageal cancer

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets