Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression profile prospectively predicts peritoneal relapse after curative surgery of gastric cancer

ABSTRACT: Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. KaplanâMeier analysis with peritoneal relapse free survival showed a significant difference between âgood signature groupâ and âpoor signature groupâ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers. Of 141 samples, 56 represented the retrospective phase and 85 represented the prospective phase.

ORGANISM(S): Homo sapiens

SUBMITTER: ATSUSHI TAKENO

PROVIDER: E-GEOD-15081 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Gene expression profile prospectively predicts peritoneal relapse after curative surgery of gastric cancer.

Takeno Atsushi A Takemasa Ichiro I Seno Shigeto S Yamasaki Makoto M Motoori Masaaki M Miyata Hiroshi H Nakajima Kiyokazu K Takiguchi Shuji S Fujiwara Yoshiyuki Y Nishida Toshiro T Okayama Toshitsugu T Matsubara Kenichi K Takenaka Yoichi Y Matsuda Hideo H Monden Morito M Mori Masaki M Doki Yuichiro Y

Annals of surgical oncology 20091211 4

<h4>Background</h4>Peritoneal relapse is the most common pattern of tumor progression in advanced gastric cancer. Clinicopathological findings are sometimes inadequate for predicting peritoneal relapse. The aim of this study was to identify patients at high risk of peritoneal relapse in a prospective study based on molecular prediction.<h4>Methods</h4>RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human p ...[more]

PMID: 20012501

Similar Datasets

Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration. Of 198 samples, 129 represented the discovery phase and 69 represented the validation phase.

Dataset Information

Gene expression profile prospectively predicts peritoneal relapse after curative surgery of gastric cancer

Publications

Gene expression profile prospectively predicts peritoneal relapse after curative surgery of gastric cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure