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The discovery and validation of ten-gene prognostic classifier in gastric cancer by whole genome expression profiling

ABSTRACT: The aim of this study is to identify and verify a prognosis set that is able to distinguish patient overall survival status based on whole genome expression profiling. Using Illumina HumanWG-6 beadarray, we analyzed the expression of 47,296 transcripts in two groups of gastric cancer patients who all underwent surgical resection. Thirty-nine of 46 samples in group one were used as a training set to discover candidates for overall survival prediction by using semi-supervised method, resulting in a panel of 10 genes as prognosis markers. This 10-marker set classified each case into a low or a high risk group with significantly different survival times (P = 0.000047) and maintained independent prognostic value in multivariate analysis. These 10 candidates were then verified in a fully independent validation set comprising 33 samples (P = 0.0009). Furthermore, the prognosis was consistent with the classical TNM staging system, and showed even better prediction. Interestingly, six of ten survival markers are ribosomal proteins, suggesting a possible association between deregulation of ribosome-related expression and poor prognosis. In conclusion, by whole genome expression profiling, 10 markers, including 6 ribosomal proteins, for overall survival prognosis of gastric cancer were found and validated, and which may be parallelly used with the TNM system.

ORGANISM(S): Homo sapiens

PROVIDER: GSE21983 | GEO | 2011/07/13

SECONDARY ACCESSION(S): PRJNA127195

REPOSITORIES: GEO

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The discovery and validation of ten-gene prognostic classifier in gastric cancer by whole genome expression profiling

Project description:The aim of this study is to identify and verify a prognosis set that is able to distinguish patient overall survival status based on whole genome expression profiling. Using Illumina HumanWG-6 beadarray, we analyzed the expression of 47,296 transcripts in two groups of gastric cancer patients who all underwent surgical resection. Thirty-nine of 46 samples in group one were used as a training set to discover candidates for overall survival prediction by using semi-supervised method, resulting in a panel of 10 genes as prognosis markers. This 10-marker set classified each case into a low or a high risk group with significantly different survival times (P = 0.000047) and maintained independent prognostic value in multivariate analysis. These 10 candidates were then verified in a fully independent validation set comprising 33 samples (P = 0.0009). Furthermore, the prognosis was consistent with the classical TNM staging system, and showed even better prediction. Interestingly, six of ten survival markers are ribosomal proteins, suggesting a possible association between deregulation of ribosome-related expression and poor prognosis. In conclusion, by whole genome expression profiling, 10 markers, including 6 ribosomal proteins, for overall survival prognosis of gastric cancer were found and validated, and which may be parallelly used with the TNM system. We investigated the transcriptome profiles of gastric cancer patients with different prognosis. Thirty-nine patients from first batch samples were used to discover prognostic markers and another 33 samples from batch two were used for validation.

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