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Prognostic value of a 25-gene assay in patients with gastric cancer after curative resection.


ABSTRACT: This study aimed to develop and validate a practical, reliable assay for prognosis and chemotherapy benefit prediction compared with conventional staging in Gastric cancer (GC). Twenty-three candidate genes with significant correlation between quantitative hybridization and microarray results plus 2 reference genes were selected to form a 25-gene prognostic classifier, which can classify patients into 3 distinct groups of different risk of mortality obtained by analyzing microarray data from 78 frozen tumor specimens. The 25-gene assay was associated with overall survival in both training (P?=?0.017) and testing cohort (P?=?0.005) (462 formalin-fixed paraffin-embedded samples). The risk prediction in stages I?+?II is significantly better than that in stages III. Analysis demonstrated that this 25-gene signature is an independent prognostic predictor and show higher prognostic accuracy than conventional TNM staging in early stage patients. Moreover, only high-risk patients in stage I?+?II were found benefit from adjuvant chemotherapy (P?=?0.043), while low-risk patients in stage III were not found benefit from adjuvant chemotherapy. In conclusion, our results suggest that this 25-gene assay can reliably identify patients with different risk for mortality after surgery, especially for stage I?+?II patients, and might be able to predict patients who benefit from chemotherapy.

SUBMITTER: Wang X 

PROVIDER: S-EPMC5548732 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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This study aimed to develop and validate a practical, reliable assay for prognosis and chemotherapy benefit prediction compared with conventional staging in Gastric cancer (GC). Twenty-three candidate genes with significant correlation between quantitative hybridization and microarray results plus 2 reference genes were selected to form a 25-gene prognostic classifier, which can classify patients into 3 distinct groups of different risk of mortality obtained by analyzing microarray data from 78  ...[more]

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