Integrated multigene expression panel to prognosticate patients with gastric cancer
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Mitsuro Kanda1, Kenta Murotani2, Haruyoshi Tanaka1, Takashi Miwa1, Shinichi Umeda1, Chie Tanaka1, Daisuke Kobayashi1, Masamichi Hayashi1, Norifumi Hattori1, Masaya Suenaga1, Suguru Yamada1, Goro Nakayama1, Michitaka Fujiwara1 and Yasuhiro Kodera1
1Department of Gastroenterological Surgery (Surgery II), Nagoya University Graduate School of Medicine, Nagoya, Japan
2Clinical Research Center, Aichi Medical University Hospital, Nagakute, Japan
Mitsuro Kanda, email: firstname.lastname@example.org
Keywords: gastric cancer; expression panel; prognosis; biomarker
Received: January 05, 2018 Accepted: February 27, 2018 Published: April 10, 2018
Most of the proposed individual markers had limited clinical utility due to the inherent biological and genetic heterogeneity of gastric cancer. We aimed to build a new molecular-based model to predict prognosis in patients with gastric cancer. A total of 200 patients who underwent gastric resection for gastric cancer were divided into learning and validation cohorts using a table of random numbers in a 1:1 ratio. In the learning cohort, mRNA expression levels of 15 molecular markers in gastric tissues were analyzed and concordance index (C-index) values of all single and combinations of the 15 candidate markers for overall survival were calculated. The multigene expression panel was designed according to C-index values and the subpopulation index. Expression scores were determined with weighting according to the coefficient of each constituent. The reproducibility of the panel was evaluated in the validation cohort. C-index values of the 15 single candidate markers ranged from 0.506–0.653. Among 32,767 combinations, the optimal and balanced expression panel comprised four constituents (MAGED2, SYT8, BTG1, and FAM46) and the C-index value was 0.793. Using this panel, patients were provisionally categorized with scores of 1–3, and clearly stratified into favorable, intermediate, and poor overall survival groups. In the validation cohort, both overall and disease-free survival rates decreased incrementally with increasing expression scores. Multivariate analysis revealed that the expression score was an independent prognostic factor for overall survival after curative gastrectomy. We developed an integrated multigene expression panel that simply and accurately stratified risk of patients with gastric cancer.
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