Literature DB >> 20012501

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

Atsushi Takeno1, Ichiro Takemasa, Shigeto Seno, Makoto Yamasaki, Masaaki Motoori, Hiroshi Miyata, Kiyokazu Nakajima, Shuji Takiguchi, Yoshiyuki Fujiwara, Toshiro Nishida, Toshitsugu Okayama, Kenichi Matsubara, Yoichi Takenaka, Hideo Matsuda, Morito Monden, Masaki Mori, Yuichiro Doki.   

Abstract

BACKGROUND: 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.
METHODS: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly, we constructed a molecular prediction system and validated its robustness and prognostic validity by 500 times multiple validation by repeated random sampling in a retrospective set of 56 (38 relapse-free and 18 peritoneal-relapse) patients. Secondly, we applied this prediction to 85 patients of the prospective set to assess predictive accuracy and prognostic validity.
RESULTS: In the retrospective phase, repeated random validation yielded approximately 68% predictive accuracy and a 22-gene expression profile associated with peritoneal relapse was identified. The prediction system identified patients with poor prognosis. In the prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan-Meier analysis of peritoneal-relapse-free survival showed a significant difference between the "good signature group" and "poor signature group" (log-rank p = 0.0017). Multivariate analysis by Cox regression hazards model identified the molecular prediction as the only independent prognostic factor for peritoneal relapse.
CONCLUSIONS: Gene expression profile inherent to primary gastric cancer tissues can be useful in prospective prediction of peritoneal relapse after curative surgery, potentially allowing individualized postoperative management to improve the prognosis of patients with advanced gastric cancer.

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Year:  2009        PMID: 20012501     DOI: 10.1245/s10434-009-0854-1

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  22 in total

1.  Discovery and validation of prognostic markers in gastric cancer by genome-wide expression profiling.

Authors:  Yue-Zheng Zhang; Lian-Hai Zhang; Yang Gao; Chao-Hua Li; Shu-Qin Jia; Ni Liu; Feng Cheng; De-Yun Niu; William Cs Cho; Jia-Fu Ji; Chang-Qing Zeng
Journal:  World J Gastroenterol       Date:  2011-04-07       Impact factor: 5.742

Review 2.  Gastric cancer-molecular and clinical dimensions.

Authors:  Roopma Wadhwa; Shumei Song; Ju-Seog Lee; Yixin Yao; Qingyi Wei; Jaffer A Ajani
Journal:  Nat Rev Clin Oncol       Date:  2013-09-24       Impact factor: 66.675

3.  Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression.

Authors:  Jordan M Winter; Laura H Tang; David S Klimstra; Weiguo Liu; Irena Linkov; Murray F Brennan; Michael I DʼAngelica; Ronald P DeMatteo; Yuman Fong; William R Jarnagin; Eileen M Oʼreilly; Peter J Allen
Journal:  Ann Surg       Date:  2013-08       Impact factor: 12.969

4.  Surgical second-look in high risk gastrointestinal stromal tumor of small intestine: A case report.

Authors:  Margherita Nannini; Maria Abbondanza Pantaleo; Fausto Catena; Stefania Romano; Salvatore Tondo; Maria Giulia Pirini; Cristian Lolli; Alessandra Maleddu; Anna Mandrioli; Lidia Gatto; Maristella Saponara; Maria Caterina Pallotti; Angelo Paolo Dei Tos; Antonio Daniele Pinna; Guido Biasco
Journal:  Int J Surg Case Rep       Date:  2012-09-19

5.  Identification of novel biomarkers, MUC5AC, MUC1, KRT7, GAPDH, CD44 for gastric cancer.

Authors:  Jie Yang
Journal:  Med Oncol       Date:  2020-03-27       Impact factor: 3.064

6.  Gene-expression signatures can distinguish gastric cancer grades and stages.

Authors:  Juan Cui; Fan Li; Guoqing Wang; Xuedong Fang; J David Puett; Ying Xu
Journal:  PLoS One       Date:  2011-03-18       Impact factor: 3.240

7.  Immunohistochemistry - microarray analysis of patients with peritoneal metastases of appendiceal or colorectal origin.

Authors:  Danielle E Green; Thejus T Jayakrishnan; Michael Hwang; Sam G Pappas; T Clark Gamblin; Kiran K Turaga
Journal:  Front Surg       Date:  2015-01-05

8.  PATHOME: an algorithm for accurately detecting differentially expressed subpathways.

Authors:  S Nam; H R Chang; K-T Kim; M-C Kook; D Hong; C H Kwon; H R Jung; H S Park; G Powis; H Liang; T Park; Y H Kim
Journal:  Oncogene       Date:  2014-03-31       Impact factor: 9.867

Review 9.  Molecular classification and prediction in gastric cancer.

Authors:  Xiandong Lin; Yongzhong Zhao; Won-Min Song; Bin Zhang
Journal:  Comput Struct Biotechnol J       Date:  2015-08-13       Impact factor: 7.271

10.  Up-regulation of CLDN1 in gastric cancer is correlated with reduced survival.

Authors:  Lars L Eftang; Ying Esbensen; Tone M Tannæs; Gustav P Blom; Ida R K Bukholm; Geir Bukholm
Journal:  BMC Cancer       Date:  2013-12-10       Impact factor: 4.430

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