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Integrated Differential Regulatory Analysis Reveals a Novel Prognostic 36-Gene Signature for Gastric Cancer in Asian Population

[ Vol. 20 , Issue. 2 ]

Author(s):

Junyi Li, Sujuan Wu, Liguang Yang, Yi-Xue Li, Bing-Ya Liu and Yuan-Yuan Li   Pages 174 - 181 ( 8 )

Abstract:


Aim and Objective: Gastric cancer is one of the most common cancers and has very high incidence and mortality rate in Asian population. To tackle the problems of infiltration and heterogeneity, more accurate biomarkers for diagnosis and prognosis as well as effective targets for treatment are needed to achieve better outcomes of gastric cancer patients. Recently, methods and algorithms for analyzing high-throughput sequencing data have greatly facilitated the molecular profiling of gastric cancer. Nevertheless, prognostic biomarkers for gastric cancer that can be potentially applied in clinic are still lacking.

Materials and Methods: In this study, we performed differential regulatory analysis based on gene co-expression network for four different cohorts of Asian gastric cancer samples and their clinical data.

Results: We identified a 36-gene prognostic signature specific for gastric cancer, particularly for Asian population. We further analyzed differential regulatory patterns related to these featured genes, such as C1S, and suggested hypotheses for investigating their roles in gastric cancer pathogenesis.

Conclusion: Findings from present study suggest a 36-gene signature which is based on differential regulatory analysis and can predict the prognosis of gastric cancer. Our research explores molecular mechanism of gastric cancer at transcriptional regulation level and provides potential drug targets. This integrated biomarker searching scheme is extendable to other cancer study for not only prognostic prediction, but also pathogenesis.

Keywords:

Differential regulatory analysis, differential co-expression analysis, co-expression network, prognostic biomarker, gastric cancer carcinogenesis, precision medicine.

Affiliation:

Key Lab of Computational Biology,CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai 201203, Key Lab of Computational Biology,CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, Shanghai Industrial Technology Institute, 1278 Keyuan Road, Shanghai 201203, Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, Shanghai Engineering Research Center of Pharmaceutical Translation, 1278 Keyuan Road, Shanghai 201203



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