Development and Experimental Validation of a Novel Prognostic Signature for Gastric Cancer

Author:

Liu Chengcheng123,Huo Yuying1ORCID,Zhang Yansong4,Yin Fumei5ORCID,Chen Taoyu6,Wang Zhenyi27ORCID,Gao Juntao27,Jin Peng8,Li Xiangyu1ORCID,Shi Minglei23,Zhang Michael Q.2379

Affiliation:

1. School of Software Engineering, Beijing Jiaotong University, Beijing 100044, China

2. MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, BNRist, Tsinghua University, Beijing 100084, China

3. School of Medicine, Tsinghua University, Beijing 100084, China

4. School of Life Sciences, Peking University, Beijing 100871, China

5. Medical School of Chinese PLA, Beijing 100853, China

6. Department of Bioinformatics, School of Basic Medicine, Peking University Health Center, Beijing 100191, China

7. Department of Automation, Tsinghua University, Beijing 100084, China

8. Senior Department of Gastroenterology, First Medical Center of Chinese PLA General Hospital, Beijing 100036, China

9. Department of Biological Sciences, Center for Systems Biology, University of Texas at Dallas, Richardson, TX 75080, USA

Abstract

Background: Gastric cancer is a malignant tumor with high morbidity and mortality. Therefore, the accurate recognition of prognostic molecular markers is the key to improving treatment efficacy and prognosis. Methods: In this study, we developed a stable and robust signature through a series of processes using machine-learning approaches. This PRGS was further experimentally validated in clinical samples and a gastric cancer cell line. Results: The PRGS is an independent risk factor for overall survival that performs reliably and has a robust utility. Notably, PRGS proteins promote cancer cell proliferation by regulating the cell cycle. Besides, the high-risk group displayed a lower tumor purity, higher immune cell infiltration, and lower oncogenic mutation than the low-PRGS group. Conclusions: This PRGS could be a powerful and robust tool to improve clinical outcomes for individual gastric cancer patients.

Funder

National Key Research and Development Program of China

Beijing Municipal Natural Science Foundation

Research Funds for the Central Universities

CAS Interdisciplinary Innovation Team

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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