iScience (Oct 2022)
The integrated landscape of eRNA in gastric cancer reveals distinct immune subtypes with prognostic and therapeutic relevance
- Xin Hu,
- Liuxing Wu,
- Yanxin Yao,
- Junfu Ma,
- Xiangchun Li,
- Hongru Shen,
- Luyang Liu,
- Hongji Dai,
- Wei Wang,
- Xinlei Chu,
- Chao Sheng,
- Meng Yang,
- Hong Zheng,
- Fengju Song,
- Kexin Chen,
- Ben Liu
Affiliations
- Xin Hu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Liuxing Wu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Yanxin Yao
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Junfu Ma
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Xiangchun Li
- Tianjin Cancer Institute, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University, Tianjin, China
- Hongru Shen
- Tianjin Cancer Institute, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University, Tianjin, China
- Luyang Liu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Hongji Dai
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Wei Wang
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Xinlei Chu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Chao Sheng
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Meng Yang
- Tianjin Cancer Institute, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University, Tianjin, China
- Hong Zheng
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Fengju Song
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
- Kexin Chen
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China; Corresponding author
- Ben Liu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China; Corresponding author
- Journal volume & issue
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Vol. 25,
no. 10
p. 105075
Abstract
Summary: The comprehensive regulation effect of eRNA on tumor immune cell infiltration and the outcome remains obscure. We comprehensively identify the eRNA-mediated immune infiltration patterns of gastric cancer (GC) samples. We creatively proposed a random forest machine-learning (ML) algorithm to map eRNA to mRNA expression patterns. The eRNA score was constructed using principal component analysis algorithms and validated in an independent cohort. Three subtypes with distinct eRNA expression patterns were determined in GC. There were significant differences between the three subtypes in the overall survival rate, immune cell infiltration characteristics, and immunotherapy response indicators. The patients in the high eRNA score group have a higher overall survival rate and might benefit from immunotherapy. This work revealed that eRNA regulation might be a new prognostic index and might offer a potential biomarker in the response of immunotherapy. Evaluating the eRNA regulation manner of GC will contribute to guiding more effective immunotherapy strategies.
