Proteomic profiling of gastric cancer with peritoneal metastasis identifies a protein signature associated with immune microenvironment and patient outcome
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Published:2023-03-17
Issue:4
Volume:26
Page:504-516
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ISSN:1436-3291
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Container-title:Gastric Cancer
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language:en
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Short-container-title:Gastric Cancer
Author:
Chen Yanyan, Cai Guoxin, Jiang Junjie, He Chao, Chen Yiran, Ding Yongfeng, Lu Jun, Zhao Wenyi, Yang Yan, Zhang Yiqin, Wu Guanghao, Wang Haiyong, Zhou Zhan, Teng LisongORCID
Abstract
Abstract
Background
Peritoneal metastasis (PM) frequently occurs in patients with gastric cancer (GC) and is a major cause of mortality. Risk stratification for PM can optimize decision making in GC treatment.
Methods
A total of 25 GC patients (13 with synchronous, 6 with metachronous PM and 6 PM-free) were included in this study. Quantitative proteomics by high-depth tandem mass tags labeling and whole-exome sequencing were conducted in primary GC and PM samples. Proteomic signature and prognostic model were established by machine learning algorithms in PM and PM-free GC, then validated in two external cohorts. Tumor-infiltrating immune cells in GC were analyzed by CIBERSORT.
Results
Heterogeneity between paired primary and PM samples was observed at both genomic and proteomic levels. Compared to primary GC, proteome of PM samples was enriched in RNA binding and extracellular exosomes. 641 differently expressed proteins (DEPs) between primary GC of PM group and PM-free group were screened, which were enriched in extracellular exosome and cell adhesion pathways. Subsequently, a ten-protein signature was derived based on DEPs by machine learning. This signature was significantly associated with patient prognosis in internal cohort and two external proteomic datasets of diffuse and mixed type GC. Tumor-infiltrating immune cell analysis showed that the signature was associated with immune microenvironment of GC.
Conclusions
We characterized proteomic features that were informative for PM progression of GC. A protein signature associated with immune microenvironment and patient outcome was derived, and it could guide risk stratification and individualized treatment.
Funder
Regional Diagnosis and Treatment Centre of the Health Planning Committee National Natural Science Foundation of China Science and Technology Plan Project of Jinhua
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Gastroenterology,Oncology,General Medicine
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