ABSTRACT
Background
An important factor in tumor development and progression is the tumor microenvironment (TME), which is heterogeneous. Previous studies have mainly investigated the expression profile and prognostic values of genes in gastric cancer (GC) at the cell population level but neglected the interactions and heterogeneity between cells.
Methods
The pattern of ligand–receptor (LR) interactions was delineated on a scRNA-seq dataset containing 44,953 cells from nine GC patients and a fourth bulk RNA-seq dataset including data from 1159 GC patients. We then constructed an LR.Score scoring model to comprehensively evaluate the influence of LR-pairs on the TME, overall survival, and immunotherapy response in GC patients from several cohorts.
Results
Cell communication network among 13 cell types was constructed based on the LR-pairs. We proposed a new molecular subtyping model for GC based on the LR-pairs and revealed the differences in prognosis, pathophysiologic features, mutation characteristics, function enrichment, and immunological characteristics among the three subtypes. Finally, an LR.Score model based on LR-pairs was developed and validated on several datasets.
Conclusions
Based on the selected LR-pairs, we successfully constructed a novel prediction model and observed its well performance on molecular subtyping, target and pathway screening, prognosis judging, and immunotherapy response predicting.
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Declaration of interest
The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.
Author contributions
Wanli Yang, Xinhui Zhao, Lili Duan and Liaoran Niu performed the data analyses and wrote the manuscript; Yujie Zhang, Wei Zhou, Yiding Li, Junfeng Chen contributed significantly to analysis and manuscript preparation; Aqiang Fan, Qibin Xie, Jinqiang Liu helped perform the analysis with constructive discussions; Yu Han, Daiming Fan, and Liu Hong contributed to the conception of the study and revised the manuscript. All authors have read and approved the submitted version.
Competing interests
The authors have declared that no competing interest exists.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/14737159.2023.2219843.