Analysis of single-cell RNA sequencing data to examine the gastric inflammation-to-cancer transition and evaluation of the effect of probiotic on precancerous lesions

Abstract

Gastric cancer (GC) is the fifth most prevalent malignancy globally. However, its heterogeneity and asymptomatic early-stage development hinder timely diagnosis and effective treatment. Here, we employed single-cell RNA sequencing to delineate the transitional features of pit mucous cells (PMCs) during the gastritis-to-cancer transition and identified 100 core genes. Characterization of the gene set revealed the role of ribosomal protein small subunit and ribosomal protein large subunit in inflammation-to-cancer transition, which promoted ribonucleoprotein complex biogenesis and cytoplasmic translation. External validation using independent cohorts confirmed that this core gene set discriminated disease progression (AUC>0.7) and was significantly enriched in GC tissues (p<0.01). Moreover, we evaluated the therapeutic intervention effects of C. butyricum and synbiotics (Weichanghao®) using a rat model of gastritis and demonstrated the targeted suppression of inflammation-to-cancer transition genes. Our findings establish the basis for early diagnosis of GC through PMC-driven molecular dynamics. Additionally, we propose microbiota-based strategies to prevent the inflammation-to-cancer transition in preneoplastic stages. Furthermore, our results highlight that dysbiosis of the gastric microbiome can be addressed using probiotic supplementations and the core gene set may provide labeling for the evaluation of probiotics-based treatment.

Keywords

Gastric cancer / Inflammation-to-cancer transition / Single-cell RNA sequencing / Probiotic

Data Availability Statement

Publicly available data was downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). Experimental data in this study are available on request to the corresponding authors

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Minmin Hu: Writing - original draft, Investigation, Formal analysis. Shiyang Xu: Writing - original draft, Investigation, Formal analysis. Ruofei Xu: Validation, Investigation. Xiangjie Qi: Resources. Xiaofeng Yu: Resources. Jinqi Wang: Investigation, Conceptualization. Yige Li: Investigation. Yangyang Liu: Validation. Guiran Xi: Validation. Junbao Yu: Validation. Mei Shi: Writing - review & editing, Supervision, Investigation.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (2021YFA0717002) and Qingdao Municipal People's Livelihood Project (22-3-7-smjk-8-nsh).

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