Single-cell transcriptomic atlas of gastric cancer reveals malignant cell heterogeneity and nominates EMB as a candidate prognostic biomarker

Gastric cancer (GC) shows marked cellular heterogeneity and a complex immune microenvironment, which limits reliable biomarkers and therapeutic targets. We constructed a primary GC single-cell atlas to resolve malignant cell states linked to prognosis and to identify candidate targets. Single-cell transcriptomes from tumor, adjacent/normal, and premalignant gastric tissues were integrated. After quality control and doublet removal, data were batch-corrected, clustered, and annotated. Malignant epithelial cells were inferred from large-scale copy-number variation patterns and re-clustered. A prognostic signature was constructed by using the top marker genes of the low-differentiation ARHGDIB⁺ malignant epithelial state as a biologically informed candidate pool, followed by univariable Cox regression and LASSO Cox modeling in the TCGA stomach adenocarcinoma cohort. Survival was evaluated by Kaplan–Meier analysis with log-rank testing, and discrimination was assessed by time-dependent receiver operating characteristic analysis. Immune context was estimated by computational deconvolution and Tumor Immune Dysfunction and Exclusion scoring. Cell-cell communication was inferred from ligand-receptor expression. EMB expression across GC cell lines was assessed using CCLE/DepMap data, and EMB knockdown efficiency was validated by RT-qPCR. EMB function was tested by shRNA knockdown followed by wound-healing and Matrigel Transwell invasion assays and immunoblotting of epithelial-mesenchymal transition markers. Thirteen major cell populations spanning epithelial, immune, and stromal lineages were identified. Copy-number analysis separated malignant from non-malignant epithelium and resolved 8 malignant epithelial clusters. An ARHGDIB + malignant epithelial state showed the lowest differentiation state and highest stem-like potential. A seven-gene signature stratified patients into high- and low-CSL groups; the high-CSL group had worse overall survival and showed bulk-level immune features consistent with an inflammatory but impaired immune context, including an increased CIBERSORT-estimated M2 macrophage fraction and higher dysfunction/exclusion scores. EMB was prioritized as a candidate prognostic hub gene, and EMB-high cells within the ARHGDIB + malignant epithelial subcluster showed inferred ligand-receptor interactions with monocytic/macrophage-related immune populations. EMB knockdown reduced gastric cancer cell migration and invasion and shifted epithelial–mesenchymal transition markers, increasing E-cadherin and decreasing N-cadherin. This primary GC single-cell atlas identifies a low-differentiation ARHGDIB⁺ malignant epithelial state and uses its marker genes to derive a seven-gene CSL signature associated with poor prognosis and bulk tumor-level immune features. EMB emerges as a candidate biomarker and functional mediator of GC cell migration and invasion, warranting further mechanistic validation.

Authors

Institutions

Publication Details

Journal
BMC Cancer
Published
2026-07-28
DOI
https://doi.org/10.1186/s12885-026-16551-9
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Single-cell transcriptomic atlas of gastric cancer reveals malignant cell heterogeneity and nominates EMB as a candidate prognostic biomarker

Liping Dai, Tianran Wang, Bingjie Ren, Erping Xu et al.
BMC Cancer
Single-cell and spatial transcriptomics
article

Single-cell transcriptomic atlas of gastric cancer reveals malignant cell heterogeneity and nominates EMB as a candidate prognostic biomarker

Liping Dai, Tianran Wang, Bingjie Ren, Erping Xu, Na Huang, Zheng Ma
article en

Abstract

Gastric cancer (GC) shows marked cellular heterogeneity and a complex immune microenvironment, which limits reliable biomarkers and therapeutic targets. We constructed a primary GC single-cell atlas to resolve malignant cell states linked to prognosis and to identify candidate targets. Single-cell transcriptomes from tumor, adjacent/normal, and premalignant gastric tissues were integrated. After quality control and doublet removal, data were batch-corrected, clustered, and annotated. Malignant epithelial cells were inferred from large-scale copy-number variation patterns and re-clustered. A prognostic signature was constructed by using the top marker genes of the low-differentiation ARHGDIB⁺ malignant epithelial state as a biologically informed candidate pool, followed by univariable Cox regression and LASSO Cox modeling in the TCGA stomach adenocarcinoma cohort. Survival was evaluated by Kaplan–Meier analysis with log-rank testing, and discrimination was assessed by time-dependent receiver operating characteristic analysis. Immune context was estimated by computational deconvolution and Tumor Immune Dysfunction and Exclusion scoring. Cell-cell communication was inferred from ligand-receptor expression. EMB expression across GC cell lines was assessed using CCLE/DepMap data, and EMB knockdown efficiency was validated by RT-qPCR. EMB function was tested by shRNA knockdown followed by wound-healing and Matrigel Transwell invasion assays and immunoblotting of epithelial-mesenchymal transition markers. Thirteen major cell populations spanning epithelial, immune, and stromal lineages were identified. Copy-number analysis separated malignant from non-malignant epithelium and resolved 8 malignant epithelial clusters. An ARHGDIB + malignant epithelial state showed the lowest differentiation state and highest stem-like potential. A seven-gene signature stratified patients into high- and low-CSL groups; the high-CSL group had worse overall survival and showed bulk-level immune features consistent with an inflammatory but impaired immune context, including an increased CIBERSORT-estimated M2 macrophage fraction and higher dysfunction/exclusion scores. EMB was prioritized as a candidate prognostic hub gene, and EMB-high cells within the ARHGDIB + malignant epithelial subcluster showed inferred ligand-receptor interactions with monocytic/macrophage-related immune populations. EMB knockdown reduced gastric cancer cell migration and invasion and shifted epithelial–mesenchymal transition markers, increasing E-cadherin and decreasing N-cadherin. This primary GC single-cell atlas identifies a low-differentiation ARHGDIB⁺ malignant epithelial state and uses its marker genes to derive a seven-gene CSL signature associated with poor prognosis and bulk tumor-level immune features. EMB emerges as a candidate biomarker and functional mediator of GC cell migration and invasion, warranting further mechanistic validation.

BMC Cancer
Henan University of Traditional Chinese Medicine (CN), First Affiliated Hospital of Henan University (CN)
Reduced inequalities
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.