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

@article{ma2026singlecell,
  title = {{Single-cell transcriptomic atlas of gastric cancer reveals malignant cell heterogeneity and nominates EMB as a candidate prognostic biomarker.}},
  author = {Zheng Ma and Na Huang and Bingjie Ren and Tianran Wang and Liping Dai and Erping Xu},
  journal = {BMC cancer},
  year = {2026},
  month = jul,
  doi = {10.1186/s12885-026-16551-9},
  url = {https://europepmc.org/article/MED/42928163},
  note = {CC BY-NC-ND},
}

TY  - JOUR
TI  - Single-cell transcriptomic atlas of gastric cancer reveals malignant cell heterogeneity and nominates EMB as a candidate prognostic biomarker.
AU  - Zheng Ma
AU  - Na Huang
AU  - Bingjie Ren
AU  - Tianran Wang
AU  - Liping Dai
AU  - Erping Xu
PY  - 2026
DA  - 2026/07/28
JO  - BMC cancer
DO  - 10.1186/s12885-026-16551-9
UR  - https://europepmc.org/article/MED/42928163
AB  - Background  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.Methods  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.Results  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.Conclusions  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.
SN  - 1471-2407
ER  -