Characterization of stem cell landscape and identification of stemness-related gene ENY2 in colorectal cancer by intergrated transcriptomic analysis^☆

Abstract

Background Cancer stem cells (CSCs) drive colorectal cancer (CRC) progression, metastasis, and therapy resistance, but their heterogeneity limits targeted treatment efficacy. Clarifying the stemness landscape and underlying mechanisms is crucial for developing effective CRC therapies.

Methods By integrating 10 ×single-cell data from GSE201348 and GSE161277, we constructed a single-cell atlas of nine primary CRC samples. CSCs were identified via scRNA-seq analyses. Using integrative bioinformatics tools, we identified ENY2 as a stemness-related marker and explored its potential role in CRC. We further compared genetic variants, immune infiltration, and drug sensitivity between high and low ENY2 expression groups.

Results Stem cell clusters (M0 and M7) in CRC were identified based on copy number variation, pseudotime trajectory, and CytoTRACE analyses. By integrating marker gene profiles, DEGs from GSE33113, CytoTRACE-based CSC genes, and prognostic genes from GSE17536, we identified two key stemness-related markers: ENY2 and PKM. ENY2 was prioritized for further analysis due to its limited investigation in CRC. Bioinformatic analyses revealed that ENY2 was significantly upregulated and associated with poor prognosis. Enrichment analyses indicated its involvement in MYC and E2F targets, G2M checkpoint, and EMT pathways. Drug sensitivity prediction suggested that high ENY2 expression may confer responsiveness to 5-fluorouracil, capecitabine, oxaliplatin, and 24 other potential agents.

Conclusions ENY2 may act as a key CSC-associated biomarker that promotes CRC tumorigenesis and metastasis via the EMT pathway, which enhance our understanding of CRC pathogenesis and highlight ENY2 as a potential target for diagnosis and therapy.

Keywords

Colorectal cancer / Cancer stem cells / Single-cell RNA-seq technology / ENY2 / EMT

Funding

This work was supported by the Wu Jieping Medical Foundation Special Fund for Clinical Research (Grant No. 320.6750.2022–07-15).

CRediT authorship contribution statement

Conceptualization：Wende Hao. Data curation：Wende Hao. Formal analysis: Wende Hao. Investigation：Wende Hao. Software：Wende Hao. Methodology：Wende Hao. Supervision：Zhenjun Wang. Funding acquisition：Huachong Ma. Writing-original draft：Wende Hao. Writing-review & editing：Huachong Ma.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Data availability

The analyzed datasets generated during the study are available from the corresponding author upon reasonable request.

Declaration of Competing Interest

The authors declare that they have no competing interests.

Acknowledgements

We thank the GEO and TCGA Database for sharing a large amount of data.

Appendix A. Supplementary material

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.gmg.2025.100067.

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