Identifying Epithelial-Cell Progression Signatures (ECPSs) from Multi-Resolution Multi-Omics Data for Translational Clinical Applications in Lung Adenocarcinoma

Chen, Xueyao; Lv, Tongxin; Wu, Yang; Fan, Fangfang; Kang, Shaobo; Dou, Renjie; Zhang, Wanmei; Li, Dongxue; Li, Rui; Ping, Yanyan

doi:10.3390/ijms27156819

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Identifying Epithelial-Cell Progression Signatures (ECPSs) from Multi-Resolution Multi-Omics Data for Translational Clinical Applications in Lung Adenocarcinoma

by

Xueyao Chen

^†,

Tongxin Lv

^†,

Yang Wu

,

Fangfang Fan

,

Shaobo Kang

,

Renjie Dou

,

Wanmei Zhang

,

Dongxue Li

,

Rui Li

and

Yanyan Ping

^*

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China

^*

Author to whom correspondence should be addressed.

^†

These authors contributed equally to this work.

Int. J. Mol. Sci. 2026, 27(15), 6819; https://doi.org/10.3390/ijms27156819

Submission received: 30 April 2026 / Revised: 17 July 2026 / Accepted: 24 July 2026 / Published: 29 July 2026

(This article belongs to the Special Issue Computational and Multi-Omics Bioinformatics in Cancer Biology and Therapy Response)

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Abstract

Dynamic transcriptomic remodeling of epithelial cells represents a critical hallmark of lung adenocarcinoma (LUAD) progression, yet epithelial-cell progression signatures (ECPSs) linked to this process remain incompletely characterized, impeding our understanding of malignant LUAD transformation. Here, we performed a multi-resolution multi-omics study and identified two functionally opposing ECPSs: a Cancer-Promoting Signature (CPS) and a Cancer-Suppressing Signature (CSS). The CPS was progressively upregulated from normal to early- and advanced-stage lesions, while the CSS was gradually downregulated, and both were validated by multi-resolution transcriptomic data. Both the CPS and CSS demonstrated robust diagnostic value for LUAD, particularly in early-stage detection (median AUC > 0.95). In seven independent validation cohorts, the CPS and CSS served as robust prognostic risk and protective factors, respectively. Their combination could better stratify LUAD patients into distinct prognostic subgroups, with the CPS_high–CSS_low subgroup showing the worst prognosis, accompanied by high genomic instability, an immunosuppressive tumor microenvironment, and resistance to chemotherapy. Notably, the CPS and CSS exhibited broad translational value in other epithelium-derived cancers. HMGA1, a key CPS gene, showed epithelium- and advanced-stage-specific high expression, which was significantly associated with poor prognosis, genomic instability, and immune escape. Collectively, our study identifies the CPS and CSS as clinically reliable ECPSs, providing valuable biomarkers for clinical application to LUAD.

Keywords: epithelial-cell progression signature; multi-omics analysis; cancer-promoting signature; cancer-suppressing signature; lung adenocarcinoma; clinical application

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MDPI and ACS Style

Chen, X.; Lv, T.; Wu, Y.; Fan, F.; Kang, S.; Dou, R.; Zhang, W.; Li, D.; Li, R.; Ping, Y. Identifying Epithelial-Cell Progression Signatures (ECPSs) from Multi-Resolution Multi-Omics Data for Translational Clinical Applications in Lung Adenocarcinoma. Int. J. Mol. Sci. 2026, 27, 6819. https://doi.org/10.3390/ijms27156819

AMA Style

Chen X, Lv T, Wu Y, Fan F, Kang S, Dou R, Zhang W, Li D, Li R, Ping Y. Identifying Epithelial-Cell Progression Signatures (ECPSs) from Multi-Resolution Multi-Omics Data for Translational Clinical Applications in Lung Adenocarcinoma. International Journal of Molecular Sciences. 2026; 27(15):6819. https://doi.org/10.3390/ijms27156819

Chicago/Turabian Style

Chen, Xueyao, Tongxin Lv, Yang Wu, Fangfang Fan, Shaobo Kang, Renjie Dou, Wanmei Zhang, Dongxue Li, Rui Li, and Yanyan Ping. 2026. "Identifying Epithelial-Cell Progression Signatures (ECPSs) from Multi-Resolution Multi-Omics Data for Translational Clinical Applications in Lung Adenocarcinoma" International Journal of Molecular Sciences 27, no. 15: 6819. https://doi.org/10.3390/ijms27156819

APA Style

Chen, X., Lv, T., Wu, Y., Fan, F., Kang, S., Dou, R., Zhang, W., Li, D., Li, R., & Ping, Y. (2026). Identifying Epithelial-Cell Progression Signatures (ECPSs) from Multi-Resolution Multi-Omics Data for Translational Clinical Applications in Lung Adenocarcinoma. International Journal of Molecular Sciences, 27(15), 6819. https://doi.org/10.3390/ijms27156819

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Identifying Epithelial-Cell Progression Signatures (ECPSs) from Multi-Resolution Multi-Omics Data for Translational Clinical Applications in Lung Adenocarcinoma

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