Development of a Novel Prognostic Model for Esophageal Squamous Cell Carcinoma: Insights into Immune Cell Interactions and Drug Sensitivity

Abstract

Esophageal squamous cell carcinoma (ESCC) presents a five-year survival rate below 20%, underscoring the need for improved prognostic markers. Our study analyzed ESCC-specific datasets to identify consistently differentially expressed genes. A Venn analysis followed by gene network interactions revealed 23 key genes, from which we built a prognostic model using the COX algorithm (p = 0.000245, 3-year AUC = 0.967). This model stratifies patients into risk groups, with high-risk individuals showing worse outcomes and lower chemotherapy sensitivity. Moreover, a link between risk scores and M2 macrophage infiltration, as well as significant correlations with immune checkpoint genes (e.g., SIGLEC15, PDCD1LG2, and HVCR2), was discovered. High-risk patients had lower Tumor Immune Dysfunction and Exclusion (TIDE) values, suggesting potential responsiveness to immune checkpoint blockade (ICB) therapy. Our efficient 23-gene prognostic model for ESCC indicates a dual utility in assessing prognosis and guiding therapeutic decisions, particularly in the context of ICB therapy for high-risk patients.

Keywords:

• Esophageal squamous cell carcinoma
• gene signature
• prognosis
• immunotherapy

Declaration of interest

No potential conflict of interest was reported by the author(s).

Data availability

The datasets used and/or analyzed during this study available from the corresponding author on reasonable request.

Additional information

Funding

This work was supported in part by grants from the Technology Commission Foundation of Shanxi Province (Grant No. 20210302124292, 20210302124296), Changzhi Medical College doctoral research fund (Grant No. 521300), Four “Batches” Innovation Project of Invigorating Medical through Science and Technology of Shanxi Province (2020SYS22), and Key Laboratory of Changzhi Medical College (ZDS202105).