Work

Selection of tumor invasion-related genes to build a prognostic model and predict immune response and potential drugs for esophageal cancer patients based on WGCNA

Year: 2025

Type: article

Abstract: Esophageal cancer (EC) has a high incidence and is highly invasive. It is meaningful to employ invasion-related genes (IRGs) to predict patients’ prognosis. We launched a weighted correlation network analysis to screen for EC tumor differentially expressed IRGs (module genes) from the TCGA-ESCA dataset. By executing univariate-LASSO-multivariate Cox regression analyses, we stepwise selected module genes to obtain prognostic feature genes and create a model. We validated the model using the external GEO dataset GSE53624. We assessed the model’s independent prognosis prediction ability. A nomogram was plotted and further validated later. GSEA was undertaken on high-risk groups (Group H). We compared immunity and tumor mutations in Group H and the low-risk group (Group L) and made small molecular drug predictions on prognostic genes. A risk prognostic model consisting of 10 genes (ARMCX2, RGS16, APLN, TRIM28, AKAP4, ZC3H12B, MAD1L1, TWIST1, TMTC2, and TADA2B) was created. ZC3H12B was significantly linked with TADA 2B, AKAP4, and TWIST1 ( P < 0.01). The model exhibited a good predictive performance, functioning as an independent prognostic factor. The predictive accuracy of the nomogram was relatively high. Pathways that were significantly enriched in Group H included base excision repair, cysteine and methionine metabolism, and porphyrin and chlorophyll metabolism ( P < 0.05). Compared with Group L, Group H had higher expression of relevant immune genes and a higher degree of tumor mutation ( P < 0.05). ZC3H12B was significantly linked with immune cells (macrophages and iDCs), showing a high degree of mutation. The IC 50 values of Lomustine, Dexrazoxane, Batracylin, and Buthioninesulphoximine were significantly positively linked with the expression of ZC3H12B ( P < 0.01). The 10-gene prognostic model can independently predict patients’ prognosis. The great correlation between ZC3H12B and multiple feature genes and immune cells may be tightly linked to EC progression.

Source: Discover Oncology

DOI: 10.1007/s12672-025-03095-w

Authors: Xueqiong Deng, Yiming Liu

Institutions: Fujian Medical University, First Affiliated Hospital of Fujian Medical University

Language: English

Topic: Esophageal Cancer Research and Treatment

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,690