ArticleAmerican journal of translational research2026
A novel prognostic signature based on epithelial-mesenchymal transition-associated genes for the prognosis and immune status in breast cancer.
Article in American journal of translational research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveBreast cancer (BC) incidence continues to rise, and recurrence and metastasis remain major contributors to mortality. The epithelial-mesenchymal transition (EMT), associated with the acquisition of invasive functions by epithelial cells, also promotes resistance to anticancer therapies. Here, an EMT-based prognostic model was developed to enhance BC outcome prediction.
methodsClinical and gene expression data from the TCGA were randomly assigned to discovery and validation cohorts. Univariate Cox regression and LASSO analyses were utilized to develop a prognostic signature. The Cell-Type Identification by Estimating Relative Subsets of RNA Transcripts and ESTIMATE algorithms were applied to evaluate the tumor microenvironment (TME). Enriched immune-associated pathways were found using GSEA. SDC1 was knocked down and overexpressed in MCF-7 and MDA-MB-231 cells, and its effects on cell proliferation, apoptosis, migration, invasion and EMT key markers were evaluated by CCK-8, flow cytometry, Transwell and Western blot.
resultsTen EMT-related genes (TP63, TFPI2, ALX4, F2RL2, LEF1, PDLIM4, NDRG2, HMGB3, SDC1, and KRT17) showed significant links with overall survival. The resulting signature was used to allocate individuals into high- and low-risk groups with distinct prognoses in both cohorts. M0 macrophages, activated natural killer cells, memory-activated CD4
conclusionThis ten-gene EMT-based signature reliably predicts BC prognosis and offers valuable insight into the tumor immune microenvironment.
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