Bridging Anoikis and the Immune Landscape: A Novel Prognostic Framework for Endometrial Cancer Survival and Therapy Response
Yingqian Yang, Hui Rong, Xinyu Liu, Yanyun Yin, Rui SunBackground
Metastatic progression remains the primary driver of mortality in endometrial cancer (EC). Anoikis resistance is a hallmark of cancer cell survival during systemic dissemination. Despite its importance, the synergy between anoikis‐related genes (ARGs) and the tumor immune microenvironment (TIME) in EC is not fully mapped. This study sought to build a practical tool to predict patient outcomes and decode the immune barriers in EC.
Methods
Using genomic data from TCGA and GEO, we screened 167 survival‐linked ARGs. We utilized advanced computational tools to categorize patients based on their genetic signatures and mapped their unique immune architectures. A three‐gene risk model was developed and integrated with clinical factors to create a predictive nomogram. To ensure the model’s biological relevance, we performed laboratory experiments (both in cell cultures and animal models) to observe how the core gene, SPTA1 , drives tumor malignancy.
Results
We established a robust prognostic signature comprising three genes ( SPTA1 , MMP9 , and RAC3 ). This model successfully divided EC patients into high‐ and low‐risk groups with significantly different survival windows. Crucially, the signature served as a mirror for the immune state: the high‐risk group was marked by increased infiltration of follicular helper T cells and M1 macrophages, whereas the low‐risk group showed higher levels of M0 macrophages and activated mast cells. ESTIMATE score further indicated higher stromal and immune infiltration levels in the low‐risk group. The experimental validation confirmed that SPTA1 acts as an oncogene, promoting EC cell proliferation, migration, and in vivo tumor growth.
Conclusion
This study reveals that ARG expression patterns are tightly linked to both clinical outcomes and the immune microenvironment in EC patients. The identified three‐gene signature and nomogram offer a dual‐purpose tool for the clinic: accurately predicting patient survival and guiding personalized treatment. These insights provide a new roadmap for managing advanced EC.