Abstract

Objectives: Heparanase (HPSE), an endoglycosidase that cleaves heparan sulfate, regulates various biological processes related to tumor progression. We explore the prognostic value of HPSE and its relationship with immunotherapy response in patients with breast cancer, to improve the effectiveness of immunotherapy and increase the survival outcomes. Methods: In the study, we explored the prognostic value of HPSE through the The Cancer Genome Atlas (TCGA) database. By using the single-sample gene set enrichment analysis (ssGSEA) method, we measured the infiltration levels of 24 immune cell types in the tumor microenvironment. Cancer Therapeutics Response Portal (CTRP) and PRISM datasets provide the area under the dose-response curve (AUC) to measure drug sensitivity. Using nomograms, we predicted overall survival ability. In vivo studies, we investigated the relationship between HPSE and immune checkpoint proteins and pro-inflammatory cytokines by immunohistochemistry of Triple-Negative Breast Cancer tumors in mice. Results: Our model demonstrated that the integrating of HPSE with the clinical stage effectively predicts patients' survival time, highlighting high HPSE expression as a prognostic risk factor for breast cancer. Then the Receiver Operating Characteristic (ROC) curve [AUC of 1 year = 0.747, AUC of 3 years = 0.731] and Decision Curve Analysis (DCA) curve illustrated the satisfactory discriminative capacity of our model, emphasizing its valuable clinical applicability. Immune-related results showed that HPSE correlates strongly with immune infiltrating cells, immune-related genes, and the anti-cancer immunity cycle. In vivo studies have demonstrated that HPSE in breast cancer is associated with increased expression of immune checkpoint proteins CD274 and cytotoxic T lymphocyte-associated protein 4 (CTLA-4) and is positively correlated with the pro-inflammatory cytokine TNF-α. Meanwhile, we analyzed the 11 types of drugs that are sensitive to the HPSE gene. Conclusion: Our results show that HPSE can serve as an effective biomarker to predict the prognosis of breast cancer patients and reflect the impact of immunotherapy.

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