Epithelial-Mesenchymal Transition States and Metabolic Reprogramming Related Signatures Predict Prognosis and Therapeutic Responses in HER2-Positive Breast Cancer

上皮-间质转化状态和代谢重编程相关特征可预测HER2阳性乳腺癌的预后和治疗反应

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Abstract

BACKGROUND: Epithelial-mesenchymal transition (EMT) and metabolic reprogramming have been shown to regulate HER2 targeted therapy resistance and tumor metastasis. We aimed to establish an EMT-associated and metabolic-related prognostic model in HER2-positive breast cancer. METHODS: mRNA expression and clinical information for HER2-positive breast cancer are downloaded from the TCGA database. The single sample gene set enrichment analysis score was used to generate EMT subtypes and identify EMT-related metabolic pathways. A prognostic risk score was developed based on the differentially expressed genes (DEGs) of the EMT-associated metabolic pathways using least absolute shrinkage and selection operator (LASSO) Cox regression and then validated in an external cohort (GSE96058). RESULTS: The EMT enriched scores differentiated the OS in the HER2-positive breast cancer TCGA cohort (p = 0.023; HR, 0.38; 95% CI, 0.16-0.9), which was also associated with the carbohydrate, amino acid, nucleotide, and tricarboxylic acid (TCA) cycle pathways (p < 0.05). A total of 10 genes based on the DEGs between the metabolic groups were used to construct the prognosis model. Patients with low-risk metabolic scores showed longer OS compared to those with high-risk metabolic scores (p < 0.001; HR, 0.09; 95% CI, 0.03-0.31). The association between OS and the metabolism score remained significant in the multivariable Cox regression (p < 0.001; HR, 0.08; 95% CI, 0.03-0.22). Similar results were observed in the validation cohort (p = 0.002; HR, 0.34; 95% CI, 0.16-0.69). CONCLUSION: EMT and metabolic reprogramming-related features are specific prognostic and potential therapeutic biomarkers for HER2-positive breast cancer patients, which warrant further studies.

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