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Background In recent years, ER+ and HER2- breast cancer of adjuvant therapy has made great progress, including chemotherapy and endocrine therapy. We found that the responsiveness of breast cancer treatment was related to the prognosis of patients. However, reliable prognostic signatures based on ER+ and HER2- breast cancer and drug resistance-related prognostic markers have not been well confirmed, This study in amied to establish a drug resistance-related gene signature for risk stratification in ER+ and HER2- breast cancer. Methods We used the data from The Cancer Genoma Atlas (TCGA) breast cancer dataset and gene expression database (Gene Expression Omnibus, GEO), constructed a risk profile based on four drug resistance-related genes, and developed a nomogram to predict the survival of patients with I-III ER+ and HER2- breast cancer. At the same time, we analyzed the relationship between immune infiltration and the expression of these four genes or risk groups. Results Four drug resistance genes (AMIGO2, LGALS3BP, SCUBE2 and WLS) were found to be promising tools for ER+ and HER2- breast cancer risk stratification. Then, the nomogram, which combines genetic characteristics with known risk factors, produced better performance and net benefits in calibration and decision curve analysis. Similar results were validated in three separate GEO cohorts. All of these results showed that the model can be used as a prognostic classifier for clinical decision-making, individual prediction and treatment, as well as follow-up.

Upon interactions with its specific ligand hepatocyte growth factor (HGF), the c-Met signal is relayed to series of downstream pathways, exerting essential biological roles. Dysregulation of the HGF-c-Met signaling pathway has been implicated in the onset, progression and metastasis of various cancers, making the HGF-c-Met axis a promising therapeutic target. Both c-Met and HGF undergo glycosylation, which appears to be biologically relevant to their function and structural integrity. Different types of glycoconjugates in the local cellular environment can also regulate HGF/c-Met signaling by distinct mechanisms. However, detailed knowledge pertaining to the glycosylation machinery of the HGF-c-Met axis as well as its potential applications in oncology research is yet to be established. This mini review highlights the significance of the HGF-c-Met signaling pathway in physiological and pathological context, and discusses the molecular mechanisms by which affect the glycosylation of the HGF-c-Met axis. Owing to the crucial role played by glycosylation in the regulation of HGF/c-Met activity, better understanding of this less exploited field may contribute to the development of novel therapeutics targeting glycoepitopes.