Multivariate Analysis of Prognostic Factors for Breast Cancer

Background: Breast cancer patients at the same stage may show different clinical prognosis or different therapeutic effects of systemic therapy. Methods: The differentially expressed genes were identified of breast cancer from GSE42568. Through survival, ROC, random forest, GSVA and Cox regression model to identify genes that can be associated with survival time in breast cancer. The molecular mechanism was identified by enrichment and GSEA, methylation and SNV analysis. Then, the expression of a key gene was verified by TCGA dataset and RT-qPCR, Western blot, immunohistochemistry. Findings: We identified 784 genes related to the 5-year survival time of breast cancer. Through ROC curve and random forest, we screened 10 prognostic genes. Which were integrated into complex by GSVA, high expression of the complex significantly promoted the recurrence free survival of breast cancer patients. Enrichment analysis showed that key genes were related to immune and metabolic related functions. Importantly, we found methylation of MEX3A and TBC1D9, and mutations events. Finally, the expression of UGCG was verified by TCGA dataset and RT-qPCR, Western blot, immunohistochemistry in our own samples. Interpretation: The results indicate that the 10 genes may be potential biomarkers and therapeutic targets for long-term survival in breast cancer, especially UGCG. Funding Statement: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: This study was approved by the human ethics review committee of Harbin Medical University. Ten cases of breast cancer were collected from the Cancer Institute of the Harbin Medical University Cancer Hospital with the informed consent of the patients.