Abstract
DNA methylation is a vital epigenetic change that regulates gene transcription and helps to keep the genome stable. The deregulation hallmark of human cancer is often defined by aberrant DNA methylation which is critical for tumor formation and controls the expression of several tumor-associated genes. In various cancers, methylation changes such as tumor suppressor gene hypermethylation and oncogene hypomethylation are critical in tumor occurrences, especially in breast cancer. Detecting DNA methylation-driven genes and understanding the molecular features of such genes could thus help to enhance our understanding of pathogenesis and molecular mechanisms of breast cancer, facilitating the development of precision medicine and drug discovery. In the present study, we retrospectively analyzed over one thousand breast cancer patients and established a robust prognostic signature based on DNA methylation-driven genes. Then, we calculated immune cells abundance in each patient and lower immune activity existed in high-risk patients. The expression of leukocyte antigen (HLA) family genes and immune checkpoints genes were consistent with the above results. In addition, more mutated genes were observed in the high-risk group. Furthermore, a in silico screening of druggable targets and compounds from CTRP and PRISM databases was performed, resulting in the identification of five target genes (HMMR, CCNB1, CDC25C, AURKA, and CENPE) and five agents (oligomycin A, panobinostat, (+)-JQ1, voxtalisib, and arcyriaflavin A), which might have therapeutic potential in treating high-risk breast cancer patients. Further in vitro evaluation confirmed that (+)-JQ1 had the best cancer cell selectivity and exerted its anti-breast cancer activity through CENPE. In conclusion, our study provided new insights into personalized prognostication and may inspire the integration of risk stratification and precision therapy.
Highlights
Breast cancer (BRCA) is a female malignancy with the highest incidence worldwide, accounting for up to 11.7% of all cancer cases. [1]
The GO enrichment results showed that many biological processes associated with immunity were enriched (Figure 3B and Table 2), which was consistent with the KEGG results. These results indicated that the DNA methylation-driven genes-based risk score could influence these pathways and predict the survival of breast cancer patients
These results suggested the prognostic significance of the DNA methylation-driven genes-based model in predicting the overall survival (OS) of breast cancer patients and the model was independent of other clinical features
Summary
Breast cancer (BRCA) is a female malignancy with the highest incidence worldwide, accounting for up to 11.7% of all cancer cases. [1]. Breast cancer (BRCA) is a female malignancy with the highest incidence worldwide, accounting for up to 11.7% of all cancer cases. In addition to systemic treatments including chemotherapy, endocrine therapy (hormone therapy), targeted therapy, and immunotherapy, surgical resection is the primary option for treating breast cancer. Early-staged, non-metastatic breast cancer is often curable. Under currently available therapies, a full recovery of patients from advanced breast cancer with distant organ metastases is challenging [3]. Early detection, diagnosis, and effective therapies are necessary for improving the survival of breast cancer patients. Prognosis prediction of breast cancer has been exhaustively investigated over the past decade, and future therapy strategies will be more concerned with individualization and personalized medicine [4, 5]
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