Harnessing Epigenetics for Breast Cancer Therapy: The Role of DNA Methylation, Histone Modifications, and MicroRNA.
Joanna SzczepanekMonika SkorupaJoanna Jarkiewicz-TretynCezary CybulskiAndrzej TretynPublished in: International journal of molecular sciences (2023)
Breast cancer exhibits various epigenetic abnormalities that regulate gene expression and contribute to tumor characteristics. Epigenetic alterations play a significant role in cancer development and progression, and epigenetic-targeting drugs such as DNA methyltransferase inhibitors, histone-modifying enzymes, and mRNA regulators (such as miRNA mimics and antagomiRs) can reverse these alterations. Therefore, these epigenetic-targeting drugs are promising candidates for cancer treatment. However, there is currently no effective epi-drug monotherapy for breast cancer. Combining epigenetic drugs with conventional therapies has yielded positive outcomes and may be a promising strategy for breast cancer therapy. DNA methyltransferase inhibitors, such as azacitidine, and histone deacetylase inhibitors, such as vorinostat, have been used in combination with chemotherapy to treat breast cancer. miRNA regulators, such as miRNA mimics and antagomiRs, can alter the expression of specific genes involved in cancer development. miRNA mimics, such as miR-34, have been used to inhibit tumor growth, while antagomiRs, such as anti-miR-10b, have been used to inhibit metastasis. The development of epi-drugs that target specific epigenetic changes may lead to more effective monotherapy options in the future.
Keyphrases
- dna methylation
- gene expression
- genome wide
- cancer therapy
- histone deacetylase
- papillary thyroid
- cell proliferation
- poor prognosis
- open label
- randomized controlled trial
- stem cells
- type diabetes
- childhood cancer
- acute myeloid leukemia
- drug induced
- copy number
- combination therapy
- long non coding rna
- drug delivery
- cell free
- mesenchymal stem cells
- deep learning
- long noncoding rna
- metabolic syndrome
- current status
- single molecule
- machine learning
- adipose tissue
- adverse drug