![Sample our Bioscience journals, sign in here to start your access, Latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5925/TOC-Subject-Sample-2021-Bioscience.jpg"})
Abstract
Histone deacetylases (HDACs) have emerged as important targets for cancer treatment. HDAC-inhibitors (HDACis) are well tolerated in patients and have been approved for the treatment of patients with cutaneous T-cell lymphoma (CTCL). To improve the clinical benefit of HDACis in solid tumors, combination strategies with HDACis could be employed. In this study, we applied Analysis of Functional Annotation (AFA) to provide a comprehensive list of genes and pathways affected upon HDACi-treatment in prostate cancer cells. This approach provides an unbiased and objective approach to high throughput data mining. By performing AFA on gene expression data from prostate cancer cell lines DU-145 (an HDACi-sensitive cell line) and PC3 (a relatively HDACi-resistant cell line) treated with HDACis valproic acid or vorinostat, we identified biological processes that are affected by HDACis and are therefore potential treatment targets for combination therapy. Our analysis revealed that HDAC-inhibition resulted among others in upregulation of major histocompatibility complex (MHC) genes and deregulation of the mitotic spindle checkpoint by downregulation of genes involved in mitosis. These findings were confirmed by AFA on publicly available data sets from HDACi-treated prostate cancer cells. In total, we analyzed 375 microarrays with HDACi treated and non-treated (control) prostate cancer cells. All results from this extensive analysis are provided as an online research source (available at the journal’s website and at http://luigimarchionni.org/HDACIs.html). By publishing this data, we aim to enhance our understanding of the cellular changes after HDAC-inhibition, and to identify novel potential combination strategies with HDACis for the treatment of prostate cancer patients.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Acknowledgments
The authors would like to thank Marianna Zahurak for her contribution to the statistical analysis for this project and René Medema for his support and discussion. This study was supported by the Prostate Cancer Foundation, the Flight Attendant Medical Research Institute (SK), NIH (National Institute of Health) - NCI (National Cancer Institute) SPORE (Specialized Programs of Research Excellence) in Prostate Cancer P50CA058236 (MAC), by NIH-NCI 5P30CA006973 (MAC, LM, SK), and Aegon International Research Fellowship in Oncology (MAC, SK). MSQK was also partially supported by a fellowship from the Catharina van Tussebroek Fund. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Supplemental Materials
Supplemental materials may be found here: http://www.landesbioscience.com/journals/epigenetics/article/25574