Pathak Shivani, Singh Vipendra Kumar, Gupta Prashant Kumar, Mahapatra Arun Kumar, Giri Rajanish, Sahu Rashmi, Sharma Rohit, Garg Neha
Department of Medicinal Chemistry, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, 221005, India.
School of Biosciences and Bioengineering, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, 175075, India.
Mol Divers. 2024 Dec 21. doi: 10.1007/s11030-024-11081-7.
Prostate cancer (PC) is among the most prevalent cancers in males. It is the leading cause of death in men, in around 48 out of 185 countries. Increased androgen receptor (AR) activity is the key factor contributing to the development or progression of newly diagnosed cases of prostate cancer. Over time, numerous compounds targeting AR have been identified, presenting encouraging avenues for suppressing its hyperactivity. In our investigation, we used the GEPIA tool to study the importance of AR in the context of prostate cancer. This tool integrates the data from TCGA and GTEx in the gene expression pattern analysis and their clinical relevance. This analysis evaluates overall survival, disease-free survival, and transcripts per million (TPM) analysis of AR in PC. We performed docking and simulation for FDA-approved anticancer drugs to assess their potential interactions with the AR. We also conducted a comprehensive analysis of drugs using a quantum calculation (DFT) which provides electronic properties, chemical reactivity, and stability using the HOMO-LUMO energy gap. This study suggests that repurposed synthetic anticancer drugs could be better options for treating prostate cancer by inhibiting AR. In this work, we have shown the potential of pomalidomide, a synthetic anticancer drug, as a potential candidate for androgen-dependent PC treatment.
前列腺癌(PC)是男性中最常见的癌症之一。在185个国家中,约有48个国家,它是男性死亡的主要原因。雄激素受体(AR)活性增加是导致新诊断前列腺癌病例发展或进展的关键因素。随着时间的推移,已经鉴定出许多靶向AR的化合物,为抑制其过度活性提供了令人鼓舞的途径。在我们的研究中,我们使用GEPIA工具来研究AR在前列腺癌背景下的重要性。该工具在基因表达模式分析及其临床相关性方面整合了来自TCGA和GTEx的数据。该分析评估了PC中AR的总生存期、无病生存期和每百万转录本(TPM)分析。我们对FDA批准的抗癌药物进行了对接和模拟,以评估它们与AR的潜在相互作用。我们还使用量子计算(DFT)对药物进行了全面分析,该计算使用HOMO-LUMO能隙提供电子性质、化学反应性和稳定性。这项研究表明,重新利用的合成抗癌药物可能是通过抑制AR治疗前列腺癌的更好选择。在这项工作中,我们已经展示了泊马度胺,一种合成抗癌药物,作为雄激素依赖性PC治疗潜在候选药物的潜力。