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利用超级计算机探索去势敏感性前列腺癌的潜在治疗组合:概念验证研究。

Exploring potential therapeutic combinations for castration-sensitive prostate cancer using supercomputers: a proof of concept study.

机构信息

Centre for Informatics and Computing, Rudjer Boskovic Institute, 10000, Zagreb, Croatia.

Department of Oncology and Nuclear Medicine, Sisters of Charity Hospital, 10000, Zagreb, Croatia.

出版信息

Sci Rep. 2024 Aug 13;14(1):18824. doi: 10.1038/s41598-024-69880-9.

DOI:10.1038/s41598-024-69880-9
PMID:39138333
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11322545/
Abstract

To address the challenge of finding new combination therapies against castration-sensitive prostate cancer, we introduce Vini, a computational tool that predicts the efficacy of drug combinations at the intracellular level by integrating data from the KEGG, DrugBank, Pubchem, Protein Data Bank, Uniprot, NCI-60 and COSMIC databases. Vini is a computational tool that predicts the efficacy of drugs and their combinations at the intracellular level. It addresses the problem comprehensively by considering all known target genes, proteins and small molecules and their mutual interactions involved in the onset and development of cancer. The results obtained point to new, previously unexplored combination therapies that could theoretically be promising candidates for the treatment of castration-sensitive prostate cancer and could prevent the inevitable progression of the cancer to the incurable castration-resistant stage. Furthermore, after analyzing the obtained triple combinations of drugs and their targets, the most common targets became clear: ALK, BCL-2, mTOR, DNA and androgen axis. These results may help to define future therapies against castration-sensitive prostate cancer. The use of the Vini computer model to explore therapeutic combinations represents an innovative approach in the search for effective treatments for castration-sensitive prostate cancer, which, if clinically validated, could potentially lead to new breakthrough therapies.

摘要

为了解决寻找针对去势敏感型前列腺癌的新联合治疗方法的挑战,我们引入了 Vini,这是一种计算工具,通过整合来自 KEGG、DrugBank、Pubchem、Protein Data Bank、Uniprot、NCI-60 和 COSMIC 数据库的数据,预测药物组合在细胞内水平的疗效。Vini 是一种计算工具,可预测药物及其组合在细胞内水平的疗效。它通过考虑所有已知的靶基因、蛋白质和小分子及其在癌症发生和发展中相互作用,全面解决了这个问题。所得结果指向新的、以前未探索过的联合治疗方法,这些方法理论上可能是治疗去势敏感型前列腺癌的有前途的候选药物,并可防止癌症不可避免地发展为无法治愈的去势抵抗阶段。此外,在分析了获得的三种药物组合及其靶点后,最常见的靶点变得清晰起来:ALK、BCL-2、mTOR、DNA 和雄激素轴。这些结果可能有助于确定针对去势敏感型前列腺癌的未来治疗方法。使用 Vini 计算机模型探索治疗组合代表了寻找针对去势敏感型前列腺癌的有效治疗方法的创新方法,如果在临床上得到验证,可能会带来新的突破性治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/bbedc12b54ea/41598_2024_69880_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/d01734d35157/41598_2024_69880_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/df0937c0bec0/41598_2024_69880_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/c8b6103067d2/41598_2024_69880_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/2d4ef9fc2262/41598_2024_69880_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/8aa941ab4bfa/41598_2024_69880_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/bbedc12b54ea/41598_2024_69880_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/d01734d35157/41598_2024_69880_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/df0937c0bec0/41598_2024_69880_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/c8b6103067d2/41598_2024_69880_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/2d4ef9fc2262/41598_2024_69880_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/8aa941ab4bfa/41598_2024_69880_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be0/11322545/bbedc12b54ea/41598_2024_69880_Fig6_HTML.jpg

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