Mugiyanto Eko, Adikusuma Wirawan, Irham Lalu Muhammad, Huang Wan-Chen, Chang Wei-Chiao, Kuo Chun-Nan
PhD Program in Clinical Drug Development of Herbal Medicine, College of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Pekajangan Pekalongan, Pekalongan, Indonesia.
Front Oncol. 2022 Dec 1;12:989077. doi: 10.3389/fonc.2022.989077. eCollection 2022.
According to the National Comprehensive Cancer Network and the American Society of Clinical Oncology, the standard treatment for pancreatic cancer (PC) is gemcitabine and fluorouracil. Other chemotherapeutic agents have been widely combined. However, drug resistance remains a huge challenge, leading to the ineffectiveness of cancer therapy. Therefore, we are trying to discover new treatments for PC by utilizing genomic information to identify PC-associated genes as well as drug target genes for drug repurposing. Genomic information from a public database, the cBio Cancer Genomics Portal, was employed to retrieve the somatic mutation genes of PC. Five functional annotations were applied to prioritize the PC risk genes: Kyoto Encyclopedia of Genes and Genomes; biological process; knockout mouse; Gene List Automatically Derived For You; and Gene Expression Omnibus Dataset. DrugBank database was utilized to extract PC drug targets. To narrow down the most promising drugs for PC, CMap Touchstone analysis was applied. Finally, ClinicalTrials.gov and a literature review were used to screen the potential drugs under clinical and preclinical investigation. Here, we extracted 895 PC-associated genes according to the cBioPortal database and prioritized them by using five functional annotations; 318 genes were assigned as biological PC risk genes. Further, 216 genes were druggable according to the DrugBank database. CMap Touchstone analysis indicated 13 candidate drugs for PC. Among those 13 drugs, 8 drugs are in the clinical trials, 2 drugs were supported by the preclinical studies, and 3 drugs are with no evidence status for PC. Importantly, we found that midostaurin (targeted PRKA) and fulvestrant (targeted ESR1) are promising candidate drugs for PC treatment based on the genomic-driven drug repurposing pipelines. In short, integrated analysis using a genomic information database demonstrated the viability for drug repurposing. We proposed two drugs (midostaurin and fulvestrant) as promising drugs for PC.
根据美国国立综合癌症网络和美国临床肿瘤学会的观点，胰腺癌（PC）的标准治疗方案是使用吉西他滨和氟尿嘧啶。其他化疗药物也已被广泛联合使用。然而，耐药性仍然是一个巨大的挑战，导致癌症治疗无效。因此，我们试图通过利用基因组信息来发现胰腺癌的新治疗方法，以识别与胰腺癌相关的基因以及用于药物再利用的药物靶基因。我们利用来自公共数据库cBio癌症基因组学门户的基因组信息来检索胰腺癌的体细胞突变基因。应用了五种功能注释来对胰腺癌风险基因进行优先级排序：京都基因与基因组百科全书；生物过程；基因敲除小鼠；自动为您生成的基因列表；以及基因表达综合数据集。利用药物银行数据库提取胰腺癌药物靶点。为了缩小最有前景的胰腺癌药物范围，应用了CMap基准分析。最后，使用ClinicalTrials.gov和文献综述来筛选处于临床和临床前研究阶段的潜在药物。在此，我们根据cBioPortal数据库提取了895个与胰腺癌相关的基因，并使用五种功能注释对它们进行了优先级排序；318个基因被指定为生物学上的胰腺癌风险基因。此外，根据药物银行数据库，有216个基因是可成药的。CMap基准分析表明有13种胰腺癌候选药物。在这13种药物中，有8种药物正在进行临床试验，2种药物得到了临床前研究的支持，3种药物在胰腺癌方面没有证据支持。重要的是，我们发现米哚妥林（靶向PRKA）和氟维司群（靶向ESR1）基于基因组驱动的药物再利用流程是有前景的胰腺癌治疗候选药物。简而言之，使用基因组信息数据库的综合分析证明了药物再利用的可行性。我们提出两种药物（米哚妥林和氟维司群）作为有前景的胰腺癌药物。
