RNA测序技术被提出作为一种有价值的技术，可基于患者肿瘤特异性突变谱来开发个体化治疗方案。在这里，我们旨在基于个体化治疗的药物再利用方法，针对35例癌症患者的错义突变，鉴定药物和抑制剂。这些错义突变属于9个类别（ABC转运蛋白、细胞凋亡、血管新生、细胞周期、DNA损伤、激酶、蛋白酶、转录因子、肿瘤抑制因子）。转录因子基因中错义突变的百分比最高。所有35个肿瘤的突变谱都经过分层热图聚类。所有7个白血病活检样本聚集在一起，与实体瘤分开。基于这些个体的突变谱，我们应用了两种策略来鉴定可能的药物候选品：首先，根据携带特定错义突变的蛋白质结构进行虚拟筛选FDA批准药物。其次，我们挖掘了药物基因相互作用（DGI）数据库（https://www.dgidb.org/），以识别针对我们35个肿瘤数据集中错义突变蛋白的批准或实验性抑制剂。总之，我们基于虚拟药物筛选和DGI基于选择抑制剂的方法，可能为对标准化疗法不再有反应的顽固性肿瘤患者提供新的个体化治疗选择。版权所有 © 2023 Elsevier Ltd. 保留所有权利。

RNA-sequencing has been proposed as a valuable technique to develop individualized therapy concepts for cancer patients based on their tumor-specific mutational profiles. Here, we aimed to identify drugs and inhibitors in an individualized therapy-based drug repurposing approach focusing on missense mutations for 35 biopsies of cancer patients. The missense mutations belonged to 9 categories (ABC transporter, apoptosis, angiogenesis, cell cycle, DNA damage, kinase, protease, transcription factor, tumor suppressor). The highest percentages of missense mutations were observed in transcription factor genes. The mutational profiles of all 35 tumors were subjected to hierarchical heatmap clustering. All 7 leukemia biopsies clustered together and were separated from solid tumors. Based on these individual mutation profiles, two strategies for the identification of possible drug candidates were applied: Firstly, virtual screening of FDA-approved drugs based on the protein structures carrying particular missense mutations. Secondly, we mined the Drug Gene Interaction (DGI) database (https://www.dgidb.org/) to identify approved or experimental inhibitors for missense mutated proteins in our dataset of 35 tumors. In conclusion, our approach based on virtual drug screening of FDA-approved drugs and DGI-based inhibitor selection may provide new, individual treatment options for patients with otherwise refractory tumors that do not respond anymore to standard chemotherapy.Copyright © 2023. Published by Elsevier Ltd.