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三阴性乳腺癌精准医学实施中的药物重新定位与亚组发现

Drug Repositioning and Subgroup Discovery for Precision Medicine Implementation in Triple Negative Breast Cancer.

作者信息

Al-Taie Zainab, Hannink Mark, Mitchem Jonathan, Papageorgiou Christos, Shyu Chi-Ren

机构信息

Institute for Data Science & Informatics, University of Missouri, Columbia, MO 65211, USA.

Department of Computer Science, College of Science for Women, University of Baghdad, Baghdad 10070, Iraq.

出版信息

Cancers (Basel). 2021 Dec 14;13(24):6278. doi: 10.3390/cancers13246278.

DOI:10.3390/cancers13246278
PMID:34944904
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8699385/
Abstract

Breast cancer (BC) is the leading cause of death among female patients with cancer. Patients with triple-negative breast cancer (TNBC) have the lowest survival rate. TNBC has substantial heterogeneity within the BC population. This study utilized our novel patient stratification and drug repositioning method to find subgroups of BC patients that share common genetic profiles and that may respond similarly to the recommended drugs. After further examination of the discovered patient subgroups, we identified five homogeneous druggable TNBC subgroups. A drug repositioning algorithm was then applied to find the drugs with a high potential for each subgroup. Most of the top drugs for these subgroups were chemotherapy used for various types of cancer, including BC. After analyzing the biological mechanisms targeted by these drugs, ferroptosis was the common cell death mechanism induced by the top drugs in the subgroups with neoplasm subdivision and race as clinical variables. In contrast, the antioxidative effect on cancer cells was the common targeted mechanism in the subgroup of patients with an age less than 50. Literature reviews were used to validate our findings, which could provide invaluable insights to streamline the drug repositioning process and could be further studied in a wet lab setting and in clinical trials.

摘要

乳腺癌(BC)是女性癌症患者死亡的主要原因。三阴性乳腺癌(TNBC)患者的生存率最低。TNBC在BC群体中具有显著的异质性。本研究利用我们新颖的患者分层和药物重新定位方法,来寻找具有共同基因谱且可能对推荐药物有相似反应的BC患者亚组。在对发现的患者亚组进行进一步检查后,我们确定了五个同质的可靶向治疗的TNBC亚组。然后应用药物重新定位算法来寻找每个亚组中具有高潜力的药物。这些亚组的大多数顶级药物都是用于包括BC在内的各种癌症的化疗药物。在分析这些药物所靶向的生物学机制后,铁死亡是在以肿瘤细分和种族作为临床变量的亚组中顶级药物诱导的常见细胞死亡机制。相比之下,对癌细胞的抗氧化作用是年龄小于50岁患者亚组中的常见靶向机制。文献综述用于验证我们的发现,这可为简化药物重新定位过程提供宝贵的见解,并可在湿实验室环境和临床试验中进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5016/8699385/d2b591bbe693/cancers-13-06278-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5016/8699385/d54f1acb504d/cancers-13-06278-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5016/8699385/faa1716d9ae1/cancers-13-06278-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5016/8699385/d2b591bbe693/cancers-13-06278-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5016/8699385/d54f1acb504d/cancers-13-06278-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5016/8699385/faa1716d9ae1/cancers-13-06278-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5016/8699385/d2b591bbe693/cancers-13-06278-g003.jpg

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本文引用的文献

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J Breast Imaging. 2021 Jan 26;3(1):12-24. doi: 10.1093/jbi/wbaa110.
2
Chemopreventive and Anticancer Property of Selenoproteins in Obese Breast Cancer.硒蛋白在肥胖型乳腺癌中的化学预防及抗癌特性
Front Pharmacol. 2021 Apr 16;12:618172. doi: 10.3389/fphar.2021.618172. eCollection 2021.
3
Explainable artificial intelligence in high-throughput drug repositioning for subgroup stratifications with interventionable potential.
铁死亡:重塑三阴性乳腺癌的新兴角色。
Front Immunol. 2023 Oct 20;14:1284057. doi: 10.3389/fimmu.2023.1284057. eCollection 2023.
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Informatics on Drug Repurposing for Breast Cancer.药物重用于乳腺癌的信息学研究。
Drug Des Devel Ther. 2023 Jun 28;17:1933-1943. doi: 10.2147/DDDT.S417563. eCollection 2023.
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Identification of Immuno-Targeted Combination Therapies Using Explanatory Subgroup Discovery for Cancer Patients with EGFR Wild-Type Gene.使用解释性子组发现法鉴定表皮生长因子受体(EGFR)野生型基因癌症患者的免疫靶向联合疗法
Cancers (Basel). 2022 Sep 29;14(19):4759. doi: 10.3390/cancers14194759.
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