Identifying Key Lysosome-Related Genes Associated with Drug-Resistant Breast Cancer Using Computational and Systems Biology Approach.

IF 1.8 4区 医学 Q3 PHARMACOLOGY & PHARMACY Iranian Journal of Pharmaceutical Research Pub Date : 2022-12-01 DOI:10.5812/ijpr-130342
Aref Shiralipour, Babak Khorsand, Leila Jafari, Mohammad Salehi, Mahsa Kazemi, Javad Zahiri, Vahid Jajarmi, Bahram Kazemi
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引用次数: 1

Abstract

Background: Drug resistance in breast cancer is an unsolved problem in treating patients. It has been recently discussed that lysosomes contribute to the invasion and angiogenesis of cancer cells. There is evidence that lysosomes can also cause multi-drug resistance. We analyzed this emerging concept in breast cancer through computational and systems biology approaches.

Objectives: We aimed to identify the key lysosome-related genes associated with drug-resistant breast cancer.

Methods: All genes contributing to the structure and function of lysosomes were inquired through the Human Lysosome Gene Database. The prioritized top 51 genes from the provided lists of Endeavour, ToppGene, and GPSy as prioritization tools were selected. All lysosomal genes and 12 breast cancer-related genes aligned to identify the most similar genes to breast cancer-related genes. Different centralities were applied to score each human protein to calculate the most central lysosomal genes in the human protein-protein interaction (PPI) network. Common genes were extracted from the results of the mentioned methods as a selected gene set. For Gene Ontology enrichment, the selected gene set was analyzed by WebGestalt, DAVID, and KOBAS. The PPI network was constructed via the STRING database. The PPI network was analyzed utilizing Cytoscape for topology network interaction and CytoHubba to extract hub genes.

Results: Based on biological studies, literature reviews, and comparing all mentioned analyzing methods, six genes were introduced as essential in breast cancer. This computational approach to all lysosome-related genes suggested that candidate genes include PRF1, TLR9, CLTC, GJA1, AP3B1, and RPTOR. The analyses of these six genes suggest that they may have a crucial role in breast cancer development, which has rarely been evaluated. These genes have a potential therapeutic implication for new drug discovery for chemo-resistant breast cancer.

Conclusions: The present work focused on all the functional and structural lysosome-related genes associated with breast cancer. It revealed the top six lysosome hub genes that might serve as therapeutic targets in drug-resistant breast cancer. Since these genes play a pivotal role in the structure and function of lysosomes, targeting them can effectively overcome drug resistance.

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利用计算和系统生物学方法鉴定与耐药乳腺癌相关的关键溶酶体相关基因。
背景:乳腺癌耐药是目前治疗中尚未解决的问题。近年来人们讨论溶酶体参与癌细胞的侵袭和血管生成。有证据表明,溶酶体也可引起多重耐药。我们通过计算和系统生物学方法分析了乳腺癌中这一新兴概念。目的:我们旨在鉴定与耐药乳腺癌相关的关键溶酶体相关基因。方法:通过人类溶酶体基因数据库查询所有与溶酶体结构和功能有关的基因。从Endeavour、ToppGene和GPSy提供的列表中选择优先排序的前51个基因作为优先排序工具。所有溶酶体基因和12个乳腺癌相关基因进行比对,以确定与乳腺癌相关基因最相似的基因。应用不同的中心性对每个人类蛋白质进行评分,以计算人类蛋白质-蛋白质相互作用(PPI)网络中最中心的溶酶体基因。从上述方法的结果中提取常见基因作为选定的基因集。对于基因本体的富集,选择的基因集通过WebGestalt、DAVID和KOBAS进行分析。通过STRING数据库构建PPI网络。利用Cytoscape进行拓扑网络相互作用分析,利用CytoHubba提取中心基因。结果:通过生物学研究、文献回顾和对所有分析方法的比较,介绍了6个在乳腺癌中必不可少的基因。这种对所有溶酶体相关基因的计算方法表明,候选基因包括PRF1、TLR9、CLTC、GJA1、AP3B1和RPTOR。对这六个基因的分析表明,它们可能在乳腺癌的发展中起着至关重要的作用,而这一点很少得到评估。这些基因对发现治疗耐药乳腺癌的新药具有潜在的治疗意义。结论:目前研究的重点是与乳腺癌相关的所有功能和结构溶酶体相关基因。它揭示了可能作为耐药乳腺癌治疗靶点的前六个溶酶体中心基因。由于这些基因在溶酶体的结构和功能中起着关键作用,靶向它们可以有效地克服耐药性。
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来源期刊
CiteScore
3.40
自引率
6.20%
发文量
52
审稿时长
2 months
期刊介绍: The Iranian Journal of Pharmaceutical Research (IJPR) is a peer-reviewed multi-disciplinary pharmaceutical publication, scheduled to appear quarterly and serve as a means for scientific information exchange in the international pharmaceutical forum. Specific scientific topics of interest to the journal include, but are not limited to: pharmaceutics, industrial pharmacy, pharmacognosy, toxicology, medicinal chemistry, novel analytical methods for drug characterization, computational and modeling approaches to drug design, bio-medical experience, clinical investigation, rational drug prescribing, pharmacoeconomics, biotechnology, nanotechnology, biopharmaceutics and physical pharmacy.
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