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基于网络医学的方法识别2型糖尿病、骨关节炎和三阴性乳腺癌相互作用组:寻找中心基因的核心

Network medicine based approach for identifying the type 2 diabetes, osteoarthritis and triple negative breast cancer interactome: Finding the hub of hub genes.

作者信息

Durrani Ilhaam Ayaz, John Peter, Bhatti Attya, Khan Jahangir Sarwar

机构信息

Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, 44000, Pakistan.

Rawalpindi Medical University, Rawalpindi, Pakistan.

出版信息

Heliyon. 2024 Aug 22;10(17):e36650. doi: 10.1016/j.heliyon.2024.e36650. eCollection 2024 Sep 15.

DOI:10.1016/j.heliyon.2024.e36650
PMID:39281650
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11401126/
Abstract

The increasing prevalence of multi-morbidities, particularly the incidence of breast cancer in diabetic/osteoarthritic patients emphasize on the need for exploring the underlying molecular mechanisms resulting in carcinogenesis. To address this, present study employed a systems biology approach to identify switch genes pivotal to the crosstalk between diseased states resulting in multi-morbid conditions. Hub genes previously reported for type 2 diabetes mellitus (T2DM), osteoarthritis (OA), and triple negative breast cancer (TNBC), were extracted from published literature and fed into an integrated bioinformatics analyses pipeline. Thirty-one hub genes common to all three diseases were identified. Functional enrichment analyses showed these were mainly enriched for immune and metabolism associated terms including advanced glycation end products (AGE) pathways, cancer pathways, particularly breast neoplasm, immune system signalling and adipose tissue. The T2DM-OA-TNBC interactome was subjected to protein-protein interaction network analyses to identify meta hub/clustered genes. These were prioritized and wired into a three disease signalling map presenting the enriched molecular crosstalk on T2DM-OA-TNBC axes to gain insight into the molecular mechanisms underlying disease-disease interactions. Deciphering the molecular bases for the intertwined metabolic and immune states may potentiate the discovery of biomarkers critical for identifying and targeting the immuno-metabolic origin of disease.

摘要

多种疾病并存的情况日益普遍,尤其是糖尿病/骨关节炎患者中乳腺癌的发病率,这凸显了探索导致癌症发生的潜在分子机制的必要性。为了解决这一问题,本研究采用系统生物学方法来确定对导致多种疾病状态的疾病间相互作用起关键作用的开关基因。先前报道的2型糖尿病(T2DM)、骨关节炎(OA)和三阴性乳腺癌(TNBC)的枢纽基因,从已发表的文献中提取并输入到一个综合生物信息学分析流程中。确定了这三种疾病共有的31个枢纽基因。功能富集分析表明,这些基因主要富集于与免疫和代谢相关的术语,包括晚期糖基化终产物(AGE)途径、癌症途径,特别是乳腺肿瘤、免疫系统信号传导和脂肪组织。对T2DM-OA-TNBC相互作用组进行蛋白质-蛋白质相互作用网络分析,以确定元枢纽/聚类基因。对这些基因进行优先级排序,并将其连接到一个三疾病信号图谱中,该图谱展示了T2DM-OA-TNBC轴上富集的分子相互作用,以深入了解疾病-疾病相互作用背后的分子机制。解读相互交织的代谢和免疫状态的分子基础,可能有助于发现对识别和靶向疾病的免疫代谢起源至关重要的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/af5bc9404ad8/gr11.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/af5bc9404ad8/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/117dd3991c37/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/971572337689/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/cf76461f2075/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/66dc6959c7d2/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/7daaef3f2ffa/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/8e52f64dd0bd/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/dfd174e1eb16/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/172fd4d7bc0e/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/cedd9cdfd3b2/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/9f5916f9b22b/gr9.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6874/11401126/af5bc9404ad8/gr11.jpg

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