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一种系统生物学方法来理解高级别浆液性卵巢癌的病理生理学:关注铁和脂肪酸代谢。

A Systems Biology Approach to Understanding the Pathophysiology of High-Grade Serous Ovarian Cancer: Focus on Iron and Fatty Acid Metabolism.

机构信息

1 Center for Quantitative Medicine, UConn Health , Farmington, Connecticut.

2 Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center , Buffalo, New York.

出版信息

OMICS. 2018 Jul;22(7):502-513. doi: 10.1089/omi.2018.0060.

Abstract

Ovarian cancer (OVC) is the most lethal of the gynecological malignancies, with diagnosis often occurring during advanced stages of the disease. Moreover, a majority of cases become refractory to chemotherapeutic approaches. Therefore, it is important to improve our understanding of the molecular dependencies underlying the disease to identify novel diagnostic and precision therapeutics for OVC. Cancer cells are known to sequester iron, which can potentiate cancer progression through mechanisms that have not yet been completely elucidated. We developed an algorithm to identify novel links between iron and pathways implicated in high-grade serous ovarian cancer (HGSOC), the most common and deadliest subtype of OVC, using microarray gene expression data from both clinical sources and an experimental model. Using our approach, we identified several links between fatty acid (FA) and iron metabolism, and subsequently developed a network for iron involvement in FA metabolism in HGSOC. FA import and synthesis pathways are upregulated in HGSOC and other cancers, but a link between these processes and iron-related genes has not yet been identified. We used the network to derive hypotheses of specific mechanisms by which iron and iron-related genes impact and interact with FA metabolic pathways to promote tumorigenesis. These results suggest a novel mechanism by which iron sequestration by cancer cells can potentiate cancer progression, and may provide novel targets for use in diagnosis and/or treatment of HGSOC.

摘要

卵巢癌(OVC)是妇科恶性肿瘤中最致命的一种,通常在疾病的晚期才被诊断出来。此外,大多数病例对化疗方法产生耐药性。因此,提高我们对疾病潜在分子依赖性的认识,以确定用于 OVC 的新型诊断和精准治疗方法非常重要。众所周知,癌细胞会隔离铁,这可能通过尚未完全阐明的机制促进癌症进展。我们使用来自临床来源和实验模型的微阵列基因表达数据开发了一种算法,以识别铁与高级别浆液性卵巢癌(HGSOC)相关途径之间的新联系,HGSOC 是 OVC 中最常见和最致命的亚型。通过我们的方法,我们确定了脂肪酸(FA)和铁代谢之间的几个联系,随后开发了一个 HGSOC 中铁参与 FA 代谢的网络。FA 摄取和合成途径在 HGSOC 和其他癌症中上调,但这些过程与铁相关基因之间的联系尚未确定。我们使用该网络得出假设,即铁和铁相关基因如何影响和相互作用 FA 代谢途径以促进肿瘤发生的具体机制。这些结果表明了癌细胞隔离铁的一种新机制,这可能为 HGSOC 的诊断和/或治疗提供新的靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbb6/6059353/56e0e34d0ec2/fig-1.jpg

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