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鉴定结直肠癌共识分子亚型的基因组规模代谢模型中的必需基因。

Identifying essential genes in genome-scale metabolic models of consensus molecular subtypes of colorectal cancer.

机构信息

Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan.

Department of Life Science, College of Science and Engineering, Fu Jen Catholic University, New Taipei City, Taiwan.

出版信息

PLoS One. 2023 May 19;18(5):e0286032. doi: 10.1371/journal.pone.0286032. eCollection 2023.

Abstract

Identifying essential targets in the genome-scale metabolic networks of cancer cells is a time-consuming process. The present study proposed a fuzzy hierarchical optimization framework for identifying essential genes, metabolites and reactions. On the basis of four objectives, the present study developed a framework for identifying essential targets that lead to cancer cell death and evaluating metabolic flux perturbations in normal cells that have been caused by cancer treatment. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. We applied nested hybrid differential evolution to solve the trilevel MDM problem to identify essential targets in genome-scale metabolic models for five consensus molecular subtypes (CMSs) of colorectal cancer. We used various media to identify essential targets for each CMS and discovered that most targets affected all five CMSs and that some genes were CMS-specific. We obtained experimental data on the lethality of cancer cell lines from the DepMap database to validate the identified essential genes. The results reveal that most of the identified essential genes were compatible with the colorectal cancer cell lines obtained from DepMap and that these genes, with the exception of EBP, LSS, and SLC7A6, could generate a high level of cell death when knocked out. The identified essential genes were mostly involved in cholesterol biosynthesis, nucleotide metabolisms, and the glycerophospholipid biosynthetic pathway. The genes involved in the cholesterol biosynthetic pathway were also revealed to be determinable, if a cholesterol uptake reaction was not induced when the cells were in the culture medium. However, the genes involved in the cholesterol biosynthetic pathway became non-essential if such a reaction was induced. Furthermore, the essential gene CRLS1 was revealed as a medium-independent target for all CMSs.

摘要

确定癌细胞基因组规模代谢网络中的关键靶标是一个耗时的过程。本研究提出了一种模糊层次优化框架,用于识别关键基因、代谢物和反应。基于四个目标,本研究开发了一个框架,用于识别导致癌细胞死亡的关键目标,并评估癌症治疗引起的正常细胞代谢通量的扰动。通过模糊集理论,将多目标优化问题转化为三层最大化决策(MDM)问题。我们应用嵌套混合差分进化来解决三层 MDM 问题,以识别五种结直肠癌共识分子亚型(CMS)的基因组规模代谢模型中的关键目标。我们使用不同的培养基来识别每个 CMS 的关键目标,并发现大多数目标都影响了所有五个 CMS,有些基因是 CMS 特异性的。我们从 DepMap 数据库中获得了关于癌细胞系致死性的实验数据,以验证鉴定的关键基因。结果表明,鉴定的关键基因与从 DepMap 获得的结直肠癌细胞系大多相容,除了 EBP、LSS 和 SLC7A6 之外,这些基因在敲除时可以产生高水平的细胞死亡。鉴定的关键基因主要涉及胆固醇生物合成、核苷酸代谢和甘油磷脂生物合成途径。还发现,如果细胞在培养基中没有诱导胆固醇摄取反应,参与胆固醇生物合成途径的基因是可确定的。然而,如果诱导了这种反应,参与胆固醇生物合成途径的基因就变得非关键。此外,关键基因 CRLS1 被揭示为所有 CMS 的一种与培养基无关的靶标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43da/10198572/00c1d5f82403/pone.0286032.g001.jpg

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