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Integrative Proteomic and Pharmacological Analysis of Colon Cancer Reveals the Classical Lipogenic Pathway with Prognostic and Therapeutic Opportunities

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NIAID Data Ecosystem2026-03-14 收录
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https://figshare.com/articles/dataset/Integrative_Proteomic_and_Pharmacological_Analysis_of_Colon_Cancer_Reveals_the_Classical_Lipogenic_Pathway_with_Prognostic_and_Therapeutic_Opportunities/22001977
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Despite recent advancements, the high mortality rate remains a concern in colon cancer (CAC). Identification of therapeutic markers could prove to be a great asset in CAC management. Multiple studies have reported hyperactivation of de novo lipogenesis (DNL), but its association with the pathology is unclear. This study aims to establish the importance as well as the prognostic and therapeutic potential of DNL in CAC. The key lipogenic enzymes fatty acid synthase along with ATP citrate lyase were quantified using an LC–MS/MS-based targeted proteomics approach in the samples along with the matched controls. The potential capacity of the proteins to distinguish between the tumor and controls was demonstrated using random forest-based class prediction analysis using the peptide intensities. Furthermore, in-depth proteomics of DNL inhibition in the CAC cell line revealed the significance of the pathway in proliferation and metastasis. DNL inhibition affected the major signaling pathways, including DNA repair, PI3K–AKT–mTOR pathway, membrane trafficking, proteasome, etc. The study revealed the upregulation of 26S proteasome machinery as a result of the treatment with subsequent induction of apoptosis. Again, in silico molecular docking-based drug repurposing was performed to find potential drug candidates. Furthermore, we have demonstrated that blocking DNL could be explored as a therapeutic option in CAC treatment.

尽管近期已取得诸多研究进展,但结肠癌(colon cancer, CAC)的高死亡率仍是临床关注的核心问题。鉴定治疗性标志物可为结肠癌的临床管理提供重要助力。已有多项研究报道了从头脂肪生成(de novo lipogenesis, DNL)的过度激活,但其与疾病病理进程的关联尚不明确。 本研究旨在明确从头脂肪生成在结肠癌中的重要价值,以及其预后评估与治疗应用潜力。研究采用基于液相色谱-串联质谱(liquid chromatography-tandem mass spectrometry, LC–MS/MS)的靶向蛋白质组学方法,对样本及其匹配对照中的关键脂肪生成酶——脂肪酸合酶(fatty acid synthase)与ATP柠檬酸裂解酶(ATP citrate lyase)进行定量检测。借助基于肽段强度的随机森林(random forest)分类预测分析,证实了上述蛋白质可有效区分肿瘤组织与对照样本。 此外,针对结肠癌细胞系中从头脂肪生成抑制的深度蛋白质组学分析,揭示了该通路在细胞增殖与转移过程中的关键意义。从头脂肪生成抑制会干扰多条核心信号通路,包括DNA修复、PI3K–AKT–mTOR通路、膜运输、蛋白酶体等。研究发现,经该治疗干预后,26S蛋白酶体系统表达上调,进而诱导细胞凋亡。 本研究还通过基于计算机模拟的分子对接(in silico molecular docking)技术开展药物重定位(drug repurposing)研究,以筛选潜在的候选治疗药物。此外,我们证实阻断从头脂肪生成可作为结肠癌治疗的潜在可行策略。
创建时间:
2023-02-02
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