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遗传工程小鼠乳腺肿瘤的蛋白质组学分析鉴定出脂肪酸代谢成员作为顺铂耐药的潜在预测标志物。

Proteomics of genetically engineered mouse mammary tumors identifies fatty acid metabolism members as potential predictive markers for cisplatin resistance.

机构信息

OncoProteomics Laboratory, Department of Medical Oncology, VU University Medical Center, De Boelelaan 1117, 1081HV Amsterdam, The Netherlands.

出版信息

Mol Cell Proteomics. 2013 May;12(5):1319-34. doi: 10.1074/mcp.M112.024182. Epub 2013 Feb 8.

DOI:10.1074/mcp.M112.024182
PMID:23397111
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3650342/
Abstract

In contrast to various signatures that predict the prognosis of breast cancer patients, markers that predict chemotherapy response are still elusive. To detect such predictive biomarkers, we investigated early changes in protein expression using two mouse models for distinct breast cancer subtypes who have a differential knock-out status for the breast cancer 1, early onset (Brca1) gene. The proteome of cisplatin-sensitive BRCA1-deficient mammary tumors was compared with that of cisplatin-resistant mammary tumors resembling pleomorphic invasive lobular carcinoma. The analyses were performed 24 h after administration of the maximum tolerable dose of cisplatin. At this time point, drug-sensitive BRCA1-deficient tumors showed DNA damage, but cells were largely viable. By applying paired statistics and quantitative filtering, we identified highly discriminatory markers for the sensitive and resistant model. Proteins up-regulated in the sensitive model are involved in centrosome organization, chromosome condensation, homology-directed DNA repair, and nucleotide metabolism. Major discriminatory markers that were up-regulated in the resistant model were predominantly involved in fatty acid metabolism, such as fatty-acid synthase. Specific inhibition of fatty-acid synthase sensitized resistant cells to cisplatin. Our data suggest that exploring the functional link between the DNA damage response and cancer metabolism shortly after the initial treatment may be a useful strategy to predict the efficacy of cisplatin.

摘要

与预测乳腺癌患者预后的各种特征不同,预测化疗反应的标志物仍然难以捉摸。为了检测这种预测性生物标志物,我们使用两种具有不同乳腺癌 1 早期发病(Brca1)基因敲除状态的小鼠模型,研究了蛋白表达的早期变化。将顺铂敏感的 BRCA1 缺陷型乳腺肿瘤的蛋白质组与类似于多形性浸润性小叶癌的顺铂耐药乳腺肿瘤的蛋白质组进行了比较。分析在给予最大耐受剂量顺铂后 24 小时进行。此时,药物敏感的 BRCA1 缺陷型肿瘤显示出 DNA 损伤,但细胞仍具有很大的活力。通过应用配对统计和定量过滤,我们为敏感和耐药模型确定了高度有区别的标志物。在敏感模型中上调的蛋白参与中心体组织、染色体浓缩、同源定向 DNA 修复和核苷酸代谢。在耐药模型中上调的主要区别性标志物主要涉及脂肪酸代谢,如脂肪酸合酶。脂肪酸合酶的特异性抑制使耐药细胞对顺铂敏感。我们的数据表明,在初始治疗后不久探索 DNA 损伤反应与癌症代谢之间的功能联系可能是预测顺铂疗效的有用策略。

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Proteomics of genetically engineered mouse mammary tumors identifies fatty acid metabolism members as potential predictive markers for cisplatin resistance.遗传工程小鼠乳腺肿瘤的蛋白质组学分析鉴定出脂肪酸代谢成员作为顺铂耐药的潜在预测标志物。
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