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非小细胞肺癌细胞系分泌组和患者痰液的蛋白质组分析揭示了顺铂反应预测的生物流体生物标志物候选物。

Proteome analysis of non-small cell lung cancer cell line secretomes and patient sputum reveals biofluid biomarker candidates for cisplatin response prediction.

机构信息

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, 1081 HV Amsterdam, the Netherlands.

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Otolaryngology/Head and Neck Surgery, 1081 HV Amsterdam, the Netherlands.

出版信息

J Proteomics. 2019 Mar 30;196:106-119. doi: 10.1016/j.jprot.2019.01.018. Epub 2019 Jan 30.

DOI:10.1016/j.jprot.2019.01.018
PMID:30710758
Abstract

Molecular markers are urgently needed to select non-small cell lung cancer (NSCLC) patients most likely to benefit from platinum-based chemotherapies. Of particular interest are proteins that can be found in biofluids like sputum for non-invasive detection. Therefore, we profiled the secretomes of 6 NSCLC cell lines with varying IC50-values for cisplatin, using label-free GeLC-MS/MS-based proteomics. Out of a total dataset of 2610 proteins, 304 proteins showed significant differences in expression levels between cisplatin sensitive and insensitive cell lines. Functional data mining revealed that the secretion of typically extracellular factors was associated with a higher sensitivity towards cisplatin, while cisplatin insensitivity correlated with increased secretion of theoretically intra-cellular proteins. Stringent statistical analysis and quantitative filtering yielded 58 biomarker candidates, 34 of which could be detected in clinical biofluids of lung cancer patients such as sputum using label-free LC-MS/MS-based proteomics. To assess performance of these biofluid biomarker candidates, we correlated protein expression with patient survival using a publically available clinical gene expression data set (GSE14814). We thus identified 3 top candidates with potential predictive value in determining cisplatin response (UGGT1, COL6A1 and MAP4) for future development as non-invasive biomarkers to guide treatment decisions. SIGNIFICANCE: Platinum-based chemotherapies are still the standard of care for NSCLC and other lung cancer types in the clinic today. However, due to chemoresistance, many patients suffer from the toxic side effects of these treatments without gaining any benefit in terms of survival. To date, no molecular biomarkers are available to predict clinical outcome of platinum-based chemotherapy. Because proteins present the functional read-out of genetic, epigenetic and translational events in the cell, a protein test is likely to be particularly suitable for response prediction. Of high relevance are proteins that are shed or secreted from cells, for example at primary tumor sites, and can be found in easily accessible biofluids like sputum for non-invasive detection. Here, we report the proteome profiling of the conditioned media (secretomes) of a panel of NSCLC cell lines in relation to cisplatin IC50 values, as a pre-clinical model, and of patient sputum as a clinical, lung cancer relevant biofluid. Using this approach in conjunction with exploration of the predictive potential in a transcriptome lung cancer patient dataset, we reveal biofluid biomarker candidates that, with further validation, may be used for non-invasive cisplatin response prediction in the future.

摘要

分子标志物对于选择最有可能从铂类化疗中获益的非小细胞肺癌(NSCLC)患者至关重要。特别感兴趣的是可以在生物体液(如痰液)中发现的用于非侵入性检测的蛋白质。因此,我们使用无标记 GeLC-MS/MS 蛋白质组学对 6 种 NSCLC 细胞系进行了 IC50 值为顺铂的分泌组学分析。在总共 2610 种蛋白质中,304 种蛋白质在顺铂敏感和不敏感细胞系之间的表达水平存在显著差异。功能数据挖掘表明,通常细胞外因子的分泌与对顺铂的更高敏感性有关,而顺铂不敏感与理论上细胞内蛋白质的分泌增加有关。严格的统计分析和定量筛选得到了 58 个生物标志物候选物,其中 34 个可以使用无标记 LC-MS/MS 蛋白质组学在肺癌患者的临床生物体液(如痰液)中检测到。为了评估这些生物流体生物标志物候选物的性能,我们使用公开的临床基因表达数据集(GSE14814)将蛋白质表达与患者生存相关联进行了分析。因此,我们确定了 3 个具有潜在预测价值的顶级候选物,可用于确定顺铂反应(UGGT1、COL6A1 和 MAP4),以作为指导治疗决策的非侵入性生物标志物进行未来开发。意义:铂类化疗仍然是 NSCLC 和当今临床中其他肺癌类型的标准治疗方法。然而,由于化疗耐药性,许多患者在没有任何生存获益的情况下遭受这些治疗的毒性副作用。迄今为止,尚无分子生物标志物可预测铂类化疗的临床疗效。因为蛋白质反映了细胞内遗传、表观遗传和翻译事件的功能读数,所以蛋白质测试可能特别适合于预测反应。特别相关的是从细胞中释放或分泌的蛋白质,例如在原发性肿瘤部位,并且可以在痰液等易于获得的生物体液中发现,用于非侵入性检测。在这里,我们报告了一组 NSCLC 细胞系在顺铂 IC50 值方面的条件培养基(分泌组)的蛋白质组学分析,作为临床前模型,以及患者痰液的蛋白质组学分析,作为临床、肺癌相关的生物流体。通过结合对转录组肺癌患者数据集的预测潜力的探索,我们揭示了具有潜在预测价值的生物流体生物标志物候选物,这些候选物在进一步验证后可能用于未来的非侵入性顺铂反应预测。

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