Renal neoplasms encompass a variety of malignant and benign tumors, including many with shared characteristics. The diagnosis of these renal neoplasms remains challenging with currently available tools. In this work, we demonstrate the total protein approach (TPA) based on high-resolution mass spectrometry (MS) as a tool to improve the accuracy of renal neoplasm diagnosis. Frozen tissue biopsies of human renal tissues [clear cell renal cell carcinoma (n = 7), papillary renal cell carcinoma (n = 5), chromophobe renal cell carcinoma (n = 5), and renal oncocytoma (n = 5)] were collected for proteome analysis. Normal adjacent renal tissue (NAT, n = 5) was used as a control. Proteins were extracted and digested using trypsin, and the digested proteomes were analyzed by label-free high-resolution MS (nanoLC-ESI-HR-MS/MS). Quantitative analysis was performed by comparison between protein abundances of tumors and NAT specimens, and the label-free and standard-free TPA was used to obtain absolute protein concentrations. A total of 205 differentially expressed proteins with the potential to distinguish the renal neoplasms were found. Of these proteins, a TPA-based panel of 24, including known and new biomarkers, was selected as the best candidates to differentiate the neoplasms. As proof of concept, the diagnostic potential of PLIN2, TUBB3, LAMP1, and HK1 was validated using semi-quantitative immunohistochemistry with a total of 128 samples assessed on tissue micro-arrays. We demonstrate the utility of combining high-resolution MS and the TPA as potential new diagnostic tool in the pathology of renal neoplasms. A similar TPA approach may be implemented in any cancer study with solid biopsies.

中文翻译：

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使用总蛋白方法的绝对定量蛋白质组学鉴定肾肿瘤中的新型临床免疫组织化学标志物


肾肿瘤包括多种恶性肿瘤和良性肿瘤，其中许多具有共同的特征。使用目前可用的工具来诊断这些肾肿瘤仍然具有挑战性。在这项工作中，我们展示了基于高分辨率质谱（MS）的总蛋白方法（TPA）作为提高肾肿瘤诊断准确性的工具。收集人肾组织的冷冻组织活检[透明细胞肾细胞癌（n = 7）、乳头状肾细胞癌（n = 5）、嫌色肾细胞癌（n = 5）和肾嗜酸细胞瘤（n = 5）]用于蛋白质组分析。正常邻近肾组织（NAT，n = 5）用作对照。使用胰蛋白酶提取和消化蛋白质，并通过无标记高分辨率 MS (nanoLC-ESI-HR-MS/MS) 分析消化的蛋白质组。通过比较肿瘤和NAT标本的蛋白质丰度进行定量分析，并使用无标记和无标准的TPA获得绝对蛋白质浓度。总共发现了 205 个具有区分肾肿瘤潜力的差异表达蛋白。在这些蛋白质中，基于 TPA 的 24 种蛋白质（包括已知和新的生物标志物）被选为区分肿瘤的最佳候选蛋白质。作为概念证明，PLIN2、TUBB3、LAMP1 和 HK1 的诊断潜力使用半定量免疫组织化学方法进行了验证，并在组织微阵列上评估了总共 128 个样本。我们展示了高分辨率 MS 和 TPA 相结合作为肾肿瘤病理学潜在新诊断工具的效用。类似的 TPA 方法可以在任何使用实体活检的癌症研究中实施。