Cancer Biomarker Research Group, Institute of Enzymology, RCNS, H-1117 Budapest, Hungary.
National Laboratory for Drug Research and Development, RCNS, H-1117 Budapest, Hungary.
Int J Mol Sci. 2023 Feb 24;24(5):4488. doi: 10.3390/ijms24054488.
Clear cell renal carcinoma is the most frequent type of kidney cancer, with an increasing incidence rate worldwide. In this research, we used a proteotranscriptomic approach to differentiate normal and tumor tissues in clear cell renal cell carcinoma (ccRCC). Using transcriptomic data of patients with malignant and paired normal tissue samples from gene array cohorts, we identified the top genes over-expressed in ccRCC. We collected surgically resected ccRCC specimens to further investigate the transcriptomic results on the proteome level. The differential protein abundance was evaluated using targeted mass spectrometry (MS). We assembled a database of 558 renal tissue samples from NCBI GEO and used these to uncover the top genes with higher expression in ccRCC. For protein level analysis 162 malignant and normal kidney tissue samples were acquired. The most consistently upregulated genes were IGFBP3, PLIN2, PLOD2, PFKP, VEGFA, and CCND1 ( < 10 for each gene). Mass spectrometry further validated the differential protein abundance of these genes (IGFBP3, = 7.53 × 10; PLIN2, = 3.9 × 10; PLOD2, = 6.51 × 10; PFKP, = 1.01 × 10; VEGFA, = 1.40 × 10; CCND1, = 1.04 × 10). We also identified those proteins which correlate with overall survival. Finally, a support vector machine-based classification algorithm using the protein-level data was set up. We used transcriptomic and proteomic data to identify a minimal panel of proteins highly specific for clear cell renal carcinoma tissues. The introduced gene panel could be used as a promising tool in the clinical setting.
透明细胞肾细胞癌是最常见的肾癌类型，其全球发病率呈上升趋势。在这项研究中，我们使用蛋白质组转录组学方法来区分透明细胞肾细胞癌（ccRCC）中的正常组织和肿瘤组织。我们使用基因阵列队列中恶性和配对正常组织样本的转录组数据，鉴定出在 ccRCC 中过度表达的顶级基因。我们收集了手术切除的 ccRCC 标本，以进一步在蛋白质组水平上研究转录组结果。使用靶向质谱法（MS）评估差异蛋白丰度。我们从 NCBI GEO 中收集了 558 个肾组织样本数据库，并利用这些数据库来揭示在 ccRCC 中表达更高的顶级基因。为了进行蛋白质水平分析，我们获得了 162 个恶性和正常的肾脏组织样本。上调最一致的基因是 IGFBP3、PLIN2、PLOD2、PFKP、VEGFA 和 CCND1（每个基因<10）。质谱进一步验证了这些基因的差异蛋白丰度（IGFBP3，=7.53×10；PLIN2，=3.9×10；PLOD2，=6.51×10；PFKP，=1.01×10；VEGFA，=1.40×10；CCND1，=1.04×10）。我们还鉴定了与总生存相关的那些蛋白质。最后，我们建立了一个基于蛋白质水平数据的支持向量机分类算法。我们使用转录组和蛋白质组数据来鉴定一组高度特异性的透明细胞肾细胞癌组织的最小蛋白。该引入的基因面板可作为临床环境中的有前途的工具。
