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Abstract：
Clear cell renal carcinoma (ccRCC), the most common subtype of renal cell carcinoma, has the high heterogeneity of a highly complex tumor microenvironment. Existing clinical intervention strategies, such as target therapy and immunotherapy, have failed to achieve good therapeutic effects. In this article, single-cell transcriptome sequencing (scRNA-seq) data from six patients downloaded from the GEO database were adopted to describe the tumor microenvironment (TME) of ccRCC, including its T cells, tumor-associated macrophages (TAMs), endothelial cells (ECs), and cancer-associated fibroblasts (CAFs). Based on the differential typing of the TME, we identified tumor cell-specific regulatory programs that are mediated by three key transcription factors (TFs), whilst the TF EPAS1/HIF-2α was identified via drug virtual screening through our analysis of ccRCC\'s protein structure. Then, a combined deep graph neural network and machine learning algorithm were used to select anti-ccRCC compounds from bioactive compound libraries, including the FDA-approved drug library, natural product library, and human endogenous metabolite compound library. Finally, five compounds were obtained, including two FDA-approved drugs (flufenamic acid and fludarabine), one endogenous metabolite, one immunology/inflammation-related compound, and one inhibitor of DNA methyltransferase (N4-methylcytidine, a cytosine nucleoside analogue that, like zebularine, has the mechanism of inhibiting DNA methyltransferase). Based on the tumor microenvironment characteristics of ccRCC, five ccRCC-specific compounds were identified, which would give direction of the clinical treatment for ccRCC patients.
摘要：
肾透明细胞癌（ccRCC），最常见的肾细胞癌亚型,具有高度复杂的肿瘤微环境的高度异质性。现有的临床干预策略,如靶向治疗和免疫疗法，未能取得良好的治疗效果。在这篇文章中,采用从GEO数据库下载的6名患者的单细胞转录组测序（scRNA-seq）数据来描述ccRCC的肿瘤微环境（TME），包括它的T细胞,肿瘤相关巨噬细胞（TAMs），内皮细胞（ECs），和癌症相关成纤维细胞（CAFs）。根据TME的差分类型，我们确定了由三个关键转录因子（TF）介导的肿瘤细胞特异性调控程序，而通过我们对ccRCC蛋白结构的分析，通过药物虚拟筛选鉴定了TFEPAS1/HIF-2α。然后，使用组合的深图神经网络和机器学习算法从生物活性化合物库中选择抗ccRCC化合物，包括FDA批准的药物库，天然产品库，和人内源性代谢物化合物库。最后,得到5个化合物,包括两种FDA批准的药物（氟芬那酸和氟达拉滨），一种内源性代谢物，一种免疫学/炎症相关化合物，和一种DNA甲基转移酶抑制剂（N4-甲基胞苷，一种胞嘧啶核苷类似物，像zebularine,具有抑制DNA甲基转移酶的机制）。基于ccRCC的肿瘤微环境特征，鉴定了五种ccRCC特异性化合物，这将为ccRCC患者的临床治疗提供指导。
