Clear-cell renal cell carcinoma (ccRCC) is the most common type of RCC; however, the intratumoral heterogeneity in ccRCC remains unclear. We first identified markers and biological features of each cell cluster using bioinformatics analysis based on single-cell and spatial transcriptome RNA-sequencing data. We found that gene copy number loss on chromosome 3p and amplification on chromosome 5q were common features in ccRCC cells. Meanwhile, NNMT and HILPDA, which are associated with the response to hypoxia and metabolism, are potential therapeutic targets for ccRCC. In addition, CD8+ exhausted T cells (LAG3+ HAVCR2+), CD8+ proliferated T cells (STMN+), and M2-like macrophages (CD68+ CD163+ APOC1+), which are closely associated with immunosuppression, played vital roles in ccRCC occurrence and development. These results were further verified by whole exome sequencing, cell line and xenograft experiments, and immunofluorescence staining. Finally, we divide patients with ccRCC into three subtypes using unsupervised cluster analysis. and generated a classifier to reproduce these subtypes using the eXtreme Gradient Boosting algorithm. Our classifier can help clinicians evaluate prognosis and design personalized treatment strategies for ccRCC. In summary, our work provides a new perspective for understanding tumor heterogeneity and will aid in the design of antitumor therapeutic strategies for ccRCC.

透明细胞肾细胞癌 (ccRCC) 是最常见的 RCC 类型；然而，ccRCC 的瘤内异质性仍不清楚。我们首先使用基于单细胞和空间转录组 RNA 测序数据的生物信息学分析来确定每个细胞簇的标记和生物学特征。我们发现 ccRCC 细胞的共同特征是 3p 染色体上的基因拷贝数丢失和 5q 染色体上的基因扩增。同时，NNMT和HILPDA与缺氧反应和代谢相关，是ccRCC的潜在治疗靶点。此外，与免疫抑制密切相关的CD8+耗竭T细胞（LAG3+ HAVCR2+）、CD8+增殖T细胞（STMN+）和M2样巨噬细胞（CD68+ CD163+ APOC1+）在ccRCC的发生、发展中发挥着重要作用。这些结果通过全外显子组测序、细胞系和异种移植实验以及免疫荧光染色进一步得到验证。最后，我们使用无监督聚类分析将 ccRCC 患者分为三个亚型。并使用 eXtreme Gradient Boosting 算法生成一个分类器来重现这些子类型。我们的分类器可以帮助临床医生评估 ccRCC 的预后并设计个性化的治疗策略。总之，我们的工作为理解肿瘤异质性提供了新的视角，并将有助于设计 ccRCC 的抗肿瘤治疗策略。