肾癌经历了明显的代谢转变，对免疫治疗干预表现出反应性。然而，肾细胞癌的代谢分类和代谢改变与免疫浸润之间的关联仍需进一步阐明。在TCGA队列中进行了无监督一致性聚类，以进行代谢分类，并比较了不同聚类之间的GESA、mRNAsi、预后、临床特征、突变负荷、免疫浸润和基因差异。基于代谢基因特征建立预后模型和Nomograms，并使用外部ICGC数据集进行验证。利用人类蛋白质图谱数据库和同济医院的免疫组织化学结果验证了正常组织和肿瘤样本中的基因表达水平。应用CCK8、凋亡分析、qPCR、皮下移植的小鼠模型和流式细胞分析研究ACAA2在肿瘤进展和抗肿瘤免疫中的作用。肾细胞癌分为3个代谢亚群，低代谢数据亚组显示出最差的预后、最高的侵袭性和AJCC分级、增强的免疫浸润但抑制性免疫表型。鉴定了ACAA2、ACAT1、ASRGL1、AKR1B10、ABCC2、ANGPTL4以构建6个基因标志预后模型，并使用ICGC队列内外部验证。ACAA2被证明是一种肿瘤抑制因子，并与更高的免疫浸润以及CD8+T细胞表达的PD-1升高相关。我们的研究提出了一种新的RCC代谢分类方法，并揭示了代谢表型和免疫表型之间的内在关联。已鉴定的基因标志可能是连接肿瘤代谢和肿瘤免疫的关键因素，并需要进一步深入研究。 ©2023年，作者。

Kidney cancer undergoes a dramatic metabolic shift and has demonstrated responsiveness to immunotherapeutic intervention. However, metabolic classification and the associations between metabolic alterations and immune infiltration in Renal cell carcinoma still remain elucidative.Unsupervised consensus clustering was conducted on the TCGA cohorts for metabolic classification. GESA, mRNAsi, prognosis, clinical features, mutation load, immune infiltration and differentially expressed gene differences among different clusters were compared. The prognosis model and nomograms were constructed based on metabolic gene signatures and verified using external ICGC datasets. Immunohistochemical results from Human Protein Atlas database and Tongji hospital were used to validate gene expression levels in normal tissues and tumor samples. CCK8, apoptosis analysis, qPCR, subcutaneously implanted murine models and flowcytometry analysis were applied to investigate the roles of ACAA2 in tumor progression and anti-tumor immunity.Renal cell carcinoma was classified into 3 metabolic subclusters and the subcluster with low metabolic profiles displayed the poorest prognosis, highest invasiveness and AJCC grade, enhanced immune infiltration but suppressive immunophenotypes. ACAA2, ACAT1, ASRGL1, AKR1B10, ABCC2, ANGPTL4 were identified to construct the 6 gene-signature prognosis model and verified both internally and externally with ICGC cohorts. ACAA2 was demonstrated as a tumor suppressor and was associated with higher immune infiltration and elevated PD-1 expression of CD8+ T cells.Our research proposed a new metabolic classification method for RCC and revealed intrinsic associations between metabolic phenotypes and immune profiles. The identified gene signatures might serve as key factors bridging tumor metabolism and tumor immunity and warrant further in-depth investigations.© 2023. The Author(s).