Wang Ning, Xu Ziyu, Zhang Lina, Lu Yanfang, Wang Yanliang, Yan Lei, Cao Huixia, Wang Limeng, Shao Fengmin
Department of Nephrology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, China.
Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People's Hospital, Zhengzhou, China.
Front Immunol. 2025 Jun 5;16:1615601. doi: 10.3389/fimmu.2025.1615601. eCollection 2025.
Fatty acid metabolism (FAM) reprogramming is a prominent feature of clear cell renal cell carcinoma (ccRCC). Nevertheless, the effect of FAM reprogramming on the heterogeneity and prognosis of ccRCC individuals remains insufficiently understood.
We utilized single-cell sequencing and spatial transcriptomics to investigate the heterogeneity of FAM in ccRCC comprehensively. Functional enrichment algorithms, including AUCell, UCell, singscore, ssGSEA, and AddModuleScore, along with hdWGCNA analysis, were used to identify hub genes influencing high FAM of ccRCC. Machine learning methods were then applied to pinpoint the optimal feature gene. The function of the selected genes in FAM was validated through clinical samples and cellular functional experiments.
The results revealed significant upregulation of FAM in malignant epithelial cells. Through five distinct enrichment scoring methods and hdWGCNA analysis, we redefined a gene set related to increased FAM at the single-cell level. By the integration of this gene set with bulk transcriptomic data and the application of machine-learning algorithms, we found four candidate genes-MYDGF, ZNHIT1, HMGN3, and ARL6IP4-that were linked to ccRCC progression. Bulk RNA sequencing validated their increased expression in ccRCC individuals, underscoring their diagnostic and prognostic potential. Single-cell analysis further revealed that these genes were primarily upregulated in malignant epithelial cells, emphasizing their cell-specific roles in ccRCC. It was verified that MYDGF could promote cell proliferation, migration and invasion while inhibiting cell apoptosis. Functional experiments further confirmed that MYDGF is a key FAM-related biomarker that enhances lipid deposition by suppressing fatty acid oxidation, thereby accelerating tumor progression.
MYDGF was identified as a FAM-related oncogenic biomarker that promotes ccRCC progression by inhibiting fatty acid oxidation. Our findings elucidated the cellular hierarchy of ccRCC from the perspective of FAM reprogramming and may offer new insights and therapeutic targets for future ccRCC treatments.
脂肪酸代谢（FAM）重编程是透明细胞肾细胞癌（ccRCC）的一个显著特征。然而，FAM重编程对ccRCC个体异质性和预后的影响仍未得到充分了解。
我们利用单细胞测序和空间转录组学全面研究ccRCC中FAM的异质性。使用包括AUCell、UCell、singscore、ssGSEA和AddModuleScore在内的功能富集算法以及hdWGCNA分析来鉴定影响ccRCC高FAM的关键基因。然后应用机器学习方法确定最佳特征基因。通过临床样本和细胞功能实验验证所选基因在FAM中的功能。
结果显示恶性上皮细胞中FAM显著上调。通过五种不同的富集评分方法和hdWGCNA分析，我们在单细胞水平重新定义了一个与FAM增加相关的基因集。通过将该基因集与批量转录组数据整合并应用机器学习算法，我们发现了四个与ccRCC进展相关的候选基因——MYDGF、ZNHIT1、HMGN3和ARL6IP4。批量RNA测序验证了它们在ccRCC个体中的表达增加，强调了它们的诊断和预后潜力。单细胞分析进一步表明，这些基因主要在恶性上皮细胞中上调，强调了它们在ccRCC中的细胞特异性作用。经证实，MYDGF可促进细胞增殖、迁移和侵袭，同时抑制细胞凋亡。功能实验进一步证实，MYDGF是一种关键的FAM相关生物标志物，通过抑制脂肪酸氧化增强脂质沉积，从而加速肿瘤进展。
MYDGF被确定为一种FAM相关的致癌生物标志物，通过抑制脂肪酸氧化促进ccRCC进展。我们的研究结果从FAM重编程的角度阐明了ccRCC的细胞层次结构，并可能为未来ccRCC治疗提供新的见解和治疗靶点。
