ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1615601
This article is part of the Research TopicTumor Microenvironment: Inflammation and Immune Signal Transduction at Single-Cell ResolutionView all articles
Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC
Provisionally accepted
- Zhengzhou University, Zhengzhou, China
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Background: 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. Methods: 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.Results: 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. Conclusions: 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.
Keywords: fatty acid metabolism, ccRCC, MYDGF, ScRNA-seq, machine learning
Received: 21 Apr 2025; Accepted: 22 May 2025.
Copyright: © 2025 Wang, Xu, Zhang, Lu, Wang, Yan, Cao, Wang and Shao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Huixia Cao, Zhengzhou University, Zhengzhou, China
Limeng Wang, Zhengzhou University, Zhengzhou, China
Fengmin Shao, Zhengzhou University, Zhengzhou, China
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