Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC
BackgroundFatty 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.MethodsWe utilized single-cell sequencing and...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1615601/full |
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| author | Ning Wang Ziyu Xu Lina Zhang Lina Zhang Yanfang Lu Yanfang Lu Yanliang Wang Yanliang Wang Lei Yan Lei Yan Huixia Cao Huixia Cao Limeng Wang Limeng Wang Fengmin Shao Fengmin Shao |
| author_facet | Ning Wang Ziyu Xu Lina Zhang Lina Zhang Yanfang Lu Yanfang Lu Yanliang Wang Yanliang Wang Lei Yan Lei Yan Huixia Cao Huixia Cao Limeng Wang Limeng Wang Fengmin Shao Fengmin Shao |
| author_sort | Ning Wang |
| collection | DOAJ |
| description | BackgroundFatty 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.MethodsWe 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.ResultsThe 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.ConclusionsMYDGF 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. |
| format | Article |
| id | doaj-art-618b9b07ff9745e6bb367764b3fc1a41 |
| institution | OA Journals |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj-art-618b9b07ff9745e6bb367764b3fc1a412025-08-20T02:02:54ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-06-011610.3389/fimmu.2025.16156011615601Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCCNing Wang0Ziyu Xu1Lina Zhang2Lina Zhang3Yanfang Lu4Yanfang Lu5Yanliang Wang6Yanliang Wang7Lei Yan8Lei Yan9Huixia Cao10Huixia Cao11Limeng Wang12Limeng Wang13Fengmin Shao14Fengmin Shao15Department of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital, Zhengzhou, ChinaDepartment of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, ChinaHenan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital, Zhengzhou, ChinaBackgroundFatty 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.MethodsWe 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.ResultsThe 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.ConclusionsMYDGF 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.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1615601/fullfatty acid metabolismccRCCMYDGFScRNA-seqmachine learning |
| spellingShingle | Ning Wang Ziyu Xu Lina Zhang Lina Zhang Yanfang Lu Yanfang Lu Yanliang Wang Yanliang Wang Lei Yan Lei Yan Huixia Cao Huixia Cao Limeng Wang Limeng Wang Fengmin Shao Fengmin Shao Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC Frontiers in Immunology fatty acid metabolism ccRCC MYDGF ScRNA-seq machine learning |
| title | Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC |
| title_full | Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC |
| title_fullStr | Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC |
| title_full_unstemmed | Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC |
| title_short | Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC |
| title_sort | cellular hierarchy framework based on single cell and bulk rna sequencing reveals fatty acid metabolic biomarker mydgf as a therapeutic target for ccrcc |
| topic | fatty acid metabolism ccRCC MYDGF ScRNA-seq machine learning |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1615601/full |
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