Integrated metabolomics and transcriptomics analysis unveils key metabolic pathways and potential biomarkers in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent histological subtype of renal cancer, with both incidence and mortality rates on the rise in recent years. This underscores the urgent need for precise diagnostic tools, effective monitoring, and improved management strategies. Advances in tumor sequencing have significantly enhanced our understanding of the molecular biology of ccRCC, leading to the identification of several potential genomic biomarkers. However, no widely accepted tissue or blood biomarker for ccRCC has been incorporated into routine clinical practice. In this study, we integrated transcriptomics and metabolomics analyses using paired cancerous and non-cancerous tissue samples from five patients who underwent radical nephrectomy. Our goal was to systematically investigate the molecular mechanisms underlying ccRCC and identify potential therapeutic targets. We identified ten shared KEGG metabolic pathways between the transcriptome and metabolome, with purine metabolism and glycerophospholipid metabolism emerging as particularly relevant to tumorigenesis and disease progression. Network analysis revealed significant correlations between specific metabolites (e.g., guanosine triphosphate and L-malic acid) and key genes (e.g., MET, SDHC, FH, and SDHB) within the molecular network of ccRCC. Additionally, we identified key enzymes in phospholipid metabolism, such as AK, LPCAT, and LPEAT, as potential therapeutic targets. Inhibiting these pathways could effectively disrupt tumor membrane formation and signal transduction. Our findings not only deepen the understanding of the molecular mechanisms driving ccRCC but also provide valuable insights for early diagnosis, prognosis evaluation, and the development of novel therapeutic strategies. Future work should focus on validating these potential biomarkers and therapeutic targets in larger cohorts and exploring their clinical utility.

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Publication Details

Journal
Discover Oncology
Published
2026-04-14
DOI
https://doi.org/10.1007/s12672-026-04612-1
Primary Topic
Renal cell carcinoma treatment
Type
article
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article

Integrated metabolomics and transcriptomics analysis unveils key metabolic pathways and potential biomarkers in clear cell renal cell carcinoma

周晓光, Yongzhuo Zhang, Zhendong Wang, Kunpeng Zhang et al.
Discover Oncology
Renal cell carcinoma treatment
article

Integrated metabolomics and transcriptomics analysis unveils key metabolic pathways and potential biomarkers in clear cell renal cell carcinoma

周晓光, Yongzhuo Zhang, Zhendong Wang, Kunpeng Zhang, Zhichao Xue
article en

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most prevalent histological subtype of renal cancer, with both incidence and mortality rates on the rise in recent years. This underscores the urgent need for precise diagnostic tools, effective monitoring, and improved management strategies. Advances in tumor sequencing have significantly enhanced our understanding of the molecular biology of ccRCC, leading to the identification of several potential genomic biomarkers. However, no widely accepted tissue or blood biomarker for ccRCC has been incorporated into routine clinical practice. In this study, we integrated transcriptomics and metabolomics analyses using paired cancerous and non-cancerous tissue samples from five patients who underwent radical nephrectomy. Our goal was to systematically investigate the molecular mechanisms underlying ccRCC and identify potential therapeutic targets. We identified ten shared KEGG metabolic pathways between the transcriptome and metabolome, with purine metabolism and glycerophospholipid metabolism emerging as particularly relevant to tumorigenesis and disease progression. Network analysis revealed significant correlations between specific metabolites (e.g., guanosine triphosphate and L-malic acid) and key genes (e.g., MET, SDHC, FH, and SDHB) within the molecular network of ccRCC. Additionally, we identified key enzymes in phospholipid metabolism, such as AK, LPCAT, and LPEAT, as potential therapeutic targets. Inhibiting these pathways could effectively disrupt tumor membrane formation and signal transduction. Our findings not only deepen the understanding of the molecular mechanisms driving ccRCC but also provide valuable insights for early diagnosis, prognosis evaluation, and the development of novel therapeutic strategies. Future work should focus on validating these potential biomarkers and therapeutic targets in larger cohorts and exploring their clinical utility.

Discover Oncology
Lanzhou University of Technology (CN), Beijing Chao-Yang Hospital, Capital Medical University (CN), National Institute of Metrology (CN), Lanzhou University (CN)
Good health and well-being
Openalex Percentile: Top 9%
Renal cell carcinoma treatment
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