PARProceedings of Anticancer Research2208-35452208-3553Bio-Byword Scientific Publishing Pty. Ltd.10.26689/par.v9i3.10570ArticleApplication of Proteomic and Metabolomic Technologies in Renal Cell Carcinoma and Research Progress of Related Biomarkershttps://artdesignp.com/journal/PAR/9/3/10.26689/par.v9i3.10570ZhangLiyuan,LiJunyan,PanYoufu2025932025-05-29Renal cell carcinoma (RCC), which accounts for about 90 percent of kidney cancers, has a distinct metabolic reprogramming profile characterized by increased aerobic glycolysis (Warburg effect), abnormal accumulation of lipids, and impaired mitochondrial function. Recent advances in high-throughput proteomic and metabolomic technologies have revolutionized our understanding of the pathophysiology of RCC, allowing for the systematic identification of disease-specific molecular signatures, elucidation of drug resistance mechanisms, and possible targets for intervention. The review focuses on the use of proteomic and metabolomic technologies in renal cell carcinoma and the research progress on related biomarkers, and is expected to provide useful information for the early detection and treatment of RCC.

Bukavina L, Bensalah K, Bray F, et al., 2022, Epidemiology of Renal Cell Carcinoma: Update. Eur Urol, 82(5): 529–542.

Jonasch E, Walker CL, Rathmell WK, 2021, Clear Cell Renal Cell Carcinoma Ontogeny and Mechanisms of Lethality. Nature Reviews Nephrology, 17(4): 245–261.

Chakraborty S, Balan M, Sabarwal A, et al., 2021, Metabolic Reprogramming in Renal Cancer: Events of a Metabolic Disease. Biochim Biophys Acta Rev Cancer, 1876(1): 188559.

Yong C, Stewart GD, Frezza C, 2020, Oncometabolites in Renal Cancer. Nature Reviews Nephrology, 16(3): 156–172.

Choueiri TK, Kaelin Jr. WG, 2020, Targeting the HIF2-VEGF Axis in Renal Cell Carcinoma. Nature Medicine, 26(10): 1519–1530.

Fallah J, Heiss BL, Joeng HK, et al., 2024, FDA Approval Summary: Belzutifan for Patients with Advanced Renal Cell Carcinoma. Clin Cancer Res, 30(22): 5003–5008.

Alva AS, 2024, Novel Approaches with HIF-2α Targeted Therapies in Metastatic Renal Cell Carcinoma. Cancers, 16.

Meléndez-Rodríguez F, Urrutia AA, Lorendeau D, et al., 2019, HIF1α Suppresses Tumor Cell Proliferation through Inhibition of Aspartate Biosynthesis. Cell Rep, 26(9): 2257–2265.

Sun RC, Denko NC, 2014, Hypoxic Regulation of Glutamine Metabolism Through HIF1 and SIAH2 Supports Lipid Synthesis that is Necessary for Tumor Growth. Cell Metab, 19(2): 285–292.

Liu R, Zou Z, Chen L, et al., 2024, FKBP10 Promotes Clear Cell Renal Cell Carcinoma Progression and Regulates Sensitivity to the HIF2α Blockade by Facilitating LDHA Phosphorylation. Cell Death Dis, 15(1): 64.

Zhang X, Li S, He J, et al., 2022, TET2 Suppresses VHL Deficiency-Driven Clear Cell Renal Cell Carcinoma by Inhibiting HIF Signaling. Cancer Res, 82(11): 2097–2109.

Li B, Qiu B, Lee DSM, et al, 2014, Fructose-1,6-bisphosphatase Opposes Renal Carcinoma Progression. Nature, 513(7517): 251–255.

Hoefflin R, Harlander S, Schfer S, et al., HIF-1α and HIF-2α Differently Regulate Tumour Development and Inflammation of Clear Cell Renal Cell Carcinoma in Mice. Nature Communications, 11: 4111.

Varela I, Tarpey P, Raine K, et al., 2011, Exome Sequencing Identifies Frequent Mutation of the SWI/SNF Complex Gene PBRM1 in Renal Carcinoma. Nature, 469(7331): 539–542.

Tang Y, Jin YH, Li HL, et al., 2022, PBRM1 Deficiency Oncogenic Addiction is Associated with Activated AKT-mTOR Signalling and Aerobic Glycolysis in Clear Cell Renal Cell Carcinoma Cells. J Cell Mol Med, 26(14): 3837–3849.

Wu Z, Ge L, Song Y, et al., 2023, ATAD2 Promotes Glycolysis and Tumor Progression in Clear Cell Renal Cell Carcinoma by Regulating the Transcriptional Activity of C-Myc. Discover Oncology, 14(1): 79.

Chen X, Li Z, Yong H, et al., 2021, TRIM21-mediated HIF-1α Degradation Attenuates Aerobic Glycolysis to Inhibit Renal Cancer Tumorigenesis and Metastasis. Cancer Lett, 508: 115–126.

Zhang C, Chen L, Liu Y, et al., 2021, Downregulated METTL14 Accumulates BPTF that Reinforces Super-enhancers and Distal Lung Metastasis via Glycolytic Reprogramming in Renal Cell Carcinoma. Theranostics, 11(8): 3676–3693.

Liu H, Li S, Liu X, et al., 2018, SIRT3 Overexpression Inhibits Growth of Kidney Tumor Cells and Enhances Mitochondrial Biogenesis. J Proteome Res, 17(9): 3143–3152.

Bian X, Liu R, Meng Y, et al., 2021, Lipid Metabolism and Cancer. J Exp Med, 218(1).

Tan SK, Hougen HY, Merchan JR, et al., 2023, Fatty Acid Metabolism Reprogramming in ccRCC: Mechanisms and Potential Targets. Nature Reviews Urology, 20(1): 48–60.

Chen J, Chen J, Huang J, et al., 2019, HIF-2α Upregulation Mediated by Hypoxia Promotes NAFLD-HCC Progression by Activating Lipid Synthesis via the PI3K-AKT-mTOR Pathway. Aging (Albany NY), 11(23).

Hua X, Ge S, Zhang L, et al., 2024, MED15 is Upregulated by HIF-2α and Promotes Proliferation and Metastasis in Clear Cell Renal Cell Carcinoma via Activation of SREBP-dependent Fatty Acid Synthesis. Cell Death Discovery, 10(1).

Shi J, Lv Q, Miao D, et al., 2024, HIF2α Promotes Cancer Metastasis through TCF7L2-Dependent Fatty Acid Synthesis in ccRCC. Research (Washington, DC), 7: 0322.

Nguyen TTM, Nguyen TH, Kim HS, et al., 2023, GPX8 Regulates Clear Cell Renal Cell Carcinoma Tumorigenesis through Promoting Lipogenesis by NNMT. J Exp Clin Cancer Res, 42(1): 42.

Zeng K, Li Q, Song G, et al., 2023, CPT2-mediated Fatty Acid Oxidation Inhibits Tumorigenesis and Enhances Sorafenib Sensitivity via the ROS/PPARγ/NF-κB Pathway in Clear Cell Renal Cell Carcinoma. Cell Signal, 110: 110838.

Zhou L, Luo Y, Liu Y, et al., 2023, Fatty Acid Oxidation Mediated by Malonyl-CoA Decarboxylase Represses Renal Cell Carcinoma Progression. Cancer Res, 83(23): 3920–3939.

Wang D, Mahmud I, Thakur VS, et al., 2024, GPR1 and CMKLR1 Control Lipid Metabolism to Support the Development of Clear Cell Renal Cell Carcinoma. Cancer Res, 84(13): 2141–2154.

Zheng M, Zhang S, Zhou J, et al., 2024, ACAT1 Suppresses Clear Cell Renal Cell Carcinoma Progression by AMPK-mediated Fatty Acid Metabolism. Translational Oncology, 47: 102043.

Rambold AS, Pearce EL, 2018, Mitochondrial Dynamics at the Interface of Immune Cell Metabolism and Function. Trends Immunol, 39(1): 6–18.

Urrutia AA, Mesa-Ciller C, Guajardo-Grence A, et al., 2024, HIF1α-dependent Uncoupling of Glycolysis Suppresses Tumor Cell Proliferation. Cell Rep, 43(4): 114103.

Kubala JM, Laursen KB, Schreiner R, et al., 2023, NDUFA4L2 Reduces Mitochondrial Respiration Resulting in Defective Lysosomal Trafficking in Clear Cell Renal Cell Carcinoma. Cancer Biol Ther, 24(1): 2170669.

Luo L, Wei D, Pan Y, et al., 2023, MFN2 Suppresses Clear Cell Renal Cell Carcinoma Progression by Modulating Mitochondria-Dependent Dephosphorylation of EGFR. Cancer Communications (London, England), 43(7): 808–833.

Sobsey CA, Ibrahim S, Richard VR, et al., 2019, Targeted and Untargeted Proteomics Approaches in Biomarker Development. PROTEOMICS, 20(9).

White NM, Masui O, Desouza LV, et al., 2014, Quantitative Proteomic Analysis Reveals Potential Diagnostic Markers and Pathways Involved in Pathogenesis of Renal Cell Carcinoma. Oncotarget, 5(2): 506–518.

Atrih A, Mudaliar MA, Zakikhani P, et al., 2014, Quantitative Proteomics in Resected Renal Cancer Tissue for Biomarker Discovery and Profiling. Br J Cancer, 110(6): 1622–1633.

Lin L, Zheng J, Zheng F, et al., 2020, Advancing Serum Peptidomic Profiling by Data-independent Acquisition for Clear-cell Renal Cell Carcinoma Detection and Biomarker Discovery. Journal of Proteomics, 215: 103671.

Borras E, Sabido E, 2017, What is Targeted Proteomics? A Concise Revision of Targeted Acquisition and Targeted Data Analysis in Mass Spectrometry. Proteomics, 17(17–18).

Di Meo A, Batruch I, Brown MD, et al., 2019, Identification of Prognostic Biomarkers in the Urinary Peptidome of the Small Renal Mass. The American Journal of Pathology, 189(12): 2366–2376.

Kalim S, Rhee EP, 2017, An Overview of Renal Metabolomics. Kidney Int, 91(1):61–69.

Wang Y, Fu D, Su J, et al., 2017, C1QBP Suppresses Cell Adhesion and Metastasis of Renal Carcinoma Cells. Scientific Reports, 7(1): 999.

Wang Y, Liu S, Tian S, et al., 2022, C1QBP Regulates Apoptosis of Renal Cell Carcinoma via Modulating Xanthine Dehydrogenase (XDH) Mediated ROS Generation. Int J Med Sci, 19(5): 842–857.

Feng C, Li Y, Li K, et al., 2021, PFKFB4 is Overexpressed in Clear Cell Renal Cell Carcinoma Promoting Pentose Phosphate Pathway that Mediates Sunitinib Resistance. Journal of Experimental & Clinical Cancer Research, 40(1): 308.

Liu J, Hanavan PD, Kras K, et al., 2019, Loss of SETD2 Induces a Metabolic Switch in Renal Cell Carcinoma Cell Lines toward Enhanced Oxidative Phosphorylation. J Proteome Res, 18(1): 331–340.

Amaro F, Carvalho M, Carvalho-Maia C, et al., 2025, Metabolic Signature of Renal Cell Carcinoma Tumours and its Correlation with the Urinary Metabolome. Metabolomics, 21(2).

Wettersten HI, Hakimi AA, Morin D, et al., 2015, Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis. Cancer Res 2015, 75(12): 2541–2552.

Yuan Y, Liu Z, Li B, et al., 2022, Integrated Analysis of Transcriptomics, Proteomics and Metabolomics Data Reveals the Role of SLC39A1 in Renal Cell Carcinoma. Front Cell Dev Biol, 10: 977960.

Li Y, Lih TM, Dhanasekaran SM, et al., 2023, Histopathologic and Proteogenomic Heterogeneity Reveals Features of Clear Cell Renal Cell Carcinoma Aggressiveness. Cancer Cell, 41(1): 139–163.

Liu J, Chang X, Qian L, et al., 2024, Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas with Intestinal or Mucinous Differentiation from Lung Metastatic Colorectal Cancer. Molecular & Cellular Proteomics, 23(5): 100766.

Han S, Liu X, Ju S, et al., 2023, New Mechanisms and Biomarkers of Lymph Node Metastasis in Cervical Cancer: Reflections from Plasma Proteomics. Clinical proteomics, 20(1): 35.

Wang F, Yu B, Yu Q, et al., 2023, NOP58 Induction Potentiates Chemoresistance of Colorectal Cancer Cells through Aerobic Glycolysis as Evidenced by Proteomics Analysis. Front Pharmacol, 14: 1295422.

Coelho M, Capela J, Anjo SI, et al., 2023, Proteomics Reveals mRNA Regulation and the Action of Annexins in Thyroid Cancer. In: International Journal of Molecular Sciences, 24: 14514–14542.

Scebba F, Salvadori S, Cateni S, et al., 2023, Top-Down Proteomics of Human Saliva, Analyzed with Logistic Regression and Machine Learning Methods, Reveal Molecular Signatures of Ovarian Cancer. Int J Mol Sci, 24(21): 3238–3253.

Carvalho LB, Teigas-Campos PAD, Jorge S, et al., 2024, Normalization Methods in Mass Spectrometry-based Analytical Proteomics: A Case Study Based on Renal Cell Carcinoma Datasets. Talanta, 266: 124953.

Thomas S, Hao L, Ricke WA, et al., 2016, Biomarker Discovery in Mass Spectrometry-based Urinary Proteomics. Proteomics Clinical applications, 10(4): 358–370.

Monteiro M, Moreira N, Pinto J, et al., 2017, GC-MS Metabolomics-based Approach for the Identification of a Potential VOC-Biomarker Panel in the Urine of Renal Cell Carcinoma Patients. J Cell Mol Med, 21(9): 2092–2105.

Liu X, Zhang M, Liu X, et al., 2019, Urine Metabolomics for Renal Cell Carcinoma (RCC) Prediction: Tryptophan Metabolism as an Important Pathway in RCC. Front Oncol, 9: 663.

Morozumi K, Kawasaki Y, Maekawa M, et al., 2022, Predictive Model for Recurrence of Renal Cell Carcinoma by Comparing Pre and Postoperative Urinary Metabolite Concentrations. Cancer Sci, 113(1): 182–194.

Oto J, Fernandez-Pardo A, Roca M, et al., 2020, Urine Metabolomic Analysis in Clear Cell and Papillary Renal Cell Carcinoma: A Pilot Study. Journal of Proteomics, 218: 103723.

Yang Y, Pang Q, Hua M, et al., 2023, Excavation of Diagnostic Biomarkers and Construction of Prognostic Model for Clear Cell Renal Cell Carcinoma based on Urine Proteomics. Front Oncol, 13: 1170567.

Liu X, Zhang M, Shao C, et al., 2023, Blood and Urine-Based Liquid Biopsy for Early-stage Cancer Investigation: Taken Clear Renal Cell Carcinoma as a Model. Mol Cell Proteomics, 22(8): 100603–100618.

Zheng L, Zhu ZR, Sneh T, et al., 2023, Circulating Succinate-modifying Metabolites Accurately Classify and Reflect the Status of Fumarate Hydratase-deficient Renal Cell Carcinoma. J Clin Invest 2023, 133(11): e165028–165015.

Wang J, Yang WY, Li XH, et al., 2022, Study on Potential Markers for Diagnosis of Renal Cell Carcinoma by Serum Untargeted Metabolomics based on UPLC-MS/MS. Front Physiol, 13: 996214–996248.

Wolrab D, Jirasko R, Peterka O, et al., 2021, Plasma Lipidomic Profiles of Kidney, Breast and Prostate Cancer Patients Differ from Healthy Controls. Sci Rep, 11(1): 20322–20314.

Zheng H, Ji J, Zhao L, et al., 2016, Prediction and Diagnosis of Renal Cell Carcinoma using Nuclear Magnetic Resonance-based Serum Metabolomics and Self-organizing Maps. Oncotarget, 7(37): 59189–59198.

Wagner M, Wiig H, 2015, Tumor Interstitial Fluid Formation, Characterization, and Clinical Implications. Front Oncol, 5: 115.

Teng PN, Hood BL, Sun M, et al., 2011, Differential Proteomic Analysis of Renal Cell Carcinoma Tissue Interstitial Fluid. J Proteome Res, 10(3): 1333–1342.

Sato T, Kawasaki Y, Maekawa M, et al., 2019, Value of Global Metabolomics in Association with Diagnosis and Clinicopathological Factors of Renal Cell Carcinoma. Int J Cancer, 145(2): 484–493.

Nizioł J, Bonifay V, Ossoliński K, et al., 2018, Metabolomic Study of Human Tissue and Urine in Clear Cell Renal Carcinoma by LC-HRMS and PLS-DA. Analytical and Bioanalytical Chemistry, 410(16): 3859–3869.

Miikkulainen P, Högel H, Seyednasrollah F, et al., 2019, Hypoxia-Inducible Factor (HIF)-Prolyl Hydroxylase 3 (PHD3) Maintains High HIF2A mRNA Levels in Clear Cell Renal Cell Carcinoma. J Biol Chem, 294(10): 3760–3771.

Kampantais S, Kotoula V, Kounatidis I, et al., 2020, mRNA Overexpression of Prolyl Hydroxylase PHD3 is Inversely Related to Nuclear Grade in Renal Cell Carcinoma. Mol Clin Oncol, 13(3): 11.

Kim KH, Lee HH, Yoon YE, et al., 2019, Prolyl Hydroxylase-3 is a Novel Renal Cell Carcinoma Biomarker. Investigative and Clinical Urology, 60(6): 425–431.

Zhang KJ, Wilson GD, Kara S, et al., 2019, Diagnostic Role of Kidney Injury Molecule-1 in Renal Cell Carcinoma. International Urology and Nephrology, 51(11): 1893–1902.

Kushlinskii NE, Gershtein ES, Naberezhnov DS, et al., 2019, Kidney Injury Molecule-1 (KIM-1) in Blood Plasma of Patients with Clear-Cell Carcinoma. Bull Exp Biol Med, 167(3): 388–392.

Koh Y, Nakano K, Katayama K, et al., 2022, Early Dynamics of Circulating Tumor DNA Predict Clinical Response to Immune Checkpoint Inhibitors in Metastatic Renal Cell Carcinoma. International Journal of Urology: Official Journal of the Japanese Urological Association, 29(5): 462–469.

Nuzzo PV, Berchuck JE, Korthauer K, et al., 2020, Detection of Renal Cell Carcinoma using Plasma and Urine Cell-free DNA Methylomes. Nature Medicine, 26(7): 1041–1043.