Research Progress of Metabolomics in Surgical Precision Medicine

doi:10.3969/j.issn.1009-976X.2025.06.009

Abstract

Abstract: Metabolomics is an important branch of systems biology, mainly studying the composition and dynamic changes of endogenous small molecules in organisms. Due to its ability to reflect the phenotype of the body and its rapid response to physiological and pathological changes, it provides an important strategy for the diagnosis and treatment of the surgical precision medicine. This article briefly describes the core concepts, mainstream methods, standard experimental procedures and quality control principles of metabolomics technology, and focuses on summarizing its main research progress in the fields of tumor and non-tumor surgery, including risk assessment, lesion identification, prognosis monitoring and perioperative management. It also analyzes the challenges that metabolomics technology currently faces in the process of clinical transformation, such as the standardization of samples and databases, the verification of result repeatability, and the complexity of deep integration of multi-omics data. In the future, with the development of nanosensors and artificial intelligence analysis technology, metabolomics technology is expected to promote the transformation of the predictive model of precision medicine in surgery.

Key words: metabolomics, surgery, precision medicine, clinical translation

摘要： 代谢组学是系统生物学的重要组成分支,主要研究生物内源性小分子的组成与动态变化。因其能够反映机体表型,对生理病理变化响应迅速,为外科精准医学的诊疗提供了重要策略。本文简述代谢组学技术的核心概念、主流手段、标准实验流程和质量控制原则,重点概括其在肿瘤与非肿瘤外科领域的主要研究进展,包括风险评估、病灶识别、预后监测及围手术期管理等方面,并分析代谢组学技术目前在临床转化过程中面临样本和数据库标准化、结果重复性验证以及多组学数据深度整合复杂等挑战。未来随着纳米传感器和人工智能解析技术的发展,代谢组学技术有望推动外科精准医学预见性模式转型。

关键词: 代谢组学, 外科, 精准医学, 临床转化

CLC Number:

R602
R730

CEN Mei-feng, PAN Wen-feng, WANG Xiao-juan. Research Progress of Metabolomics in Surgical Precision Medicine[J]. Lingnan Modern Clinics In Surgery, 2025, 25(06): 399-409.

岑美凤, 潘文锋, 王小娟. 代谢组学在外科精准医学的研究进展[J]. 岭南现代临床外科, 2025, 25(06): 399-409.

References

[1] Ogrinc N, Saudemont P, Takats Z, et al.Cancer Surgery 2.0: Guidance by Real-Time Molecular Technologies[J]. Trends Mol Med, 2021, 27(6): 602-615.
[2] Coutu B, Ryan E, Christensen D, et al.Positive margins matter regardless of subsequent resection findings[J]. Oral Oncol, 2022, 128: 105850.
[3] Chougule T, Gupta RK, Saini J, et al.Radiomics signature for temporal evolution and recurrence patterns of glioblastoma using multimodal magnetic resonance imaging[J]. NMR Biomed, 2022, 35(3): e4647.
[4] Geraghty BJ, Dasgupta A, Sandhu M, et al.Predicting survival in patients with glioblastoma using MRI radiomic features extracted from radiation planning volumes[J]. J Neurooncol, 2022, 156(3): 579-588.
[5] Aftab K, Aamir FB, Mallick S, et al.Radiomics for precision medicine in glioblastoma[J]. J Neurooncol, 2022, 156(2): 217-231.
[6] Han YZ, Du BX, Zhu XY, et al.Lipid metabolism disorder in diabetic kidney disease[J]. Frontiers in Endocrinology, 2024,15: 1336402.
[7] Armstrong DG, Boulton AJM, Bus SA.Diabetic Foot Ulcers and Their Recurrence[J]. N Engl J Med, 2017, 376(24): 2367-2375.
[8] Holland WL, Summers SA.Sphingolipids, insulin resistance, and metabolic disease: new insights from in vivo manipulation of sphingolipid metabolism[J]. Endocr Rev, 2008, 29(4): 381-402.
[9] Li TA, Apte U.Bile Acid Metabolism and Signaling in Cholestasis, Inflammation, and Cancer[J]. Adv Pharmacol, 2015, 74: 263-302.
[10] Newgard CB.Interplay between lipids and branched-chain amino acids in development of insulin resistance[J]. Cell Metab, 2012, 15(5): 606-614.
[11] Younossi Z, Anstee QM, Marietti M, et al.Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention[J]. Nat Rev Gastroenterol Hepatol, 2018, 15(1): 11-20.
[12] Blackburn PR, Gass JM, Vairo FPE, et al.Maple syrup urine disease: mechanisms and management[J]. Appl Clin Genet, 2017, 10: 57-66.
[13] Rickels MR, Robertson RP.Pancreatic Islet Transplantation in Humans: Recent Progress and Future Directions[J]. Endocr Rev, 2019, 40(2): 631-668.
[14] Ketavarapu V, Ramunaidu A, Ragi N, et al.Plasma lipidomics stratify type3c and type 2 diabetes: implications for precision treatment[J]. Pancreatology, 2023, 23(8): e12.
[15] Liu XJ, Locasale JW.Metabolomics: A Primer[J]. Trends Biochem Sci, 2017, 42(4): 274-284.
[16] Qiu S, Cai Y, Yao H, et al.Small molecule metabolites: discovery of biomarkers and therapeutic targets[J]. Signal Transduct Target Ther, 2023, 8(1): 132.
[17] Ma X, Fernández FM.Advances in mass spectrometry imaging for spatial cancer metabolomics[J]. Mass Spectrom Rev, 2024, 43(2): 235-268.
[18] Phelps DL, Balog J, Gildea LF, et al.The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS)[J]. Br J Cancer, 2018, 118(10): 1349-1358.
[19] Nicholson JK, Connelly J, Lindon JC, et al.Metabonomics: a platform for studying drug toxicity and gene function[J]. Nat Rev Drug Discov, 2002, 1(2): 153-161.
[20] Astarita G, Kelly RS, Lasky-Su J.Metabolomics and lipidomics strategies in modern drug discovery and development[J]. Drug Discov Today, 2023, 28(10): 103751.
[21] Karnovsky A, Li S.Pathway Analysis for Targeted and Untargeted Metabolomics[J]. Methods Mol Biol, 2020, 2104: 387-400.
[22] Hajnajafi K, Iqbal MA.Mass-spectrometry based metabolomics: an overview of workflows, strategies, data analysis and applications[J]. Proteome Sci, 2025, 23(1): 5.
[23] Han XL, Gross RW.The foundations and development of lipidomics[J]. J Lipid Res, 2022, 63(2): 100164.
[24] Planque M, Igelmann S, Campos AMF, et al.Spatial metabolomics principles and application to cancer research[J]. Curr Opin Chem Biol, 2023, 76: 102362.
[25] Emwas AH, Szczepski K, Al-Younis I, et al.Fluxomics - New Metabolomics Approaches to Monitor Metabolic Pathways[J]. Front Pharmacol, 2022, 13: 805782.
[26] Gika H, Virgiliou C, Theodoridis G, et al.Untargeted LC/MS-based metabolic phenotyping (metabonomics/metabolomics): The state of the art[J]. J Chromatogr B Analyt Technol Biomed Life Sci, 2019, 1117: 136-147.
[27] Beale DJ, Pinu FR, Kouremenos KA, et al.Review of recent developments in GC-MS approaches to metabolomics-based research[J]. Metabolomics, 2018, 14(11): 152.
[28] Wishart DS, Cheng LL, Copié V, et al.NMR and Metabolomics-A Roadmap for the Future[J]. Metabolites, 2022, 12(8): 678.
[29] Boiteau RM, Hoyt DW, Nicora CD, et al.Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction[J]. Metabolites, 2018, 8(1): 8.
[30] He MJ, Pu W, Wang X, et al.Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies[J]. Front Oncol, 2022, 12: 891018.
[31] Paraskevaidi M, Cameron SJS, Whelan E, et al.Laser-assisted rapid evaporative ionisation mass spectrometry (LA-REIMS) as a metabolomics platform in cervical cancer screening[J]. EBioMedicine, 2020, 60: 103017.
[32] Chetwynd AJ, Dunn WB, Rodriguez-Blanco G.Collection and Preparation of Clinical Samples for Metabolomics[J]. Adv Exp Med Biol, 2017, 965: 19-44.
[33] Mosley JD, Schock TB, Beecher CW, et al.Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics[J]. Metabolomics, 2024, 20(2): 20.
[34] Lippa KA, Aristizabal-Henao JJ, Beger RD, et al.Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)[J]. Metabolomics, 2022, 18(4): 24.
[35] Rocca-Serra P, Salek RM, Arita M, et al.Data standards can boost metabolomics research, and if there is a will, there is a way[J]. Metabolomics, 2016, 12: 14.
[36] Čuklina J, Lee CH, Williams EG, et al.Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial[J]. Mol Syst Biol, 2021, 17(8): e10240.
[37] Altea-Manzano P, Decker-Farrell A, Janowitz T, et al.Metabolic interplays between the tumour and the host shape the tumour macroenvironment[J]. Nat Rev Cancer, 2025, 25(4): 274-292.
[38] Lyu S, Gildor N, Zhang Q, et al.Rewiring cancer metabolism: oncogenic signaling pathways and targeted therapeutics[J]. Sci China Life Sci, 2025, 68(11): 3281-3302.
[39] Jin H, Wang J, Wang Z, et al.Lipid metabolic reprogramming in tumor microenvironment: from mechanisms to therapeutics[J]. J Hematol Oncol, 2023, 16(1): 103.
[40] Wu XJ, Tan XJ, Bao YQ, et al.Landscape of metabolic alterations and treatment strategies in breast cancer[J]. Genes Dis, 2025, 12(5): 101521.
[41] Gao ZY, Zhou WX, Lv XY, et al.Metabolomics as a Critical Tool for Studying Clinical Surgery[J]. Crit Rev Anal Chem, 2024, 54(7): 2245-2258.
[42] Damerell V, Klaassen-Dekker N, Brezina S, et al.Circulating tryptophan-kynurenine pathway metabolites are associated with all-cause mortality among patients with stage I-III colorectal cancer[J]. Int J Cancer, 2025, 156(3): 552-565.
[43] Nenkov M, Ma Y, Ga?ler N, et al. Metabolic Reprogramming of Colorectal Cancer Cells and the Microenvironment: Implication for Therapy[J]. Int J Mol Sci, 2021, 22(12): 6262.
[44] Zhu MJ, Hu YY, Gu YJ, et al.Role of amino acid metabolism in tumor immune microenvironment of colorectal cancer[J]. Am J Cancer Res, 2025, 15(1): 233-247.
[45] Martínez-Reyes I, Chandel NS.Cancer metabolism: looking forward[J]. Nat Rev Cancer, 2021, 21(10): 669-680.
[46] Steeg PS.Tumor metastasis: mechanistic insights and clinical challenges[J]. Nat Med, 2006, 12(8): 895-904.
[47] Zhan QR, Liu BX, Situ XH, et al.New insights into the correlations between circulating tumor cells and target organ metastasis[J]. Signal Transduct Target Ther, 2024, 9(1): 211-233.
[48] Dai CS, Mishra A, Edd J, et al.Circulating tumor cells: Blood-based detection, molecular biology, and clinical applications[J]. Cancer Cell, 2025, 43(8): 1399-1422.
[49] Bergers G, Fendt SM.The metabolism of cancer cells during metastasis[J]. Nature reviews. Cancer, 2021, 21(3): 162-180.
[50] Sreekumar A, Poisson LM, Rajendiran TM, et al.Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression[J]. Nature, 2009, 457(7231): 910-914.
[51] Cao YY, Zhao R, Guo K, et al.Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma[J]. Front Oncol, 2022, 11:744667.
[52] Han J, Qin W, Li Z, et al.Tissue and serum metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma[J]. Clin Chim Acta, 2019, 488: 68-75.
[53] Padthaisong S, Phetcharaburanin J, Klanrit P, et al.Integration of global metabolomics and lipidomics approaches reveals the molecular mechanisms and the potential biomarkers for postoperative recurrence in early-stage cholangiocarcinoma[J]. Cancer Metab, 2021, 9(1): 30.
[54] Abooshahab R, Zarkesh M, Hedayati M.Metabolomics fingerprinting of thyroid malignancies: a GC/MS-based approach for subtype classification and biomarker discovery[J]. BMC cancer, 2025, 25(1): 1-13.
[55] Chen F, Dai X, Zhou C, et al.Integrated analysis of the faecal metagenome and serum metabolome reveals the role of gut microbiome-associated metabolites in the detection of colorectal cancer and adenoma[J]. Gut, 2022, 71(7): 1315-1325.
[56] Coker OO, Liu C, Wu WKK, et al.Altered gut metabolites and microbiota interactions are implicated in colorectal carcinogenesis and can be non-invasive diagnostic biomarkers[J]. Microbiome, 2022, 10(1): 35.
[57] Seum T, Frick C, Cardoso R, et al.Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection[J]. NPJ Precis Oncol, 2024, 8(1): 244.
[58] 刘金豪, 王季堃, 史祚秀, 等. 血清氨基酸水平与结直肠癌淋巴结转移关系的初步研究[J] .中华普通外科杂志, 2021, 36(6) : 468-469.
[59] Wang Z, Liu X, Liu X, et al.UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma[J]. BMC Cancer, 2019, 19(1): 1195.
[60] Liu XY, Zhang MX, Liu X, et al.Urine metabolomics for renal cell carcinoma (RCC) prediction: tryptophan metabolism as an important pathway in RCC[J]. Front Oncol, 2019, 9: 663.
[61] Sato T, Kawasaki Y, Maekawa M, et al.Accurate quantification of urinary metabolites for predictive models manifest clinicopathology of renal cell carcinoma[J]. Cancer Sci, 2020, 111(7): 2570-2578.
[62] Xu ZY, Huang YD, Hu C, et al.Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicentre study[J]. Gut, 2023, 72(11): 2051-2067.
[63] Gong SS, Huang RF, Wang ME, et al.Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer[J]. J Transl Med, 2024, 22(1): 1016.
[64] Fan Y, Zhou X, Xia T, et al.Human plasma metabolomics for identifying differential metabolites and predicting molecular subtypes of breast cancer[J]. Oncotarget, 2016, 7(9): 9925-9938.
[65] Li KK, Wang RM, Gu ZY, et al.Serum metabolic profiling enables diagnosis, prognosis, and monitoring for brainstem gliomas[J]. Nat Commun, 2025, 16(1): 6108.
[66] Xu Y, Hu X, Yuan Y, et al.Prediction of Lung Cancer Metastasis Risk Based on Single-Cell Metabolic Profiling of Circulating Tumor Cells[J]. Adv Sci (Weinh), 2025, 12(39): e08878.
[67] Hese LV, Vleeschouwer SD, Theys T, et al.Towards real-time intraoperative tissue interrogation for REIMS-guided glioma surgery[J]. J Mass Spectrom Adv Clin Lab, 2022, 24: 80-89.
[68] Balog J, Sasi-Szabó L, Kinross J, et al. Intraoperative tissue identification using rapid evaporative ionization mass spectrometry [J]. Sci Transl Med, 2013, 5(194): 194ra93.
[69] Tzafetas M, Mitra A, Paraskevaidi M, et al.The intelligent knife (iKnife) and its intraoperative diagnostic advantage for the treatment of cervical disease[J]. Proc Natl Acad Sci, 2020, 117(13): 7338-7346.
[70] Alexander J, Gildea L, Balog J, et al.A novel methodology for in vivo endoscopic phenotyping of colorectal cancer based on real-time analysis of the mucosal lipidome: a prospective observational study of the iKnife[J]. Surg Endosc, 2017, 31(3): 1361-1370.
[71] Koundouros N, Karali E, Tripp A, et al. Metabolic Fingerprinting Links Oncogenic PIK3CA with Enhanced Arachidonic Acid-Derived Eicosanoids [J]. Cell, 2020, 181(7): 1596-1611.e27.
[72] King ME, Zhang J, Lin JQ, et al.Rapid diagnosis and tumor margin assessment during pancreatic cancer surgery with the MasSpec Pen technology[J]. Proc Natl Acad Sci U S A, 2021, 118(28): e2104411118.
[73] Sans M, Zhang J, Lin JQ, et al.Performance of the MasSpec Pen for Rapid Diagnosis of Ovarian Cancer[J]. Clin Chem, 2019, 65(5): 674-683.
[74] Garza KY, King ME, Nagi C, et al.Intraoperative Evaluation of Breast Tissues During Breast Cancer Operations Using the MasSpec Pen[J]. JAMA Netw Open, 2024, 7(3): e242684.
[75] Kumar BS.Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview[J]. Anal Methods, 2023, 15(31): 3768-3784.
[76] Eberlin LS, Norton I, Orringer D, et al.Ambient mass spectrometry for the intraoperative molecular diagnosis of human brain tumors[J]. Natl Acad Sci, 2013, 110(5): 1611-1616.
[77] Santagata S, Eberlin LS, Norton I, et al.Intraoperative mass spectrometry mapping of an onco-metabolite to guide brain tumor surgery[J]. Proc Natl Acad Sci, 2014, 111(30): 11121-11126.
[78] Yang XH, Song XW, Zhang XX, et al.In situ DESI-MSI lipidomic profiles of mucosal margin of oral squamous cell carcinoma[J]. EBioMedicine, 2021, 70: 103529.
[79] Yang XH, Zhang XX, Jing Y, et al.Amino acids signatures of distance-related surgical margins of oral squamous cell carcinoma[J]. EBioMedicine, 2019, 48: 81-91.
[80] Vaysse P, Demers I, Hout MFCMVD, et al.Evaluation of the Sensitivity of Metabolic Profiling by Rapid Evaporative Ionization Mass Spectrometry: Toward More Radical Oral Cavity Cancer Resections[J]. Anal Chem, 2022, 94(19): 6939-6947.
[81] Vaysse PM, Kooreman LFS, Engelen SME, et al.Stromal vapors for real-time molecular guidance of breast-conserving surgery[J]. Sci Rep, 2020, 10(1): 20109.
[82] Eberlin LS, Tibshirani RJ, Zhang J, et al.Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging[J]. Proc Natl Acad Sci, 2014, 111(7): 2436-2441.
[83] Zhang JL, Yu WD, Ryu SW, et al.Cardiolipins are biomarkers of mitochondria-rich thyroid oncocytic tumors[J]. Cancer Res, 2016, 76(22): 6588-6597.
[84] Abedini A, Levinsohn J, Kl?tzer KA, et al. Single-cell multi-omic and spatial profiling of human kidneys implicates the fibrotic microenvironment in kidney disease progression[J]. Nat Genet, 2024, 56(8): 1712-1724.
[85] Wu JH, Fang XQ, Zhang HY, et al.Point-of-care mass spectrometry metabolomic analysis enabling intraoperative brain tumor diagnosis[J]. Theranostics, 2025, 15(16): 8137-8149.
[86] Guenther S, Muirhead LJ, Speller AVM, et al.Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry[J]. Cancer Res, 2015, 75(9): 1828-1837.
[87] Mondal S, Sthanikam Y, Kumar A, et al.Mass Spectrometry Imaging of Lumpectomy Specimens Deciphers Diacylglycerols as Potent Biomarkers for the Diagnosis of Breast Cancer[J]. Anal Chem, 2023, 95(20): 8054-8062.
[88] Vo D, Trinh KTL.Emerging Biomarkers in Metabolomics: Advancements in Precision Health and Disease Diagnosis[J]. Int J Mol Sci, 2024, 25(23): 13190.
[89] Horn DL, Bettcher LF, Navarro SL, et al.Persistent metabolomic alterations characterize chronic critical illness after severe trauma[J]. J Trauma Acute Care Surg, 2021, 90(1): 35-45.
[90] Pandey S.Advances in metabolomics in critically ill patients with sepsis and septic shock[J]. Clin Exp Emerg Med, 2025, 12(1): 4-15.
[91] Langley RJ, Tsalik EL, Velkinburgh JCV, et al. An integrated clinico-metabolomic model improves prediction of death in sepsis [J]. Sci Transl Med, 2013, 5(195): 195ra95.
[92] Rogers AJ, Mcgeachie M, Baron RM, et al.Metabolomic derangements are associated with mortality in critically ill adult patients[J]. PLoS One, 2014, 9(1): e87538.
[93] Stanimirova I, Banasik M, Z?bek A, et al. Serum metabolomics approach to monitor the changes in metabolite profiles following renal transplantation[J]. Sci Rep, 2020, 10(1): 17223.
[94] Serkova NJ, Zhang Y, Coatney JL, et al.Early detection of graft failure using the blood metabolic profile of a liver recipient[J]. Transplantation, 2007, 83(4): 517-521.
[95] Tsai H, Lo C, Lee C, et al.A panel of biomarkers in the prediction for early allograft dysfunction and mortality after living donor liver transplantation[J]. Am J Transl Res, 2021, 13(1): 372-382.
[96] Simonato M, Fochi I, Vedovelli L, et al.Urinary metabolomics reveals kynurenine pathway perturbation in newborns with transposition of great arteries after surgical repair[J]. Metabolomics, 2019, 15(11): 145.
[97] Correia GDS, Ng KW, Wijeyesekera A, et al.Metabolic Profiling of Children Undergoing Surgery for Congenital Heart Disease[J]. Crit Care Med, 2015, 43(7): 1467-1476.
[98] Cui HT, Chen YH, Li K, et al.Untargeted metabolomics identifies succinate as a biomarker and therapeutic target in aortic aneurysm and dissection[J]. Eur Heart J, 2021, 42(42): 4373-4385.
[99] Chen XM, Ye JY, Lei H, et al.Novel potential diagnostic serum biomarkers of metabolomics in osteoarticular tuberculosis patients: A preliminary study[J]. Front Cell Infect Microbiol, 2022, 12: 827528.
[100] Duan XL, Zhang T, Ou LL, et al.1H NMR-based metabolomic study of metabolic profiling for the urine of kidney stone patients[J]. Urolithiasis, 2020, 48(1): 27-35.
[101] Lv JL, Pan C, Cai YP, et al.Plasma metabolomics reveals the shared and distinct metabolic disturbances associated with cardiovascular events in coronary artery disease[J]. Nat Commun, 2024, 15(1): 5729.
[102] Chen CY, Wang J, Pan DH, et al.Applications of multi-omics analysis in human diseases[J]. MedComm, 2023, 4(4): e315.