Metabolomic analysis of biological material using LC-MS in the quest for urinary system cancer biomarkers – review
PDF

Keywords

mass spectrometry
metabolomics
kidney cancer
bladder cancer

Abstract

Kidney cancer (RCC) and bladder cancer (BC) are among the most frequently diagnosed cancers worldwide. They are characterized by high mortality and recurrence rates. In response to the rising incidence and mortality rates, scientists are exploring innovative diagnostic and therapeutic methods. Metabolomics, which analyzes metabolite levels, may enable early diagnosis and monitoring of therapy progress. Compared to other omics technologies, it focuses on the outcomes of metabolite activity, providing a unique perspective on processes occurring in cancer cells. Metabolomic analyses utilize techniques such as mass spectrometry. These methods allow the identification of biomarkers and precise determination of the chemical composition of biological samples. However, the most commonly used method is liquid chromatography-mass spectrometry (LC-MS), which enables the most comprehensive screening of cancer metabolomes. Recent studies show significant progress in recognizing characteristic metabolites associated with urological cancers, although this area remains partially unexplored. Research on circulating metabolites, especially in easily accessible samples like blood or urine, demonstrates promising potential in clinical practice. Study results reveal differences in metabolic profiles between various stages of cancer advancement, which may have clinical significance. The future of this field involves an increasing number of clinical cohorts, standardization of sample preparation, and further improvements in instrument sensitivity and speed. LC-MS-based metabolomics has the potential to contribute to the improvement of diagnostics, therapy, and the quality of life for patients with urological cancers. However, challenges, such as the lack of uniform methodologies and understanding of metabolite determinants, require further research and innovation.

https://doi.org/10.7862/rc.2024.1
PDF

References

Wang, W., Rong, Z., Wang, G. et al. Cancer metabolites: promising biomarkers for cancer liquid biopsy. Biomark Res. 11, 66 (2023).

Nizioł, J., Ossoliński, K., Płaza-Altamer, A. et al. Untargeted ultra-high-resolution mass spectrometry metabolomic profiling of blood serum in bladder cancer. Sci Rep. 12, 15156 (2022).

Nizioł J, Ossoliński K, Tripet BP, et al. Nuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based metabolome profiling of urine samples from kidney cancer patients. J Pharm Biomed Anal. 193, 113752 (2021).

Xin Ma, Facundo M. Fernández. Advances in mass spectrometry imaging for spatial cancer metabolomics. Mass Spec Rev. 43(2), 21804 (2022).

Macklin, A., Khan, S. Kislinger, T. Recent advances in mass spectrometry based clinical proteomics: applications to cancer research. Clin Proteom. 17, 17 (2020).

Zeki, Ö. C. et al. Integration of GC–MS and LC–MS for untargeted metabolomics profiling. J Pharm Biomed Analysis. 190, 113509 (2020).

Schmidt, D. R., Patel R., Kirsch D. et al. Metabolomics in cancer research and emerging applications in clinical oncology. CA A Cancer J Clin. 71(4), 333-358 (2021).

Kind T, Tolstikov V, Fiehn O, et al. A comprehensive urinary metabolomic approach for identifying kidney cancer. Analytical Biochemistry. 363(2), 185-195 (2007).

Issaq HJ, Nativ O., Waybright T. et al. Detection of Bladder Cancer in Human Urine by Metabolomic Profiling Using High Performance Liquid Chromatography/Mass Spectrometry. J Urol. 179(6) 2422 2426 (2008).

Oto J., Fernández-Pardo Á., Roca M. et al. LC–MS metabolomics of urine reveals distinct profiles for non-muscle-invasive and muscle-invasive bladder cancer. World J Urol. 40, 2387–2398 (2022).

Yang M., Liu X., Tang X. et al. LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer. Front. Oncol. 13, 1160965 (2023).

Lin L., Yu Q., Yan X. et al. Direct infusion mass spectrometry or liquid chromatography mass spectrometry for human metabonomics? A serum metabonomic study of kidney cancer. Analyst, 135(11) 2970-2978. (2010).

Lin L., Huang Z., Chen Y. et al. LC-MS-based serum metabolic profiling for genitourinary cancer classification and cancer type-specific biomarker discovery. Proteomics. 12, 2238–2246 (2012).

Liu X., Zhang M., Cheng X. et al. LC-MS-Based Plasma Metabolomics and Lipidomics Analyses for Differential Diagnosis of Bladder Cancer and Renal Cell Carcinoma. Front. Oncol. 10, 717 (2020).

Bar N., Korem T., Weissbrod O. et al. A reference map of potential determinants for the human serum metabolome. Nature. 588, 135–140 (2020).

Huang Z., Lin L., Gao Y. et al. Bladder cancer determination via two urinary metabolites: a biomarker pattern approach. Mol Cell Proteomics. 10(10) M111.007922 (2011).

Putluri N., Shojaie A., Vasu V.T. et al. Metabolomic profiling reveals potential markers and bioprocesses altered in bladder cancer progression. Cancer Res. 71(24) 7376-86 (2011).

Alberice J.V., Amaral A.F.S., Armitage E.G. et al. Searching for urine biomarkers of bladder cancer recurrence using a liquid chromatography-mass spectrometry and capillary electrophoresis-mass spectrometry metabolomics approach. J Chromatogr A. 1318, 163-70 (2013).

Jin X., Yun S.J., Jeong P. et al. Diagnosis of bladder cancer and prediction of survival by urinary metabolomics. Oncotarget. 5(6) 1635-1645 (2014).

Shao C.H., Chen C.L., Lin J.Y.et al. Metabolite marker discovery for the detection of bladder cancer by comparative metabolomics. Oncotarget. 8(24) 38802-38810 (2017).

Łuczykowski K., Warmuzińska N., Operacz S.,et al. Metabolic Evaluation of Urine from Patients Diagnosed with High Grade (HG) Bladder Cancer by SPME-LC-MS Method. Molecules. 26(8) 2194 (2021).

Zhang M., Liu X., Liu X. et al. A pilot investigation of a urinary metabolic biomarker discovery in renal cell carcinoma. Int Urol Nephrol. 52(3) 437-446 (2020).

Tan G., Wang H., Yuan J. et al. Three serum metabolite signatures for diagnosing low-grade and high grade bladder cancer. Sci Rep. 7, 46176 (2017).

Sahu D., Lotan Y., Wittmann B. et al. Metabolomics analysis reveals distinct profiles of nonmuscle invasive and muscle-invasive bladder cancer. Cancer Med. 6(9) 2106-2120 (2017).

Vantaku V., Donepudi S.R., Piyarathna D.W.B. et al. Large-scale profiling of serum metabolites in African American and European American patients with bladder cancer reveals metabolic pathways associated with patient survival. Cancer. 125(6) 921-932 (2019).

Amara C.S., Ambati C.R., Vantaku V. et al. Serum Metabolic Profiling Identified a Distinct Metabolic Signature in Bladder Cancer Smokers: A Key Metabolic Enzyme Associated with Patient Survival. Cancer Epidemiol Biomarkers Prev. 28(4) 770-781 (2019).