Metabolomic biomarkers of multiple myeloma: A systematic review

• Published in: Biochimica et biophysica acta. Reviews on cancer 2024-09, Vol.1879 (5), p.189151, Article 189151
• Main Authors: Varzieva, Valeria G., Mesonzhnik, Natalia V., Ilgisonis, Irina S., Belenkov, Yuri N., Kozhevnikova, Maria V., Appolonova, Svetlana A.
• Format: Article
• Language: English
• Subjects: Amino acids; Biomarkers; Biomarkers, Tumor - analysis; Biomarkers, Tumor - metabolism; Diagnosis; Humans; Lipid metabolism; Metabolomics; Metabolomics - methods; Multiple myeloma; Multiple Myeloma - diagnosis; Multiple Myeloma - metabolism; Multiple Myeloma - pathology; Prognosis; Systematic review
• ISSN: 0304-419X; 1879-2561; 1879-2561
• DOI: 10.1016/j.bbcan.2024.189151

Multiple myeloma (MM) is an incurable malignancy of clonal plasma cells. Various diagnostic methods are used in parallel to accurately determine stage and severity of the disease. Identifying a biomarker or a panel of biomarkers could enhance the quality of medical care that patients receive by adopting a more personalized approach. Metabolomics utilizes high-throughput analytical platforms to examine the levels and quantities of biochemical compounds in biosamples. The aim of this review was to conduct a systematic literature search for potential metabolic biomarkers that may aid in the diagnosis and prognosis of MM. The review was conducted in accordance with PRISMA recommendations and was registered in PROSPERO. The systematic search was performed in PubMed, CINAHL, SciFinder, Scopus, The Cochrane Library and Google Scholar. Studies were limited to those involving people with clinically diagnosed MM and healthy controls as comparators. Articles had to be published in English and had no restrictions on publication date or sample type. The quality of articles was assessed according to QUADOMICS criteria. A total of 709 articles were collected during the literature search. Of these, 436 were excluded based on their abstract, with 26 more removed after a thorough review of the full text. Finally, 16 articles were deemed relevant and were subjected to further analysis of their data. A number of promising candidate biomarkers was discovered. Follow-up studies with large sample sizes are needed to determine their suitability for clinical applications. •Significant dysregulation of amino acid metabolism affects both progression and prognosis of multiple myeloma.•Changes in lipid metabolism in multiple myeloma offer potential diagnostic biomarkers.•Research is crucial to confirm clinical utility of biomarkers for multiple myeloma diagnosis and prognosis.