Detection of early relapse in multiple myeloma patients
Abstract Background Multiple myeloma (MM) represents the second most common hematological malignancy characterized by the infiltration of the bone marrow by plasma cells that produce monoclonal immunoglobulin. While the quality and length of life of MM patients have significantly increased, MM remai...
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BMC
2025-01-01
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| Series: | Cell Division |
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| Online Access: | https://doi.org/10.1186/s13008-025-00143-3 |
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| author | Tereza Růžičková Monika Vlachová Lukáš Pečinka Monika Brychtová Marek Večeřa Lenka Radová Simona Ševčíková Marie Jarošová Josef Havel Luděk Pour Sabina Ševčíková |
| author_facet | Tereza Růžičková Monika Vlachová Lukáš Pečinka Monika Brychtová Marek Večeřa Lenka Radová Simona Ševčíková Marie Jarošová Josef Havel Luděk Pour Sabina Ševčíková |
| author_sort | Tereza Růžičková |
| collection | DOAJ |
| description | Abstract Background Multiple myeloma (MM) represents the second most common hematological malignancy characterized by the infiltration of the bone marrow by plasma cells that produce monoclonal immunoglobulin. While the quality and length of life of MM patients have significantly increased, MM remains a hard-to-treat disease; almost all patients relapse. As MM is highly heterogenous, patients relapse at different times. It is currently not possible to predict when relapse will occur; numerous studies investigating the dysregulation of non-coding RNA molecules in cancer suggest that microRNAs could be good markers of relapse. Results Using small RNA sequencing, we profiled microRNA expression in peripheral blood in three groups of MM patients who relapsed at different intervals. In total, 24 microRNAs were significantly dysregulated among analyzed subgroups. Independent validation by RT-qPCR confirmed changed levels of miR-598-3p in MM patients with different times to relapse. At the same time, differences in the mass spectra between groups were identified using matrix-assisted laser desorption/ionization time of flight mass spectrometry. All results were analyzed by machine learning. Conclusion Mass spectrometry coupled with machine learning shows potential as a reliable, rapid, and cost-effective preliminary screening technique to supplement current diagnostics. |
| format | Article |
| id | doaj-art-9cf988bb156948ac8fc303f75f8d85bf |
| institution | Kabale University |
| issn | 1747-1028 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Cell Division |
| spelling | doaj-art-9cf988bb156948ac8fc303f75f8d85bf2025-02-02T12:33:47ZengBMCCell Division1747-10282025-01-0120111110.1186/s13008-025-00143-3Detection of early relapse in multiple myeloma patientsTereza Růžičková0Monika Vlachová1Lukáš Pečinka2Monika Brychtová3Marek Večeřa4Lenka Radová5Simona Ševčíková6Marie Jarošová7Josef Havel8Luděk Pour9Sabina Ševčíková10Babak Myeloma Group, Department of Pathophysiology, Faculty of Medicine, Masaryk UniversityBabak Myeloma Group, Department of Pathophysiology, Faculty of Medicine, Masaryk UniversityResearch Centre for Applied Molecular Oncology (RECAMO), Masaryk Memorial Cancer InstituteBabak Myeloma Group, Department of Pathophysiology, Faculty of Medicine, Masaryk UniversityCentre for Molecular Medicine, Central European Institute of Technology, Masaryk UniversityCentre for Molecular Medicine, Central European Institute of Technology, Masaryk UniversityBabak Myeloma Group, Department of Pathophysiology, Faculty of Medicine, Masaryk UniversityDepartment of Internal Medicine, Hematology and Oncology, University Hospital BrnoDepartment of Chemistry, Faculty of Science, Masaryk UniversityDepartment of Internal Medicine, Hematology and Oncology, University Hospital BrnoBabak Myeloma Group, Department of Pathophysiology, Faculty of Medicine, Masaryk UniversityAbstract Background Multiple myeloma (MM) represents the second most common hematological malignancy characterized by the infiltration of the bone marrow by plasma cells that produce monoclonal immunoglobulin. While the quality and length of life of MM patients have significantly increased, MM remains a hard-to-treat disease; almost all patients relapse. As MM is highly heterogenous, patients relapse at different times. It is currently not possible to predict when relapse will occur; numerous studies investigating the dysregulation of non-coding RNA molecules in cancer suggest that microRNAs could be good markers of relapse. Results Using small RNA sequencing, we profiled microRNA expression in peripheral blood in three groups of MM patients who relapsed at different intervals. In total, 24 microRNAs were significantly dysregulated among analyzed subgroups. Independent validation by RT-qPCR confirmed changed levels of miR-598-3p in MM patients with different times to relapse. At the same time, differences in the mass spectra between groups were identified using matrix-assisted laser desorption/ionization time of flight mass spectrometry. All results were analyzed by machine learning. Conclusion Mass spectrometry coupled with machine learning shows potential as a reliable, rapid, and cost-effective preliminary screening technique to supplement current diagnostics.https://doi.org/10.1186/s13008-025-00143-3Multiple myelomaLiquid biopsyRelapsemicroRNAMALDI-TOF MSSmall RNA seq |
| spellingShingle | Tereza Růžičková Monika Vlachová Lukáš Pečinka Monika Brychtová Marek Večeřa Lenka Radová Simona Ševčíková Marie Jarošová Josef Havel Luděk Pour Sabina Ševčíková Detection of early relapse in multiple myeloma patients Cell Division Multiple myeloma Liquid biopsy Relapse microRNA MALDI-TOF MS Small RNA seq |
| title | Detection of early relapse in multiple myeloma patients |
| title_full | Detection of early relapse in multiple myeloma patients |
| title_fullStr | Detection of early relapse in multiple myeloma patients |
| title_full_unstemmed | Detection of early relapse in multiple myeloma patients |
| title_short | Detection of early relapse in multiple myeloma patients |
| title_sort | detection of early relapse in multiple myeloma patients |
| topic | Multiple myeloma Liquid biopsy Relapse microRNA MALDI-TOF MS Small RNA seq |
| url | https://doi.org/10.1186/s13008-025-00143-3 |
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