Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis
Abstract Background Multiple myeloma (MM) is the most aggressive and prevalent primary malignant tumor within the blood system, and can be classified into grades RISS-I, II, and III. High-grade tumors are associated with decreased survival rates and increased recurrence rates. To better understand m...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-02-01
|
| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-024-05848-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823861629850222592 |
|---|---|
| author | Xiaoxue Wang Longhao Cheng Aijun Liu Lihong Liu Lili Gong Guolin Shen |
| author_facet | Xiaoxue Wang Longhao Cheng Aijun Liu Lihong Liu Lili Gong Guolin Shen |
| author_sort | Xiaoxue Wang |
| collection | DOAJ |
| description | Abstract Background Multiple myeloma (MM) is the most aggressive and prevalent primary malignant tumor within the blood system, and can be classified into grades RISS-I, II, and III. High-grade tumors are associated with decreased survival rates and increased recurrence rates. To better understand metabolic disorders and expand the potential targets for MM, we conducted large-scale untargeted metabolomics on plasma samples from MM patients and healthy controls (HC). Methods Our study included 33 HC, 38 newly diagnosed MM patients (NDMM) categorized into three RISS grades (grade I: n = 5; grade II: n = 19; grade III: n = 8), and 92 MM patients post-targeted therapy with bortezomib-based regimens. Simultaneously, MM cell lines were employed for validation studies. Metabolites were analyzed and identified using ultra high liquid chromatography coupled with Q Orbitrap mass spectrometry (UPLC-HRMS), followed by verification through a self-built database. Results Compared with HC participants, a total of 70 metabolites were identified as undergoing significant changes in NDMM. These metabolites were significantly enriched in citrate cycle, choline metabolism, glycerophospholipid metabolism, and sphingolipid metabolism, etc. Notably, a panel of circulating plasma metabolite biomarkers, including lactic acid and leucine, has emerged not only as diagnostic indicators but also as valuable tools for tumor surveillance, aiding in the assessment of disease stage and prognostic evaluation. Moreover, 14 differential metabolites were identified in both MM cell lines and MM patients. Among these, intracellular levels of lactate and leucine significantly decreased in vitro, aligning with the plasma results. Conclusion Our findings on key metabolites and metabolic pathways provide novel insights into the exploration of diagnostic and therapeutic targets for MM. A prospective study is essential to validate these discoveries for future MM patient care. |
| format | Article |
| id | doaj-art-37bff4abe4db48619b79f46b0d4f19bd |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-37bff4abe4db48619b79f46b0d4f19bd2025-02-09T12:52:33ZengBMCJournal of Translational Medicine1479-58762025-02-0123111310.1186/s12967-024-05848-7Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosisXiaoxue Wang0Longhao Cheng1Aijun Liu2Lihong Liu3Lili Gong4Guolin Shen5Department of Pharmacy, China-Japan Friendship HospitalInstitute of Clinical Medical Sciences, State Key Laboratory of Respiratory Health and Multimorbidity, China-Japan Friendship Hospital, Capital Medical UniversityDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical UniversityDepartment of Pharmacy, China-Japan Friendship HospitalInstitute of Clinical Medical Sciences, State Key Laboratory of Respiratory Health and Multimorbidity, China-Japan Friendship Hospital, Capital Medical UniversityInstitute of Chemicals Safety, Chinese Academy of Inspection and QuarantineAbstract Background Multiple myeloma (MM) is the most aggressive and prevalent primary malignant tumor within the blood system, and can be classified into grades RISS-I, II, and III. High-grade tumors are associated with decreased survival rates and increased recurrence rates. To better understand metabolic disorders and expand the potential targets for MM, we conducted large-scale untargeted metabolomics on plasma samples from MM patients and healthy controls (HC). Methods Our study included 33 HC, 38 newly diagnosed MM patients (NDMM) categorized into three RISS grades (grade I: n = 5; grade II: n = 19; grade III: n = 8), and 92 MM patients post-targeted therapy with bortezomib-based regimens. Simultaneously, MM cell lines were employed for validation studies. Metabolites were analyzed and identified using ultra high liquid chromatography coupled with Q Orbitrap mass spectrometry (UPLC-HRMS), followed by verification through a self-built database. Results Compared with HC participants, a total of 70 metabolites were identified as undergoing significant changes in NDMM. These metabolites were significantly enriched in citrate cycle, choline metabolism, glycerophospholipid metabolism, and sphingolipid metabolism, etc. Notably, a panel of circulating plasma metabolite biomarkers, including lactic acid and leucine, has emerged not only as diagnostic indicators but also as valuable tools for tumor surveillance, aiding in the assessment of disease stage and prognostic evaluation. Moreover, 14 differential metabolites were identified in both MM cell lines and MM patients. Among these, intracellular levels of lactate and leucine significantly decreased in vitro, aligning with the plasma results. Conclusion Our findings on key metabolites and metabolic pathways provide novel insights into the exploration of diagnostic and therapeutic targets for MM. A prospective study is essential to validate these discoveries for future MM patient care.https://doi.org/10.1186/s12967-024-05848-7Multiple myelomaBiomarkersMetabolomicsPeripheral plasmaMetabolic pathways |
| spellingShingle | Xiaoxue Wang Longhao Cheng Aijun Liu Lihong Liu Lili Gong Guolin Shen Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis Journal of Translational Medicine Multiple myeloma Biomarkers Metabolomics Peripheral plasma Metabolic pathways |
| title | Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis |
| title_full | Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis |
| title_fullStr | Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis |
| title_full_unstemmed | Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis |
| title_short | Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis |
| title_sort | metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis staging and prognosis |
| topic | Multiple myeloma Biomarkers Metabolomics Peripheral plasma Metabolic pathways |
| url | https://doi.org/10.1186/s12967-024-05848-7 |
| work_keys_str_mv | AT xiaoxuewang metabolomicsapproachrevealskeyplasmabiomarkersinmultiplemyelomafordiagnosisstagingandprognosis AT longhaocheng metabolomicsapproachrevealskeyplasmabiomarkersinmultiplemyelomafordiagnosisstagingandprognosis AT aijunliu metabolomicsapproachrevealskeyplasmabiomarkersinmultiplemyelomafordiagnosisstagingandprognosis AT lihongliu metabolomicsapproachrevealskeyplasmabiomarkersinmultiplemyelomafordiagnosisstagingandprognosis AT liligong metabolomicsapproachrevealskeyplasmabiomarkersinmultiplemyelomafordiagnosisstagingandprognosis AT guolinshen metabolomicsapproachrevealskeyplasmabiomarkersinmultiplemyelomafordiagnosisstagingandprognosis |