{"title":"Enhancing staging in multiple myeloma using an m6A regulatory gene-pairing model.","authors":"Yating Deng, Hongkai Zhu, Hongling Peng","doi":"10.1007/s10238-024-01526-6","DOIUrl":null,"url":null,"abstract":"<p><p>Multiple myeloma (MM) is characterized by clonal plasma cell proliferation in the bone marrow, challenging prognosis prediction. We developed a gene-pairing prognostic risk model using m6A regulatory genes and a nested LASSO method. A cutoff of - 0.133 categorized MM samples into high-risk and low-risk groups. The model showed strong prognostic performance in 2088 newly diagnosed MM samples and predicted response to combination therapy (daratumumab, carfilzomib, lenalidomide, and dexamethasone) in patients who failed or relapsed from bortezomib-containing regimens, with an AUC of 0.9. It distinguished between smoldering MM and MM (cutoff: - 0.45) and between MM and plasma cell leukemia (cutoff: 0.0857). Single-cell analysis revealed higher risk scores at relapse. Combining MM cell lines and sample data, we identified potential drugs and targets (ADAT2 and NUP153) effective against high-risk MM. Integrating the m6A risk model with the International Staging System (ISS) enhanced stratification accuracy. These insights support precision treatment of MM.</p>","PeriodicalId":10337,"journal":{"name":"Clinical and Experimental Medicine","volume":"25 1","pages":"40"},"PeriodicalIF":3.2000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11742005/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and Experimental Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10238-024-01526-6","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Multiple myeloma (MM) is characterized by clonal plasma cell proliferation in the bone marrow, challenging prognosis prediction. We developed a gene-pairing prognostic risk model using m6A regulatory genes and a nested LASSO method. A cutoff of - 0.133 categorized MM samples into high-risk and low-risk groups. The model showed strong prognostic performance in 2088 newly diagnosed MM samples and predicted response to combination therapy (daratumumab, carfilzomib, lenalidomide, and dexamethasone) in patients who failed or relapsed from bortezomib-containing regimens, with an AUC of 0.9. It distinguished between smoldering MM and MM (cutoff: - 0.45) and between MM and plasma cell leukemia (cutoff: 0.0857). Single-cell analysis revealed higher risk scores at relapse. Combining MM cell lines and sample data, we identified potential drugs and targets (ADAT2 and NUP153) effective against high-risk MM. Integrating the m6A risk model with the International Staging System (ISS) enhanced stratification accuracy. These insights support precision treatment of MM.
期刊介绍:
Clinical and Experimental Medicine (CEM) is a multidisciplinary journal that aims to be a forum of scientific excellence and information exchange in relation to the basic and clinical features of the following fields: hematology, onco-hematology, oncology, virology, immunology, and rheumatology. The journal publishes reviews and editorials, experimental and preclinical studies, translational research, prospectively designed clinical trials, and epidemiological studies. Papers containing new clinical or experimental data that are likely to contribute to changes in clinical practice or the way in which a disease is thought about will be given priority due to their immediate importance. Case reports will be accepted on an exceptional basis only, and their submission is discouraged. The major criteria for publication are clarity, scientific soundness, and advances in knowledge. In compliance with the overwhelmingly prevailing request by the international scientific community, and with respect for eco-compatibility issues, CEM is now published exclusively online.