Evidence map›Paper›PMID 41405832›Full record

ArticleFrontiers of medicine2025

Plasma cell development-based prediction of prognosis and treatment response in individual multiple myeloma.

Sitao Jiang, Yuan Yang, Man Yao, Ayaz Ali Samo, Pengli Xiao, Qinglan Cao, Jiuyi Li, Huijuan Wang, Wenming Chen, Xuzhang Lu and 2 more

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Article in Frontiers of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

12 authors.

Sitao JiangDepartment of Biology, Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, 100875, China.
Yuan YangDepartment of Biology, Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, 100875, China.
Man YaoDepartment of Biology, Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, 100875, China.
Ayaz Ali SamoDepartment of Physiology, University of Sindh, Jamshoro, 76080, Pakistan.
Pengli XiaoDepartment of Biology, Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, 100875, China.
Qinglan CaoDepartment of Biology, Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, 100875, China.
Jiuyi LiCollege of Life Sciences, Sichuan Normal University, Chengdu, 610101, China.
Huijuan WangDepartment of Hematology, Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Wenming ChenDepartment of Hematology, Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Xuzhang Lu *Department of Hematology, Changzhou No. 2 People's Hospital, The Affiliated Hospital of Nanjing Medical University, Changzhou, 213100, China.
Yin Wu *Department of Hematology, Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Xiaolong Fan *Department of Biology, Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, 100875, China. xfan@bnu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We hypothesized that gene networks converged between plasma cell development and multiple myeloma (MM) pathogenesis may better explain the clinical heterogeneity in individual MM patients. Here, we transformed the reciprocal expression pattern between a gene module centered on the expression of MCL1 and another gene module represented by the expression of TLR10 from individual MM transcriptomes into a myeloma classification score (MCS). MCS enabled prognostication in 1738 patients with newly diagnosed MM (NDMM) and 319 patients with relapsed/refractory MM (RRMM) from our own observational cohort, from MMRF, and from five prospective trials. MCS also enabled the discrimination between progressive and stable disease states in the longitudinal samples from 85 patients in MMRF and the PETHEMA/GEM2012MENOS65 trial. MCS further enabled prediction of the responses to bortezomib-based treatment in 425 patients enrolled in the HOVON-65/GMMG-HD4 and APEX (039) trials, and the response to carfilzomib-based treatment in 86 transplantation-eligible patients from MMRF. MCS-defined risk groups harbored distinct targetable pathways, including unfolded protein response, replication stress, genomic instability and interferon responses. However, MCS-based individualized prediction of prognosis and treatment response was independent of the hitherto available prognostic models. Thus, MCS represents an alternative biomarker for risk stratification and prediction of treatment response in individual MM patients.

Indexed as

individualized molecular subtypingmultiple myelomaproteasome inhibitorrisk stratificationtreatment response

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.