Construction of a treatment response prediction model for multiple myeloma based on multi-omics and machine learning.

This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2025-04-28
DOI
https://doi.org/10.11817/j.issn.1672-7347.2025.240691
Primary Topic
Genetics, Bioinformatics, and Biomedical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Construction of a treatment response prediction model for multiple myeloma based on multi-omics and machine learning.

Xionghui Zhou, Rong Gui, Jing Liu, Meng Gao
PubMed
Genetics, Bioinformatics, and Biomedical Research
article

Construction of a treatment response prediction model for multiple myeloma based on multi-omics and machine learning.

Xionghui Zhou, Rong Gui, Jing Liu, Meng Gao
article en

Abstract

This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.

PubMedVol. 50(4)
Central South University (CN), Third Xiangya Hospital (CN)
Good health and well-being
Openalex Percentile: Top 82%
Genetics, Bioinformatics, and Biomedical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.