FTO–CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification

The FTO-CHRM3 axis contributes to MM progression via calcium signaling pathway dysregulation, and the exploration of its underlying mechanisms provides insights for targeted MM interventions.

Authors

Institutions

Publication Details

Journal
Annals of Hematology
Published
2026-03-23
DOI
https://doi.org/10.1007/s00277-026-06940-2
Primary Topic
Multiple Myeloma Research and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

FTO–CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification

Tiantian Sun, Ting Bin, Johnny Cheuk On Tang, Bo Lü et al.
Annals of Hematology
Multiple Myeloma Research and Treatments
article

FTO–CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification

Tiantian Sun, Ting Bin, Johnny Cheuk On Tang, Bo Lü, Mei Xie, Xue-Fei Deng
article en

Abstract

The FTO-CHRM3 axis contributes to MM progression via calcium signaling pathway dysregulation, and the exploration of its underlying mechanisms provides insights for targeted MM interventions.

Annals of HematologyVol. 105(4)
Sun Yat-sen University (CN), The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
No poverty
Openalex Percentile: Top 13%
Multiple Myeloma Research and Treatments
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.