Prognostic implications of metabolism-related genes in acute myeloid leukemia

A novel metabolic gene signature was developed to stratify risk and predict prognosis in AML, serving as an independent prognostic factor. CA13 was identified as a potential therapeutic target. This study provides new insights into the prognostic and therapeutic implications of metabolic genes in AML.

Authors

Institutions

Publication Details

Journal
Frontiers in Genetics
Published
2024-10-03
DOI
https://doi.org/10.3389/fgene.2024.1424365
Citations
3
Primary Topic
Acute Myeloid Leukemia Research
Type
article
Field-Weighted Citation Impact
1.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prognostic implications of metabolism-related genes in acute myeloid leukemia

Mianyang Li, Chengliang Yin, Na Ren, Ruibin Li et al.
3 citations
Frontiers in Genetics
Acute Myeloid Leukemia Research
1.36
article

Prognostic implications of metabolism-related genes in acute myeloid leukemia

Mianyang Li, Chengliang Yin, Na Ren, Ruibin Li, Chengbin Wang, Jianan Wang
article en
3 citations

Abstract

A novel metabolic gene signature was developed to stratify risk and predict prognosis in AML, serving as an independent prognostic factor. CA13 was identified as a potential therapeutic target. This study provides new insights into the prognostic and therapeutic implications of metabolic genes in AML.

Frontiers in GeneticsVol. 15
Chinese PLA General Hospital (CN), General Hospital of Shenyang Military Region (CN), PLA Academy of Military Science (CN)
Openalex Percentile: Top 17%
Acute Myeloid Leukemia Research
1.36
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.