Evidence map›Paper›PMID 41581315›Full record

ReviewTranslational oncology2026

NPM1c⁺-driven lncRNA dysregulation in AML: Mechanisms, Controversies and translational roadblocks.

Qiang Zhang, Yu Fu, Jihong Zhang

Abstract readReview
In one paragraph

Review in Translational oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Qiang ZhangHematology Laboratory, Sheng Jing Hospital of China Medical University, Shenyang, China; The Maternal and Child Health Care Hospital of Guangxi Zhuang Autonomous Region, Guangxi Birth Defects Prevention and Control Institute, Nanning, China.
Yu FuHematology Laboratory, Sheng Jing Hospital of China Medical University, Shenyang, China.
Jihong ZhangHematology Laboratory, Sheng Jing Hospital of China Medical University, Shenyang, China. Electronic address: southmedical@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the landscape of acute myeloid leukemia (AML) research, mutations in nucleophosmin 1 (NPM1) are the most prevalent genetic alterations. The leukemogenic mutant variant, NPM1c⁺, is associated with a distinct gene expression profile linked to leukemia, but the downstream oncogenic pathways remain only partially understood. Long non-coding RNAs (lncRNAs) are RNA molecules with known regulatory roles in human development and disease. Research implicates many lncRNAs in hematopoiesis and leukemogenesis, revealing correlations between their expression and clinical parameters in AML patients. While NPM1c⁺ AML exhibits a distinct lncRNA signature, it remains contentious whether these molecules are bona fide drivers or passenger events, and how their context-dependent functions can be therapeutically exploited. This review focuses on lncRNAs in NPM1c⁺ AML, highlighting their roles in pathogenesis, prognosis, and chemoresistance. By systematically elucidating the role of lncRNAs as pivotal factors in the diagnosis, treatment, and prognosis of NPM1c⁺ AML, this study addresses a gap in the existing literature. Our analysis of specific lncRNAs, such as HOTAIRM1, HOXB-AS3, CRNDE, HOXBLINC, LONA, IFEX9, XLOC_109948, and HOTTIP, enhances our understanding of the molecular mechanisms underlying AML in the context of NPM1c⁺. These findings lay the groundwork for developing targeted therapies and improved prognostic tools for NPM1c⁺AML.

Indexed as

Acute myeloid leukemiaLong noncoding RNAsNPM1

Identifiers

PMID41581315
PMCPMC12860268

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.