Evidence map›Paper›PMID 40078288›Full record

ReviewFrontiers in pharmacology2025

Mitochondria-associated non-coding RNAs and their impact on drug resistance.

Xingna An, Lina Sun, Huan Zheng, Yinghui Xiao, Weixia Sun, Dehai Yu

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Xingna AnDepartment of Core Facility, The First Hospital of Jilin University, Changchun, Jilin, China.
Lina SunDepartment of Hematology-Oncology, Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin, China.
Huan ZhengDepartment of Hematology-Oncology, Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin, China.
Yinghui XiaoDepartment of Core Facility, The First Hospital of Jilin University, Changchun, Jilin, China.
Weixia Sun *Department of Nephrology, The First Hospital of Jilin University, Changchun, Jilin, China.
Dehai Yu *Department of Core Facility, The First Hospital of Jilin University, Changchun, Jilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug resistance is a prevalent challenge in clinical disease treatment, often leading to disease relapse and poor prognosis. Therefore, it is crucial to gain a deeper understanding of the molecular mechanisms underlying drug resistance and to develop targeted strategies for its effective prevention and management. Mitochondria, as vital energy-producing organelles within cells, have been recognized as key regulators of drug sensitivity. Processes such as mitochondrial fission, fusion, mitophagy, changes in membrane potential, reactive oxygen species (ROS) accumulation, and oxidative phosphorylation (OXPHOS) are all linked to drug sensitivity. Non-coding RNAs (ncRNAs) enriched in mitochondria (mtncRNA), whether transcribed from mitochondrial DNA (mtDNA) or from the nucleus and transported to mitochondria, can regulate the transcription and translation of mtDNA, thus influencing mitochondrial function, including mitochondrial substance exchange and energy metabolism. This, in turn, directly or indirectly affects cellular sensitivity to drugs. This review summarizes the types of mtncRNAs associated with drug resistance and the molecular mechanisms regulating drug resistance. Our aim is to provide insights and strategies for overcoming drug resistance by modulating mtncRNAs.

Indexed as

cancerdrug resistancelncRNAmicroRNAmitochondria

Identifiers

PMID40078288
PMCPMC11897306

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Registered trials

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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.