Evidence map›Paper›PMID 39882259›Full record

ReviewFrontiers in cell and developmental biology2024

MicroRNAs in pancreatic cancer drug resistance: mechanisms and therapeutic potential.

Fangying Dong, Jing Zhou, Yijie Wu, Zhaofeng Gao, Weiwei Li, Zhengwei Song

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
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.

Fangying DongEmergency Department, The Second Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China.
Jing ZhouDepartment of Surgery, The Second Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China.
Yijie WuDepartment of general practice, Taozhuang Branch of the First People's Hospital of Jiashan, Jiaxing, Zhejiang, China.
Zhaofeng GaoDepartment of Surgery, The Second Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China.
Weiwei LiEmergency Department, The Second Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China.
Zhengwei SongDepartment of Surgery, The Second Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer (PC) remains one of the most lethal malignancies, primarily due to its intrinsic resistance to conventional therapies. MicroRNAs (miRNAs), key regulators of gene expression, have been identified as crucial modulators of drug resistance mechanisms in this cancer type. This review synthesizes recent advancements in our understanding of how miRNAs influence treatment efficacy in PC. We have thoroughly summarized and discussed the complex role of miRNA in mediating drug resistance in PC treatment. By highlighting specific miRNAs that are implicated in drug resistance pathways, we provide insights into their functional mechanisms and interactions with key molecular targets. We also explore the potential of miRNA-based strategies as novel therapeutic approaches and diagnostic tools to overcome resistance and improve patient outcomes. Despite promising developments, challenges such as specificity, stability, and effective delivery of miRNA-based therapeutics remain. This review aims to offer a critical perspective on current research and propose future directions for leveraging miRNA-based interventions in the fight against PC.

Indexed as

chemoresistance mechanismsdrug resistancemicroRNApancreatic cancertherapeutic targeting

Identifiers

PMID39882259
PMCPMC11774998

What OpenQuestion holds

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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.