Evidence mapPaperPMID 39730979Full record

ReviewMedical oncology (Northwood, London, England)2024

Unraveling non-coding RNAs in breast cancer: mechanistic insights and therapeutic potential.

Muqtada Shaikh, Gaurav Doshi

Abstract readReview
PubMed Publisher
In one paragraph

Review in Medical oncology (Northwood, London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

2 authors.

Muqtada ShaikhDepartment of Pharmacology, SVKM's Dr. Bhanuben Nanavati College of Pharmacy, Mumbai, 400 056, India.
Gaurav DoshiDepartment of Pharmacology, SVKM's Dr. Bhanuben Nanavati College of Pharmacy, Mumbai, 400 056, India. gaurav.pharmacology@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer remains a leading global health challenge requiring innovative, therapeutic strategies to improve patient outcomes. This review explores the pivotal roles of non-coding RNAs (ncRNAs), including long non-coding RNA, micro RNA, and circular RNA, in breast cancer biology. We highlight how these molecules regulate critical signaling pathways, influence tumor microenvironments, and contribute to treatment resistance. Our findings underscore the potential of ncRNAs as biomarkers for early diagnosis and as treatment targets for personalized treatment strategies. To pave the way for innovative cancer management approaches, we investigate the complex interactions of ncRNAs and their impact on tumor progression. This comprehensive review enhances our understanding of breast cancer biology while emphasizing the translational significance of ncRNA research in developing effective treatment strategies. Additional research and clinical studies are required to confirm the diagnostic and medicinal value of ncRNAs in breast cancer. Investigating the complex networks of ncRNA interactions and their links to other biological pathways can lead to the discovery of new treatment targets. Furthermore, leveraging advanced technologies, such as machine learning and multi-omics methods, will be critical in improving our understanding of ncRNAs biomarkers and translating these insights into impactful clinical applications.

Indexed as

Biomarkers, TumorBreast NeoplasmsRNA, UntranslatedFemaleGene Expression Regulation, NeoplasticHumansRNA, CircularRNA, Long NoncodingTumor MicroenvironmentBiomarkers, TumorRNA, CircularRNA, Long NoncodingRNA, UntranslatedBreast cancerCircular RNALong non-coding RNAMicro RNANon-coding RNAsTargeted therapy

Identifiers

PMID39730979

What Socratic holds

Textmetadata
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.