Evidence map›Paper›PMID 38002007›Full record

ReviewBiomedicines2023

MicroRNAs as Molecular Biomarkers for the Characterization of Basal-like Breast Tumor Subtype.

Muhammad Tariq, Vinitha Richard, Michael J Kerin

Open access · goldAbstract readReview
In one paragraph

Review in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 23% of its field
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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Precision medicine in breast cancer (Review).Molecular and clinical oncology · 2024
    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

3 authors.

Muhammad TariqDiscipline of Surgery, Lambe Institute for Translational Research, H91 TK33 Galway, Ireland.ORCID 0009-0007-7614-8289
Vinitha RichardDiscipline of Surgery, Lambe Institute for Translational Research, H91 TK33 Galway, Ireland.ORCID 0000-0002-5534-9205
Michael J KerinDiscipline of Surgery, Lambe Institute for Translational Research, H91 TK33 Galway, Ireland.

Funding

Science Foundation Ireland 18/SPP/3522
6 · The paper itself

Abstract

Breast cancer is a heterogeneous disease highlighted by the presence of multiple tumor variants and the basal-like breast cancer (BLBC) is considered to be the most aggressive variant with limited therapeutics and a poor prognosis. Though the absence of detectable protein and hormonal receptors as biomarkers hinders early detection, the integration of genomic and transcriptomic profiling led to the identification of additional variants in BLBC. The high-throughput analysis of tissue-specific micro-ribonucleic acids (microRNAs/miRNAs) that are deemed to have a significant role in the development of breast cancer also displayed distinct expression profiles in each subtype of breast cancer and thus emerged to be a robust approach for the precise characterization of the BLBC subtypes. The classification schematic of breast cancer is still a fluid entity that continues to evolve alongside technological advancement, and the transcriptomic profiling of tissue-specific microRNAs is projected to aid in the substratification and diagnosis of the BLBC tumor subtype. In this review, we summarize the current knowledge on breast tumor classification, aim to collect comprehensive evidence based on the microRNA expression profiles, and explore their potential as prospective biomarkers of BLBC.

Indexed as

basal-like breast cancerclassificationhormone receptorsmicroRNAstranscriptomicstriple-negative breast cancer

Identifiers

PMID38002007
PMCPMC10669494
OpenAlexW4388524859

What Socratic holds

Textmetadata
LicenceCC BY
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.