Evidence map›Paper›PMID 38898123›Full record

ArticleScientific reports2024

Subtype-specific alternative splicing events in breast cancer identified by large-scale data analysis.

Yui Deguchi, Chie Kikutake, Mikita Suyama

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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
–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

4 citing papers in PubMed.

  1. Review
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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.

Yui DeguchiDivision of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, 812-8582, Japan.
Chie KikutakeDivision of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, 812-8582, Japan.
Mikita SuyamaDivision of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, 812-8582, Japan. mikita@bioreg.kyushu-u.ac.jp.

Funding

Core Research for Evolutional Science and Technology JP19gm1310001Japan Society for the Promotion of Science 20K15780
6 · The paper itself

Abstract

Genome analysis in cancer has focused mainly on elucidating the function and regulatory mechanisms of genes that exhibit differential expression or mutation in cancer samples compared to normal samples. Recently, transcriptome analysis revealed that abnormal splicing events in cancer samples could contribute to cancer pathogenesis. Moreover, splicing variants in cancer reportedly generate diverse cancer antigens. Although abnormal splicing events are expected to be potential targets in cancer immunotherapy, the exploration of such targets and their biological significance in cancer have not been fully understood. In this study, to explore subtype-specific alternative splicing events, we conducted a comprehensive analysis of splicing events for each breast cancer subtype using large-scale splicing data derived from The Cancer Genome Atlas and found subtype-specific alternative splicing patterns. Analyses indicated that genes that produce subtype-specific alternative splicing events are potential novel targets for immunotherapy against breast cancer. The subtype-specific alternative splicing events identified in this study, which were not identified by mutation or differential expression analysis, bring new significance to previously overlooked splicing events.

Indexed as

Alternative SplicingBreast NeoplasmsGene Expression Regulation, NeoplasticData AnalysisFemaleGene Expression ProfilingHumansMutation

Identifiers

PMID38898123
PMCPMC11187070

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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.