Evidence map›Paper›PMID 36656436›Full record

ReviewGenes & genomics2023

Alternative splicing: a new breakthrough for understanding tumorigenesis and potential clinical applications.

Jiyeon Park, Joonhyuck Park, Yeun-Jun Chung

Abstract readReview
PubMed Publisher
In one paragraph

Review in Genes & genomics, 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
–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. Article
  2. Review
  3. Article
  4. 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

3 authors.

Jiyeon ParkPrecision Medicine Research Center, Seoul, Republic of Korea.ORCID 0000-0001-5993-261X
Joonhyuck ParkDepartment of Biomedicine & Health Sciences, Graduate School, Seoul, Republic of Korea. joonpark@catholic.ac.kr.ORCID 0000-0003-1509-724X
Yeun-Jun ChungPrecision Medicine Research Center, Seoul, Republic of Korea. yejun@catholic.ac.kr.ORCID 0000-0002-6943-5948

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlternative splicing (AS) is a post-transcriptional process that produces transcript variants, thus leading to transcriptome complexity. Recently, the scope of AS studies has been greatly expanded toward clinical applications owing to the abundance of RNA sequencing data.

objectiveThis review consists of two parts. We first summarize bioinformatic resources that are useful for large-scale cancer-related AS studies. We then highlight the research efforts to utilize AS events for predicting clinical outcomes and planning therapeutic strategies.

resultsComputational approaches to interrogate AS events have been reviewed under three categories: (1) databases to provide functional and clinical annotation of AS events, (2) analytical tools to identify cancer-associated AS event, and (3) methods to identify splicing-related DNA variants and splicing-derived neoantigens. We also present the recent progress in exploring the clinical utility of AS under four categories: (1) identification of AS events for cancer prognosis, (2) utilization of AS events in molecular classification of various cancers, (3) regulatory mechanisms of AS underlying drug resistance, and (4) potential use of AS in cancer therapy.

conclusionThis review will be helpful for understanding the biological implications of AS in cancer and facilitate the development of AS markers for cancer prognosis and treatment. We anticipate that future studies will lead to the application of genome-wide AS profiles in cancer precision medicine.

Indexed as

Alternative SplicingNeoplasmsCarcinogenesisHumansRNA SplicingTranscriptomeAlternative splicingBiomarkerCancer researchDrug resistanceNeoantigen

Identifiers

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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.