Evidence map›Paper›PMID 42462457›Full record

ReviewTranslational oncology2026

The role of splicing factor SRSF3 in cancer progression: Mechanisms, biomarkers, and therapeutic implications.

Shidong Wang, Hong Teng, Hongyan Han, Kangjie Hong

Abstract readReview
In one paragraph

Review in Translational oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Shidong WangDepartment of Respiratory medicine, Shaoxing Second Hospital, Shaoxing, China.
Hong TengDepartment of Respiratory medicine, Shaoxing Second Hospital, Shaoxing, China.
Hongyan HanDepartment of Respiratory medicine, Shaoxing Second Hospital, Shaoxing, China.
Kangjie HongDepartment of Neurology, Chun'an First People's Hospital, Hangzhou, China. Electronic address: xzlwhkj@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alternative splicing is increasingly recognized as a critical layer of oncogenic regulation, yet the biological meaning of individual splicing factors remains highly context dependent. Serine/arginine-rich splicing factor 3 (SRSF3) has been widely described as an oncogenic splicing regulator in colorectal, cervical, lung, pancreatic, and other cancers; however, emerging evidence also suggests tumor-suppressive or context-specific functions in selected malignancies. This review critically evaluates current knowledge of SRSF3 in cancer by moving beyond a catalogue of downstream targets. We discuss how SRSF3 controls cancer-associated splicing programs, how these events intersect with signaling pathways, metabolism, immune regulation, and therapeutic resistance, and why the same factor may produce divergent biological outcomes depending on tumor lineage, RNA-binding partners, and target isoforms. We also examine unresolved controversies, including whether SRSF3 is a universal oncogenic driver or a context-dependent regulator, whether SRSF3 expression alone is sufficient as a biomarker, and how cancer-specific splicing events can be therapeutically targeted without disrupting essential RNA processing in normal tissues. Finally, we highlight translational barriers, including limited clinical validation, delivery challenges for RNA-based therapeutics, toxicity risks, and compensatory splicing networks. A more precise understanding of SRSF3-dependent splicing vulnerabilities may support future biomarker development and rational combination therapies.

Indexed as

Alternative splicingBiomarkerCancer progressionSRSF3Targeted therapy

Identifiers

PMID42462457
PMCPMC13383856

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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.