Evidence map›Paper›PMID 42194066›Full record

ReviewBiomolecules2026

TIF1 Family Proteins as Modulators of Cell Death: Mechanisms and Therapeutic Opportunities.

Dong Yang, Yuchen Chen

Abstract readReview
In one paragraph

Review in Biomolecules, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Dong YangDivision of Nephrology, Department of Medicine, University of Connecticut School of Medicine, Farmington, CT 06030, USA.ORCID 0000-0003-3207-7953
Yuchen ChenDivision of Surgical Sciences, Department of Surgery, University of Virginia, Charlottesville, VA 22903, USA.ORCID 0000-0001-8558-3062

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Regulated cell death is essential for development, tissue homeostasis, host defense, and disease. Beyond apoptosis, it is now clear that other forms of cell death, including ferroptosis, pyroptosis, and necroptosis, also contribute to pathology, often in interconnected rather than isolated ways. Within this broader framework, the transcriptional intermediary factor 1 (TIF1) family, comprising TRIM24, TRIM28, TRIM33, and TRIM66, has emerged as an important group of regulators linking stress adaptation, cell-state control, and cell death susceptibility. Although these proteins belong to the same family, they influence cell death through distinct and context-dependent mechanisms. Across the TIF1 family, apoptosis is by far the most extensively studied cell death phenotype, whereas links to ferroptosis, pyroptosis, and necroptosis remain more limited, more context dependent, and more unevenly distributed across individual members. Cell death often becomes evident when TIF1-dependent stress-buffering programs are disrupted, highlighting both their biological importance and potential therapeutic relevance. At the same time, family-level differences are emerging, while the underlying mechanisms remain incompletely understood, and recent advances in this field have not been synthesized. This review summarizes how TIF1 family members intersect with different cell death programs, discusses emerging translational opportunities and challenges, and highlights key mechanistic questions for future study.

Indexed as

Cell DeathTranscription FactorsAnimalsApoptosisFerroptosisHumansNuclear ProteinsNuclear Proteinstranscriptional intermediary factor 1Transcription Factorsapoptosiscell deathferroptosisnecroptosispyroptosistherapeutic targetingTRIM24TRIM28TRIM33TRIM66

Identifiers

PMID42194066
PMCPMC13204414

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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.