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Record W4415709969 · doi:10.1101/2025.10.28.685175

The HNF4A Q164X Mutation Impairs Transcriptional Activation in Vitro but Its Heterozygosity Suppresses Liver Tumorigenesis in Vivo

2025· preprint· W4415709969 on OpenAlexfundno aff
Dawid Winiarczyk, Hossein Khodadadi, Effi Haque, Piotr Poznański, Mariusz Sacharczuk, Hiroaki Taniguchi

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Language
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
FundersInstitute of GeneticsNarodowym Centrum Nauki
KeywordsLoss of heterozygosityCarcinogenesisDownregulation and upregulationMutationIn vitroMutantTranscriptional regulationHepatocyte nuclear factorsHepatocyteGene

Abstract

fetched live from OpenAlex

Abstract Hepatocyte nuclear factor 4 alpha (HNF4A) is a master regulator of hepatic differentiation and metabolism. Here, we identify and characterize a truncating Q164X mutation that impairs HNF4A transcriptional activity in vitro and causes embryonic lethality when homozygous. Functional assays revealed that the Q164X protein retains nuclear localization but exhibits severely reduced DNA binding and transcriptional activation. CRISPR-generated Q164X mice showed no viable homozygotes, confirming the essential role of HNF4A in early embryogenesis. Unexpectedly, heterozygous Q164X mutants displayed reduced liver tumorigenesis following diethylnitrosamine and high-fat diet treatment, despite downregulation of HNF4A target genes such as ApoB and Hnf1a . These results suggest that partial HNF4A deficiency may trigger compensatory metabolic networks that protect against carcinogenic stress. Collectively, our study establishes Q164X as a loss-of-function HNF4A mutation with paradoxical tumor-suppressive effects in vivo.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.225
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicPancreatic function and diabetes→French-language works237,207→