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Record W4391873715 · doi:10.1093/jcag/gwad061.026

A26 BIOLOGICAL CHARACTERIZATION OF THE INTERACTION BETWEEN SIRT1 AND HNF4Α2 IN INTESTINAL EPITHELIAL CELLS

2024· article· en· W4391873715 on OpenAlexaffabout
JS Pulido, Christine M. Jones, François Boudreau

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCharacterization (materials science)ChemistryCell biologyBiologyPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract Background Colorectal cancer (CRC) is the third most common cancer in Canada. HNF4A locus is amplified in CRC, while additional reports suggest that hepatocyte nuclear factor 4 alpha (HNF4α) is associated with increased proliferation and disease development. This dual role as a tumor suppressor or oncoprotein might be due to the production of 12 spliced isoforms with structural differences and variable tissue expression. It suggests distinct functions for each isoform according to their specific interaction complexes. However, little is known about the nature of these protein complexes and their biological functions during intestinal physiopathology. Recently, using a BioID2 and mass spectrometry approach, our laboratory showed a possible interaction between HNF4α2 and sirtuin 1 (SIRT1) in intestinal epithelial cells from a colon carcinoma (HCT116). HNF4α2 is one of the most potent isoforms in the control of transcriptional activity of multiple intestinal epithelial genes related to regulating cell death, angiogenesis, apoptosis, response to injury, and response to drugs, among others. Aims To characterize the possible interaction between HNF4α2 and SIRT1 in intestinal epithelial cells at the biological level. Methods We performed SIRT1 knockdown using shRNAs in HCT116 cells expressing the HNF4α2 isoform in an inducible manner by doxycycline (DOX). Subsequently, we conducted a proximity ligation assay to validate the interaction between HNF4α2 and SIRT1 in HCT116 cells. Additionally, protein purification was performed to validate their physical interaction through EMSA. A transcriptome analysis was carried out using RNA-seq to define the biological processes involved in the interaction between the two proteins. Results We observed an interaction signal between HNF4α2 and SIRT1 in HCT116 cells, similar to that observed for IRFBB2, whose interaction with HNF4α2 has been previously validated. This signal decreased when cells were treated with shRNA for SIRT1 and was not observed in cells not induced by DOX. EMSA analyses revealed a direct interaction signal between HNF4α2 and SIRT1. RNA-seq analyses showed a loss in the regulation of over 95% of genes targeted by HNF4α2 when cells were treated with shRNA for SIRT1. An enrichment analysis for GO annotations using ShyniGO v. 0.77 software showed an enrichment of genes for biological processes such as apoptosis, inflammation, cell migration, cell invasion, cell death, and various cancer-related signaling pathways. Conclusions SIRT1 displays physical interaction with HNF4α2 and significantly affects the transcriptional regulation of this isoform in the context of epithelial cells. Their interaction is involved in processes related to intestinal inflammation and cancer progression. Pharmacological targeting of SIRT1 could represent a viable strategy in treating CRC and other intestinal diseases Funding Agencies CIHRNSERC

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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
Published2024
Admission routes2
Has abstractyes

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