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Abstract A010: Assay development to assess the efficiency and stability of candidate molecules for transcriptional gene silencing of FOXP3, using a human tumor-derived cell line

2023· article· en· W4389227987 on OpenAlexaboutno aff
Carolinne T. Fogagnolo, Daniela Sayuri Mizobuti, Marcio C. Bajgelman

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsGene silencingBiologyFOXP3Transcription factorCell biologyTranscriptional regulationEpigeneticsEffectorCancer researchTherapeutic gene modulationGene expressionImmune systemGeneImmunologyGeneticsRegulator gene

Abstract

fetched live from OpenAlex

Abstract Regulatory T cells play an important role to modulate the balance between immunotolerance and immunosurveillance. These cells have the property of inhibiting effector lymphocytes and may antagonize antitumor immunity. Regulatory T cells are originated in the thymus, or even converted from peripheral lymphocytes by factors produced in the tumor microenvironment. Clinical data suggests that regulatory T cell infiltration correlates with poor prognosis in the treatment of solid tumors. The FOXP3 transcription factor is considered a master key to control the phenotype of regulatory T cells. It was previously shown, that the ectopic expression of FOXP3 can induce an immunosuppressive phenotype in lymphocytes. In contrast, it has been observed that mutations in the FOXP3 gene can cause impaired immunosuppressive activity mediated by regulatory T cells, such as the autoimmunity syndrome known as IPEX. In this sense, the FOXP3 transcription factor may be an interesting target, looking for inactivation of the immunosuppressive phenotype of regulatory T cells, to potentiate antitumor response. In this work, we present an assay development to investigate the potential of transcriptional interference RNA candidates to silence FOXP3 expression. In contrast to post-transcriptional gene silencing method, which targets messenger RNA and depends on a constant supply or efficient turn-over of the inhibitory molecule, the transcriptional gene silencing targets the cellular DNA genome, inducing epigenetic changes that may control the target gene transcription. We employed the human MCF-7 tumor cell line, which has endogenous and constitutive expression of FOXP3 as a target model to test transcriptional gene silencing candidates. This cell line is transduced with lentiviral vectors harboring interfering RNA sequences driven to the FOXP3 promoter region. The RNA interference candidates are then evaluated for their ability to induce DNA methylation, by bisulfite method, and transcriptional gene silencing of FOXP3, by qPCR. We performed the screening of candidates for FOXP3 transcriptional silencing, in comparison to a post-transcriptional interference RNA control. The lentiviral transduced cells are easily expanded and allow a temporal analysis of target gene expression. In this model, we observed the possibility of finding transcriptional interference RNA candidates that exhibited high efficiency and stability, that may be used for research purposes, or even for the investigation of new therapeutic possibilities in immuno-oncology. Citation Format: Carolinne T Fogagnolo, Daniela S Mizobuti, Marcio C Bajgelman. Assay development to assess the efficiency and stability of candidate molecules for transcriptional gene silencing of FOXP3, using a human tumor-derived cell line [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A010.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.073
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.223
GPT teacher head0.442
Teacher spread0.219 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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