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Record W4362543029 · doi:10.1158/1538-7445.am2023-1502

Abstract 1502: PRAME modulates the effect of retinoids on keratinocyte differentiation and cell cycle progression in basal cell carcinoma and cutaneous squamous cell carcinoma

2023· article· en· W4362543029 on OpenAlexaff
Brandon Ramchatesingh, Ivan V. Litvinov

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsCancer researchBiologyRetinoidKeratinocyteCell cycleMolecular biologyCell cultureCellRetinoic acidBiochemistry

Abstract

fetched live from OpenAlex

Abstract Substantial research supports the use of retinoids as prophylactics and treatments for keratinocyte carcinomas (KC). However, the practical applications of these compounds for KC management are limited by a poor understanding of the molecular basis of retinoid resistance. Preferentially Expressed Antigen in Melanoma (PRAME) is a cancer-testis antigen that functions as a retinoic acid receptor repressor and as a substrate recognition subunit for Cullin-2 E3 ubiquitin ligase, targeting degradation of cell cycle regulatory factors. PRAME is ectopically expressed in both types of KC: basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC). The functions and clinicopathological relevance of PRAME expression in BCC and SCC are unknown. The purpose of this study is to investigate the effect of PRAME on retinoid sensitivity and the pathogenesis of BCC and SCC. Cell lines representative of human BCC, SCC and immortalized keratinocytes were subjected to shRNA-mediated PRAME knockdown, PRAME knockout using CRISPR-Cas9, and ORF overexpression. Cells were treated with retinoids (all-trans retinoic acid, acitretin or tazarotene), and subjected to assays for cell proliferation (e.g., flow cytometric cell cycle analysis, label-free confluence tracking, Ki-67 immunofluorescence, etc.), cell death/survival (e.g., clonogenic assay, caspase staining, etc.) and for retinoid-induced gene expression changes (RT-qPCR and immunoblotting, etc.). PRAME overexpression attenuated retinoid-induced changes in cytokeratin expression in immortalized keratinocytes and SCC cells. PRAME knockdown in BCC and SCC cells augmented retinoid-induced changes in cytokeratin expression. Importantly, PRAME overexpression attenuated the pro-differentiation synergy between high calcium culture conditions and retinoid treatment in immortalized keratinocytes. PRAME also altered expression of several cell cycle regulatory proteins (p14/ARF, p16/INK4A, p21/Waf, p27/Kip1, etc.), which was in turn reflected accelerated cell proliferation dynamics in some PRAME-overexpressing cell lines. PRAME also conferred increased resistance to retinoid-induced cell cycle arrest in SCC cells, which was restored by PRAME knockdown. Furthermore, PRAME expression was inversely correlated with the pro-apoptotic protein Tazarotene Inducible Gene 3 (TIG3) in SCC cells. Our results implicate PRAME in KC tumorigenesis and differentiation, and suggest that PRAME could serve as a therapeutic target to optimize the use of retinoids to manage these cancers. We propose future studies to determine the clinicopathological relevance of PRAME expression in KC, PRAME-targeting strategies to enhance retinoid sensitivity, and the use skin tissue organoid models to study the effect of PRAME on epidermal differentiation dynamics in premalignant skin and KCs. Citation Format: Brandon Liam Ramchatesingh, Ivan Litvinov. PRAME modulates the effect of retinoids on keratinocyte differentiation and cell cycle progression in basal cell carcinoma and cutaneous squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1502.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.343
Teacher spread0.318 · 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 designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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