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Record W4288042207 · doi:10.3390/cancers14153630

The Contributions of Cancer-Testis and Developmental Genes to the Pathogenesis of Keratinocyte Carcinomas

2022· review· en· W4288042207 on OpenAlexafffund
Brandon Ramchatesingh, Jennifer Gantchev, Amelia Martínez Villarreal, Raman Preet Kaur Gill, Marine Lambert, Sriraam Sivachandran, Philippe Lefrançois, Ivan V. Litvinov

Bibliographic record

VenueCancers · 2022
Typereview
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchConsejo Nacional de Ciencia y Tecnología
KeywordsCancer researchCarcinogenesisVismodegibBasal cell carcinomaPathogenesisCancerBiologyKeratinocyteImmunotherapyMedicineImmunologyBioinformaticsPathologyBasal cellGeneticsCell culture

Abstract

fetched live from OpenAlex

Keratinocyte carcinomas are among the most prevalent malignancies worldwide. Basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) are the two cancers recognized as keratinocyte carcinomas. The standard of care for treating these cancers includes surgery and ablative therapies. However, in recent years, targeted therapies (e.g., cetuximab for cSCC and vismodegib/sonidegib for BCC) have been used to treat advanced disease as well as immunotherapy (e.g., cemiplimab). These treatments are expensive and have significant toxicities with objective response rates approaching ~50-65%. Hence, there is a need to dissect the molecular pathogenesis of these cancers to identify novel biomarkers and therapeutic targets to improve disease management. Several cancer-testis antigens (CTA) and developmental genes (including embryonic stem cell factors and fetal genes) are ectopically expressed in BCC and cSCC. When ectopically expressed in malignant tissues, functions of these genes may be recaptured to promote tumorigenesis. CTAs and developmental genes are emerging as important players in the pathogenesis of BCC and cSCC, positioning themselves as attractive candidate biomarkers and therapeutic targets requiring rigorous testing. Herein, we review the current research and offer perspectives on the contributions of CTAs and developmental genes to the pathogenesis of keratinocyte carcinomas.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.054
GPT teacher head0.343
Teacher spread0.290 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2022
Admission routes2
Has abstractyes

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