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Record W4399731110 · doi:10.1016/j.ejmg.2024.104956

Retinoblastoma caused by an RB1 variant with unusually low penetrance in a Danish family

2024· article· en· W4399731110 on OpenAlexaff
Pernille Axél Gregersen, Peter S. Jensen, Rikke Christensen, Dietmar Lohmann, Hilary Racher, Brenda L. Gallie, Steen F. Urbak

Bibliographic record

VenueEuropean Journal of Medical Genetics · 2024
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsHospital for Sick ChildrenImpactUniversity of Toronto
Fundersnot available
KeywordsPenetranceRetinoblastomaGeneticsAlleleBiologyGenetic counselingGenePhenotype

Abstract

fetched live from OpenAlex

Retinoblastoma is the most common eye cancer in children. It is caused by pathogenic alterations of both alleles of the tumor suppressor gene RB1. In heritable retinoblastoma, a constitutional RB1 variant predisposes the cells to tumor formation, and loss of the other allele is a prerequisite for the development of retinoblastoma. Heritable retinoblastoma is inherited in an autosomal dominant manner; however, the majority of cases are the result of a de novo pathogenic RB1 variant. Penetrance is usually high (>90%), but with marked inter-familial variability. In some families, penetrance is incomplete and family members who develop tumors tend to remain unilaterally affected. Moreover, some families with low penetrance also show a parent-of-origin effect. We describe a patient with unilateral retinoblastoma caused by a previously unreported likely pathogenic RB1 variant (c.1199T>C) that disrupts a highly conserved amino acid residue within the A-box functional domain. Segregation analysis showed that the variant had unusually low penetrance as nine non-affected family members carried the same variant. We emphasize the use of genetic analysis on tumor DNA for classifying the RB1 variant, and underline the challenges in clinical management and counseling of families carrying the specific RB1 variant.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.279
Teacher spread0.265 · 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 designCase report
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

Citations3
Published2024
Admission routes1
Has abstractyes

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