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Record W4415453421 · doi:10.1210/jendso/bvaf149.2483

SUN-281 The Crucial Role of the TP53 Carrier Gene in Human Tumorigenesis: Implications for Cancer Screening

2025· article· en· W4415453421 on OpenAlexaboutno aff
Maria Candida Barisson Villares Fragoso, Maria E Sousa, Mariana Braga Lacerda, Marina Buchpiguel, Madson Q. Almeida, Ana Cláudia Latronico, Berenice B. Mendonça, Debora Parreiras Di Matteo, Wallison de Medeiros Sales Lins, Marcelo Biscegli Jatene

Bibliographic record

VenueJournal of the Endocrine Society · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsnot available
Fundersnot available
KeywordsMalignancyDiseaseFamily historyCancerGenetic testingGenePediatric cancerExon

Abstract

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Abstract Disclosure: M.C. Fragoso: None. M. Sousa: None. M. Lacerda: None. M. Buchpiguel: None. M. Almeida: None. A. Latronico: None. B. Mendonça: None. D. Di Matteo: None. W. Lins: None. M. Jatene: None. Introduction: Li-Fraumeni Syndrome (LFS) is an autosomal dominant disorder caused by pathogenic variants (PV) in TP53, encoding a transcription factor critical for tumor suppression. Around 20% of LFS families carry one of six hotspot PVs (p.R175H, p.G245S, p.R248Q, p.R248W, p.R273H, p.R282W). TP53 variants influence disease penetrance, cancer predisposition, and secondary malignancy risk. Common tumors include adrenocortical carcinoma, soft tissue sarcomas, and bone tumors. The clinical and genetic aspects of this syndrome predispose individuals to develop multiple types of cancer at an early age. Given the severity and associated risks, a panel of experts recommends that all individuals with a confirmed clinical or molecular diagnosis undergo strict surveillance. Early screening using the Toronto Protocol is essential for detecting and intervening in malignancies at initial stages. To illustrate the clinical impact of PV in TP53 and surveillance importance, we report a pediatric case. Case Report: A 5-year-old boy with a significant family history of cancer in close relatives before the age of 45 was diagnosed with LFS. Genetic analysis revealed c.818G>A (p.Arg273H), a heterozygous variant in exon 8. The child had no gestational or perinatal complications. To date, no signs or symptoms of hormonal hyperfunction have been observed. Systematic screening for syndrome-associated malignancies was initiated using imaging studies, including annual Magnetic Resonance Imaging (MRI) of the chest, abdomen, pelvis, and brain. In February 2023, a chest MRI revealed a 2.5 cm nodule on the right side. PET-FDG imaging identified a nodular lesion with increased uptake, with a metabolic size of 6.7 × 4.6 × 4.2 cm, to the right of the midline (SUVmax: 6,8). A thymus biopsy via radiointervention confirmed a type B1 thymoma, leading to an initial decision for surveillance. In July, a follow-up MRI showed a heterogeneous solid mass with cystic areas and no contrast enhancement, measuring 5.5 × 4.5 × 3.7 cm in the anterior mediastinum, paracardiac on the right. This mass showed a significant increase in size within just five months and was not detected in a previous examination in 2021, surgical excision was performed. Histopathological analysis confirmed thymic carcinoma. Conclusion: LFS plays a crucial role in the pathogenesis of pediatric cancers, with PV in TP53 being associated with an increased predisposition to aggressive tumors with a poorer prognosis. Although the relationship between thymic tumors and pathogenic TP53 changes is rare, particularly in pediatric populations, surgical resection is a fundamental therapeutic approach for controlling neoplasms linked to the syndrome. This case highlights the importance of genetic and imaging screening in timely detection and management of malignancies in LFS patients. Presentation: Sunday, July 13, 2025

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.322
Teacher spread0.305 · 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 designTheoretical or conceptual
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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