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Record W3081724831 · doi:10.1158/1538-7445.am2020-3553

Abstract 3553: Three-dimensional (3D) telomere signatures of sporadic pediatric papillary thyroid carcinoma (PTC)

2020· article· en· W3081724831 on OpenAlexaff
Luiza Sisdelli, Maria Isabel Cunha Vieira Cordioli, Fernanda Vaisman, Osmar Monte, Carlos Alberto Longui, Adriano Namo Cury, Monique Oliveira Freitas, Aline Rangel‐Pozzo, Sabine Mai, Janete M. Cerutti

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTelomereCarcinogenesisThyroid carcinomaThyroid cancerPopulationMedicinePathologyCancerThyroidPapillary thyroid cancerFluorescence in situ hybridizationInternal medicineCancer researchGastroenterologyBiologyEndocrinologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract The incidence of thyroid carcinoma has increased worldwide, including in pediatric patients. Papillary thyroid carcinoma (PTC) is the most common subtype. Previous studies have suggested that clinical presentation and outcome diverge between pediatric and adult PTC and that this difference is likely due to distinct genetic alterations. BRAF V600E point mutation is highly prevalent in adults, while genetic fusions (RET/PTC, AGK-BRAF, ETV6-NTRK3) are the most prevalent events in the pediatric population. As telomere loss or dysfunction results in aneuploidy and chromosomal rearrangements, which can promote carcinogenesis, we investigated the three-dimensional (3D) structure of the telomeres in the nuclei from 21 pediatric patients (≤18 y.o), representing 16 PTC cases (with paired normal and tumor tissues for five of them) and five normal thyroid tissues from patients undergoing thyroidectomy for reasons other than cancer. We performed quantitative fluorescence in situ hybridization (FISH), 3D imaging, and 3D telomere analysis using TeloView® software to examine telomere dysfunction. The parameters examined included total number of signals (numbers of telomeres), total number of telomere aggregates, a/c ratio (indicating the phase of the cell cycle), total intensity (telomere length) and nuclear volume. Thyroid cancer cells showed lower average intensity of signals (p<0.0001) and lower intensity signals (p<0.0001), as well as higher nuclear volume (p<0.0001), compared to normal thyroid cells. In addition, tumour cells showed a higher a/c ratio (p<0.0001), indicating that they are more actively dividing than normal cells, which correlates with the high proliferation rate of cancer cells. We did not observe any alterations related to the total number of telomere signals and total number of aggregates, which suggests no significant aneuploidies occurring with these samples. The 3D nuclear telomere signature was able to detect differences in telomere architecture in tumours, compared to normal. Further analysis is necessary to define whether nuclear telomere architecture and specific genetic alterations observed in pediatric thyroid cancer are associated. Citation Format: Luiza Sisdelli, Maria Isabel Cordioli, Fernanda Vaisman, Osmar Monte, Carlos Longui, Adriano N. Cury, Monique O. Freitas, Aline Rangel-Pozzo, Sabine Mai, Janete Cerutti. Three-dimensional (3D) telomere signatures of sporadic pediatric papillary thyroid carcinoma (PTC) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3553.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.351
Teacher spread0.282 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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