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Record W2988733311 · doi:10.1182/blood-2019-124559

3D Telomeric Fingerprint of Advanced Cutaneous T-Cell Lymphoma

2019· article· en· W2988733311 on OpenAlexaff
Marc Bienz, Cheryl Taylor‐Kashton, Naciba Benlimame, Tina Petrogiannis‐Haliotis, Kevin Pehr, Sabine Mai, Hans Knecht

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsResearch Institute in Oncology and HematologyUniversity of ManitobaMcGill UniversityCancerCare ManitobaJewish General Hospital
Fundersnot available
KeywordsMycosis fungoidesCD30TelomereMalignancyFluorescence in situ hybridizationCutaneous T-cell lymphomaPathologyBiologyMedicineLymphomaCancer researchGeneticsDNA

Abstract

fetched live from OpenAlex

Introduction Cutaneous T-cell lymphomas (CTCLs) are characterized by dermal and epidermal infiltration of skin homing clonal CD4+ memory T-cells. Little is known about the oncogenic events driving either the progression of skin-limited disease such as Mycosis Fungoides (MF) to a leukemic form or Sézary Syndrome (SS), and there are no histologic means to predict evolution. Genetic instability is a hallmark of malignancy progression and telomere remodeling has been shown to play a role in the progression of hematological malignancies. Thus, the aim of this study is to characterize the three-dimensional (3D) telomeric organization in early and advanced CTCLs. Methods We performed 3D telomeric quantitative fluorescent in situ hybridization (3D Telo-Q-FISH) of 5mm skin tissue slides of 10 patients with MF and SS and of CD4+ lymphocytes of 3 healthy controls (Figure 1). Using the program TeloView (Vermolen et al., 2005), the proportion of telomeres of low intensity (TLI) (<5000 u), the nuclear volume and the total number of telomeric signals per cell were calculated. Patients were stratified based on CD30 expression (CD30 high, n=3 versus CD30 low, n=7) and clinical stage (early stages I-IIA, n=6 versus advanced stages IIB-IV, n=4). Results TLI represented 27% of telomeres in CTCL cells compared to 16% in control lymphocytes (p<0.0001). The highest proportion of TLIs was found in tumors CD30 high (34%), compared to 22% in tumors CD30 low (p<0.0001). Similar findings were observed when stratifying for advanced and early clinical stages (30% vs 24%, p<0.0001). Nuclear volume and total number of telomeric signals increased in CTCL cells expressing CD30 (both p<0.0001), and in CTCL cells associated with advanced clinical stages (p=0.0021 and p=0.001, respectively). However, as expected, nuclear volume and total number of telomeric signals were higher in control cells compared to CTCL cells (both p<0.0001). Conclusion We report clear evidence that CTCLs with either CD30 expression or advanced clinical stage are associated with loss of telomeres and telomeric signal intensity. These very small telomeres, termed 't-stumps', are a hallmark feature in many tumor cells. Analysis of the nuclear volume and total number of telomeric signals suggest that CTCL cells undergo in a first step telomere shortening and loss compared to healthy controls. In a second step further telomeric shortening associated with chromosomal rearrangements and bridge-breakage-fusion cycles may be involved in the progression of CTCL. Disclosures Pehr: Merck: Consultancy, Other: Clinical research on Alzheimers Drug; Eli Lilly: Consultancy, Other: Clinical research on Alzheimers Drug; galderma: Consultancy, Other: tactupump Forte; Actelion: Consultancy; valeant: Consultancy; CeraVe: Consultancy; Janssen-Cilag: Other: Train the trainer.

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 score0.002
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)0.0020.000

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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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