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Record W3187034576 · doi:10.3390/curroncol28040241

Discrimination of Cancer Stem Cell Markers ALDH1A1, BCL11B, BMI-1, and CD44 in Different Tissues of HNSCC Patients

2021· article· en· W3187034576 on OpenAlexvenueno aff
Kariem Sharaf, Axel Lechner, Stefan P. Haider, Robert Wiebringhaus, Christoph Walz, Gisela Kranz, Martin Canis, Frank Haubner, Olivier Gires, Philipp Baumeister

Bibliographic record

VenueCurrent Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsnot available
Fundersnot available
KeywordsCD44MedicineHead and neck squamous-cell carcinomaCancer stem cellCancerOncologyPathologyLymph nodeMetastasisStem cellStem cell markerInternal medicineCancer researchHead and neck cancerCellBiology

Abstract

fetched live from OpenAlex

Cancer stem cells (CSCs) are accountable for the progress of head and neck squamous cell carcinoma (HNSCC). This exploratory study evaluated the expression of molecular CSC markers in different tissues of HNSCC patients. Tissue specimens of primary tumor, lymph node metastases and macroscopically healthy mucosa of 12 consecutive HNSCC patients, that were treated with surgery and adjuvant radio(chemo)therapy upon indication, were collected. Samples were assessed for the expression of p16 as a surrogate for HPV-related disease and different molecular stem cell markers (ALDH1A1, BCL11B, BMI-1, and CD44). In the cohort, seven patients had HPV-related HNSCC; six thereof were oropharyngeal squamous cell carcinoma. While expression of BMI-1 and BCL11B was significantly lower in healthy mucosa than both tumor and lymph node metastasis, there were no differences between tumor and lymph node metastasis. In the HPV-positive sub-cohort, these differences remained significant for BMI-1. However, no significant differences in these three tissues were found for ALDH1A1 and CD44. In conclusion, this exploratory study shows that CSC markers BMI-1 and BCL11B discriminate between healthy and cancerous tissue, whereas ALDH1A1 and CD44 were expressed to a comparable extent in healthy mucosa and cancerous tissues.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.066
GPT teacher head0.387
Teacher spread0.321 · 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 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

Citations15
Published2021
Admission routes1
Has abstractyes

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