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Record W2809554354 · doi:10.1111/apm.12828

Molecular features of adenoid cystic carcinoma with an emphasis on micro<scp>RNA</scp>expression

2018· review· en· W2809554354 on OpenAlexaboutno aff
Simon Andreasen

Bibliographic record

VenueApmis · 2018
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsmicroRNAAdenoid cystic carcinomaEmphasis (telecommunications)CarcinomaComputational biologyCancer researchMedicinePathologyBiologyGeneticsComputer scienceGene

Abstract

fetched live from OpenAlex

Adenoid cystic carcinoma (ACC) is a rare malignancy most often affecting the salivary glands.Despite its slow growth, it has a grave prognosis characterized by frequent local recurrences, distant metastases, and tumor-related mortality often several years after a seemingly uncomplicated clinical course.The same features characterize ACC in the lacrimal gland, whereas ACC in the breast is an indolent disease.The molecular mechanisms involved in the metastatic process of ACC are poorly-understood despite being a major cause of ACC-related mortality.Also, molecular markers with prognostic value in salivary gland ACC are highly warranted in order to identify patients at high risk of recurrent disease.Increased understanding of the molecular characteristics involved in ACC has the potential to aid in individualized follow-up programs and ultimately in novel treatments.In order to investigate the molecular background of this, we conducted a series of studies evaluating i) the clinical, genetic, and microRNA (miRNA) expressional differences between ACC of the salivary gland, lacrimal gland, and breast, ii) the genetic and miRNA expressional differences between paired primary and metastatic salivary gland ACC, and iii) the value of miRNA as independent prognostics factors in a large material of salivary gland ACC.We found that ACC from the salivary gland, lacrimal gland, and breast were very similar in all parameters except for miRNA expression.Here, breast ACC was different from ACC of the two other sites and were more similar to normal breast tissue.In contrast, paired primary and metastatic salivary gland ACC were similar in their patterns of chromosomal aberrations, point mutations were few and heterogeneous, and miRNA expression did not differ significantly.Different subgroups of salivary gland ACC separated according to miRNA expression, and several miRNAs were found to be independent prognostic markers for overall and recurrence-free survival.In conclusion, salivary gland and lacrimal gland ACC are highly similar entities with breast ACC having a normal-like pattern of miRNA expression.The development of metastatic disease in salivary gland ACC is a heterogeneous biological process in which the involvement of miRNA is not clear, whereas several, wellcharacterized miRNAs function as independent prognostic markers in salivary gland ACC.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2018
Admission routes1
Has abstractyes

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