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Record W4286716089 · doi:10.1038/s41379-022-01100-z

Mucoepidermoid carcinoma (MEC) and adenosquamous carcinoma (ASC), the same or different entities?

2022· review· en· W4286716089 on OpenAlexaff
Valerie A. White, Martin Hyrcza, Jochen K. Lennerz, Julia Thierauf, Dilani Lokuhetty, Ian A. Cree, Blanca Iciar Indave

Bibliographic record

VenueModern Pathology · 2022
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsUniversity of Calgary
FundersNational Cancer InstituteWorld Health OrganizationU.S. Department of Health and Human Services
KeywordsAdenosquamous carcinomaMucoepidermoid carcinomaKRASCarcinomaMedicineInternal medicinePathologySebaceous carcinomaOncologyAdenocarcinomaCancerColorectal cancer

Abstract

fetched live from OpenAlex

Mucoepidermoid carcinoma (MEC) and adenosquamous carcinoma (ASC) have overlapping histopathological appearances and sites of occurrence, which may cause diagnostic difficulty impacting subsequent treatment. We conducted a systematic review of the scientific literature to determine whether molecular alterations were sufficiently different in MEC and ASC to aid in classifying the two entities. We searched Medline, Embase and Web of Science for studies reporting molecular determinations of ASC and/or MEC and screened retrieved records for eligibility. Two independent researchers reviewed included studies, assessed methodological quality and extracted data. Of 8623 identified records, 128 articles were included for analysis: 5 which compared the two tumors in the same investigation using the same methods and 123 which examined the tumors separately. All articles, except one were case series of moderate to poor methodological quality. The 5 publications examining both tumors showed that 52/88 (59%) MEC and 0% of 110 ASC had rearrangement of the MAML2 gene as detected by FISH and/or RT-PCR, but did not investigate other genes. In the entire series MEC had MAML2 gene rearrangement in 1337/2009 (66.6%) of tumors studied. The articles examining tumors separately found that MEC had mutations in EGFR (11/329 cases, 3.3%), KRAS (11/266, 4.1%) and ERBB2 (9/126, 7.1%) compared with ASC that had mutations in EGFR (660/1705, 38.7%), KRAS (143/625, 22.9%) and ERBB2 (6/196, 3.1%). The highest level of recurrent mutations was in pancreatic ASC where (108/126, 85.7%) reported mutations in KRAS. The EGFR mutations in ASC were similar in number and kind to those in lung adenocarcinoma. By standards of systematic review methodology and despite the large number of retrieved studies, we did not find adequate evidence for a distinctive molecular profile of either MEC or ASC that could definitively aid in its classification, especially in histologically difficult cases that are negative for MAML2 rearrangement. The case series included in this review indicate the relevance of MAML2 rearrangement to support the diagnosis of MEC, findings that should be confirmed by additional research with adequate study design.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.090
GPT teacher head0.324
Teacher spread0.234 · 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.

Study designOther design
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

Citations16
Published2022
Admission routes1
Has abstractyes

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