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p63 Expression in Lung Carcinoma

2004· article· en· W2038602639 on OpenAlexaff
Nicholas Au, A M Gown, Maggie C.U. Cheang, David Huntsman, Erika Yorida, W. Mark Elliott, Jonathan Flint, John C. English, C. Blake Gilks, H. Leighton Grimes

Bibliographic record

VenueApplied immunohistochemistry & molecular morphology · 2004
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsSt. Paul's HospitalBC Cancer AgencyUniversity of British ColumbiaVancouver General Hospital
FundersNational Cancer Institute
KeywordsImmunohistochemistryTissue microarrayPathologyMonoclonal antibodyLungMedicineLarge cellCellNeuroendocrine tumorsCarcinomaMonoclonalAdenocarcinomaAntibodyBiologyCancerInternal medicineImmunology

Abstract

fetched live from OpenAlex

p63 is a recently discovered member of the p53 family that has been shown to be important in the development of epithelial tissues. p63 may also play a role in squamous cell carcinomas of the lung, head and neck, and cervix, and its expression is increased in these tumors. The purpose of this study was to investigate the expression of p63 in a broad spectrum of histologic types of lung tumors. A total of 441 cases of primary lung tumors with follow-up data were identified, and the paraffin-embedded tissue blocks were used to construct a duplicate core tissue microarray. After review of the tissue cores, 408 cases, consisting of 123 squamous cell carcinomas, 93 adenocarcinomas, 68 large cell carcinomas, 68 classic carcinoids, 31 atypical carcinoids, 11 large cell neuroendocrine carcinomas, and 14 small cell carcinomas, were adequate for analysis. Immunohistochemistry was performed at 2 different laboratories using monoclonal antibody 4A4 to detect the expression of p63, using different staining protocols. p53 expression was also studied with immunohistochemistry using monoclonal antibody DO-7. Kaplan-Meier curves were plotted to compare the survival of p63-expressing versus nonexpressing tumors. A large proportion of squamous cell carcinomas expressed p63 (96.9%), most showing strong positive nuclear immunoreactivity. Expression in other nonsmall cell lung cancers was also present. Thirty percent of adenocarcinomas and 37% of large cell carcinomas showed p63 expression. In the neuroendocrine tumors, an increasing proportion of tumors stained for p63 as tumor grade increased; 1.9% of classic carcinoids, 30.8% of atypical carcinoids, 50% of large cell neuroendocrine carcinomas, and 76.9% of small cell carcinomas were positive. Approximately half of the positively staining neuroendocrine cases showed strong staining. Expression of p63 was of prognostic significance in neuroendocrine tumors (P < 0.0001), with higher-grade tumors more likely to express p63. Correlation between p63 and p53 expression was not observed (P = 0.18) in nonsmall cell lung cancer; however, a significant correlation between the 2 markers was found in neuroendocrine tumors (P < 0.0001). p63 staining was repeated with a different staining protocol, yielding similar results overall but a lower percentage of positive cases (34.2% vs. 48.4% of tumors positive). In conclusion, p63 expression is consistently expressed in squamous cell carcinoma in the lung, but is also expressed in a subset of adenocarcinomas and large cell carcinomas. Pulmonary neuroendocrine tumors also show p63 staining in some instances, particularly in higher-grade tumors, and the majority of small cell carcinomas are p63-positive. These results suggest that p63 may be involved in oncogenesis in a broader range of tumors than was previously thought.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.005
GPT teacher head0.243
Teacher spread0.238 · 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

Citations161
Published2004
Admission routes1
Has abstractyes

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