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Record W2146358354

Analysis of gene expression in ductal carcinoma in situ of the breast.

2002· article· en· W2146358354 on OpenAlexaff
Adewale Adeyinka, Ethan Emberley, Yulian Niu, Linda Snell, Leigh C. Murphy, Heidi Sowter, Charles C. Wykoff, Adrian L. Harris, Peter H. Watson

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDuctal carcinomaBiologyNecrosisGene expressionPathologyIn situ hybridizationBreast cancerLaser capture microdissectionMammary glandCancer researchCancerGeneMedicineGenetics
DOInot available

Abstract

fetched live from OpenAlex

PURPOSE: The risk of recurrence and progression of ductal carcinoma in situ (DCIS) of the breast is best designated by morphological indicators, including the presence of necrosis. Our purpose was to identify molecular alterations underlying progression of DCIS. EXPERIMENTAL DESIGN: We have compared gene expression within a cohort of six cases of DCIS with necrosis (DCIS(necrosis+)) and four cases without necrosis (DCIS(necrosis-)) using microdissection and cDNA microarray. RESULTS: A set of 69 cDNAs from a group of 1,181 was identified that were consistently differentially expressed. Among this set, the mRNA for angio-associated migratory cell protein and a serine threonine protein kinase, nuclear Dbf2 related, were consistently higher in DCIS(necrosis+) and were also found to be overexpressed in the T47D breast cancer cell line subjected to hypoxia. Further study of angio-associated migratory cell protein by quantitative reverse transcriptase-PCR and in situ hybridization analysis of 37 cases of DCIS confirmed higher mRNA expression in DCIS(necrosis+) (P = 0.0095). CONCLUSIONS: This study shows that although levels of gene expression are mostly similar between morphologically different DCIS, consistent differences in expression of a subset of genes can be identified between DCIS with and without necrosis.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.184

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 head0.011
GPT teacher head0.200
Teacher spread0.188 · 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

Citations89
Published2002
Admission routes1
Has abstractyes

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