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Record W2946814355

A biocomputational approach to the study of differential nature of E2 dependent breast cells

2006· article· en· W2946814355 on OpenAlexaff
Soma Barman, James Davie

Bibliographic record

VenueCancer Research · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGeneSerial analysis of gene expressionBreast cancerBiologyContext (archaeology)Microarray analysis techniquesGene expressionGene expression profilingCancer researchGeneticsCancer
DOInot available

Abstract

fetched live from OpenAlex

4184 Introduction: Estrogen (E2) is pivotal to normal breast development and in initiation and progression of breast carcinoma. Despite identification of novel E2 targets in breast from SAGE and microarray (MA) generated gene expression data, differences in the adaptive mechanisms favoring proliferation in E2 responsive cancer cells remain unknown, more so in the context of normal breast (NB) cells. Objectives: to study the differential nature of two E2 responsive breast cell lines (E2 deprived), MCF7 and ZR75 from the publicly available SAGE and MA expression data using biocomputational tools. Data analysis: SAGE software extracted significant genes were also analyzed by Audic Claverie, Fisher and Chi2 statistical tests (IDEG6), yielding 230 (MCF7) and 134 (ZR75) genes (p≤0.05, MCF7/NB or ZR75/NB ≥ 5/≤ -5). DAVID tool annotated 133 (ZR75) and 227 (MCF7) genes. Classified genes included 32% (biological process P), 35% (molecular function F), and 32% (component C) leaving ∼ 68% (high) genes unclassified in both. However, GO term utilization (P, F, C) among the classified genes was comparable (P 32.3%, F 34.6%, C 32.3%-ZR75 and P 32.2%, F 32.6%, C 27.8%-MCF7). Pathway differences were also identified by GenMAPP tool. Further, SAGE dataset was compared with Affymetrix MA dataset for MCF7. Finding summary: The two cell lines differentially expressed 9 out of ∼ 75 common genes and 160 (MCF7) and 96 (ZR75) genes were specific. GenMAPP revealed the differences in proteosomal degradation pathways and utilization of energy pathways, such as glycolysis & gluconeogenesis and electron transport chain genes expressing proteins for complexes I, III, IV, V, MCF7 up-regulating more genes (Table 1). In contrast to MCF7, ZR75 down-regulated more immune response genes. Conclusions: while both E2 responsive cells can thrive under harsh E2 deprived conditions, ZR75 cells possess a greater capability of minimizing energy requirements, proteosomal degradation, and compromising immune responses, resembling the more aggressive ER negative breast cancer cells. In contrast, MCF7 cells highly utilize these pathways rendering them less aggressive. These differences can be exploited for specific targeting of hormone dependent breast cancer.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.029
GPT teacher head0.353
Teacher spread0.324 · 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 designBench or experimental
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

Citations0
Published2006
Admission routes1
Has abstractyes

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