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Record W2123872331 · doi:10.1139/o08-069

Comparative proteomic analysis reveals differentially expressed proteins regulated by a potential tumor promoter, BRE, in human esophageal carcinoma cells

2008· article· en· W2123872331 on OpenAlexvenueno aff
Hai Bin Chen, Ke Pan, Florence Tang, Yiu‐Loon Chui, Chen Ling, Zhong Jing Su, Zhong Shen, En‐Min Li, Wei Xie, KK Lee

Bibliographic record

VenueBiochemistry and Cell Biology · 2008
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyCarcinogenesisProhibitinRNA interferenceDownregulation and upregulationCancer researchCarcinomaMolecular biologyGene silencingGeneCell biologyRNABiochemistryGenetics

Abstract

fetched live from OpenAlex

Esophageal tumorigenesis is a complex and cascading process, involving the interaction of many genes and proteins. In this study, we have used the comparative proteomic approach to identify tumor-associated proteins and explore the carcinogenic mechanisms. Two-dimensional electrophoresis (2-DE) and MALDI-TOF MS analysis of esophageal carcinoma and control cells revealed 10 proteins that were upregulated. A further 10 proteins were downregulated. Among these 20 differentially expressed proteins, brain and reproductive organ-expressed (BRE) protein was identified as a potential tumor promoter. It was high expressed by the esophageal carcinoma cells, as confirmed by RT-PCR and immunoblotting. BRE has been reported to be a stress-responsive protein. To gain further insight into its function, BRE expression was silenced in esophageal carcinoma cells using BRE-specific small interference RNA. It was discovered that silencing BRE expression downregulated prohibitin expression, but upregulated tumor-suppressor p53 expression. Furthermore, cyclin A and CDK2 expressions were suppressed suggesting that BRE inhibited cell proliferation. These results implied that BRE plays a significant role in mediating antiapoptotic and proliferative responses in esophageal carcinoma cells.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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 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

Citations28
Published2008
Admission routes1
Has abstractyes

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