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Record W2081166852 · doi:10.1158/1538-7445.am2011-3038

Abstract 3038: Characterization of ZHX1 in node-negative breast cancer

2011· article· en· W2081166852 on OpenAlexaff
Kristine S. Louis, Dushanthi Pinnaduwage, Anna Marie Mulligan, Shelley B. Bull, Irene L. Andrulis

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsSt. Michael's HospitalLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsBreast cancerLymphovascular invasionTranscription factorMetastasisCancerCancer researchOncologyMedicineBiologyTissue microarrayGeneInternal medicinePathologyGenetics

Abstract

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Abstract Women with breast cancer but without local metastasis to the axillary lymph nodes (ANN) have a good prognosis. However, 20 to 30% of patients with ANN breast cancer will still experience recurrence and distant metastases. Lymphatic invasion (LVI) is an important prognostic factor for ANN breast cancer. Therefore, LVI status was incorporated to provide a unique approach to identify novel genes related to outcome in ANN breast cancer. Gene expression microarrays were used to discriminate between tumors 1) with or without LVI (LVI+ or LVI-, respectively) and 2) from patients who experienced early recurrence (within 4 years) and those who were disease-free (for at least 10 years). Biostatistical analyses were performed to compile a list of statistically significant genes common to both comparisons. Zinc fingers and homeoboxes 1 (ZHX1) was identified as a candidate gene involved in LVI and associated with early recurrence of ANN breast cancer. Real-time RT-PCR (qPCR) was performed to quantify ZHX1 expression in a subset of cell lines and tumor samples. ZHX1 is expressed at different levels, mostly at an intermediate level in the tumors. A more network-based approach was used to examine biological pathways that may be associated with this poor prognosis. We discovered that ZHX1 may be involved in transcription, signaling, metabolism, and development, which is consistent with previous findings. ZHX1 binds to the other two members of the ZHX family, ZHX2 and ZHX3. All three members bind to the activation domain of the alpha subunit of nuclear transcription factor γ (NF-γ). NF-γ activates transcription of several genes, including the cell cycle progression gene, cell division cycle 25 homolog C (CDC25C). However, ZHX2 represses promoter activity of CDC25C, which would prevent cells from progressing into mitosis. Since ZHX1 binds to ZHX2 and NF-γ, this suggests that ZHX1 may be involved in the cell cycle. ZHX1 is significantly over-expressed in LVI+ tumors and in those from patients who experienced early recurrence of ANN breast cancer. The potential role of ZHX1 in the cell cycle may be associated with this poor prognosis. Gene and protein expression of ZHX1 and its candidate interactors are being quantified in cell lines via qPCR and Western blotting, respectively, and potential correlations examined. Immunohistochemistry is being performed on tissue microarrays to observe ZHX1 protein levels and localization and correlate with gene expression. Cell lines are being transfected via vector- or siRNA- based methods to over-express or knock down ZHX1, respectively. Alterations in tumorigenicity are being investigated via MTT proliferation and migration and/or invasion assays. Findings may aid in determining which ANN breast cancer patients may benefit from systemic therapy and identifying novel targets for cancer therapeutics. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3038. doi:10.1158/1538-7445.AM2011-3038

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.050
GPT teacher head0.354
Teacher spread0.304 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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