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Record W2126944439 · doi:10.18632/oncotarget.4546

Genetic determinants of FOXM1 overexpression in epithelial ovarian cancer and functional contribution to cell cycle progression

2015· article· en· W2126944439 on OpenAlexaffabout
Carter J. Barger, Wa Zhang, Joanna C. Hillman, Aimee Stablewski, Michael J. Higgins, Barbara C. Vanderhyden, Kunle Odunsi, Adam R. Karpf

Bibliographic record

VenueOncotarget · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFOXO transcription factor regulation
Canadian institutionsUniversity of Ottawa
FundersCancer Institute, University of PittsburghUniversity of Illinois at Urbana-ChampaignNational Cancer InstituteNational Institutes of HealthQueen Mary University of LondonOvarian Cancer Research FundRoswell Park Cancer InstituteU.S. Department of Defense
KeywordsFOXM1Cancer researchOvarian cancerCell cycleCell cycle progressionCell growthBiologyMedicineCancerBioinformaticsOncologyGenetics

Abstract

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// Carter J. Barger 1 , Wa Zhang 1 , Joanna Hillman 2 , Aimee B. Stablewski 2 , Michael J. Higgins 2 , Barbara C. Vanderhyden 3 , Kunle Odunsi 4, 5, 6 , Adam R. Karpf 1 1 Eppley Institute and Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE, 68198, USA 2 Department of Molecular and Cellular Biology, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA 3 Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, K1H 8M5, Canada 4 Department of Immunology, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA 5 Department of Gynecologic Oncology, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA 6 Center for Immunotherapy, Roswell Park Cancer Institute, Buffalo, NY, 14263, USA Correspondence to: Adam R. Karpf, e-mail: adam.karpf@unmc.edu Keywords: FOXM1, epithelial ovarian cancer, p53, Rb, E2F1 Received: March 17, 2015 Accepted: July 06, 2015 Published: July 16, 2015 ABSTRACT The FOXM1 transcription factor network is frequently activated in high-grade serous ovarian cancer (HGSOC), the most common and lethal subtype of epithelial ovarian cancer (EOC). We used primary human EOC tissues, HGSOC cell lines, mouse and human ovarian surface epithelial (OSE) cells, and a murine transgenic ovarian cancer model to investigate genetic determinants of FOXM1 overexpression in EOC, and to begin to define its functional contribution to disease pathology. The Cancer Genome Atlas (TCGA) data indicated that the FOXM1 locus is amplified in ~12% of HGSOC, greater than any other tumor type examined, and that FOXM1 amplification correlates with increased expression and poor survival. In an independent set of primary EOC tissues, FOXM1 expression correlated with advanced stage and grade. Of the three known FOXM1 isoforms, FOXM1c showed highest expression in EOC. In murine OSE cells, combined knockout of Rb1 and Trp53 synergistically induced FOXM1. Consistently, human OSE cells immortalized with SV40 Large T antigen (IOSE-SV) had significantly higher FOXM1 expression than OSE immortalized with hTERT (IOSE-T). FOXM1 was overexpressed in murine ovarian tumors driven by combined Rb1 / Trp53 disruption. FOXM1 induction in IOSE-SV cells was partially dependent on E2F1, and FOXM1 expression correlated with E2F1 expression in human EOC tissues. Finally, FOXM1 functionally contributed to cell cycle progression and relevant target gene expression in human OSE and HGSOC cell models. In summary, gene amplification, p53 and Rb disruption, and E2F1 activation drive FOXM1 expression in EOC, and FOXM1 promotes cell cycle progression in EOC cell models.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.274
Teacher spread0.261 · 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

Citations93
Published2015
Admission routes2
Has abstractyes

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