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Record W2499543174 · doi:10.1158/1538-7445.am2016-2922

Abstract 2922: Loss of retinoblastoma protein dysregulates HIF1-mediated genetic programs, and promotes tumor cell invasiveness and neuroendocrine differentiation in prostate cancer cells

2016· article· en· W2499543174 on OpenAlexaff
Mark P. Labrecque, Mandeep Takhar, Rebecca Nason, Stephanie Santacruz, Kevin J. Tam, Shabnam Massah, Anne Haegert, Robert H. Bell, Manuel Altamirano-Dimas, Colin C. Collins, Frank Lee, Gratien G. Préfontaine, Michael Cox, Timothy V. Beischlag

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsPrevention of Organ FailureUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsAryl hydrocarbon receptor nuclear translocatorNeuroendocrine differentiationBiologyCancer researchLNCaPRetinoblastoma proteinMetastasisProtein kinase BProstate cancerCell biologyTranscription factorSignal transductionCancerCell cycleGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Loss of tumour suppressor proteins, such as the retinoblastoma protein (Rb), results in tumour progression and metastasis. Metastasis is facilitated by low oxygen availability within the tumour that is detected by hypoxia inducible factors (HIFs). The HIF1 complex, HIF1α and its dimerization partner the aryl hydrocarbon receptor nuclear translocator (ARNT), is the master regulator of the hypoxic response. Previously, we demonstrated that Rb represses the transcriptional response to hypoxia by virtue of its association with HIF1. In this report, we further characterized the role of Rb in HIF1-regulated genetic programs by stably ablating Rb expression with retrovirally-introduced short hairpin RNA in LNCaP and 22rV1 human prostate cancer cells. DNA microarray analysis revealed that Rb regulates specific chromosomal gene clusters and loss of Rb in conjunction with hypoxia leads to dysregulation of HIF1-regulated genetic programs that promote cell invasion and neuroendocrine differentiation. Gene ontology analysis of the hypoxia-inducible genes sensitive to loss of Rb revealed that a significant portion of these genes are involved in neuroendocrine differentiation (NED), specifically ENO2, KISS1R and HTR5A. ENO2 is the bonafide marker of neuroendocrine differentiation and it's presence is a signature of late stage castrate resistant prostate cancer. Furthermore, we have functional evidence KISS1R is linked to intracellular calcium mobilization in 22RV1 cells. We have demonstrated that increased expression of HIF-regulated genes in response to loss of Rb activates Akt and ERK signaling pathways and promotes neuroendocrine differentiation and invasion. Inhibition of these signaling pathways significantly decreased actin polymerization in LNCaP cells. For the first time, we have established a direct link between hypoxic tumour environments, Rb inactivation and progression to late stage metastatic neuroendocrine prostate cancer. Understanding the molecular pathways responsible for progression of benign prostate tumours to metastasized and lethal forms will aid in the development of more effective prostate cancer therapies. Citation Format: Mark Labrecque, Mandeep Takhar, Rebecca J. Nason, Stephanie Santacruz, Kevin Tam, Shabnam Massah, Anne Haegert, Robert Bell, Manuel Altamirano-Dimas, Colin Collins, Frank Lee, Gratien Prefontaine, Michael Cox, Timothy Beischlag. Loss of retinoblastoma protein dysregulates HIF1-mediated genetic programs, and promotes tumor cell invasiveness and neuroendocrine differentiation in prostate cancer cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2922.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.001

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 head0.016
GPT teacher head0.286
Teacher spread0.269 · 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
Published2016
Admission routes1
Has abstractyes

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