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Record W2021181403 · doi:10.1158/0008-5472.can-2148-2

Dysregulation of Sterol Response Element-Binding Proteins and Downstream Effectors in Prostate Cancer during Progression to Androgen Independence

2004· article· en· W2021181403 on OpenAlexaff
Susan Ettinger, Richard Sobel, Tanis G. Whitmore, Majid Akbari, Dawn R. Bradley, Martin Gleave, Colleen C. Nelson

Bibliographic record

VenueCancer Research · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsLNCaPProstate cancerSterol regulatory element-binding proteinEndocrinologyAndrogenInternal medicineLipogenesisBiologyCancer researchTumor progressionBicalutamideDihydrotestosteroneFatty acid synthaseAndrogen receptorCancerSterolMedicineCholesterolLipid metabolismHormone

Abstract

fetched live from OpenAlex

Androgen ablation, the most common therapeutic treatment used for advanced prostate cancer, triggers the apoptotic regression of prostate tumors. However, remissions are temporary because surviving prostate cancer cells adapt to the androgen-deprived environment and form androgen-independent (AI) tumors. We hypothesize that adaptive responses of surviving tumor cells result from dysregulated gene expression of key cell survival pathways. Therefore, we examined temporal alterations to gene expression profiles in prostate cancer during progression to androgen independence at several time points using the LNCaP xenograft tumor model. Two key genes, sterol response element-binding protein (SREBP)-1 and -2 (SREBP-1a,-1c, and -2), were consistently dysregulated. These genes are known to coordinately control the expression of the groups of enzymes responsible for lipid and cholesterol synthesis. Northern blots revealed modest increased expression of SREBP-1a, -1c, and -2 after castration, and at androgen independence (day 21-28), the expression levels of both SREBP-1a and -1c were significantly greater than precastrate levels. Changes in SREBP-1 and -2 protein expression were observed by Western analysis. SREBP-1 68-kDa protein levels were maintained throughout progression, however, SREBP-2 68-kDa protein expression increased after castration and during progression (3-fold). SREBPs are transcriptional regulators of over 20 functionally related enzymes that coordinately control the metabolic pathways of lipogenesis and cholesterol synthesis, some of which were likewise dysregulated during progression to androgen independence. RNA levels of acyl-CoA-binding protein/diazepam-binding inhibitor and fatty acid synthase decreased significantly after castration, and then, during progression, increased to levels greater than or equal to precastrate levels. Expression of farnesyl diphosphate synthase did not decrease after castration but did increase significantly during progression to androgen independence. Levels of SREBP cleavage-activating protein, a regulator of SREBP transcriptional activity, decreased after castration and increased significantly at androgen independence. In clinical prostate cancer specimens from patients with varying grades of disease, the stained tissue sections showed high levels of SREBP-1 protein compared with noncancerous prostate tissue. After hormone withdrawal therapy, tumor levels of SREBP-1 decreased significantly after 6 weeks. AI tumors expressed significantly higher levels of SREBP-1. In summary, the LNCaP xenograft model of human prostate cancer as well as clinical specimens of prostate cancer demonstrated an up-regulation of SREBPs and their downstream effector genes during progression to androgen independence. As the AI phenotype emerges, enzymes critical for lipogenesis and cholesterol synthesis are activated and likely contribute significantly to cell survival of AI prostate 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)0.000
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 score0.002
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.364
Teacher spread0.347 · 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".

Quick stats

Citations283
Published2004
Admission routes1
Has abstractyes

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