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Abstract LB-293: High-throughput proteomic analysis identifies protein s as a modulator of high grade and castrate-resistant prostate cancer

2012· article· en· W2325289331 on OpenAlexaff
Punit Saraon, Keith Jarvi, Eleftherios P. Diamandis

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsDU145LNCaPProstate cancerProstateCancer researchAndrogenCancerAndrogen deprivation therapyInternal medicineMedicineOncologyBiologyHormone

Abstract

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Abstract High-Throughput Proteomic Analysis Identifies Protein S as a Potential Modulator of Castrate-Resistant Prostate Cancer Punit Saraon, Daniela Cretu, Colm Morrissey, Keith Jarvi, Eleftherios P. Diamandis Androgen-deprivation remains the principal therapy for advanced and metastatic prostate cancers. However, some cancer cells can survive this treatment and transform themselves to a more aggressive androgen-independent prostate cancer (AIPC). An understanding of the molecular alterations that occur during the progression to androgen-independence is an integral step to generate effective targeted therapies. Using Mass Spectrometry, we compared the proteomes of androgen independent cell lines (PC3, DU145, PPC1, LNCaP-SF, 22Rv1) to androgen-dependent (LNCaP, VCaP) and normal prostate epithelial (RWPE) cell lines. We identified more than 100 proteins that were differentially secreted in the androgen independent cell lines, based on spectral counts. Of these, Protein S (PROS1) was elevated in the secretomes of all of the AIPC cell lines, with no detectable secretions in normal and androgen dependent cell lines. Using qPCR, we observed significantly higher tissue expression levels of PROS1 in prostate cancer samples (p<0.05), further indicating its importance in prostate cancer progression. Similarly, immunohistochemistry analysis revealed elevation of PROS1 during high grade prostate cancer (Gleason ≥ 8), and further elevation in castrate-resistant metastatic prostate cancer lesions. We also observed its elevation in high grade prostate cancer seminal plasma samples (P<0.05). To understand the functional role of PROS1 with respect to prostate cancer progression, we generated stable PROS1 knock-downs in DU145 cells, and performed cell migration and viability assays. In-vitro scratch assays measuring cell migration and proliferation revealed that PROS1 enhanced growth of prostate cancer cells, as there was significantly reduced wound closure in shPROS1 DU145 cells compared to scrambled control cells (p<0.05). In addition, cell viability assays showed that shPROS1 cells had reduced survival rates compared to scrambled cells when treated with the chemotherapeutic agents, docetaxel and paclitaxel, indicating its role as a potential anti-apoptotic factor. Taken together, our preliminary results show that PROS1 is elevated during high grade and castrate-resistant prostate cancer, and promotes prostate cancer migration and cell survival. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-293. doi:1538-7445.AM2012-LB-293

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.043
GPT teacher head0.389
Teacher spread0.346 · 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".

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Citations0
Published2012
Admission routes1
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