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Record W2327927685 · doi:10.1158/1538-7445.am2013-1527

Abstract 1527: Investigation the role of prostate cancer derived exosomes on their tumor microenvironment.

2013· article· en· W2327927685 on OpenAlexaff
Elham Hosseini‐Beheshti, Christine Liu, Hans Adomat, Emma S. Tomlinson Guns

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMicrovesiclesMicrovesicleParacrine signallingProstate cancerCancer researchCancerSecretionCancer cellMedicineTumor microenvironmentExosomeCell biologyBiologyPathologymicroRNAInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction: Prostate cancer (PCa) is the leading type of cancer diagnosed in men. In 2012, approximately 241,740 new cases of PCa will be diagnosed in the United States. Prompt diagnosis of the disease can substantially improve its clinical outcome. Improving capability for early detection, as well as developing new therapeutic targets in advanced disease are research priorities that will ultimately lead to better patient survival. Eukaryotic cells secrete proteins via distinct regulated mechanisms which are either ER/Golgi dependent or microvesicle mediated. The release of microvesicles has been shown to provide a novel mechanism for intercellular communication. Exosomes are nanometer sized cup-shaped membrane vesicles which are secreted from normal and cancerous cells. They are present in various biological fluids such as serum, milk, urine, malignant ascites and amniotic fluid. Recent studies have demonstrated that cancerous cells secret exosomes which may be differentiated from those derived from normal cells upon their composition. Therefore, exosomes could be used in facilitating early diagnosis via less invasive procedures or be candidates for novel therapeutic approaches for different pathological disorders. Studies on tumour-related microvesicles suggest that exosomes play a significant role in paracrine signaling pathway thus potentially influencing cancer progression via different mechanisms. Methods and Results: Exosomes were purified from the conditioned media (CM) from different PCa cell lines after 72 hours in serum free media treatment. Using differential centrifugation cell debris and protein aggregates were removed from CM. Finally exosomes were isolated in a 30% sucrose cushion using ultracentrifugation. Further analysis using transmission electron microscopy validated the integrity of purified exosomes. Western blot analysis was also used to probe for different exosome markers. Proteomic mass spectrometry of exosomes reveals that exosomes derived from specific PCa cells present potential markers of PCa progression. Transfer of exosomes to non-identical cells in culture was visualised using confocal microscopy of fluorescence labeled exosomes as well as exosomal GFP tagged protein. Phenotypic change in recipient cells was studied upon exposure to exosomes derived from non-identical prostate cell lines and an impact on cell survival pathways associated with tumor microenvironment were observed. Conclusion: This study revealed that PCa derived exosomes represent a conduit for protein/genetic information transfer into their tumor microenvironment conferring pro-cell survival and metastasis. Citation Format: Elham Hosseini-Beheshti, Christine Liu, Hans Adomat, Emma S. (Tomlinson) Guns. Investigation the role of prostate cancer derived exosomes on their tumor microenvironment. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1527. doi:10.1158/1538-7445.AM2013-1527

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 score0.007

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 head0.023
GPT teacher head0.303
Teacher spread0.280 · 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
Published2013
Admission routes1
Has abstractyes

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