MétaCan
Menu
Back to cohort
Record W4399622071 · doi:10.1038/s41467-024-49424-5

Prostate cancer reshapes the secreted and extracellular vesicle urinary proteomes

2024· article· en· W4399622071 on OpenAlexafffund
Amanda Khoo, Meinusha Govindarajan, Zhuyu Qiu, Lydia Liu, Vladimir Ignatchenko, Matthew Waas, Andrew Macklin, Alexander Keszei, Sarah Neu, Brian P. Main, Lifang Yang, Raymond S. Lance, Michelle R. Downes, O. John Semmes, Danny Vesprini, Stanley K. Liu, Julius O. Nyalwidhe, Paul C. Boutros, Thomas Kislinger

Bibliographic record

VenueNature Communications · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsSunnybrook Health Science CentrePrincess Margaret Cancer CentreUniversity of TorontoHealth Sciences CentreUniversity Health Network
FundersCommon FundNational Institute of Neurological Disorders and StrokeNational Cancer InstituteNational Center for Advancing Translational SciencesNational Human Genome Research InstituteProstate Cancer FoundationNational Institute on Drug AbuseHospital for Sick ChildrenNational Heart, Lung, and Blood InstituteNational Institute of Mental HealthNIH Office of the DirectorCanadian Institutes of Health ResearchProstate Cancer CanadaNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsProteomeProstate cancerMicrovesiclesBiomarkerGenitourinary systemExtracellular vesicleUrineUrinary systemProstateSecretory proteinBiomarker discoveryBiologyPopulationCancerExtracellularProteomicsComputational biologyBioinformaticsCell biologyMedicineSecretionBiochemistryGeneEndocrinologymicroRNAGeneticsAnatomy

Abstract

fetched live from OpenAlex

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.300
Teacher spread0.289 · 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 teacher head, 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

Citations29
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicExtracellular vesicles in diseaseFrench-language works237,207