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Record W3011700050 · doi:10.1002/sctm.19-0286

Propagation of human prostate tissue from induced pluripotent stem cells

2020· article· en· W3011700050 on OpenAlexfundno aff
Anastasia C. Hepburn, Emma L. Curry, Mohammad Moad, Rebecca E. Steele, Omar E. Franco, Laura Wilson, Parmveer Singh, Adriana Buskin, Susan E. Crawford, Luke Gaughan, Ian G. Mills, Simon W. Hayward, Craig Robson, Rakesh Heer

Bibliographic record

VenueStem Cells Translational Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
FundersMedical Research CouncilImperial Experimental Cancer Medicine CentreEuropean CommissionMedical Research Council CanadaCancer Research UKProstate Cancer Foundation
KeywordsInduced pluripotent stem cellProstateStromal cellProstate cancerStem cellOrganoidMedicineTranslational researchMesenchymeEmbryonic stem cellPathologyMesenchymal stem cellBiologyCancer researchBioinformaticsComputational biologyCancerInternal medicineNeuroscienceCell biology

Abstract

fetched live from OpenAlex

Abstract Primary culture of human prostate organoids and patient-derived xenografts is inefficient and has limited access to clinical tissues. This hampers their use for translational study to identify new treatments. To overcome this, we established a complementary approach where rapidly proliferating and easily handled induced pluripotent stem cells enabled the generation of human prostate tissue in vivo and in vitro. By using a coculture technique with inductive urogenital sinus mesenchyme, we comprehensively recapitulated in situ 3D prostate histology, and overcame limitations in the primary culture of human prostate stem, luminal and neuroendocrine cells, as well as the stromal microenvironment. This model now unlocks new opportunities to undertake translational studies of benign and malignant prostate disease. Significance statement Growing cells from prostate cancer biopsies in the laboratory to study mechanisms of disease and to discover new treatments is fraught with difficulties and often not possible. This work establishes a new means to grow “mini 3D prostates” in the laboratory. It shows proof of concept that genetic modifications are possible in this innovative model, which lays the foundations for new preclinical approaches to personalized care previously considered too challenging. Specifically, in future work, one can develop genetically engineered prostate cancers in a dish, tailored to the specific genetic profiles of individual patients, and determine their best response to a range of drug treatments.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.063
GPT teacher head0.314
Teacher spread0.251 · 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

Citations37
Published2020
Admission routes1
Has abstractyes

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