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Record W4287958183 · doi:10.1016/j.euros.2022.06.007

Combining Antiandrogens with Immunotherapy for Bladder Cancer Treatment

2022· article· en· W4287958183 on OpenAlexafffund
Marjorie Besançon, Typhaine Gris, France‐Hélène Joncas, Valérie Picard, Alain Bergeron, Yves Fradet, Paul Toren

Bibliographic record

VenueEuropean Urology Open Science · 2022
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsUniversité Laval
FundersJanssen PharmaceuticalsFonds de Recherche du Québec - SantéFerring PharmaceuticalsAstellas Pharma CanadaCanadian Cancer Society Research InstituteBayerCancer Research SocietyAbbVieMerckSanofiBristol-Myers SquibbAmgen
KeywordsEnzalutamideImmunotherapyMedicineImmune systemBladder cancerProstate cancerCancer researchCancerAndrogen receptorOncologyAntiandrogensIn vivoDurvalumabInternal medicineImmunologyBiologyPembrolizumab

Abstract

fetched live from OpenAlex

Background: Men are three to four times more likely to be diagnosed with bladder cancer (BCa) than women, who often have more aggressive tumors. Intravesical bacillus Calmette-Guerin (BCG) for non-muscle-invasive bladder cancer (NMIBC) is one of the first immunotherapies, with use of immune checkpoint inhibitors for BCa immunotherapy expanding. Sex hormones, and notably androgens, might impact the outcome of these therapies. Objective: To understand immunological sex differences in BCa and investigate androgen receptor (AR) inhibition as a novel strategy to improve the response to BCa immunotherapy. Design setting and participants: studies used the subcutaneous MBT-2 BCa model in male and female C3H mice. The AR antagonist enzalutamide was given alone or in combination with anti-programmed cell death protein-1 (anti-PD-1) or intratumoral BCG + poly(I:C) treatments. Outcome measurements and statistical analysis: . Flow cytometry and RNA sequencing characterized the immune cells present in murine and human tumors. Descriptive comparisons were performed for MBT-2 tumors between sexes and with human NMIBC tumors. Results and limitations: The MBT-2 model shows multiple similarities to the immune composition of human NMIBC tumors and recapitulates previously observed human tumor immune cell sex differences. Enzalutamide in combination with either anti-PD-1 or BCG + poly(I:C) treatment in male mice synergized to improve response rates. Notably, the proportion of complete responses in male mice treated with the combination treatment resembles that observed in female mice with either immunotherapy alone. Limitations include the sample size for murine experiments. Conclusions: Our results suggest that combining AR antagonism with immunotherapy in male BCa patients may potentiate the antitumor immune response and increase response rates. The MBT-2 model appears relevant to investigate immunological BCa sex differences. Patient summary: Our studies suggest that combining antiandrogen treatments with BCa immunotherapy may improve response rates in men. We also demonstrate the utility of the MBT-2 mouse model to study sex differences in BCa.

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 score0.006

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)0.0020.000

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 head0.042
GPT teacher head0.338
Teacher spread0.297 · 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

Citations26
Published2022
Admission routes2
Has abstractyes

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