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Apparent plasticity in the biological response to neoadjuvant chemotherapy in muscle-invasive bladder cancer.

2018· article· en· W2790746043 on OpenAlexaff
Roland Seiler, Ewan A. Gibb, Natalie Qiqi Wang, Htoo Zarni Oo, Hung‐Ming Lam, Kim E.M. van Kessel, Mandeep Takhar, Nicholas Erho, Brian Winters, James J. Douglas, Bas W.G. van Rhijn, Gottfrid Sjödahl, Ellen C. Zwarthoff, George N. Thalmann, Elai Davicioni, Joost L. Boormans, Marc Dall’Era, Michiel Simon Van Der Heijden, Jonathan L. Wright, Peter C. Black

Bibliographic record

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsUniversity of British ColumbiaGenome British Columbia
Fundersnot available
KeywordsCystectomyBladder cancerCisplatinMedicinePathologyNeoadjuvant therapyImmunohistochemistryChemotherapyCancer researchGATA3CancerOncologyInternal medicineBiologyBreast cancerGene

Abstract

fetched live from OpenAlex

433 Background: After cisplatin-based neoadjuvant chemotherapy (NAC) almost two thirds of patients have residual muscle-invasive bladder cancer (MIBC) present at radical cystectomy (RC). The alterations induced by NAC in these cisplatin-resistant tumors remain largely unstudied. Here, we aim to investigate the characteristics of cisplatin-resistant tumors. Methods: RC samples were available for gene expression analysis from 133 patients with residual invasive disease after cisplatin-based NAC, of whom 116 had matched pre-NAC samples. In addition, the tumor bed (scar tissue) of 21 post-NAC RC specimens with no residual tumor was profiled. Unsupervised consensus clustering (CC) was performed and the CC were investigated for their biological and clinical characteristics. H&E and immunohistochemistry (KRT5/6, GATA3, KI67 and CD8) were used to confirm tissue sampling and gene expression analysis. Results: Unsupervised consensus clustering yielded four distinct consensus clusters (CC). Consistent basal-(CC1) and luminal-like (CC2) phenotype similar to pre-NAC subtyping was observed in 42% of cases. One third of cases became immune-infiltrated (CC3) in the post-NAC setting but lacked basal and luminal markers. These tumors expressed a strong T-cell signature, chemokine signaling and checkpoint molecules. Conversely, CC4 was associated with healing/scarring. This ‘scar-like’ character of CC4 was consistent with the scar samples. Despite being pathological non-responders, the relative risk of death for CC4 was 2.8 and 3 times less than CC2-Luminal (p = 0.038) and CC3-Infiltrated (p = 0.018), respectively. Luminal-like pre-NAC samples were more likely to adopt a scar-like character (CC4) in the post-NAC setting, while the basal-like tumors were more likely to develop luminal features (CC2). Conclusions: This study expands our knowledge of cisplatin-resistant MIBC by suggesting molecular subtypes to understand the biology of these tumors. Clinical trials are necessary to test the impact of these molecular subtypes with respect to selection of adjuvant and salvage treatments. Post-NAC immune infiltration could have implications for subsequent immunotherapy.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.173
GPT teacher head0.493
Teacher spread0.320 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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