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Record W2883866956 · doi:10.1158/2326-6066.cir-18-0037

Response to Immune Checkpoint Inhibition in Two Patients with Alveolar Soft-Part Sarcoma

2018· article· en· W2883866956 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Immunology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoMount Sinai HospitalHospital for Sick ChildrenPrincess Margaret Cancer Centre
FundersMedImmune
KeywordsAlveolar soft part sarcomaSarcomaMedicineSoft tissue sarcomaImmunotherapyImmune checkpointImmune systemCancer researchImmunologyPathology

Abstract

fetched live from OpenAlex

Abstract Alveolar soft-part sarcoma (ASPS) is a morphologically distinctive mesenchymal tumor characterized by a canonical ASPL–TFE3 fusion product. In the metastatic setting, standard cytotoxic chemotherapies are typically ineffective. Studies have suggested modest clinical response to multitargeted receptor tyrosine kinase inhibitors. Here, we report sustained partial responses in two patients with immune checkpoint inhibition treated with either durvalumab (anti–PD-L1) alone or in combination with tremelimumab (anti–CTLA-4), which appeared unrelated to tumor immune infiltrates or mutational burden. Genomic analysis of these patients, and other cases of ASPS, demonstrated molecular mismatch-repair deficiency signatures. These findings suggest that immune checkpoint blockade may be a useful therapeutic strategy for ASPS. Cancer Immunol Res; 6(9); 1001–7. ©2018 AACR.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.047
GPT teacher head0.388
Teacher spread0.341 · 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