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Record W4396863343 · doi:10.1177/17588359241250158

Clinical activity of pembrolizumab in refractory <i>MDM2</i> -amplified advanced intimal sarcomas

2024· article· en· W4396863343 on OpenAlexaff
Maurício Fernando Silva Almeida Ribeiro, Elizabeth G. Demicco, Albiruni Ryan Abdul Razak

Bibliographic record

VenueTherapeutic Advances in Medical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsMount Sinai HospitalPrincess Margaret Cancer CentreUniversity of Toronto
FundersGenentechDeciphera PharmaceuticalsIterion TherapeuticsKaryopharm TherapeuticsAmgenPfizerDaiichi Sankyo EuropeBristol-Myers SquibbSymphogenGlaxoSmithKline
KeywordsPembrolizumabMedicineSarcomaTumor microenvironmentRefractory (planetary science)OncologySoft tissue sarcomaInternal medicineImmunotherapyChemotherapyPathologyCancer researchCancer

Abstract

fetched live from OpenAlex

Intimal sarcoma (InS) is an ultra-rare and aggressive subtype of soft tissue sarcoma (STS). It usually arises in large mediastinal arteries and the heart. In the advanced setting, sequential cytotoxic chemotherapy is often used, mainly based on retrospective studies and case series but with modest benefit. The use of immune checkpoint inhibitors is a promising strategy for some STS, but identifying biomarkers of response remains challenging due to disease rarity and heterogeneity. A reactive and pro-inflammatory tumor microenvironment (TME) is believed to be associated with better outcomes for patients receiving anti-PD-1-based regimens, generating the rationale to explore this strategy in malignancies with this characteristic, such as InS. We report three cases of advanced InS patients experiencing partial response to pembrolizumab-based therapy despite low tumor mutational burden and absence of mismatch-repair deficiency. We hypothesize that TME-related characteristics such as PD-L1 expression and the presence of tertiary lymphoid structures might explain this phenomenon.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.442
Teacher spread0.400 · 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 designOther design
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

Citations7
Published2024
Admission routes1
Has abstractyes

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