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Predicting response and toxicity to PD-1 inhibition using serum autoantibodies identified from immuno-mass spectrometry

2020· preprint· en· W3023607046 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueF1000Research · 2020
Typepreprint
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsLunenfeld-Tanenbaum Research InstitutePrincess Margaret Cancer CentreMount Sinai HospitalUniversity Health NetworkUniversity of Toronto
FundersGenentechServierRegeneron PharmaceuticalsMersana TherapeuticsKaryopharm TherapeuticsPTC TherapeuticsPrincess Margaret Cancer FoundationSanofiMerckGlaxoSmithKlineAmgenPfizerMorphoSysCelgeneSymphogenAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsAutoantibodyOpen peer reviewPlant biologyToxicityMedicineMass spectrometryImmunologyPharmacologyPhysiologyBiologyChemistryInternal medicineAntibodyChromatographyBotany

Abstract

fetched live from OpenAlex

<ns3:p> <ns3:bold>Background:</ns3:bold> Validated biomarkers are needed to identify patients at increased risk of immune-related adverse events (irAEs) to immune checkpoint blockade (ICB). Antibodies directed against endogenous antigens can change after exposure to ICB. </ns3:p> <ns3:p> <ns3:bold>Methods:</ns3:bold> Patients with different solid tumors stratified into cohorts received pembrolizumab every 3 weeks in a Phase II trial (INSPIRE study). Blood samples were collected prior to first pembrolizumab exposure (baseline) and approximately 7 weeks (pre-cycle 3) into treatment. In a discovery analysis, autoantibody target immuno-mass spectrometry was performed in baseline and pre-cycle 3 pooled sera of 24 INSPIRE patients based on clinical benefit (CBR) and irAEs. </ns3:p> <ns3:p> <ns3:bold>Results:</ns3:bold> Thyroglobulin (Tg) and thyroid peroxidase (TPO) were identified as the candidate autoantibody targets. In the overall cohort of 78 patients, the frequency of CBR and irAEs from pembrolizumab was 31% and 24%, respectively. Patients with an anti-Tg titer increase ≥1.5x from baseline to pre-cycle 3 were more likely to have irAEs relative to patients without this increase in unadjusted, cohort adjusted, and multivariable models (OR=17.4, 95% CI 1.8–173.8, p=0.015). Similarly, patients with an anti-TPO titer ≥ 1.5x from baseline to pre-cycle 3 were more likely to have irAEs relative to patients without the increase in unadjusted and cohort adjusted (OR=6.1, 95% CI 1.1–32.7, p=0.035) models. Further, the cohort adjusted analysis showed patients with anti-Tg titer greater than median (10.0 IU/mL) at pre-cycle 3 were more likely to have irAEs (OR=4.7, 95% CI 1.2–17.8, p=0.024). Patients with pre-cycle 3 anti-TPO titers greater than median (10.0 IU/mL) had a significant difference in overall survival (23.8 vs 11.5 months; HR=1.8, 95% CI 1.0–3.2, p=0.05). </ns3:p> <ns3:p> <ns3:bold>Conclusions:</ns3:bold> Patient increase ≥1.5x of anti-Tg and anti-TPO titers from baseline to pre-cycle 3 were associated with irAEs from pembrolizumab, and patients with elevated pre-cycle 3 anti-TPO titers had an improvement in overall survival. </ns3:p>

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
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 head0.074
GPT teacher head0.374
Teacher spread0.300 · 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