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Rapid expansion of M-MDSCs and association with high levels of plasma TSLP and primary resistance to PD-1 inhibitors in metastatic NSCLC.

2020· article· en· W3032874360 on OpenAlexaff
Sally C. M. Lau, Stephanie WY Wong, Ben X. Wang, Devalben Patel, Aline Fusco Fares, Ming‐Sound Tsao, Penelope Ann Bradbury, Geoffrey Liu, Natasha B. Leighl, Frances A. Shepherd, Pamela S. Ohashi, Adrian G. Sacher

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineThymic stromal lymphopoietinPeripheral blood mononuclear cellMyeloidMyeloid-derived Suppressor CellOncologyImmune systemImmunologyInternal medicineImmunotherapyCancer researchCancerSuppressorBiology

Abstract

fetched live from OpenAlex

3084 Background: Elevated frequency of peripheral myeloid cell populations has consistently been associated with poor response to immune checkpoint inhibitors (ICI) in metastatic non-small cell lung cancer (mNSCLC). The mechanisms underlying this relationship remains poorly understood. Thymic stromal lymphopoietin (TSLP), a cytokine involved in T-cell maturation, has been implicated in a complex feedback loop leading to tumor growth and expansion of myeloid populations. We hypothesized that TSLP levels directly correlate with the presence and expansion of myeloid derived suppressor cell (MDSC) populations and sought to explore their association with response to PD-1 inhibitors in mNSCLC. Methods: mNSCLC patients treated with ICIs underwent baseline and serial blood collection. Peripheral blood mononuclear cells (PBMC) were analyzed by high-dimensional flow cytometry using validated panels to evaluate T/B/NK-cell, Treg and myeloid populations. Plasma cytokines including TSLP were analyzed using ELISA and Luminex assays. Cox and logistic regressions were utilized to correlate biomarkers with progression-free survival (PFS), overall survival (OS) and radiographic response. Results: 30 mNSCLC patients treated with single-agent ICI were included in the analysis. TSLP level was significantly associated with expansion of monocytic(M)-MDSCs in response to ICI treatment (p=0.02). M-MDSC frequency after a median of 20 days of ICI treatment was significantly associated with progressive disease (PD), reduced PFS and OS (all p<0.05) whereas no correlation was seen with baseline M-MDSC frequency. Patients with a doubling of M-MDSCs (n=11) after treatment had a primary PD rate of 64% vs 24% (OR 7.0, p=0.04) and significantly worse median PFS (2.5 vs 7.8 months, HR 2.6 p=0.04). Conclusions: Early expansion of circulating M-MDSCs after treatment with PD-1 inhibitors is associated with elevated baseline TSLP levels and primary disease progression following ICI therapy in mNSCLC. These findings suggest that elevated TSLP and early expansion of myeloid populations may represent an important mechanism of primary resistance to PD-1 inhibitors in mNSCLC.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.062
GPT teacher head0.349
Teacher spread0.287 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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