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Record W4379984631 · doi:10.1158/1538-7445.am2023-2109

Abstract 2109: Analytical characterization of a multiplex panel measuring 45 cytokines by proximity extension assay in plasma from subjects with NSCLC

2023· article· en· W4379984631 on OpenAlexaff
Anne Jang, Daniel L. Feingold, Mark H. Watson, Gwënaël Pottiez, Rudolf Guilbaud, Nicholas Dupuis

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsMultiplexImmune systemCytokineImmunoassayLung cancerCancerImmunologyMedicineCancer researchOncologyInternal medicineBiologyAntibodyBioinformatics

Abstract

fetched live from OpenAlex

Abstract Introduction Cytokines are fundamental regulators of immune system processes and are responsible for the differentiation, proliferation, and function of immune cells. With many anti-cancer therapeutic strategies focused on targeting or harnessing the immune system, or components thereof, quantification of circulating cytokines has become important to describe the pharmacodynamic and mechanistic effects of these investigational therapies. To support these efforts, new multiplexed immunoassay panels have been developed to expand the available options for broad spectrum characterization of cytokine profiles from biospecimens. Here we characterize the analytical performance of one such panel based on proximity extension assay technology to measure 45 cytokines in plasma. Experimental Procedures Plasma samples (n = 27) from patients with non-small cell lung cancer (NSCLC), along with age-matched plasma samples (n = 6) from healthy normal subjects were analyzed using the Olink Cytokine 48 kit. Samples were thawed and processed according to manufacturer instructions for the incubation, extension, and detection on the Olink Signature Q100 instrument. A subset of the screened samples was run in quadruplicate across multiple runs and analyzed on two separate instruments. Results Of the 45 cytokines assayed, 41 had values above the assay limit of detection in ≥75% of samples analyzed. When compared to the normal human plasma, 26 cytokines were significantly elevated (p-value ≤ 0.05) in plasma from NSCLC subjects, including those known to be associated both with poor (e.g., IL-1β, IL-6) and good prognosis (e.g., IFN-γ). Furthermore, many of the cytokines with significant differences were of low abundance; 13 of the 26 cytokines had mean values ≤ 20.0 pg/mL. For two of the incurred samples which were run across multiple replicates and runs, with mid- to high- levels of cytokines, the median intra-assay CV across all assays was 6.2% with 90% of the assays demonstrating CVs of less than 12%. This only increased to a 7.7% median CV in inter-run comparison with 90% of the assays remaining below 12%. Additional results from the incurred sample analysis will be presented. Conclusions These results demonstrate that multiplex cytokine analysis, based on proximity extension assays, can be effectively deployed to screen a large number of targets and can uncover clinically relevant changes in low abundant cytokines. Citation Format: Anne Jang, Daniel Feingold, Mark H. Watson, Gwenaël Pottiez, Rudolf Guilbaud, Nicholas Francois Dupuis. Analytical characterization of a multiplex panel measuring 45 cytokines by proximity extension assay in plasma from subjects with NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2109.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.094
GPT teacher head0.366
Teacher spread0.272 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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