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Record W2789628875 · doi:10.1093/ecco-jcc/jjx180.672

P545 Antigenic response to CT-P13 and remicade in inflammatory bowel disease patients shows similar epitope recognition

2018· article· en· W2789628875 on OpenAlexaff
João Gonçalves, María José Dus Santos, Rita C. Acúrcio, Inês Iria, Luís F. Gouveia, Paula M. Brito, Andrea Chagas Santos, Ana Barbas, Joana Galvão, Isabelle Francielle Bezerra Barbosa, F Aires da Silva, A Alcobia, Marco Cavaco, Mariana de Melo Cardoso, José Delgado Alves, John Carey, Thomas Dörner, João Eurico Fonseca, Carolina Palmela, Joana Torres, Catarina Vieira, D. Trabuco, Gionata Fiorino, Anne S. Strik, Miri Yavzori, Iria Garcı́a de la Rosa, LLASM Correia, Fernando Magro, G. D’Haens, Shomron Ben‐Horin, Péter L. Lakatos, Silvio Danese

Bibliographic record

VenueJournal of Crohn s and Colitis · 2018
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsMcGill UniversityMontreal General Hospital
Fundersnot available
KeywordsEpitopeImmunogenicityMedicineInfliximabAntibodyAntigenMonoclonal antibodyInflammatory bowel diseaseImmunologyDiseaseInternal medicineTumor necrosis factor alpha

Abstract

fetched live from OpenAlex

The present study aimed to investigate the cross-reactivity of the CT-P13-reactive sera with Remicade to address the feasibility of therapy switch. To further consolidate the equivalent immunogenicity between the two versions of infliximab we have characterised the epitopes recognised by anti-infliximab antibodies and compared them between CT-P13 and Remicade. Sera of patients with IBD with measurable anti-CT-P13 antibodies (Remsima or Inflectra) were tested for their cross-reactivity to five batches of Remicade and CT-P13. Sera from patients containing high levels of anti-drug antibodies (>1.0 μg/ml) were used for screening a phage-display library of infliximab peptides and compare antigenic epitopes of anti-CT-P13 and anti-Remicade ADA. Monoclonal antibodies derived from naïve individuals and IBD patients treated with anti-CT-P13 were obtained to gain information on the epitope specificity between anti-CT-P13 and anti-Remicade sera. All 42 anti-CT-P13 and 37 anti-Remicade IBD sera were cross-reactive with Remicade and CT-P13, respectively. ADA concentrations against Remicade or CT-P13 were strongly correlated (r values between 0.92 and 0.99, p < 0.001 for all experiments, Spearman’s correlation test). ADA-negative controls for CT-P13 (5 healthy individuals, 15 patients with RA) were also negative for anti-Remicade. Anti-CT-P13 sera of patients with IBD (n = 32) exerted similar functional inhibition on CT-P13 or Remicade TNF-α binding capacity and showed reduced binding to CT-P13 in the presence of five different batches of CT-P13 and Remicade. Anti-CT-P13 and anti-Remicade IBD sera selectively enriched phage-peptides from the VH (CDR1 and CDR3) and VL domains (CDR2 and CDR3) of infliximab. Important epitopes were also localised in the constant domain of infliximab heavy-chain (CH1, CH2, and CH3). Sera reactivity detected major infliximab epitopes in these regions to synthetic peptides in 60–79% of patients, and no significant differences were identified between CT-P13 and Remicade ADA. Minor epitopes were localised in framework regions of infliximab with reduced antibody reactivity shown in 30–50% of patients. Monoclonal antibodies derived from naïve individuals and ADA-positive IBD patients treated with CT-P13 provided comparable epitope specificity to five different batches of CT-P13 and Remicade. The present study is the first to compare specific antigenic epitopes between CT-P13 and Remicade, as well as to identify antibody-binding sites on different versions of infliximab with polyclonal and monoclonal IBD sera. The results strongly support a similar antigenic profile for Remicade and CT-P13 and point toward a safe switching between the two drugs in ADA-negative patients.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.018
GPT teacher head0.293
Teacher spread0.275 · 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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Citations1
Published2018
Admission routes1
Has abstractyes

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