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Record W4383499400 · doi:10.1093/bjd/ljad174.020

O20 Advanced melanoma is associated with distinct circulating B-cell profiles enriched with immunoregulatory and autoreactive features

2023· article· en· W4383499400 on OpenAlexaff
Zena Willsmore, Silvia Crescioli, Lucy H. Booth, Roman Laddach, Rozalyn Yorke, R. J. C. Harris, Jitesh Chauhan, Alicia M. Chenoweth, Rebecca Adams, Gabriel Osborn, Ashley Di Meo, Ioannis Prassas, Jenny L. C. Geh, Akshay J. Patel, Gary Middleton, Alastair D. MacKenzie Ross, Ciaran Healey, Eleftherios P. Diamandis, Khushboo Sinha, Yin Wu, Sean Whittaker, Esperanza Perucha, Sophie Papa, Katie E. Lacy, Sophia N. Karagiannis

Bibliographic record

VenueBritish Journal of Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsImmunologyAntibodyB cellIsotypeMelanomaAutoantibodyImmune systemPopulationBiologyMedicineCancer researchMonoclonal antibody

Abstract

fetched live from OpenAlex

Abstract There is increasing evidence that B cells play a significant role in the immunobiology of melanoma; however, reports of the pro- vs. antitumour roles of B cells are inconsistent. We hypothesized that advanced melanoma favours regulatory B-cell phenotypes and class switching to less effective antibody isotypes. We conducted an in-depth characterization of the circulating humoral compartment in patients with advanced stage III/IV melanoma (n = 46), compared to healthy volunteers (n = 16). Phenotyping of circulating B cells was performed using B-cell-directed mass cytometry (CyTOF); serum immunoglobulin antibody isotyping was conducted using multiplex immunoassay; and immuno-mass spectrometry was employed to screen serum IgGs for autoantibodies against > 13 000 candidate human proteins. The melanoma B-cell compartment was enriched in naïve CD21lo B cells, plasmablasts and double-negative B cells, compared to samples from healthy controls. These populations shared significant characteristics with phenotypes enriched in classical autoimmune diseases, most notably systemic lupus erythematosus (SLE). An enriched plasmablast population showed the highest median scaled expression of regulatory B-cell markers interleukin (IL)-10 and CD95 (Fas) of all B-cell populations, suggesting a potential immunosuppressive role. Consistent with an IL-10-enriched, T helper 2-biased environment, serum antibody isotyping revealed enrichment of IgG4, a less effective antibody isotype that may promote tumour propagation, in patients with melanoma, compared to healthy controls. In support of an autoreactive immune response, immuno-mass spectrometry screening of serum IgGs revealed altered autoreactivity in sera from patients with melanoma vs. with healthy control sera. Some autoantibodies were found exclusively in patients with melanoma, and these were reactive against human proteins recognized in carcinogenesis and proteins localized to the skin. Correlations between autoreactivity to tubulin cytoskeletal components and tumour burden was also identified. These findings show parallels with SLE, where one of the principal defects is an increased presence of apoptotic cell components and a breakdown of tolerance to cell-associated autoantigens. This may also suggest that localized immune reactivity in the tumour microenvironment may be reflected in an altered regulatory and autoreactive circulating humoral compartment. Our data identify distinct immature and regulatory B-cell signatures in patients with advanced melanoma that share characteristics with those reported in autoimmune diseases. Tumour-associated immune suppression may skew class switching to less effective antibody isotypes and toward regulatory B-cell phenotypes likely to favour tumour progression.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.255
Teacher spread0.245 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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