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Record W6920886201 · doi:10.6084/m9.figshare.25397536

Additional file 1 of CAR T cells and T cells phenotype and function are impacted by glucocorticoid exposure with different magnitude

2024· article· en· W6920886201 on OpenAlexaff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsCD19CD8T cellCytotoxic T cellInterleukin 21PhenotypeInterleukin 3

Abstract

fetched live from OpenAlex

Additional file 1: Figure S1. UT T cells phenotype. A Representative plot of the differentiation subsets defined by CCR7 and CD45RA markers. B Memory phenotype of CAR + and untransduced (UT) fractions of CD3 + T cells in CD19, M28z and MBBz CAR T cell products.GR expression (MFI) in the naïve and TCM memory subsets of (C) UT (from CD19 CAR cell product) CD4 + and CD8 + T cells; (D) of the UT (from M28z and MBBz CAR cell products) CD4 + (left) and CD8 + (right) T cells. n = 5 donors for CD19 CAR T cells and n = 4 donors for M28z and MBBz CAR T cells. Student t test was used to compare GR in different subsets. Medians are represented. *p < 0.05, **p < 0.01. Figure S2. Impact of GC exposure on UT T cells phenotype. Frequency of CD19 CAR T cells (A) and CD4/CD8 ratio in CD19 CAR T cells (B) overtime after Dx (green) or MP (blue) exposure. C. Representative plot of LAG-3, PD-1 and TIM-3 expression without GC exposure or with 10µg/ml Dx. D. Frequency of LAG-3, PD-1, and TIM-3 in CD19 CAR + T cells without or after 1 and 3 exposures with Dx or MP. Relative surface expression of LAG-3, PD-1, andTIM-3 in CAR + and UT CD4 + (E) and CD8 + (F) T cells after 3 exposures with Dx (left) or MP (right). G Frequency of PD-1 in CD4 + and CD8 + CD19 CAR + T cells without or after 3 exposures with Dx or after 3 exposures with Dx and RU-486 (10−5M). H Relative expression of LAG-3, PD-1, and TIM-3 in CD4 + and CD8 + UT T cells after 3 exposures of Dx (left) or MP (right). n = 6 donors. Friedman test with Dunn’s correction was used to compare marker’s expression between 3 conditions. Wilcoxon matched-pairs signed rank test was used to compare marker’s expression in CAR + vs. UT or CD4 + vs. CD8 + T cells. Medians are represented. * p < 0.05, ** p < 0.01, *** p < 0.001. Figure S3. Impact of GCs exposure on CD19 CAR + T cells effector functions. A. Relative frequency of IFNγ + , TNF + or IL2 + CD4 + or CD8 + CD19 CAR and UT after a single exposure with Dx (top) or MP (bottom) after PMA/ionomycin stimulation. B. Frequency of CD107a- IFNγ- TNF- IL2- CD4 + and CD8 + CAR (circle) and UT (square) T cells after 3 exposures with Dx or Dx + RU-486 after PMA/ionomycin stimulation. Frequency of CD107a + , IFNγ + , TNF and IL-2 + CAR CD4 + and CD8 + T cells without GC exposure (0) or 1 exposure with low or high doses of GC (0.1 µg/ml and 10 µg/ml Dx and 0.5µg/ml, 50 µg/ml, and 100 µg/ml MP) following a single (C) or 3 (D) stimulations with CD19 + K562 tumor cells. E. Pie chart showing the number of functions of CD8 + CAR T cells without GC exposure compared to Dx or MP exposure following a single (n = 8 donors) or 3 stimulations (n = 5 donors) with CD19 + K562 tumor cells. Two-way ANOVA with Sidak’s correction was used to compare CD107a + , IFNγ + , TNF and IL-2 + cells frequency at different doses of Dx and MP. Friedman test with Dunn’s correction was used to compare multifunction between the 3 different conditions. Medians are represented. * p < 0.05, ** p < 0.01, *** p < 0.001. Figure S4. Impact of GCs exposure on M28z and MBBz CAR + T cells phenotype and functions. Frequency of M28z and MBBz CAR T cells (A) and CD4/CD8 ratio in CAR T cells (B) without GC exposure (0) or after 3 exposures with low and high concentration of Dx or MP. Frequency of LAG-3 (C), PD-1 (D) and TIM-3 (E) in M28z and MBBz CAR T cells without GC exposure (0) or after 3 exposures with low and high concentration of Dx or MP. Relative surface expression of LAG-3, PD-1 and TIM-3 in CAR + and UT fractions of CD8 + M28z and MBBz T cells following 3 exposures with Dx (F) or MP (G). Frequency of CD107a + , IFNγ + , TNF and IL-2 + CD4 + (H) and CD8 + (I) M28z and MBBz CAR T cells without GC exposure (0) compared to Dx or MP exposure following 3 stimulations with MSLN + K562 tumor cells. A-E n = 6, F&G n = 11 and H&I n = 5 donors. Two-way ANNOVA with Sidak’s correction was used to compare CD107a + , IFNγ + , TNF and IL-2 + cells frequency at different doses of Dx and MP. Mann–Whitney test was used to the surface expressions and functions in M28z vs. MBBz. Medians are represented. * p < 0.05, ** p < 0.01, *** p < 0.001. Figure S5. M28z and MBBz CD4 + and CD8 + CAR T cells phenotype after GC removal. A Representative histograms of GFP and MSLN expression and co-expression on K562 target cells as compared to control K562 (GFP-MSLN-). Relative frequency of LAG-3, PD-1 and TIM-3 in M28z and MBBz CD4 + (B&D) and CD8 + (C&E) CAR T cells after 3 exposures with Dx (B-C) or MP (D-E) and 48h rest in a GC-free medium. n = 5 donors. Student t test was used to compare surface marker expression in GC-exposed vs. GC-rested conditions. * p < 0.05, ** p < 0.01, *** p < 0.001.

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)0.002
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.901
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9010.176

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 head0.017
GPT teacher head0.241
Teacher spread0.223 · 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.

Study designBench or experimental
Domainnot available
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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