CD8+ T CELLS AND THEIR ANTIGENS IN END-ORGAN DAMAGE IN LUPUS NEPHRITIS
Notice bibliographique
Résumé
PV006 / #242 Poster Topic: AS01 - Adaptive Immunity Background/Purpose Lupus Nephritis (LN) is a severe and frequent complication of systemic lupus erythematosus (SLE). It is increasingly clear that the LN kidney hosts pathogenic mechanisms contributing to disease severity, with CD8+ T lymphocytes coming to the fore as relevant players. Their pathogenicity may be due to their recognition of renal (neo/modified/cryptic) antigens and consequent tissue damage. Methods We performed scRNASeq on flow-sorted CD8+ T cells from kidney, urine and blood samples at diagnosis, from 2 patients with active LN, using a T cell adapted SmartSeq2 method. Three to 5 additional patients will be included in the future. T cell receptor (TCR) repertoire analyses were performed on the scRNASeq data. To identify antigen(s) that may be recognized by tissue-enriched TCRs, we use a functional in vitro screening assay: Reporter T cell lines (expressing an NFAT-responsive GFP element and a TCR of interest) are co-cultured with modified HEK293T target cells (expressing a patient HLA, and a cDNA library from the autologous kidney biopsy). Autologous EBV-transformed B cells are used as controls for TCR recognition of virally infected cells. This allows for live-cell screening for T cells recognizing antigens presented by target cells, by virtue of their expression of GFP. Results We identified a restricted TCR repertoire, enriched in kidney and urine as compared to blood, in both patients. This may suggest local, antigen-driven expansion. Moreover, the most repeated TCRs in kidney largely overlapped with those from paired urine (but not blood), suggesting that urine can mirror kidney CD8+ T cell populations. We have begun by screening for antigens recognized by the 5 most highly repeated TCRs from kidney and urine from 1 of the 2 patients (Figure 1): a poor responder with high renal CD8+ T cell infiltration and renal damage (histology and clinical tests). Four of the 5 TCRs showed robust recognition of autologous EBV-B cells. Intriguingly, the fifth TCR (that did not show reactivity to B-EBV cells) was identified in T cells expressing a dual TCR α-chain. We hypothesize that this T cell clone may have been positively selected thanks to the reactivity of 1 of its TCRs to EBV-infected cells, but that its second TCR (with the same β-chain but a different α-chain) could be reactive to kidney autoantigens. Screening of the cDNA library with this (non EBV-B cell-reactive) TCR has shown promising results in the first step of the screening process; this will be repeated with further subcloning in order to identify the antigenic peptide responsible for the activation. Figure 1. Clonal expansion of CD8+ T cells as reflected by TCR repertoire in 1 renal biopsy, from a patient with poor outcome. Frequency of cells with identical TCR-β CDR3, by scRNA-Seq of CD8+ cells, or (bottom-right) deep-sequencing of blood (Adaptive Biotechnologies). Colors: specific to each clonotype, across tissues. n: Number of single-cells Conclusions Identifying the antigen(s) responsible for local CD8+ T cell expansion may be key in addressing kidney-based pathogenic mechanisms in LN. These antigen(s) may be expressed in the case of some but not all patients (or, for eg, differ in terms of abundance or spatio-temporal distribution), and may be associated with outcome. The nature of the antigen(s) may also provide information on disease-promoting cellular/molecular processes that occur in the LN kidney.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».