Aberrant Cathepsin S Induces a Supportive Immune Microenvironment in Follicular Lymphoma
Notice bibliographique
Résumé
The highly variable clinical course of follicular lymphoma (FL) is determined by the molecular heterogeneity of the tumor cells and complex interactions with the microenvironment. Here, we provide biochemical, structural, functional and clinical evidence that aberrant Cathepsin S (CTSS) activity induces a supportive immune microenvironment in FL. By targeted DNA sequencing of 305 diagnostic FL biopsies, we identified somatic mutations of CTSS in 8% of cases (24/305), mostly clustered at Y132 (19/24) converting Y to D (16/19). A subset of CTSS Y132 mutations (N=5) occurred at lower variant allele frequencies (5-10%), indicating subclonality. Another 13% of FL had CTSS amplifications (37/286). CTSS Y132 mutations and CTSS amplifications were mutually exclusive. In a cohort of 51 FL, CTSS amplifications were associated with higher CTSS expression (P=0.05). Of note, a subset of FL without CTSS amplifications also had higher CTSS expression, suggesting additional mechanisms of transcriptional dysregulation. CTSS is a cysteine protease that is highly expressed in endolysosomes of antigen presenting cells and malignant B-cells. CTSS is involved in proteolytical processing of antigenic peptides for presentation on MHC-II to be recognized by antigen specific CD4+ T-cells. CTSS is synthesized as an inactive zymogen, which is converted to its active form by autocatalytic cleavage of the autoinhibitory propeptide (pro-CTSS). We used CRISPR/Cas9 to introduce CTSS Y132D into Karpas422, a B-cell lymphoma cell line that harbors the FL hallmark translocation t(14;18). Single-cell derived Y132D mutant clones showed >3-fold higher ratios of active CTSS to pro-CTSS (N=4, P=0.0003). Immunoprecipitated CTSS Y132D had >3-fold higher in vitro substrate cleavage activity compared to CTSS wild type (WT) (N=6, P=0.001). We purified pro-CTSS WT and Y132D and assayed their in vitro autocatalytic cleavage over time. The time required to convert 50% of pro-CTSS decreased from 17 minutes for WT to 11 minutes for Y132D (N=3, P=0.04). In contrast, purified active CTSS WT and Y132 had similar in vitro cleavage activities. Molecular dynamics simulations showed that the Y132D mutation shortens the distances by ~2Å between the catalytic triad of active CTSS (C139, H278, N298) and a stretch of amino acids from the proform (L80, G81, D82, S94), which may facilitate intramolecular cleavage. By mass spectrometry we could indeed detect novel intermediate-sized CTSS fragments. Thus, Y132D does not increase the activity of the mature enzyme but is a gain-of-function mutation by accelerating the conversion from pro-CTSS to catalytically active CTSS. CD74 (invariant chain) is a physiologic CTSS substrate that plays critical roles in the assembly, trafficking and stabilization of peptide-free MHC-II. CTSS cleaves CD74, thereby allowing binding and presentation of antigens on MHC-II to antigen specific CD4+ T-cells. We could show that CTSS Y132D enhanced CD74 cleavage in Karpas422 cells. We then tested the impact of CTSS on antigen specific CD4+ T-cell activation in co-culture assays. CTSS knock-out lymphoma cells were broadly incapable of activating CD4+ T-cells. Overexpression of CTSS WT activated CD4+ T-cells more efficiently compared to empty vector control. CTSS Y132 had the highest capacity to stimulate antigen specific CD4+ T-cell responses. Furthermore, in primary FL biopsies (N=51) CTSS Y132 mutations had gene expression profiles linked with antigen-processing and chemokine perturbation, including CXCL13, a B-cell chemoattractant produced by activated CD4+ T-follicular helper cells. Lastly, we aimed to correlate CTSS aberrations with clinical outcome in patients who received standard immunochemotherapy (R-CHOP) for advanced FL (N=51 with available CTSS mutation and gene expression data). Compared to all other patients (N=34), patients with CTSS Y132 mutations or CTSS overexpression (N=17) had longer failure free survival (P=0.012) and overall survival (P=0.041). In summary, we propose that aberrant CTSS activity - even if only present in a FL subclone - can elicit a CD4+ T-cell driven tumor-promoting immune response, which could be amplified within the microenvironment via pro-inflammatory and chemotactic cytokines and substantially impact the biology and clinical course of the disease. Thus, aberrant CTSS activity is a promising biomarker and therapeutic target in FL and potentially also other tumors. Disclosures Klapper: Roche, Takeda, Amgen, Regeneron: Honoraria, Research Funding. Hiddemann:Bayer: Research Funding; Roche: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Vector Therapeutics: Consultancy, Honoraria. Steidl:Juno Therapeutics: Consultancy; Bristol-Myers Squibb: Research Funding; Nanostring: Patents & Royalties: Filed patent on behalf of BC Cancer; Roche: Consultancy; Tioma: Research Funding; Seattle Genetics: Consultancy; Bayer: Consultancy. Kridel:Gilead Sciences: Research Funding. Weinstock:Celgene: Research Funding; Verastem Oncology: Research Funding. Weigert:Novartis: Research Funding; Roche: Research Funding.
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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) | 0,001 | 0,000 |
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 ».