Abstract PO-072: Durvalumab in combination with radioactive iodine in recurrent/metastatic thyroid cancers: Update on clinical and correlative analyses
Notice bibliographique
Résumé
Abstract Background: We hypothesized that radioactive iodine (RAI) can enhance the presentation of thyroid cancer immunogenic self- and neo-antigens to enhance the clinical benefit of immune checkpoint inhibitors (ICI). We conducted a phase 1 trial of RAI in combination with durvalumab (durva; anti-PD-L1) in patients (pts) with recurrent/metastatic (R/M) thyroid cancer. We report updated clinical outcomes and biological correlates performed on trial samples. Methods: Pts were required to have RECIST measurable R/M thyroid cancer with either >1 RAI-avid tumor(s) on the most recent RAI scan or one tumor with SUVmax <10 on FDG-PET. Prior therapies were allowed. Pts received durva 1500 mg IV every 4 weeks in combination with recombinant human TSH (rhTSH)-stimulated RAI (100 mCi) administered during cycle 1. Primary endpoint was safety and secondary endpoints included progression-free survival (PFS), defined as time from first durva dose until progression (PD) or death of any cause. Pre-treatment and on-treatment biopsies of the same target lesion were obtained from enrolled pts if feasible. Bulk RNA sequencing (RNAseq) was performed to assess transcriptomic characteristics of key tumor immune profiles and their correlation to PFS. Results: 11 pts enrolled; 7 pts underwent tumor biopsies. No dose-limiting toxicities or grade ≥3 adverse events related to drug were observed. BOR was 2 pts with partial responses, 7 pts with stable disease, and 2 pts with PD. Median PFS was 9.8 months with all patients eventually having PD events. Four pts had durable PFS >12 months. RNAseq analysis was performed on the tumor biopsies. Linear correlation analysis of transcriptome data from on-treatment tumors demonstrated a strong association between PFS and transcriptional scores for HLA expression (R2=0.76), MHC class I expression (R2=0.74), and NK/T cell cytolytic activity (CYT) (R2=0.69). The on-treatment tumors from pts with PFS >12 months had higher interferon-gamma (IFN-γ), HLA, MHC class I and CYT scores than pts with PFS<12 months (p<0.01). Baseline PD-L1 expression (normalized transcripts per million) was also significantly higher in pts with PFS>12 months (p=0.02). Detectable anti-TG and/or elevated anti-TPO (>1 IU/mL) autoantibody levels in pre-treatment serum samples (n=10) correlated with longer PFS on study treatment (p<0.03). RNAseq gene set enrichment analysis (GSEA) of on- vs pre-treatment samples showed durva-RAI increased thyroid autoimmunity gene sets in addition to the induction of IFN-γ and antigen presentation pathway. Conclusions: Durva-RAI has a favorable safety profile and is associated with prolonged PFS (>12 months) in a subset of pts with R/M thyroid cancer. Transcriptomic profiling reveals that durva-RAI enhancement of tumor antigen presentation and inflammation with T cell activation correlates to prolonged disease control. Enhancing pre-existing, subclinical autoimmunity against thyroid self-antigens may contribute to ICI efficacy. Further studies are needed to evaluate these hypotheses, including how RAI may contribute to ICI efficacy. Citation Format: Antoine Desilets, Winston Wong, Gnana P. Krishnamoorthy, Eric Jeffrey Sherman, Lara Dunn, Anuja Kriplani, James Vincent Fetten, Loren S. Michel, Erin McDonald, Ravinder K. Grewal, Mona Sabra, Laura Boucai, Stephanie Fish, Sofia Haque, Irina Ostrovnaya, Ronald A. Ghossein, James A. Fagin, David G. Pfister, Alan Loh Ho. Durvalumab in combination with radioactive iodine in recurrent/metastatic thyroid cancers: Update on clinical and correlative analyses [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-072.
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 | 0,007 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».