1472 Assessing the correlation between CD8 cell PET Imaging with 89-Zr-Crefmirlimab Berdoxam and CD8 cell immunohistochemistry in patients with advanced cancer receiving immunotherapy
Notice bibliographique
Résumé
Background CD8 T-cells (CD8s) mediate the effects of most cancer immunotherapies. CD8s are typically assessed by biopsy which is inherently limited by sample availability, intratumoral and intrapatient heterogeneity, and difficulty with repeated, longitudinal assessment. Non-invasive CD8 PET imaging with 89-Zr-Crefmirlimab Berdoxam (crefmirlimab) could circumvent these barriers and has previously demonstrated feasibility and safety. Methods We conducted a Phase II, prospective multicenter study to test the correlation between crefmirlimab PET signal and CD8 cell quantity by immunohistochemistry (IHC) in patients with solid tumors receiving standard of care immunotherapy. Patients underwent a baseline CD8 PET scan within 1 week prior to starting immunotherapy. A second crefmirlimab PET scan was performed 4-6 weeks after starting immunotherapy. Pre-treatment tissue and a biopsy 4-6 weeks on-treatment were used for CD8 IHC assessment by SP-57 antibody stain. Bone biopsies and those with <5% tumor were excluded. The primary endpoint was the correlation between PET uptake in the biopsied tumors [SUVmax, SUVmean, SUVpeak; normalized to reference tissue] and CD8 IHC results [CD8 cells/mm2] using the Spearman’s correlation coefficient. Results Among 52 enrolled patients with ≥1 crefmirlimab scan and corresponding biopsy, 48 patients had 35 baseline biopsies and 34 on-treatment biopsies evaluable for the primary endpoint. Eight solid tumor types were represented with renal cell carcinoma (RCC, n=21 samples), melanoma (n=23), and non-small cell lung cancer (NSCLC, n=17) being the most common. Among the examined imaging parameters, SUVmean of the biopsied tumor, normalized to Aorta (SUVmean/SUVaorta) provided the best correlation. For all 69 biopsied lesions, the SUVmean/SUVmean aorta correlated with CD8 cell density [cells per mm2] by IHC with a Spearman’s correlation coefficient of 0.58 (95% CI: 0.385 - 0.697). For the 35 baseline biopsies the correlation was 0.66 (95%CI: 0.387 - 0.825), and for the 34 on-treatment biopsies the correlation was 0.48 (95% CI: 0.148 - 0.713). The correlation for RCC, melanoma, and NSCLC was 0.77 (95% CI: 0.552 - 0.913), 0.55 (95% CI: 0.084 - 0.727), and 0.54 (95% CI: -0.121 - 0.774), respectively. The mean SUVmean lesion/SUVmean aorta and mean CD8 cell density were 1.71 (IQR: 0.93-1.55) and 509 (IQR:114-461) at baseline and 2.43 (IQR: 0.80-3.60) and 759 (IQR:158-963) post-treatment respectively. Conclusions Non-invasive CD8 PET scanning with crefmirlimab correlates with CD8 assessment by IHC and permits whole patient, longitudinal CD8s assessment. Crefmirlimab imaging is under investigation as a biomarker for immunotherapy responsiveness in ongoing trials (NCT05013099) and could ultimately provide a useful tool for immunotherapy drug development and clinical management. Trial Registration NCT03802123 Ethics Approval The study was conducted in accordance with the Declaration of Helsinki and the International Conference on Harmonization Guidelines for Good Clinical Practice (ICH-GCP) All patients provided written informed consent.
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 | 0,001 | 0,001 |
| 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 ».