Abstract PO-048: Baseline blood DNA methylation-based immune profiles are associated with survival outcomes in head and neck cancer patients on immune checkpoint therapy
Notice bibliographique
Résumé
Abstract Background: Standard-of-care anti-PD-1 therapy does not provide long-lasting benefits for most patients with recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC). A current biomarker of potential response, PD-ligand-1 combined proportion score, has limitations due to the heterogeneity and availability of tumor samples. The development of peripheral blood-based biomarkers offers a contemporary noninvasive sample for immunotherapy response. DNA methylation-based immune cell deconvolution provides opportunities for developing blood-based biomarkers to predict immunotherapy response outcomes in HNSCC. Methods: Our study is an ongoing prospective multi-center study aimed at identifying blood DNA methylation biomarkers of therapy response in patients with R/M HNSCC undergoing standard-of-care, FDA-approved anti-PD-1 therapy. DNA isolated from these samples underwent bisulfite conversion and methylation profiling using the Illumina EPIC microarray. Peripheral blood immune profiles were generated using cellular deconvolution. 58 consecutive R/M HNSCC patients with anti-PD-1 monotherapy were included (4/31/23). We investigated 47 immune variables for relation with progression-free survival (PFS) and overall survival (OS) using Cox proportional-hazard models adjusted for age, sex, and a marker for corticosteroid exposure (NDMI). Immune variables were treated as continuous and binary predictors in the models. A data-based statistical cutpoint (surv_cutpoint) was used to dichotomize the immune variables. Differences between the baseline immune profiles of patients who received anti-PD-1 monotherapy with durable clinical benefit for at least one year (Benefit group) and patients who experienced progression or death within 100 days (Non-benefit group) from the start of therapy were modeled using linear regression, adjusted for age, sex, and NDMI. A p-value < 0.05 was used as the cut-off for statistical significance. Results: In 58 patients with R/M HNSCC who received only anti-PD-1 therapy for this preliminary analysis, a granulocytic myeloid-derived suppressor cell (gMDSC) score was consistently associated with PFS as a continuous (HR: 1.27) and a binary variable (HR: 2.70). Several immune profiling variables were significantly associated with PFS and OS as a binary variable. Consistently, baseline neutrophil proportion (PFS HR 3.62; OS HR: 4.67), total T cell count (PFS HR 0.32; OS HR: 0.25), total lymphocyte proportion (PFS HR 0.36; OS HR: 0.27), lymphocyte to monocyte ratio (PFS HR 0.43; OS HR: 0.32), monocyte count (PFS HR 2.50; OS HR: 2.84), and total CD4T cell count (PFS HR 0.37; OS HR: 0.38) were associated with PFS and OS. A significantly lower gMDSC score was observed in the Benefit group compared to the Non-benefit group. Conclusion: DNA methylation-based immune profiling in peripheral blood at baseline identifies clinically relevant biomarkers of benefit from anti-PD-1 therapy. Our results promise the potential development of new blood-based DNA methylation biomarkers to predict immunotherapy response before treatment. Citation Format: Ze Zhang, Kartik Sehgal, Keisuke Shirai, Rondi Butler, Min Kyung Lee, Annette Molinaro, John Wiencke, Devin Koestler, Hannah Stolrow, Geat Ramush, Lucas Salas, Robert Haddad, Karl Kelsey, Brock Christensen. Baseline blood DNA methylation-based immune profiles are associated with survival outcomes in head and neck cancer patients on immune checkpoint therapy [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-048.
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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 | 0,001 |
| 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) | 0,002 | 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 ».