Abstract PR006: DNA repair inhibition via targeting ATR activates cGAS/STING signaling, promotes anti-tumor immunity, and is a synthetic lethal strategy to augment immunotherapy response in preclinical models and clinical samples of small cell lung cancer
Notice bibliographique
Résumé
Abstract Introduction: Small cell lung cancer (SCLC) is the most aggressive subtype of lung cancer. Clinical trials of immune checkpoint blockade (ICB) combined with chemotherapy delivered only very modest benefits. In this study, we investigated the effect of targeting ataxia telangiectasia and rad3-related (ATR), the primary activator of the replication stress response, in SCLC. Clinical samples from treatment naïve and treated SCLC patients were analyzed by single cell and bulk RNA sequencing to ascertain the intratumoral transcriptional heterogeneity and the surrounding tumor microenvironment (TME). Methods: In this study, we investigated the effect of ATR inhibition either alone or in combination with PD-L1 blockade in multiple immunocompetent mouse models of SCLC. The downstream effects of ATR inhibition were assessed by bulk RNA sequencing, and multicolor flow cytometry. The SCLC clinical samples from treatment naïve and patients treated were analyzed by single cell and bulk RNA sequencing. Results: In multiple immunocompetent SCLC mouse models, ATR inhibition (ATRi) remarkably enhanced the anti-tumor effect of PD-L1 blockade. We next tested the ATR inhibition either alone or in combination with PD-L1 in the second-line regimen for SCLC. We observed that ATR inhibition in combination with PD-L1 blockade significantly reduced tumor volume and prolonged survival of aggressive mice models when compared to PD-L1 alone. Targeting ATR enhanced the expression of PD-L1, activated the cGAS/STING pathway, induced the expression of Type I and II interferon pathways, and caused significant infiltration of cytotoxic and memory/effector T-cells into tumors. Interestingly, ATRi also led to significant induction of MHC class I in SCLC in vitro and in vivo models. Single-cell RNA sequencing data provided a deep annotation of SCLC phenotypes and the surrounding immune TME. Treatment and subtype are associated with substantial phenotypic changes in the SCLC immune microenvironment, with greater T-cell dysfunction in SCLC-N than in SCLC-A. Moreover, a recurrent highly metastatic SCLC subset is associated with exhausted CD8+ T-cells and a pro-fibrotic, immunosuppressive monocyte/macrophage population, suggesting possible tumor-immune coordination to promote metastasis. Specifically, analysis of pre-and post-treatment clinical samples from a proof-of-concept study of a first-in-class ATR inhibitor, VX970 (berzosertib), and topotecan, in patients with relapsed SCLCs, validated the induction of MHC class I and interferon pathway genes, for the first time in this disease. Conclusion: We provide insight into tumor and immune biology in SCLC at single-cell resolution. Further, we show ATRi as a potentially transformative vulnerability of SCLC. Given the increasing importance of immunotherapy for the management of SCLC and that ATR inhibitors are already in clinical trials, combining ATR inhibitors with PD-L1-blockade offers an attractive strategy for the treatment of SCLC and contributes to the rapid translation of this combination into the clinic. Citation Format: Triparna Sen. DNA repair inhibition via targeting ATR activates cGAS/STING signaling, promotes anti-tumor immunity, and is a synthetic lethal strategy to augment immunotherapy response in preclinical models and clinical samples of small cell lung cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr PR006.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».