Abstract B041: Defining the Determinants of Immune Response in DNA Homologous Recombination Deficient Tumors
Notice bibliographique
Résumé
Abstract Immune checkpoint blockade (ICB) has shown unprecedented success in improving clinical outcomes for numerous cancer patients, but many patients still fail to respond to treatment. Studies have demonstrated that the tumor microenvironment, tumor mutational burden, and patient DNA Damage Repair (DDR) deficiency may play a key role in determining response to ICB. To better characterize this and define key determinants of ICB response, we created an isogenic knockout BRCA2 in a murine 4T1 metastatic TNBC background to model these differential clinical responses and to assess how these tumor-intrinsic programs influence the tumor immune microenvironment to poise tumors for immunotherapy response. Differential immune landscapes were found via scRNAseq at baseline and with ICB driven by tumor DDR status with notable differences in the myeloid compartment and CXCR3-expressing T cell, NK, pDC, DCs, and plasma cells. Differential expression and interferon stimulated gene (ISG) metagene analysis showed notable differences in ISG expression in DDR-deficient samples at baseline, particularly in clusters containing monocytes and macrophages. Additionally, differential expression of CXCL10 in monocytes/macrophages and assessment of ligand-receptor interactions by CellChat similarly showed enhanced contribution CXCL10-CXCR3. Parallel bulk RNAseq analysis showed increased production of T cell trafficking chemokines that would poise the tumor for response to ICB. Our lab established a genetic interferon reporter system to measure both tumor intrinsic interferon-driven inflammation in cis and in trans with tumor associated macrophages, which enables multidimensional tracking of bidirectional signaling between tumor cells and macrophages by flow. This system enabled screening of inhibitors and tumor knockout cell lines to identify that tumor-intrinsic cGAS/STING and IFNb1 reinforce production of tumor and myeloid CXCL10/11 to poise the tumor for response to ICB. Further assessment of tumor cell lines via cellular fractionation experiments identified the presence of both gDNA and R-loops in the cytoplasm of BRCA2-mutant mammary cancer cell lines that may be detected as damage associated molecular patterns by tumor cells or myeloid cells in the tumor bed. Future studies aim at validating this DDR-driven production of IFNb1 as a driver of T cell chemokines in vivo; tumor-intrinsic knockout of IFNb1 and other T cell promoting chemokines (CXCL10/11/CCL5) to assess tumor or myeloid driven nature of this response to ICB and depletion of myeloid cells are being performed in parallel to assess contribution of tumor and myeloid cells, respectively. Taken together, our results have important implications for understanding the key drivers of ICB response in the tumor microenvironment and how patient-intrinsic mutations differentially poise the microenvironment for immunotherapy response. Citation Format: Natalie Vaninov, Robert Samstein. Defining the Determinants of Immune Response in DNA Homologous Recombination Deficient Tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B041.
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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 | 0,006 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».