Abstract 6154: Distinct immunosuppressive environments elicited in vessel co-opting and angiogenic colorectal cancer liver metastases and changes following treatment
Notice bibliographique
Résumé
Abstract Colorectal cancer (CRC) is the third most common cancer worldwide and 50% of CRC patients develop liver metastases. Colorectal cancer liver metastases (CRCLM) present as two major histological growth patterns (HGP) that predict response to treatment/survival: 1. angiogenic tumors characterized by a desmoplastic stroma separating CRC cells from the liver parenchyma and are highly angiogenic and 2. co-opting tumors where tumor cells infiltrate the parenchymal cells in the liver and grow by co-opting the sinusoidal blood vessels between the liver cell plates without sprouting angiogenesis. Angiogenic tumors receiving neoadjuvant anti-angiogenics (anti-VEGF) and chemotherapy have more than double the 5-year overall survival compared to patients with co-opting tumors who have received the same neoadjuvant regimen. In addition, our clinical data revealed that anti-angiogenics could negatively affect outcomes in patients with co-opting lesions. The goal of our study is to understand how the immune system affects the development of the two distinct CRCLM tumors. We used both Nanostring GeoMX spatial protein profiling platform, immunohistochemistry and immunofluorescence, to identify the immune landscapes in chemonaïve and treated human CRCLM tumors. We observed that angiogenic tumors were rich in both CD4 and CD8 T cells with a near absence of neutrophils and macrophages. These adaptive immune cells were also FOXP3 positive indicating an immunosuppressive phenotype. Interestingly, we observed that vessel co-opting tumors have far fewer infiltrating lymphocytes than angiogenic tumors, but interestingly have greater numbers of innate cells - mostly neutrophils and macrophages. The macrophages were further characterized as being M2, tumor promoting, leading to an immunosuppressive environment. We then went on to analyze treated tumors. For those patients treated with chemotherapy alone we observed a larger infiltration of T cells in the angiogenic tumors and the appearance of T cells infiltrating the co-opting tumors. Surprisingly, in patients treated with chemotherapy and anti-angiogenic drugs (ie. anti-VEGF), which is part of the standard of care, the co-opting tumors no longer demonstrated the presence of T cell infiltration and had a similar profile to the chemonaïve tumors. This could explain why chemotherapy in co-opting tumors had a higher overall survival compared to those treated with chemotherapy and anti-VEGF. These results suggest developing treatments aimed at reshaping the different immune landscape in angiogenic and co-opting CRCLM to yield beneficial results for patient overall survival. Furthermore, the identification of immune cells or immune mediators facilitating the development of these two tumor would identify immune cell targets for immunotherapies. Citation Format: Diane H. Kim, Thomas Z. Mayer, Stephanie K. Petrillo, Anthoula Lazaris, Peter Metrakos. Distinct immunosuppressive environments elicited in vessel co-opting and angiogenic colorectal cancer liver metastases and changes following treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6154.
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 | 0,000 | 0,000 |
| 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 ».