Abstract A064 Characterizing the immune microenvironment and examining the effect of tumour-targeted MRgHIFU mediated hyperthermia in combination with thermosensitive liposomal doxorubicin in a mouse model of embryonal rhabdomyosarcoma
Notice bibliographique
Résumé
Abstract Introduction Embryonal rhabdomyosarcoma (ERMS) is the most common pediatric soft tissue sarcoma. High risk patients have poor survival rates and second line chemotherapies such as doxorubicin cause systemic toxicity. We combined thermosensitive liposomal doxorubicin (TLD) with magnetic resonance-guided high intensity focused ultrasound (MRgHIFU). TLD encapsulates doxorubicin in a thermosensitive liposome, thus releasing doxorubicin only once heated to 40°C. MRgHIFU is a non-invasive, non-ionizing technique used to locally heat tumors for targeted drug release. MRgHIFU+TLD treatment resulted in improved survival in a syngeneic mouse model of ERMS. Hyperthermia (HT) can also modulate the immune response, and the immune microenvironment (IM) of RMS is undercharacterized. Therefore, identifying effective immunotherapeutic targets and increasing tumor immunogenicity is warranted. The aim of this study is to characterize the IM of this ERMS model and understand the effect of chemotherapy and HT on immune infiltrates over time. Methods Mice were divided into either an HT or normothermia (NT) group. The HT group underwent tumor-targeted MRgHIFU, while the NT group received no HT. Both groups received free doxorubicin (FD) and TLD via tail vein resulting in 6 treatment groups: untreated, FD, TLD, HT, HT+FD, and HT+TLD. Tumors were resected at 24 and 168 hours post-treatment (hpt) and immunohistochemistry (IHC) was performed on tumor sections for CD11b (myeloid immune cells), CD3 (T cells) and B220 (B cells). IHC was quantified using HALO image analysis software. Imaging mass cytometry (IMC) was conducted on a subset of tumors using a panel of >10 additional markers to spatially visualize immune cell subpopulations. Observations IHC mice (n=105) showed that most of the tumor infiltrating immune cells were CD11b+, with significantly fewer CD3+, and even fewer B220+ cells (x̄ =2107, 381, 16 cells/mm2 respectively, p≤ 0.0001 for all). TLD treatment alone decreased CD11b+ and CD3+ immune cell presence in tumors at 24 hpt (p=0.001, 0.016). However, HT+TLD treatment increased CD11b+ cells compared to TLD alone at 24 hpt (p=0.008), likely due to HT-mediated release of doxorubicin. FD treatment alone decreased CD11b+ cells at both 24 and 168 hpt (p=0.033, 0.02). The addition of HT at 24 hpt decreased CD3+ cells in the FD treated tumors (p=0.003). HT treatment increased B220+ cells in tumors at 168 hpt (p=0.016). IMC showed a high presence of macrophage specific markers, with low levels of B cells, neutrophils, and cytotoxic/regulatory T cells. Conclusions The IM of this ERMS model is macrophage dominant and lymphocyte deficient. HT, FD, and TLD affected tumor infiltrating immune cells at different time points post-treatment and expanding the IMC cohort will inform how we can harness HT+TLD to create a greater synergistic effect with immunotherapies while reducing toxicity. IM characterization within this model establishes a framework for future immunotherapeutic study within the RMS landscape to pioneer preclinical testing. Citation Format: Julia Nomikos, Claire Wunker, Adam C. Waspe, Yael Babichev, Karolina Piorkowska, Suzanne Wong, Warren Foltz, J. Ted Gerstle, Elizabeth G. Demicco, Abha A. Gupta, Cynthia J. Guidos, James M. Drake, Rebecca A. Gladdy. Characterizing the immune microenvironment and examining the effect of tumour-targeted MRgHIFU mediated hyperthermia in combination with thermosensitive liposomal doxorubicin in a mouse model of embryonal rhabdomyosarcoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A064.
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 | 0,001 |
| 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 ».