2024
MetFinder: A Tool for Automated Quantitation of Metastatic Burden in Histological Sections From Preclinical Models
Karz A, Coudray N, Bayraktar E, Galbraith K, Jour G, Shadaloey A, Eskow N, Rubanov A, Navarro M, Moubarak R, Baptiste G, Levinson G, Mezzano V, Alu M, Loomis C, Lima D, Rubens A, Jilaveanu L, Tsirigos A, Hernando E. MetFinder: A Tool for Automated Quantitation of Metastatic Burden in Histological Sections From Preclinical Models. Pigment Cell & Melanoma Research 2024 PMID: 39254030, DOI: 10.1111/pcmr.13195.Peer-Reviewed Original ResearchTumor contentMetastasis burdenMetastatic burdenTumor burdenMelanoma metastasesPreclinical modelsMurine modelPreclinical studiesMeasurable metastasesMelanoma researchTherapeutic approachesDeep neural networksHistopathological sectionsMechanisms of melanoma metastasisMetastasisHistological sectionsAI-based algorithmsAutomated quantificationWhole slide imagesAutomated quantitationNeural network
2023
1070 ‘Decoy-resistant’ IL-18 in combination with CTLA-4 blockade enhances anti-tumor efficacy in preclinical models of renal cell carcinoma
Schoenfeld D, Djureinovic D, Zhang L, Mann J, Huck J, Jilaveanu L, Ring A, Kluger H. 1070 ‘Decoy-resistant’ IL-18 in combination with CTLA-4 blockade enhances anti-tumor efficacy in preclinical models of renal cell carcinoma. 2023, a1177-a1179. DOI: 10.1136/jitc-2023-sitc2023.1070.Peer-Reviewed Original Research