Amanda Kirane

This study establishes patient-derived melanoma organoids (PDMOs) that retain tumor-immune heterogeneity and show context-dependent responses to immune checkpoint blockade.

The paper constructs a pan-cancer single-cell atlas to improve tumor identity inference and identify genetic vulnerabilities by integrating high-quality malignant cells across multiple cancers.

This study uses single-cell and spatial transcriptomics to identify distinct tumor states in uterine leiomyosarcomas and proposes drug targets based on these states.

This paper introduces a BBB-penetrating nanoconjugate for glioblastoma treatment that modulates the PD-1/PD-L1 axis without antibodies, showing improved brain accumulation and immune activation in vitro and in vivo.

This study maps PD-1/PD-L1 functional interactions in melanoma tissues before and after ICB, showing spatial heterogeneity and persistent interactions post-treatment.

This paper uses single-cell Raman spectroscopy and machine learning to predict therapeutic response in melanoma, achieving >96% accuracy in cell line classification and 91% accuracy in patient drug resistance inference.

This study identifies six myeloid cell clusters in melanoma using scRNA-seq, finding that M_C1 subtype frequency predicts survival and immunotherapy response.