Sean Jordan

Medulloblastoma is the most common pediatric malignancy of the brain and spine and a major cause of childhood cancer-related morbidity and mortality. Novel therapeutic approaches are urgently needed. The malignant behavior of this disease is influenced both by cell intrinsic factors and by the complex interactions of the tumor cells with its tumor microenvironment. Recent scientific and technological advancements allow increased ability to interrogate the microenvironment in terms of composition...

Multiple myeloma (MM) displays significant genetic heterogeneity, making it challenging to distinguish malignant from non-malignant plasma cells in single-cell datasets. Existing marker-based and CNV detection methods require manual intervention or high computational resources, limiting their scope. We developed a supervised deep learning autoencoder to classify malignant cells across MM and its precursor stages and validated its performance and biological relevance. The model outperformed...

CONCLUSIONS: By integrating these innovative features, with specialized survival analyses on single-cell cluster markers, co-expression modules, regulatory networks, and ligand-receptor pairs, Survival Genie 2 represents a novel tool for expanding the translational impact of cancer research, enabling the precise identification of biomarkers and therapeutic targets. Survival Genie 2 is available at https://bhasinlab.bmi.emory.edu/SurvivalGenie2/home.

Multiple myeloma (MM) is a plasma cell malignancy shaped by dynamic interactions between MM cells and non-malignant cells in the immune microenvironment. To spatially profile the influence of cellular context on MM and immune cell expression, we developed a multimodal framework integrating 10x Genomics Visium HD, 10x Genomics Xenium, and clinically annotated single-cell RNA (scRNA-seq) sequencing datasets. Visium HD enabled unbiased, whole transcriptome, spatial discovery at 16 µm resolution,...