Jennifer A. Moliterno

Decoding Spatial Programs in Human Glioblastoma Through Surprisal Information-Theoretical Analysis

This paper uses surprisal information-theoretic analysis on spatial transcriptomic data from human glioblastoma to uncover hidden spatial programs and interactions not detected by standard methods.

Multicellular Spatial Programs Define the Histopathological Architecture of Meningioma

This study identifies multicellular spatial molecular programs in meningiomas using multi-omic data and develops a model to infer these programs from histopathology.

Analysis of the phosphorylation networks characterizing distinct phenotypic states in glioblastoma cell Populations

The paper identifies phenotype-specific signaling networks in glioblastoma cells, showing that invasive spread is linked to DNA damage response and AKT-mTOR activation, with 14-3-3 proteins mediating phosphorylation and predictive phospho-site signatures for patient survival.

Spatial epigenomic niches underlie glioblastoma cell state plasticity

This study identifies two epigenetically-defined spatial niches in glioblastoma that influence cell state plasticity through local and long-range molecular signals.

spARC Recovers Human Glioma Spatial SignalingNetworks with Graph Filtering

The paper introduces spARC, a method to recover spatial signaling networks in gliomas, revealing an Osteopontin-CD44 interaction enriched in grade IV astrocytomas.