Tyler Risom

The paper identifies spatially distinct epithelial states in PDAC that correlate with immunosuppressive myeloid niches and poor prognosis.

The paper identifies a novel class of mature lymphoid aggregates in NSCLC using spatial proteomics and develops a classifier to improve CPI biomarker eligibility.

The paper develops a framework to decode TLS maturation in NSCLC using spatial omics data and deep learning, identifying two distinct spatial ecosystems linked to patient outcomes.

The paper uses spatial imaging and computational analysis to identify features in metastatic tumors that predict response to immune checkpoint inhibition in TNBC patients.

SPEX provides a web-based platform for spatial omics analysis, enabling modular and user-friendly processing of spatial transcriptomics and proteomics data.

The paper introduces Mesmer, a deep learning algorithm for cell segmentation in tissue images, achieving human-level performance and enabling automated feature extraction.