Elizabeth M. Jaffee

The paper calibrates a spatial QSP model using CODEX data to predict TME states and identify biomarkers for HCC immunotherapy response.

This study shows antigen-presenting cancer-associated fibroblasts (apCAFs) in murine pancreatic tumors influence regulatory T cell phenotype and function through CXCL9 and CCL22, affecting immune checkpoint blockade response.

The paper introduces dominoSignal, a software tool that statistically tests differential cell signaling from single-cell data to infer changes in cell-cell communication networks.

This study integrates single-cell and spatial transcriptomics to identify prognostic fibroblast subpopulations in thyroid cancer progression.

The paper introduces a framework for mathematical modeling of multicellular systems using interpretable cell behavior rules derived from biological knowledge and multi-omics data.

The paper introduces FunCN, a method to analyze cellular neighborhoods in PDAC, revealing distinct immune interactions in primary and metastatic sites.

The paper investigates how cancer-associated fibroblasts (CAF) influence tumor cell behavior in pancreatic ductal adenocarcinoma by driving EMT and altering cell subtypes, with IL-8 playing a key modulatory role.

The paper uses virtual patient models to evaluate biomarkers for predicting response to PD-1 blockade in TNBC, finding that early on-treatment biomarkers and blood-based markers offer better performance.

This study examines TLS in HCC treated with neoadjuvant immunotherapy, finding TLS correlate with better outcomes and show distinct morphological and functional features in tumor regression.

This study identifies SEMA3D as a dual driver of pancreatic ductal adenocarcinoma progression and metastasis through tumor- and nerve-derived mechanisms involving macrophage reprogramming.

This study uses spatial multi-omics to identify TLS-associated immune niches in PDAC that correlate with improved survival in immunotherapy responders.

The paper characterizes a novel syngeneic murine breast cancer model (NT2.5-LM) that exhibits rapid and widespread metastases, enabling study of metastatic progression and therapeutic responses.

The paper introduces computational tools for NMF analysis of single-cell RNA-seq data, demonstrating their use in quantifying cell state transitions in pancreatic cancer.

This paper introduces SpaceMarkers, a method to infer molecular changes from cell-cell interactions in spatial transcriptomics data, applied to tumor-immune interactions in metastasis and immunotherapy.

This paper introduces EVAsc, a method to analyze expression variation in scRNA-seq data to quantify tumor heterogeneity across cell types, subtypes, and patients.