# Project 2 Human Tumor Analysis > **NIH NIH U54** · STANFORD UNIVERSITY · 2024 · $482,856 ## Abstract SUMMARY/ABSTRACT: PROJECT 2 Metastasis is the primary cause of cancer-related death. Our recent evidence establishes a new paradigm, “lymph node tolerization,” in which the lymph node (LN) tissue environment creates a conditioned, systemic metastatic state across tissues and organs. This proposal aims to identify and characterize unidentified changes that create tolerize LNs, leading to the discovery of new biomarkers, drug targets, and treatment strategies. Using a spatial systems biology approach that combines multiplexed in situ imaging with single-cell RNA sequencing technologies, we will characterize tumor microenvironments across the host metastatic ecosystem, in HNSCC and LUAD. We hypothesize that spatially resolved stromal-immune interactions in LNs together with stromal-malignant properties in a primary tumor set the stage for metastasis. We will explore mechanistic properties of these processes using organoid models of human-derived cells and mouse models. In Aim 1, we will use using single-cell spatial proteomics to identify a pro-metastatic microenvironment in uninvolved LNs of HNSCC and LUAD cancer patients by reconstructing and comparing spatially resolved tumor-stroma-immune colocalization patterns of patient-derived uninvolved LNs, involved LNs, and primary tumors. These analyses will compare cell types and cell-cell co-localization patterns in the tissue environments of N0 and N+ patients. In addition, we will probe cell composition and colocalization patterns together with extracellular matrix architecture to ascertain the role of ECM in establishing and maintaining the pro-metastatic microenvironment in uninvolved LNs. In Aim 2, we will discover cell-cell interactions in uninvolved LNs that predispose them to colonization by malignant cells by reconstructing and comparing cell-cell interactions uninvolved LNs, involved LNs, and primary tumors inferred through integrative analysis of spatial information with single-cell RNA-sequencing. We will develop novel biocomputational approaches to integrate spatial features from CODEX with single cell RNA sequencing data to identify proximal cell-cell interactions among tumor-stromal and stromal-immune cell types associated with LN metastases. We will then evaluate selected cell-cell interactions in organoid models of human-derived cells, including perturbation with CRISPR-facilitated gene editing to reveal mechanistic insights. In Aim 3, we will predict spatiotemporal progression in tumor- stromal and stromal-immune colocalization patterns through spatially-aware Markov modeling and relate these patterns to changes in human-derived LNs and primary tumors associated with metastatic progression. We will build a spatially aware Markov model using spatially resolved time series data generated using tumor-stromal and immune-stromal organoids generated from human-derived cells, to identify spatial motifs of tumor-stromal and immune-stromal spatial patterning. This approach will illuminate spat... ## Key facts - **NIH application ID:** 10931495 - **Project number:** 5U54CA274511-02 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** SYLVIA KATINA PLEVRITIS - **Activity code:** U54 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $482,856 - **Award type:** 5 - **Project period:** 2023-09-19 → 2028-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10931495 ## Citation > US National Institutes of Health, RePORTER application 10931495, Project 2 Human Tumor Analysis (5U54CA274511-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10931495. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*