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Most research on the cancer metastatic cascade involves tracking cancer cell invasion, migration, arrest, and distant tissue colonization – centered mainly on tumor properties and activities. Our previous work introduced a new paradigm, “lymph node (LN) tolerization,” that redefines LNs from passive way stops in metastasis to active command centers that instigate a systemic switch to immune tolerance. We hypothesize that this switch enables tumor cells to advance unobstructed through previously guarded host defense mechanisms. Knowing how to reprogram LN tolerization may provide novel spatial biomarkers and therapeutic targets.

Even though LNs are commonly assessed in cancer patients to determine disease stage and treatment plan, they are understudied in the context of metastasis. Our multidisciplinary team is applying genomic and single-cell in-situ imaging technologies to iteratively analyze changes in tumor, immune, and stromal interactions before, during, and after LN colonization in two cancers, head and neck cancer (HNCC) and lung adenocarcinoma (LUAD). These technologies are fueling the growth of spatial systems biology as a distinct field capable of unprecedented characterization of tissue microenvironments as complex ecosystems of interacting cell types including epithelial, immune, stromal and endothelial cells. 

We are dedicated to promoting our early investigators as the next generation thought leaders applying principles of systems biology to the study of metastasis. Our Outreach Core activity will ensure that our Research Center’s scientific and methodological advances in applying the principles of cancer systems biology toward the study of tumor-immune-stromal interactions are fully disseminated among cancer researchers and broader scientific communities.

PROJECT 1: Mouse models analysis of lymph node and distant metastasis
Edgar Engleman, MD, Lead

Our prior data in a mouse model showed that by colonizing LNs, tumor cells induce tumor-specific immune tolerance through interactions with LN immune cells. Leukocytes then establish systemic immune tolerance throughout the host, seeding metastatic spread. We identified a conserved transcriptional signature for LN metastases in humans, suggesting that the mechanisms driving LN metastasis and immune tolerance in our mouse model are relevant to human cancers. We hypothesize that local interactions between tumor cells, leukocytes, and stroma within LNs tolerize distant tissues before, during, and after LN colonization. We expect these interactions will involve cell-cell interactions; architectural changes within LNs, tumors, and distant tissues; as well as host-wide trafficking of various cell populations. Using syngeneic mouse models, we will identify the mechanisms by which tumor-immune-stromal interactions in lymph node microenvironments using three approaches. 1) Use a high-dimensional imaging platform (CODEX) to uncover longitudinal changes in local microenvironments across the host. 2) Use spatial transcriptomics to determine how gene expression patterns of cells interacting with malignant cells differ from those at a distance. To confirm the functional significance of these targets identified and those identified in Project 2, we will combine CRISPR-mediated gene editing of LN metastatic tumors with cell-depletion studies and knockout mice/inducible mouse models. 3) Use a novel cell-labeling platform to evaluate trafficking of leukocytes and stromal cells from tumor-involved LNs to distant sites and back to the primary tumor.

PROJECT 2: Human tumor analysis of lymph node and distant metastasis
Sylvia Plevritis, PhD, Lead

Using human tissues, we can now quantitatively compare the spatial biology of uninvolved LNs and their concurrent primary tumors by applying recent advances in multiplexed in situ imaging with single-cell sequencing technologies. 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 test this hypothesis by spatially phenotyping human tumor samples across a spectrum of clinical stages, including early stages. 1) We will reconstruct and compare spatially resolved tumor-stroma-immune colocalization patterns in samples from HNSCC and LUAD cancer patients of uninvolved LNs, involved LNs, and primary tumors. We will also probe cell composition and colocalization patterns within the extracellular matrix (ECM) to ascertain its role in establishing and maintaining a pro-metastatic microenvironment in uninvolved LNs. 2) We will discover cell-cell interactions in uninvolved LNs using novel biocomputational approaches to integrate spatial features from CODEX with single-cell RNA sequencing data, toward identifying 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. 3) We will use spatially-aware Markov modeling to predict tumor-stromal and stromal-immune colocalization patterns in human-derived LNs and primary tumors associated with metastatic progression.

Joseph Shrager, MD, co-Lead
John Sunwoo, MD, PhD, co-Lead
Parag Mallik, PhD, co-Lead

Both Project 1 and Project 2 will use a shared resource core dedicated to the acquisition of patient samples and associated clinical annotation and data management. These efforts will yield highly multiplexed, multi-scale datasets that will be analyzed by novel bio-computational methods to reconstruct intracellular and intercellular molecular interaction networks to identify, then functionally validate, critical mediators of metastasis. This Core will provide to all our Center researchers the expertise and facilities for fresh and archived specimen acquisition, genomic and image data processing, and data sharing. We will 1) develop a fresh tissue biospecimen repository of HNSCC and LUAD samples, as well as mouse models of metastasis for single-cell RNA sequencing scRNA-seq)and CODEX analysis; 2) construct clinically annotated tissue microarrays of fixed primary, LN, and distant metastases to validate findings from Center projects on large independent cohorts; 3) perform quality control, processing, and basic analyses using existing robust pre-processing and analysis pipelines for scRNA-seq, CODEX, and immunohistochemistry data; and 4) leverage Center-generated data in the context of larger publicly available cohorts as well as identify, curate, pre-process, and analyze public data relevant to the Center’s aims. Baseline meta-analyses of the relationship between gene expression data and LN/distant metastasis will be linked to insights from internally generated datasets. All data and analyses will be available to the broader CCSB consortium.