Reticker-Flynn, N. E. | Search bioRxiv

bioRxiv2023

The temporal progression of immune remodeling during metastasis.

Tumor metastasis requires systemic remodeling of distant organ microenvironments which impacts immune cell phenotypes, population structure, and intercellular communication networks. However, our understanding of immune phenotypic dynamics in the metastatic niche remains incomplete. Here, we longitudinally assayed lung immune cell gene expression profiles in mice bearing PyMT-driven metastatic breast tumors from the onset of primary tumorigenesis, through formation of the pre-metastatic niche, to the final stages of metastatic outgrowth. Computational analysis of these data revealed an ordered series of immunological changes that correspond to metastatic progression. Specifically, we uncovered a TLR-NF{kappa}B myeloid inflammatory program which correlates with pre-metastatic niche formation and mirrors described signatures of CD14+ activated MDSCs in the primary tumor. Moreover, we observed that cytotoxic NK cell proportions increased over time which illustrates how the PyMT lung metastatic niche is both inflammatory and immunosuppressive. Finally, we predicted metastasis-associated immune intercellular signaling interactions involving Igf1 and Ccl6 which may organize the metastatic niche. In summary, this work identifies novel immunological signatures of metastasis and discovers new details about established mechanisms that drive metastatic progression. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/539153v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1333376org.highwire.dtl.DTLVardef@77c937org.highwire.dtl.DTLVardef@3b78b1org.highwire.dtl.DTLVardef@70d497_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefMcGinnis et al. report a longitudinal scRNA-seq atlas of lung immune cells in mice bearing PyMT-driven metastatic breast tumors and identify immune cell transcriptional states, shifts in population structure, and rewiring of cell-cell signaling networks which correlate with metastatic progression. HighlightsO_LILongitudinal scRNA-seq reveals distinct stages of immune remodeling before, during, and after metastatic colonization in the lungs of PyMT mice. C_LIO_LITLR-NF{kappa}B inflammation correlates with pre-metastatic niche formation and involves both tissue-resident and bone marrow-derived myeloid cell populations. C_LIO_LIInflammatory lung myeloid cells mirror activated primary tumor MDSCs, suggesting that primary tumor-derived cues induce Cd14 expression and TLR-NF{kappa}B inflammation in the lung. C_LIO_LILymphocytes contribute to the inflammatory and immunosuppressive lung metastatic microenvironment, highlighted by enrichment of cytotoxic NK cells in the lung over time. C_LIO_LICell-cell signaling network modeling predicts cell type-specific Ccl6 regulation and IGF1-IGF1R signaling between neutrophils and interstitial macrophages. C_LI

immunology↗

bioRxiv2022

Identification of cell types in multiplexed in situ images by combining protein expression and spatial information using CELESTA reveals novel spatial biology

Advances in multiplexed in situ imaging are revealing important insights in spatial biology. However, cell type identification remains a major challenge in imaging analysis, with most existing methods involving substantial manual assessment and subjective decisions for thousands of cells. We propose a novel machine learning algorithm, CELESTA, which uses both cells protein expression and spatial information to identify cell type of individual cells. We demonstrate the performance of CELESTA on multiplexed immunofluorescence in situ images of colorectal cancer and head and neck cancer. Using the cell types identified by CELESTA, we identify tissue architecture associated with lymph node metastasis in HNSCC, which we validate in an independent cohort. By coupling our in situ spatial analysis with single-cell RNA-sequencing data on proximal sections of the same tissue specimens, we identify and validate cell-cell crosstalk associated with lymph node metastasis, demonstrating the power of spatial biology to reveal clinically-relevant cellular interactions.

bioinformatics↗

bioRxiv2020

Transient cell-in-cell formation underlies tumor resistance to immunotherapy

Despite the remarkable success of immunotherapy in cancer, most patients will develop resistant tumors. While the main conceptual paradigm suggests that relapsed clones emerge through a process of clonal selection and immunoediting, currently little evidence directly demonstrates this process in epithelial cancers. To study this process, we established several mouse models in which tumors drastically regress following immunotherapy, yet resistant tumors relapse within a few weeks of treatment cessation. Whole exome analyses indicated that relapsed tumors share hundreds of neo-antigens with the primary tumors and are comparably killed by reactive T cells. Examination of tumor cells that survive immunotherapies revealed that they structure a transient cell-in-cell formation, which is impenetrable to immune-derived cytotoxic compounds and to chemotherapies. This formation is mediated predominantly by a cell-membrane protein on activated T cells, which subsequently induces epidermal growth factor receptors and STAT3 phosphorylation in tumors cells. In contrast to previous reports on cell-in-cell formations, here both cells remain alive and can disseminate into single tumor cells once T cells are no longer present. Overall, this work highlights a powerful resistance mechanism which enable tumor cells to survive immune pressure and provides a new theoretical framework for combining chemotherapies and immunotherapies.

immunology↗