Cancer-associated fibroblast classification in single-cell and spatial proteomics dataCancer-associated fibroblasts (CAFs) are a diverse cell population within the tumour microenvironment, where they have critical effects on tumour evolution and patient prognosis. To define CAF phenotypes, we analyse a single-cell RNA sequencing (scRNA-seq) dataset of over 16,000 stromal cells from tumours of 14 breast cancer patients, based on which we define and functionally annotate nine CAF phenotypes and one class of pericytes. We validate this classification system in four additional cancer types and use highly multiplexed imaging mass cytometry on matched breast cancer samples to confirm our defined CAF phenotypes at the protein level and to analyse their spatial distribution within tumours. This general CAF classification scheme will allow comparison of CAF phenotypes across studies, facilitate analysis of their functional roles, and potentially guide development of new treatment strategies in the future.
Cancer-associated fibroblast phenotypes are associated with patient outcome in non-small cell lung cancerDespite advances in treatment, lung cancer survival rates remain low. A better understanding of the cellular heterogeneity and interplay of cancer-associated fibroblasts (CAFs) within the tumor microenvironment will support the development of personalized therapies. We report a spatially resolved single-cell imaging mass cytometry (IMC) analysis of CAFs in a non-small cell lung cancer cohort of 1,070 patients. We identify four prognostic patient groups based on 11 CAF phenotypes with distinct spatial distributions and show that CAFs are independent prognostic factors for patient survival. The presence of tumor-like CAFs is strongly correlated with poor prognosis. In contrast, inflammatory CAFs and interferon-response CAFs are associated with inflamed tumor microenvironments and higher patient survival. High density of matrix CAFs is correlated with low immune infiltration and is negatively correlated with patient survival. In summary, our data identify phenotypic and spatial features of CAFs that are associated with patient outcome in NSCLC.
Classifying cancer-associated fibroblasts—The good, the bad, and the targetAcquired resistance to anti-PD1 therapy in patients with NSCLC associates with immunosuppressive T cell phenotypeAbstract Immune checkpoint inhibitor treatment has the potential to prolong survival in non-small cell lung cancer (NSCLC), however, some of the patients develop resistance following initial response. Here, we analyze the immune phenotype of matching tumor samples from a cohort of NSCLC patients showing good initial response to immune checkpoint inhibitors, followed by acquired resistance at later time points. By using imaging mass cytometry and whole exome and RNA sequencing, we detect two patterns of resistance¨: One group of patients is characterized by reduced numbers of tumor-infiltrating CD8 + T cells and reduced expression of PD-L1 after development of resistance, whereas the other group shows high CD8 + T cell infiltration and high expression of PD-L1 in addition to markedly elevated expression of other immune-inhibitory molecules. In two cases, we detect downregulation of type I and II IFN pathways following progression to resistance, which could lead to an impaired anti-tumor immune response. This study thus captures the development of immune checkpoint inhibitor resistance as it progresses and deepens our mechanistic understanding of immunotherapy response in NSCLC.
Distinct actin cytoskeleton behaviour in primary and immortalised T-cellsCytoskeletal actin dynamics are crucial for the activation of T-cells. Immortalised Jurkat T-cells have been the model system of choice to examine and correlate the dynamics of the actin cytoskeleton and the immunological synapse leading to T-cell activation. However, it has remained unclear whether immortalised cellular systems, such as Jurkat T-cells can recapitulate the cytoskeletal behaviour of primary T-cells. Studies delineating the cytoskeletal behaviour of Jurkat T-cells in comparison to primary T-cells are lacking. Here, we employ live-cell super-resolution microscopy to investigate the cytoskeletal actin organisation and dynamics of living primary and immortalised Jurkat T-cells at the appropriate spatiotemporal resolution. Under comparable activation conditions, we found differences in the architectural organisation and dynamics of Jurkat and primary mouse and human T-cells. Although the three main actin network architectures in Jurkat T-cells were reminiscent of primary T-cells, there were differences in the organisation and molecular mechanisms underlying these networks. Our results highlight mechanistic distinctions in the T-cell model system most utilised to study cytoskeletal actin dynamics.