Rarity: discovering rare cell populations from single-cell imaging data.

MOTIVATION: Cell type identification plays an important role in the analysis and interpretation of single-cell data and can be carried out via supervised or unsupervised clustering approaches. Supervised methods are best suited where we can list all cell types and their respective marker genes a priori, while unsupervised clustering algorithms look for groups of cells with similar expression properties. This property permits the identification of both known and unknown cell populations, making unsupervised methods suitable for discovery. Success is dependent on the relative strength of the expression signature of each group as well as the number of cells. Rare cell types therefore present a particular challenge that is magnified when they are defined by differentially expressing a small number of genes. RESULTS: Typical unsupervised approaches fail to identify such rare subpopulations, and these cells tend to be absorbed into more prevalent cell types. In order to balance these competing demands, we have developed a novel statistical framework for unsupervised clustering, named Rarity, that enables the discovery process for rare cell types to be more robust, consistent, and interpretable. We achieve this by devising a novel clustering method based on a Bayesian latent variable model in which we assign cells to inferred latent binary on/off expression profiles. This lets us achieve increased sensitivity to rare cell populations while also allowing us to control and interpret potential false positive discoveries. We systematically study the challenges associated with rare cell type identification and demonstrate the utility of Rarity on various IMC datasets. AVAILABILITY AND IMPLEMENTATION: Implementation of Rarity together with examples is available from the Github repository (https://github.com/kasparmartens/rarity).

Immunogenomics of Colorectal Cancer Response to Checkpoint Blockade: Analysis of the KEYNOTE 177 Trial and Validation Cohorts.

BACKGROUND & AIMS: Colorectal cancer (CRC) shows variable response to immune checkpoint blockade, which can only partially be explained by high tumor mutational burden (TMB). We conducted an integrated study of the cancer tissue and associated tumor microenvironment (TME) from patients treated with pembrolizumab (KEYNOTE 177 clinical trial) or nivolumab to dissect the cellular and molecular determinants of response to anti- programmed cell death 1 (PD1) immunotherapy. METHODS: We selected multiple regions per tumor showing variable T-cell infiltration for a total of 738 regions from 29 patients, divided into discovery and validation cohorts. We performed multiregional whole-exome and RNA sequencing of the tumor cells and integrated these with T-cell receptor sequencing, high-dimensional imaging mass cytometry, detection of programmed death-ligand 1 (PDL1) interaction in situ, multiplexed immunofluorescence, and computational spatial analysis of the TME. RESULTS: In hypermutated CRCs, response to anti-PD1 immunotherapy was not associated with TMB but with high clonality of immunogenic mutations, clonally expanded T cells, low activation of Wnt signaling, deregulation of the interferon gamma pathway, and active immune escape mechanisms. Responsive hypermutated CRCs were also rich in cytotoxic and proliferating PD1+CD8 T cells interacting with PDL1+ antigen-presenting macrophages. CONCLUSIONS: Our study clarified the limits of TMB as a predictor of response of CRC to anti-PD1 immunotherapy. It identified a population of antigen-presenting macrophages interacting with CD8 T cells that consistently segregate with response. We therefore concluded that anti-PD1 agents release the PD1-PDL1 interaction between CD8 T cells and macrophages to promote cytotoxic antitumor activity.

B cells in human lymphoid structures.

Most B cells in the human body are present in tissues where they support immune responses to pathogens, vaccines, autoantigens, and tumours. Despite their clear importance, they are very difficult to study and there are many areas of uncertainty that are difficult to resolve because of limited tissue access. In this review, we consider the zonal structure of lymphoid tissues, the B cell subsets they contain, and how these are regulated. We also discuss the impact that methods of deep interrogation have made on our current knowledge base, especially with respect to studies of cells from dissociated tissues. We discuss in some detail the controversial B cells with marginal zone distribution that some consider being archived memory B cells. We anticipate that more we understand of B cells in tissues and the niches they create, the more opportunities will be identified to harness their potential for therapeutic benefit.

ZFP36 stabilizes RIP1 via degradation of XIAP and cIAP2 thereby promoting ripoptosome assembly.

BACKGROUND: ZFP36 is an mRNA binding protein that exerts anti-tumor activity in glioblastoma by triggering cell death, associated to an increase in the stability of the kinase RIP1. METHODS: We used cell death assays, size exclusion chromatography, Co-Immunoprecipitation, shRNA lentivectors and glioma neural stem cells to determine the effects of ZFP36 on the assembly of a death complex containing RIP1 and on the induction of necroptosis. RESULTS: Here we demonstrate that ZFP36 promotes the assembly of the death complex called Ripoptosome and induces RIP1-dependent death. This involves the depletion of the ubiquitine ligases cIAP2 and XIAP and leads to the association of RIP1 to caspase-8 and FADD. Moreover, we show that ZFP36 controls RIP1 levels in glioma neural stem cell lines. CONCLUSIONS: We provide a molecular mechanism for the tumor suppressor role of ZFP36, and the first evidence for Ripoptosome assembly following ZFP36 expression. These findings suggest that ZFP36 plays an important role in RIP1-dependent cell death in conditions where IAPs are depleted.

Double-negative B cells and DNASE1L3 colocalise with microbiota in gut-associated lymphoid tissue.

Intestinal homeostasis is maintained by the response of gut-associated lymphoid tissue to bacteria transported across the follicle associated epithelium into the subepithelial dome. The initial response to antigens and how bacteria are handled is incompletely understood. By iterative application of spatial transcriptomics and multiplexed single-cell technologies, we identify that the double negative 2 subset of B cells, previously associated with autoimmune diseases, is present in the subepithelial dome in health. We show that in this location double negative 2 B cells interact with dendritic cells co-expressing the lupus autoantigens DNASE1L3 and C1q and microbicides. We observe that in humans, but not in mice, dendritic cells expressing DNASE1L3 are associated with sampled bacteria but not DNA derived from apoptotic cells. We propose that fundamental features of autoimmune diseases are microbiota-associated, interacting components of normal intestinal immunity.

A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially-resolved tissue phenotyping at single-cell resolution.

Multiplexed imaging technologies enable the study of biological tissues at single-cell resolution while preserving spatial information. Currently, high-dimension imaging data analysis is technology-specific and requires multiple tools, restricting analytical scalability and result reproducibility. Here we present SIMPLI (Single-cell Identification from MultiPLexed Images), a flexible and technology-agnostic software that unifies all steps of multiplexed imaging data analysis. After raw image processing, SIMPLI performs a spatially resolved, single-cell analysis of the tissue slide as well as cell-independent quantifications of marker expression to investigate features undetectable at the cell level. SIMPLI is highly customisable and can run on desktop computers as well as high-performance computing environments, enabling workflow parallelisation for large datasets. SIMPLI produces multiple tabular and graphical outputs at each step of the analysis. Its containerised implementation and minimum configuration requirements make SIMPLI a portable and reproducible solution for multiplexed imaging data analysis. Software is available at "SIMPLI [ https://github.com/ciccalab/SIMPLI ]".

Disrupted Peyer's Patch Microanatomy in COVID-19 Including Germinal Centre Atrophy Independent of Local Virus.

Confirmed SARS-coronavirus-2 infection with gastrointestinal symptoms and changes in microbiota associated with coronavirus disease 2019 (COVID-19) severity have been previously reported, but the disease impact on the architecture and cellularity of ileal Peyer's patches (PP) remains unknown. Here we analysed post-mortem tissues from throughout the gastrointestinal (GI) tract of patients who died with COVID-19. When virus was detected by PCR in the GI tract, immunohistochemistry identified virus in epithelium and lamina propria macrophages, but not in lymphoid tissues. Immunohistochemistry and imaging mass cytometry (IMC) analysis of ileal PP revealed depletion of germinal centres (GC), disruption of B cell/T cell zonation and decreased potential B and T cell interaction and lower nuclear density in COVID-19 patients. This occurred independent of the local viral levels. The changes in PP demonstrate that the ability to mount an intestinal immune response is compromised in severe COVID-19, which could contribute to observed dysbiosis.

Comparative assessment of genes driving cancer and somatic evolution in non-cancer tissues: an update of the Network of Cancer Genes (NCG) resource.

BACKGROUND: Genetic alterations of somatic cells can drive non-malignant clone formation and promote cancer initiation. However, the link between these processes remains unclear and hampers our understanding of tissue homeostasis and cancer development. RESULTS: Here, we collect a literature-based repertoire of 3355 well-known or predicted drivers of cancer and non-cancer somatic evolution in 122 cancer types and 12 non-cancer tissues. Mapping the alterations of these genes in 7953 pan-cancer samples reveals that, despite the large size, the known compendium of drivers is still incomplete and biased towards frequently occurring coding mutations. High overlap exists between drivers of cancer and non-cancer somatic evolution, although significant differences emerge in their recurrence. We confirm and expand the unique properties of drivers and identify a core of evolutionarily conserved and essential genes whose germline variation is strongly counter-selected. Somatic alteration in even one of these genes is sufficient to drive clonal expansion but not malignant transformation. CONCLUSIONS: Our study offers a comprehensive overview of our current understanding of the genetic events initiating clone expansion and cancer revealing significant gaps and biases that still need to be addressed. The compendium of cancer and non-cancer somatic drivers, their literature support, and properties are accessible in the Network of Cancer Genes and Healthy Drivers resource at http://www.network-cancer-genes.org/ .

Two subsets of human marginal zone B cells resolved by global analysis of lymphoid tissues and blood.

B cells generate antibodies that are essential for immune protection, but their subgroups are poorly defined. Here, we perform undirected deep profiling of B cells in matched human lymphoid tissues from deceased transplant organ donors and blood. In addition to identifying unanticipated features of tissue-based B cell differentiation, we resolve two subsets of marginal zone B (MZB) cells differing in cell surface and transcriptomic profiles, clonal relationships to other subsets, enrichment of genes in the NOTCH pathway, distribution bias within splenic marginal zone microenvironment, and immunoglobulin repertoire diversity and hypermutation frequency. Each subset is present in spleen, gut-associated lymphoid tissue, mesenteric lymph nodes, and blood. MZB cells and the lineage from which they are derived are depleted in lupus nephritis. Here, we show that this depletion is of only one MZB subset. The other remains unchanged as a proportion of total B cells compared with health. Thus, it is important to factor MZB cell heterogeneity into studies of human B cell responses and pathology.

KLF4 Mediates the Effect of 5-ASA on the ß-Catenin Pathway in Colon Cancer Cells.

Mesalazine (5-ASA) is an aminosalicylate anti-inflammatory drug capable of inducing µ-protocadherin, a protein expressed by colorectal epithelial cells that is downregulated upon malignant transformation. Treatment with 5-ASA restores µ-protocadherin expression and promotes the sequestration of ß-catenin to the plasma membrane. Here, we show that 5-ASA-induced µ-protocadherin expression is directly regulated by the KLF4 transcription factor. In addition, we suggest the existence of a dual mechanism whereby 5-ASA-mediated ß-catenin inhibition is caused by µ-protocadherin-dependent sequestration of ß-catenin to the plasma membrane and by the direct binding of KLF4 to ß-catenin. In addition, we found that 5-ASA treatment suppresses the expression of miR-130a and miR-135b, which target KLF4 mRNA, raising the possibility that this mechanism is involved in the increased expression of KLF4 induced by 5-ASA. Cancer Prev Res; 11(8); 503-10. ©2018 AACR.

Loss of ZFP36 expression in colorectal cancer correlates to wnt/ ß-catenin activity and enhances epithelial-to-mesenchymal transition through upregulation of ZEB1, SOX9 and MACC1.

The mRNA-destabilizing protein ZFP36 has been previously described as a tumor suppressor whose expression is lost during colorectal cancer development. In order to evaluate its role in this disease, we restored ZFP36 expression in different cell contexts, showing that the presence of this protein impairs the epithelial-to-mesenchymal transition (EMT) and induces a higher susceptibility to anoikis. Consistently, we found that ZFP36 inhibits the expression of three key transcription factors involved in EMT: ZEB1, MACC1 and SOX9. Finally, we observed for the first time that its expression negatively correlates with the activity of Wnt/ß-catenin pathway, which is constitutively activated in colorectal cancer. This evidence provides a clue on the mechanism leading to the loss of ZFP36 in CRC.