Blood and immune development in human fetal bone marrow and Down syndrome.

Haematopoiesis in the bone marrow (BM) maintains blood and immune cell production throughout postnatal life. Haematopoiesis first emerges in human BM at 11-12 weeks after conception1,2, yet almost nothing is known about how fetal BM (FBM) evolves to meet the highly specialized needs of the fetus and newborn. Here we detail the development of FBM, including stroma, using multi-omic assessment of mRNA and multiplexed protein epitope expression. We find that the full blood and immune cell repertoire is established in FBM in a short time window of 6-7 weeks early in the second trimester. FBM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell subsets emerging for the first time. The substantial expansion of B lymphocytes in FBM contrasts with fetal liver at the same gestational age. Haematopoietic progenitors from fetal liver, FBM and cord blood exhibit transcriptional and functional differences that contribute to tissue-specific identity and cellular diversification. Endothelial cell types form distinct vascular structures that we show are regionally compartmentalized within FBM. Finally, we reveal selective disruption of B lymphocyte, erythroid and myeloid development owing to a cell-intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in Down syndrome (trisomy 21).

Mapping Rora expression in resting and activated CD4+ T cells.

The transcription factor Rora has been shown to be important for the development of ILC2 and the regulation of ILC3, macrophages and Treg cells. Here we investigate the role of Rora across CD4+ T cells in general, but with an emphasis on Th2 cells, both in vitro as well as in the context of several in vivo type 2 infection models. We dissect the function of Rora using overexpression and a CD4-conditional Rora-knockout mouse, as well as a RORA-reporter mouse. We establish the importance of Rora in CD4+ T cells for controlling lung inflammation induced by Nippostrongylus brasiliensis infection, and have measured the effect on downstream genes using RNA-seq. Using a systematic stimulation screen of CD4+ T cells, coupled with RNA-seq, we identify upstream regulators of Rora, most importantly IL-33 and CCL7. Our data suggest that Rora is a negative regulator of the immune system, possibly through several downstream pathways, and is under control of the local microenvironment.

Skin dendritic cells in melanoma are key for successful checkpoint blockade therapy.

BACKGROUND: Immunotherapy with checkpoint inhibitors has shown impressive results in patients with melanoma, but still many do not benefit from this line of treatment. A lack of tumor-infiltrating T cells is a common reason for therapy failure but also a loss of intratumoral dendritic cells (DCs) has been described. METHODS: We used the transgenic tg(Grm1)EPv melanoma mouse strain that develops spontaneous, slow-growing tumors to perform immunological analysis during tumor progression. With flow cytometry, the frequencies of DCs and T cells at different tumor stages and the expression of the inhibitory molecules programmed cell death protein-1 (PD-1) and T-cell immunoglobulin and mucin-domain containing-3 (TIM-3) on T cells were analyzed. This was complemented with RNA-sequencing (RNA-seq) and real-time quantitative PCR (RT-qPCR) analysis to investigate the immune status of the tumors. To boost DC numbers and function, we administered Fms-related tyrosine 3 ligand (Flt3L) plus an adjuvant mix of polyI:C and anti-CD40. To enhance T cell function, we tested several checkpoint blockade antibodies. Immunological alterations were characterized in tumor and tumor-draining lymph nodes (LNs) by flow cytometry, CyTOF, microarray and RT-qPCR to understand how immune cells can control tumor growth. The specific role of migratory skin DCs was investigated by coculture of sorted DC subsets with melanoma-specific CD8+ T cells. RESULTS: Our study revealed that tumor progression is characterized by upregulation of checkpoint molecules and a gradual loss of the dermal conventional DC (cDC) 2 subset. Monotherapy with checkpoint blockade could not restore antitumor immunity, whereas boosting DC numbers and activation increased tumor immunogenicity. This was reflected by higher numbers of activated cDC1 and cDC2 as well as CD4+ and CD8+ T cells in treated tumors. At the same time, the DC boost approach reinforced migratory dermal DC subsets to prime gp100-specific CD8+ T cells in tumor-draining LNs that expressed PD-1/TIM-3 and produced interferon γ (IFNγ)/tumor necrosis factor α (TNFα). As a consequence, the combination of the DC boost with antibodies against PD-1 and TIM-3 released the brake from T cells, leading to improved function within the tumors and delayed tumor growth. CONCLUSIONS: Our results set forth the importance of skin DC in cancer immunotherapy, and demonstrates that restoring DC function is key to enhancing tumor immunogenicity and subsequently responsiveness to checkpoint blockade therapy.

Single-cell sequencing reveals clonal expansions of pro-inflammatory synovial CD8 T cells expressing tissue-homing receptors in psoriatic arthritis.

Psoriatic arthritis (PsA) is a debilitating immune-mediated inflammatory arthritis of unknown pathogenesis commonly affecting patients with skin psoriasis. Here we use complementary single-cell approaches to study leukocytes from PsA joints. Mass cytometry demonstrates a 3-fold expansion of memory CD8 T cells in the joints of PsA patients compared to peripheral blood. Meanwhile, droplet-based and plate-based single-cell RNA sequencing of paired T cell receptor alpha and beta chain sequences show pronounced CD8 T cell clonal expansions within the joints. Transcriptome analyses find these expanded synovial CD8 T cells to express cycling, activation, tissue-homing and tissue residency markers. T cell receptor sequence comparison between patients identifies clonal convergence. Finally, chemokine receptor CXCR3 is upregulated in the expanded synovial CD8 T cells, while two CXCR3 ligands, CXCL9 and CXCL10, are elevated in PsA synovial fluid. Our data thus provide a quantitative molecular insight into the cellular immune landscape of psoriatic arthritis.

Mosquito cellular immunity at single-cell resolution.

Hemocytes limit the capacity of mosquitoes to transmit human pathogens. Here we profile the transcriptomes of 8506 hemocytes of Anopheles gambiae and Aedes aegypti mosquito vectors. Our data reveal the functional diversity of hemocytes, with different subtypes of granulocytes expressing distinct and evolutionarily conserved subsets of effector genes. A previously unidentified cell type in An. gambiae, which we term "megacyte," is defined by a specific transmembrane protein marker (TM7318) and high expression of lipopolysaccharide-induced tumor necrosis factor-α transcription factor 3 (LL3). Knockdown experiments indicate that LL3 mediates hemocyte differentiation during immune priming. We identify and validate two main hemocyte lineages and find evidence of proliferating granulocyte populations. This atlas of medically relevant invertebrate immune cells at single-cell resolution identifies cellular events that underpin mosquito immunity to malaria infection.

Single-Cell RNA Sequencing Reveals a Dynamic Stromal Niche That Supports Tumor Growth.

Here, using single-cell RNA sequencing, we examine the stromal compartment in murine melanoma and draining lymph nodes (LNs) at points across tumor development, providing data at http://www.teichlab.org/data/. Naive lymphocytes from LNs undergo activation and clonal expansion within the tumor, before PD1 and Lag3 expression, while tumor-associated myeloid cells promote the formation of a suppressive niche. We identify three temporally distinct stromal populations displaying unique functional signatures, conserved across mouse and human tumors. Whereas "immune" stromal cells are observed in early tumors, "contractile" cells become more prevalent at later time points. Complement component C3 is specifically expressed in the immune population. Its cleavage product C3a supports the recruitment of C3aR+ macrophages, and perturbation of C3a and C3aR disrupts immune infiltration, slowing tumor growth. Our results highlight the power of scRNA-seq to identify complex interplays and increase stromal diversity as a tumor develops, revealing that stromal cells acquire the capacity to modulate immune landscapes from early disease.

Spatiotemporal immune zonation of the human kidney.

Tissue-resident immune cells are important for organ homeostasis and defense. The epithelium may contribute to these functions directly or by cross-talk with immune cells. We used single-cell RNA sequencing to resolve the spatiotemporal immune topology of the human kidney. We reveal anatomically defined expression patterns of immune genes within the epithelial compartment, with antimicrobial peptide transcripts evident in pelvic epithelium in the mature, but not fetal, kidney. A network of tissue-resident myeloid and lymphoid immune cells was evident in both fetal and mature kidney, with postnatal acquisition of transcriptional programs that promote infection-defense capabilities. Epithelial-immune cross-talk orchestrated localization of antibacterial macrophages and neutrophils to the regions of the kidney most susceptible to infection. Overall, our study provides a global overview of how the immune landscape of the human kidney is zonated to counter the dominant immunological challenge.

A cellular census of human lungs identifies novel cell states in health and in asthma.

Human lungs enable efficient gas exchange and form an interface with the environment, which depends on mucosal immunity for protection against infectious agents. Tightly controlled interactions between structural and immune cells are required to maintain lung homeostasis. Here, we use single-cell transcriptomics to chart the cellular landscape of upper and lower airways and lung parenchyma in healthy lungs, and lower airways in asthmatic lungs. We report location-dependent airway epithelial cell states and a novel subset of tissue-resident memory T cells. In the lower airways of patients with asthma, mucous cell hyperplasia is shown to stem from a novel mucous ciliated cell state, as well as goblet cell hyperplasia. We report the presence of pathogenic effector type 2 helper T cells (TH2) in asthmatic lungs and find evidence for type 2 cytokines in maintaining the altered epithelial cell states. Unbiased analysis of cell-cell interactions identifies a shift from airway structural cell communication in healthy lungs to a TH2-dominated interactome in asthmatic lungs.

Nuclear receptor NR2F6 inhibition potentiates responses to PD-L1/PD-1 cancer immune checkpoint blockade.

Analyzing mouse tumor models in vivo, human T cells ex vivo, and human lung cancer samples, we provide direct evidence that NR2F6 acts as an immune checkpoint. Genetic ablation of Nr2f6, particularly in combination with established cancer immune checkpoint blockade, efficiently delays tumor progression and improves survival in experimental mouse models. The target genes deregulated in intratumoral T lymphocytes upon genetic ablation of Nr2f6 alone or together with PD-L1 blockade reveal multiple advantageous transcriptional alterations. Acute Nr2f6 silencing in both mouse and human T cells induces hyper-responsiveness that establishes a non-redundant T-cell-inhibitory function of NR2F6. NR2F6 protein expression in T-cell-infiltrating human NSCLC is upregulated in 54% of the cases (n = 303) and significantly correlates with PD-1 and CTLA-4 expression. Our data define NR2F6 as an intracellular immune checkpoint that suppresses adaptive anti-cancer immune responses and set the stage for clinical validation of targeting NR2F6 for next-generation immuno-oncological regimens.

Targeting immune checkpoints potentiates immunoediting and changes the dynamics of tumor evolution.

The cancer immunoediting hypothesis postulates a dual role of the immune system: protecting the host by eliminating tumor cells, and shaping the tumor by editing its genome. Here, we elucidate the impact of evolutionary and immune-related forces on editing the tumor in a mouse model for hypermutated and microsatellite-instable colorectal cancer. Analyses of wild-type and immunodeficient RAG1 knockout mice transplanted with MC38 cells reveal that upregulation of checkpoint molecules and infiltration by Tregs are the major tumor escape mechanisms. Our results show that the effects of immunoediting are weak and that neutral accumulation of mutations dominates. Targeting the PD-1/PD-L1 pathway using immune checkpoint blocker effectively potentiates immunoediting. The immunoediting effects are less pronounced in the CT26 cell line, a non-hypermutated/microsatellite-instable model. Our study demonstrates that neutral evolution is another force that contributes to sculpting the tumor and that checkpoint blockade effectively enforces T-cell-dependent immunoselective pressure.

Neoantigens Generated by Individual Mutations and Their Role in Cancer Immunity and Immunotherapy.

Recent preclinical and clinical studies have proved the long-standing hypothesis that tumors elicit adaptive immune responses and that the antigens driving effective T-cell response are neoantigens, i.e., peptides that are generated from somatically mutated genes. Hence, the characterization of neoantigens and the identification of the immunogenic ones are of utmost importance for improving cancer immunotherapy and broadening its efficacy to a larger fraction of patients. In this review, we first introduce the methods used for the quantification of neoantigens using next-generation sequencing data and then summarize results obtained using these tools to characterize the neoantigen landscape in solid cancers. We then discuss the importance of neoantigens for cancer immunotherapy using checkpoint blockers, vaccination, and adoptive T-cell transfer. Finally, we give an overview over emerging aspects in cancer immunity, including tumor heterogeneity and immunoediting, and give an outlook on future prospects.

Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade.

The Cancer Genome Atlas revealed the genomic landscapes of human cancers. In parallel, immunotherapy is transforming the treatment of advanced cancers. Unfortunately, the majority of patients do not respond to immunotherapy, making the identification of predictive markers and the mechanisms of resistance an area of intense research. To increase our understanding of tumor-immune cell interactions, we characterized the intratumoral immune landscapes and the cancer antigenomes from 20 solid cancers and created The Cancer Immunome Atlas (https://tcia.at/). Cellular characterization of the immune infiltrates showed that tumor genotypes determine immunophenotypes and tumor escape mechanisms. Using machine learning, we identified determinants of tumor immunogenicity and developed a scoring scheme for the quantification termed immunophenoscore. The immunophenoscore was a superior predictor of response to anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) and anti-programmed cell death protein 1 (anti-PD-1) antibodies in two independent validation cohorts. Our findings and this resource may help inform cancer immunotherapy and facilitate the development of precision immuno-oncology.

A survey of tools for variant analysis of next-generation genome sequencing data.

Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Specifically, whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in the human genetics community due to the moderate costs, manageable data amounts and straightforward interpretation of analysis results. While whole-exome and, in the near future, whole-genome sequencing are becoming commodities, data analysis still poses significant challenges and led to the development of a plethora of tools supporting specific parts of the analysis workflow or providing a complete solution. Here, we surveyed 205 tools for whole-genome/whole-exome sequencing data analysis supporting five distinct analytical steps: quality assessment, alignment, variant identification, variant annotation and visualization. We report an overview of the functionality, features and specific requirements of the individual tools. We then selected 32 programs for variant identification, variant annotation and visualization, which were subjected to hands-on evaluation using four data sets: one set of exome data from two patients with a rare disease for testing identification of germline mutations, two cancer data sets for testing variant callers for somatic mutations, copy number variations and structural variations, and one semi-synthetic data set for testing identification of copy number variations. Our comprehensive survey and evaluation of NGS tools provides a valuable guideline for human geneticists working on Mendelian disorders, complex diseases and cancers.

Mathematical models for translational and clinical oncology.

In the context of translational and clinical oncology, mathematical models can provide novel insights into tumor-related processes and can support clinical oncologists in the design of the treatment regime, dosage, schedule, toxicity and drug-sensitivity. In this review we present an overview of mathematical models in this field beginning with carcinogenesis and proceeding to the different cancer treatments. By doing so we intended to highlight recent developments and emphasize the power of such theoretical work.We first highlight mathematical models for translational oncology comprising epidemiologic and statistical models, mechanistic models for carcinogenesis and tumor growth, as well as evolutionary dynamics models which can help to describe and overcome a major problem in the clinic: therapy resistance. Next we review models for clinical oncology with a special emphasis on therapy including chemotherapy, targeted therapy, radiotherapy, immunotherapy and interaction of cancer cells with the immune system.As evident from the published studies, mathematical modeling and computational simulation provided valuable insights into the molecular mechanisms of cancer, and can help to improve diagnosis and prognosis of the disease, and pinpoint novel therapeutic targets.

Bioinformatics for cancer immunology and immunotherapy.

Recent mechanistic insights obtained from preclinical studies and the approval of the first immunotherapies has motivated increasing number of academic investigators and pharmaceutical/biotech companies to further elucidate the role of immunity in tumor pathogenesis and to reconsider the role of immunotherapy. Additionally, technological advances (e.g., next-generation sequencing) are providing unprecedented opportunities to draw a comprehensive picture of the tumor genomics landscape and ultimately enable individualized treatment. However, the increasing complexity of the generated data and the plethora of bioinformatics methods and tools pose considerable challenges to both tumor immunologists and clinical oncologists. In this review, we describe current concepts and future challenges for the management and analysis of data for cancer immunology and immunotherapy. We first highlight publicly available databases with specific focus on cancer immunology including databases for somatic mutations and epitope databases. We then give an overview of the bioinformatics methods for the analysis of next-generation sequencing data (whole-genome and exome sequencing), epitope prediction tools as well as methods for integrative data analysis and network modeling. Mathematical models are powerful tools that can predict and explain important patterns in the genetic and clinical progression of cancer. Therefore, a survey of mathematical models for tumor evolution and tumor-immune cell interaction is included. Finally, we discuss future challenges for individualized immunotherapy and suggest how a combined computational/experimental approaches can lead to new insights into the molecular mechanisms of cancer, improved diagnosis, and prognosis of the disease and pinpoint novel therapeutic targets.