Azizi E, Carr AJ, Plitas G, Cornish AE, Konopacki C, Prabhakaran S, Nainys J, Wu K, Kiseliovas V, Setty M, Choi K, Fromme RM, Dao P, McKenney PT, Wasti RC, Kadaveru K, Mazutis L, Rudensky AY, Pe'er D. Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment. Cell 2018; 174: 1293-1308. e36. [PMID: 29961579 DOI: 10.1016/j.cell.2018.05.060]

De novo prediction of cell-type complexity in single-cell RNA-seq and tumor microenvironments

This study describes a computational method for determining statistical support to varying levels of heterogeneity provided by single-cell RNA-sequencing data with applications to tumor samples.

Recent single-cell transcriptomic studies revealed new insights into cell-type heterogeneities in cellular microenvironments unavailable from bulk studies. A significant drawback of currently available algorithms is the need to use empirical parameters or rely on indirect quality measures to estimate the degree of complexity, i.e., the number of subgroups present in the sample. We fill this gap with a single-cell data analysis procedure allowing for unambiguous assessments of the depth of heterogeneity in subclonal compositions supported by data. Our approach combines nonnegative matrix factorization, which takes advantage of the sparse and nonnegative nature of single-cell RNA count data, with Bayesian model comparison enabling de novo prediction of the depth of heterogeneity. We show that the method predicts the correct number of subgroups using simulated data, primary blood mononuclear cell, and pancreatic cell data. We applied our approach to a collection of single-cell tumor samples and found two qualitatively distinct classes of cell-type heterogeneity in cancer microenvironments.

Sensitive Quantitative Proteomics of Human Hematopoietic Stem and Progenitor Cells by Data-independent Acquisition Mass Spectrometry

Physiological processes in multicellular organisms depend on the function and interactions of specialized cell types operating in context. Some of these cell types are rare and thus obtainable only in minute quantities. For example, tissue-specific stem and progenitor cells are numerically scarce, but functionally highly relevant, and fulfill critical roles in development, tissue maintenance, and disease. Whereas low numbers of cells are routinely analyzed by genomics and transcriptomics, corresponding proteomic analyses have so far not been possible due to methodological limitations. Here we describe a sensitive and robust quantitative technique based on data-independent acquisition mass spectrometry. We quantified the proteome of sets of 25,000 human hematopoietic stem/multipotent progenitor cells (HSC/MPP) and three committed progenitor cell subpopulations of the myeloid differentiation pathway (common myeloid progenitors, megakaryocyte-erythrocyte progenitors, and granulocyte-macrophage progenitors), isolated by fluorescence-activated cell sorting from five healthy donors. On average, 5,851 protein groups were identified per sample. A subset of 4,131 stringently filtered protein groups was quantitatively compared across the 20 samples, defining unique signatures for each subpopulation. A comparison of proteomic and transcriptomic profiles indicated HSC/MPP-specific divergent regulation of biochemical functions such as telomerase maintenance and quiescence-inducing enzymes, including isocitrate dehydrogenases. These are essential for maintaining stemness and were detected at proteome, but not transcriptome, level. The method is equally applicable to almost any rare cell type, including healthy and cancer stem cells or physiologically and pathologically infiltrating cell populations. It thus provides essential new information toward the detailed biochemical understanding of cell development and functionality in health and disease.

The Unmixing Problem: A Guide to Applying Single-Cell RNA Sequencing to Bone

Bone is composed of a complex mixture of many dynamic cell types. Flow cytometry and in vivo lineage tracing have offered early progress toward deconvoluting this heterogeneous mixture of cells into functionally well-defined populations suitable for further studies. Single-cell sequencing is poised as a key complementary technique to better understand the cellular basis of bone metabolism and development. However, single-cell sequencing approaches still have important limitations, including transcriptional effects of cell isolation and sparse sampling of the transcriptome, that must be considered during experimental design and analysis to harness the power of this approach. Accounting for these limitations requires a deep knowledge of the tissue under study. Therefore, with the emergence of accessible tools for conducting and analyzing single-cell RNA sequencing (scRNA-seq) experiments, bone biologists will be ideal leaders in the application of scRNA-seq to the skeleton. Here we provide an overview of the steps involved with a single-cell sequencing analysis of bone, focusing on practical considerations needed for a successful study. © 2019 American Society for Bone and Mineral Research.

The single-cell sequencing: new developments and medical applications

Single-cell sequencing technologies can be used to detect the genome, transcriptome and other multi-omics of single cells. They can show the differences and evolutionary relationships of various cells. This review introduces the latest advances in single-cell sequencing technologies and their applications in oncology, microbiology, neurology, reproduction, immunology, digestive and urinary systems, highlighting the important role that single-cell sequencing techniques play in these areas.

Divide and conquer: A perspective on biochips for single-cell and rare-molecule analysis by next-generation sequencing

Recent advances in biochip technologies that connect next-generation sequencing (NGS) to real-world problems have facilitated breakthroughs in science and medicine. Because biochip technologies are themselves used in sequencing technologies, the main strengths of biochips lie in their scalability and throughput. Through the advantages of biochips, NGS has facilitated groundbreaking scientific discoveries and technical breakthroughs in medicine. However, all current NGS platforms require nucleic acids to be prepared in a certain range of concentrations, making it difficult to analyze biological systems of interest. In particular, many of the most interesting questions in biology and medicine, including single-cell and rare-molecule analysis, require strategic preparation of biological samples in order to be answered. Answering these questions is important because each cell is different and exists in a complex biological system. Therefore, biochip platforms for single-cell or rare-molecule analyses by NGS, which allow convenient preparation of nucleic acids from biological systems, have been developed. Utilizing the advantages of miniaturizing reaction volumes of biological samples, biochip technologies have been applied to diverse fields, from single-cell analysis to liquid biopsy. From this perspective, here, we first review current state-of-the-art biochip technologies, divided into two broad categories: microfluidic- and micromanipulation-based methods. Then, we provide insights into how future biochip systems will aid some of the most important biological and medical applications that require NGS. Based on current and future biochip technologies, we envision that NGS will come ever closer to solving more real-world scientific and medical problems.

Current best practices in single-cell RNA-seq analysis: a tutorial

Single-cell RNA-seq has enabled gene expression to be studied at an unprecedented resolution. The promise of this technology is attracting a growing user base for single-cell analysis methods. As more analysis tools are becoming available, it is becoming increasingly difficult to navigate this landscape and produce an up-to-date workflow to analyse one's data. Here, we detail the steps of a typical single-cell RNA-seq analysis, including pre-processing (quality control, normalization, data correction, feature selection, and dimensionality reduction) and cell- and gene-level downstream analysis. We formulate current best-practice recommendations for these steps based on independent comparison studies. We have integrated these best-practice recommendations into a workflow, which we apply to a public dataset to further illustrate how these steps work in practice. Our documented case study can be found at https://www.github.com/theislab/single-cell-tutorial This review will serve as a workflow tutorial for new entrants into the field, and help established users update their analysis pipelines.

JAK/STAT inhibition in macrophages promotes therapeutic resistance by inducing expression of protumorigenic factors

Tumor-associated macrophages contribute to tumor progression and therapeutic resistance in breast cancer. Within the tumor microenvironment, tumor-derived factors activate pathways that modulate macrophage function. Using in vitro and in vivo models, we find that tumor-derived factors induce activation of the Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) pathway in macrophages. We also demonstrate that loss of STAT3 in myeloid cells leads to enhanced mammary tumorigenesis. Further studies show that macrophages contribute to resistance of mammary tumors to the JAK/STAT inhibitor ruxolitinib in vivo and that ruxolitinib-treated macrophages produce soluble factors that promote resistance of tumor cells to JAK inhibition in vitro. Finally, we demonstrate that STAT3 deletion and JAK/STAT inhibition in macrophages increases expression of the protumorigenic factor cyclooxygenase-2 (COX-2), and that COX-2 inhibition enhances responsiveness of tumors to ruxolitinib. These findings define a mechanism through which macrophages promote therapeutic resistance and highlight the importance of understanding the impact of targeted therapies on the tumor microenvironment.

Mutual editing of alternative splicing between breast cancer cells and macrophages

Breast cancer is a highly heterogeneous disease and numerous secreted factors may differentially contribute to a macrophage phenotype whose extensive infiltration is generally regarded as indicative of an unfavorable outcome. How different breast tumor cells and macrophage cells interplay or influence each other on the alternative splicing (AS) level have not been characterized. Here, we exploited one previous study, which investigated the interplay between macrophages and estrogen receptor-positive (ER⁺) breast cancer and triple-negative breast cancer (TNBC) at the transcriptional level, to investigate the tumor-macrophage crosstalk at the AS level. In the present study, it was demonstrated that biological processes such as DNA damage and DNA repair were significantly affected both in ER⁺ breast cancer and TNBC by co-culturing with macrophages, whereas biological pathways altered in macrophages co-cultured with tumor cells depended on the breast cancer type. Specifically, biological processes altered in macrophages co-cultured with ER⁺ breast cancer were enriched in RNA processing and translation-related pathways whereas biological processes altered in macrophages co-cultured with TNBC were mainly enriched in protein transport pathways. We also analyzed the sequence features of skip exons among different conditions. In addition, putative splicing factors which were responsible for the altered AS profile in each condition were identified. The findings of the present study revealed significant tumor-macrophage crosstalk at the AS level which may facilitate the development of new therapeutic strategies for cancer.

Targeting the Tumor Microenvironment in Renal Cell Cancer Biology and Therapy

Renal cell cancer (RCC) is a highly vascularized and immunogenic tumor type. The inhibition of vessel formation by anti-angiogenic therapies, as well as the stimulation of the immune system by immunotherapy has revolutionized the therapeutic landscape of RCC in recent years. Nevertheless, both therapies are associated with therapy resistance due to a highly dynamic, adaptive and heterogeneous tumor microenvironment (TME). The aim of this short review article is to provide an overview of the components of the RCC TME as well as to discuss their contribution to disease progression. In addition, we report on preclinical and clinical findings and how the different TME components can be modulated to impede treatment progression as well as to overcome therapy resistance to anti-angiogenic or immunomodulating therapy concepts. Furthermore, we discuss the predictive and prognostic role of the TME in RCC therapy. We also report on the concept of combinational targeting of anti-angiogenic therapies and immune checkpoint inhibitor therapy, also including the latest results of clinical studies discussed at recent oncological meetings. Finally, promising new therapeutic targets within the TME are mentioned.

Heterogeneity and fate choice: T cell exhaustion in cancer and chronic infections

CD8 T cell differentiation is a tightly regulated process generating effector and memory T cells over the course of acute infections. In cancer and chronic infection, this differentiation program is derailed, and antigen-specific CD8 T cells differentiate to a hyporesponsive state generally referred to as T cell exhaustion. Here, we review recent findings on heterogeneity of tumor-specific T cells and exhausted T cells during chronic infections, discussing distinct differentiation state dynamics, fate choices, and functional states. Delineating the regulatory mechanisms defining distinct T cell states and determining the requirements for therapeutic reprogramming of these states will provide needed insights for the design of effective immunotherapies for the treatment of cancer and chronic infections.

Dissecting intratumoral myeloid cell plasticity by single cell RNA-seq

Tumor-infiltrating myeloid cells are the most abundant leukocyte population within tumors. Molecular cues from the tumor microenvironment promote the differentiation of immature myeloid cells toward an immunosuppressive phenotype. However, the in situ dynamics of the transcriptional reprogramming underlying this process are poorly understood. Therefore, we applied single cell RNA-seq (scRNA-seq) to computationally investigate the cellular composition and transcriptional dynamics of tumor and adjacent normal tissues from 4 early-stage non-small cell lung cancer (NSCLC) patients. Our scRNA-seq analyses identified 11 485 cells that varied in identity and gene expression traits between normal and tumor tissues. Among these, myeloid cell populations exhibited the most diverse changes between tumor and normal tissues, consistent with tumor-mediated reprogramming. Through trajectory analysis, we identified a differentiation path from CD14+ monocytes to M2 macrophages (monocyte-to-M2). This differentiation path was reproducible across patients, accompanied by increased expression of genes (eg, MRC1/CD206, MSR1/CD204, PPARG, TREM2) with significantly enriched functions (Oxidative phosphorylation and P53 pathway) and decreased expression of genes (eg, CXCL2, IL1B) with significantly enriched functions (TNF-α signaling via NF-κB and inflammatory response). Our analysis further identified a co-regulatory network implicating upstream transcription factors (JUN, NFKBIA) in monocyte-to-M2 differentiation, and activated ligand-receptor interactions (eg, SFTPA1-TLR2, ICAM1-ITGAM) suggesting intratumoral mechanisms whereby epithelial cells stimulate monocyte-to-M2 differentiation. Overall, our study identified the prevalent monocyte-to-M2 differentiation in NSCLC, accompanied by an intricate transcriptional reprogramming mediated by specific transcriptional activators and intercellular crosstalk involving ligand-receptor interactions.

Dean Flow Assisted Single Cell and Bead Encapsulation for High Performance Single Cell Expression Profiling

Droplet microfluidics-based platform (Drop-seq) has been shown to be a powerful tool for single cell expression profiling. Nevertheless, this platform required the simultaneous encapsulation of single cell and single barcoded bead, the incidence of which was very low, limiting its efficiency. Spiral channels were reported to focus the barcoded beads and thus increased the efficiency, but focusing of cells was not demonstrated, which could potentially further enhance the performance. Here, we designed spiral and serpentine channels to focus both bead and cell solutions and implemented this microfluidic design on Drop-seq. We characterized the effect of cell/bead concentration on encapsulation results and tested the performance by coencapsulating barcoded beads and human-mouse cell mixtures followed by sequencing. The results showed ∼300% and ∼40% increase in cell utilization rate compared to the traditional Drop-seq device and the device focusing beads alone, respectively. This chip design showed great potential for high efficiency single cell expression profiling.

Targeting the Interplay between Epithelial-to-Mesenchymal-Transition and the Immune System for Effective Immunotherapy

Over the last decade, both early diagnosis and targeted therapy have improved the survival rates of many cancer patients. Most recently, immunotherapy has revolutionized the treatment options for cancers such as melanoma. Unfortunately, a significant portion of cancers (including lung and breast cancers) do not respond to immunotherapy, and many of them develop resistance to chemotherapy. Molecular characterization of non-responsive cancers suggest that an embryonic program known as epithelial-mesenchymal transition (EMT), which is mostly latent in adults, can be activated under selective pressures, rendering these cancers resistant to chemo- and immunotherapies. EMT can also drive tumor metastases, which in turn also suppress the cancer-fighting activity of cytotoxic T cells that traffic into the tumor, causing immunotherapy to fail. In this review, we compare and contrast immunotherapy treatment options of non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC). We discuss why, despite breakthrough progress in immunotherapy, attaining predictable outcomes in the clinic is mostly an unsolved problem for these tumors. Although these two cancer types appear different based upon their tissues of origin and molecular classification, gene expression indicate that they possess many similarities. Patient tumors exhibit activation of EMT, and resulting stem cell properties in both these cancer types associate with metastasis and resistance to existing cancer therapies. In addition, the EMT transition in both these cancers plays a crucial role in immunosuppression, which exacerbates treatment resistance. To improve cancer-related survival we need to understand and circumvent, the mechanisms through which these tumors become therapy resistant. In this review, we discuss new information and complementary perspectives to inform combination treatment strategies to expand and improve the anti-tumor responses of currently available clinical immune checkpoint inhibitors.

Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression

PURPOSE

Cutaneous T-cell lymphomas (CTCL), encompassing a spectrum of T-cell lymphoproliferative disorders involving the skin, have collectively increased in incidence over the last 40 years. Sézary syndrome is an aggressive form of CTCL characterized by significant presence of malignant cells in both the blood and skin. The guarded prognosis for Sézary syndrome reflects a lack of reliably effective therapy, due, in part, to an incomplete understanding of disease pathogenesis.

EXPERIMENTAL DESIGN

Using single-cell sequencing of RNA and the machine-learning reverse graph embedding approach in the Monocle package, we defined a model featuring distinct transcriptomic states within Sézary syndrome. Gene expression used to differentiate the unique transcriptional states were further used to develop a boosted tree classification for early versus late CTCL disease.

RESULTS

Our analysis showed the involvement of FOXP3 + malignant T cells during clonal evolution, transitioning from FOXP3 + T cells to GATA3 + or IKZF2 + (HELIOS) tumor cells. Transcriptomic diversities in a clonal tumor can be used to predict disease stage, and we were able to characterize a gene signature that predicts disease stage with close to 80% accuracy. FOXP3 was found to be the most important factor to predict early disease in CTCL, along with another 19 genes used to predict CTCL stage.

CONCLUSIONS

This work offers insight into the heterogeneity of Sézary syndrome, providing better understanding of the transcriptomic diversities within a clonal tumor. This transcriptional heterogeneity can predict tumor stage and thereby offer guidance for therapy.

Droplet-based single cell RNAseq tools: a practical guide

Droplet based scRNA-seq systems such as Drop-seq, inDrop and Chromium 10X have been the catalyst for the wide adoption of high-throughput scRNA-seq technologies in the research laboratory. In order to understand the capabilities of these systems to deeply interrogate biology; here we provide a practical guide through all the steps involved in a typical scRNA-seq experiment. Through comparing and contrasting these three main droplet based systems (and their derivatives), we provide an overview of all critical considerations in obtaining high quality and biologically relevant data. We also discuss the limitations of these systems and how they fit into the emerging field of Genomic Cytometry.

The B-side of Cancer Immunity: The Underrated Tune

Tumor-infiltrating lymphocytes are known to be critical in controlling tumor progression. While the role of T lymphocytes has been extensively studied, the function of B cells in this context is still ill-defined. In this review, we propose to explore the role of B cells in tumor immunity. First of all we define their dual role in promoting and inhibiting cancer progression depending on their phenotype. To continue, we describe the influence of different tumor microenvironment factors such as hypoxia on B cells functions and differentiation. Finally, the role of B cells in response to therapy and as potential target is examined. In accordance with the importance of B cells in immuno-oncology, we conclude that more studies are required to throw light on the precise role of B cells in the tumor microenvironment in order to have a better understanding of their functions, and to design new strategies that efficiently target these cells by immunotherapy.

The emergent landscape of the mouse gut endoderm at single-cell resolution

Here we delineate the ontogeny of the mammalian endoderm by generating 112,217 single-cell transcriptomes, which represent all endoderm populations within the mouse embryo until midgestation. We use graph-based approaches to model differentiating cells, which provides a spatio-temporal characterization of developmental trajectories and defines the transcriptional architecture that accompanies the emergence of the first (primitive or extra-embryonic) endodermal population and its sister pluripotent (embryonic) epiblast lineage. We uncover a relationship between descendants of these two lineages, in which epiblast cells differentiate into endoderm at two distinct time points-before and during gastrulation. Trajectories of endoderm cells were mapped as they acquired embryonic versus extra-embryonic fates and as they spatially converged within the nascent gut endoderm, which revealed these cells to be globally similar but retain aspects of their lineage history. We observed the regionalized identity of cells along the anterior-posterior axis of the emergent gut tube, which reflects their embryonic or extra-embryonic origin, and the coordinated patterning of these cells into organ-specific territories.

Single-cell transcriptomic landscape of nucleated cells in umbilical cord blood

BACKGROUND

For both pediatric and adult patients, umbilical cord blood (UCB) transplant is a therapeutic option for a variety of hematologic diseases, such as blood cancers, myeloproliferative disorders, genetic diseases, and metabolic disorders. However, the level of cellular heterogeneity and diversity of nucleated cells in UCB has not yet been assessed in an unbiased and systemic fashion. In the present study, nucleated cells from UCB were subjected to single-cell RNA sequencing to simultaneously profile the gene expression signatures of thousands of cells, generating a rich resource for further functional studies. Here, we report the transcriptomes of 17,637 UCB cells, covering 12 major cell types, many of which can be further divided into distinct subpopulations.

RESULTS

Pseudotemporal ordering of nucleated red blood cells identifies wave-like activation and suppression of transcription regulators, leading to a polarized cellular state, which may reflect nucleated red blood cell maturation. Progenitor cells in UCB also comprise 2 subpopulations with activation of divergent transcription programs, leading to specific cell fate commitment. Detailed profiling of cytotoxic cell populations unveiled granzymes B and K signatures in natural killer and natural killer T-cell types in UCB.

CONCLUSIONS

Taken together, our data form a comprehensive single-cell transcriptomic landscape that reveals previously unrecognized cell types, pathways, and mechanisms of gene expression regulation. These data may contribute to the efficacy and outcome of UCB transplant, broadening the scope of research and clinical innovations.

Tumor derived EDIL3 modulates the expansion and osteoclastogenesis of myeloid derived suppressor cells in murine breast cancer model

Epidermal growth factor-like repeats and discoidin I like domain 3 (EDIL3) is an integrin ligand which is implicated in bone metabolism and bone marrow myelopoiesis. Recently, myeloid derived suppressor cells (MDSCs) as osteoclast progenitor have been demonstrated in several kinds of cancers including breast cancer. In this paper we explored the association between tumor derived EDIL3 and MDSCs in a murine breast cancer model. Knockdown of EDIL3 in MDA-MB-231 breast cancer cells inhibited the expansion of tumor induced MDSCs in bone marrow. However, generation of bone marrow derived MDSCs in vitro was not affected by recombinant EDIL3. Osteoclastogenesis of MDSCs was dose-dependently inhibited by recombinant EDIL3 in vitro via binding to Mac-1 but not LFA-1. Moreover, in accordance with previous studies, our data showed that tumor derived EDIL3 was involved in tumor associated bone loss. The convoluted effects of EDIL3 on MDSCs compose a potential mechanism hired by tumor cells for perpetration approximately.

Immune contexture defined by single cell technology for prognosis prediction and immunotherapy guidance in cancer

Tumor immune microenvironment is closely related to tumor initiation, prognosis, and response to immunotherapy. The immune landscapes, number of infiltrating immune cells, and the localization of lymphocytes in the tumor vary in across different types of tumors. The immune contexture in cancer, which is determined by the density, composition, functional state and organization of the leukocyte infiltrate of the tumor, can yield information relevant to the prediction of treatment response and patients’ prognosis. Better understanding of the immune atlas in human tumors have been achieved with the development and application of single-cell analysis technology, which has provided a reference for prognosis, and insights on new targets for immunotherapy. In this review, we summarized the different characteristics of immune contexture in cancer defined by a variety of single-cell techniques, which have enhanced our understanding on the pathophysiology of the tumor microenvironment. We believe that there are much more to be uncovered in this rapidly developing field of medicine, and they will predict the prognosis of cancer patients and guide the rational design of immunotherapies for success in cancer eradication.

Deciphering Macrophage and Monocyte Code to Stratify Human Breast Cancer Patients

In this issue of Cancer Cell, Cassetta et al. present a detailed analysis of the transcriptional profile imprinted on monocytes and macrophages by human breast and endometrial cancers, proposing SIGLEC1 and CCL8 as novel biomarkers in tumor-associated macrophages for breast cancer patient stratification and prognosis.

A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer

Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor cell composition, including phenotypic abnormalities and phenotype dominance. Relationship analyses between tumor and immune cells revealed characteristics of ecosystems related to immunosuppression and poor prognosis. High frequencies of PD-L1⁺ tumor-associated macrophages and exhausted T cells were found in high-grade ER⁺ and ER^- tumors. This large-scale, single-cell atlas deepens our understanding of breast tumor ecosystems and suggests that ecosystem-based patient classification will facilitate identification of individuals for precision medicine approaches targeting the tumor and its immunoenvironment.

Immune checkpoint modulators in cancer immunotherapy: Recent advances and combination rationales

As a new hallmark of cancer, immune surveillance evading plays a critical role in carcinogenesis. Through modulating the immune checkpoints, immune cells in tumor microenvironment can be harnessed to battle cancer cells. In recent years, the administration of anti-CTLA or/and anti-PD-1/L1 antibody has exhibited unexpected antitumor effect in multiple types of cancer, motivating the researchers to find more potential immune checkpoints as clinical targets. A wealth of clinical trials have been done to evaluate the safety and efficacy of monotherapy or combination therapy with immune checkpoint modulators. However, there still exist problems such as low response rate and adverse events in the clinical, which in turn leads us to the basic study. The better understanding of the crosstalk between the immune cells and the cancer cells within the microenvironment may inspire us new ideas for cancer treatment. In this review, we mainly summarize the recent advances in application of immune checkpoint modulators and the combination rationales, and discuss the problems existing in the precision therapy with immune checkpoint modulators.

Unleashing Type-2 Dendritic Cells to Drive Protective Antitumor CD4+ T Cell Immunity

Differentiation of proinflammatory CD4⁺ conventional T cells (T_conv) is critical for productive antitumor responses yet their elicitation remains poorly understood. We comprehensively characterized myeloid cells in tumor draining lymph nodes (tdLN) of mice and identified two subsets of conventional type-2 dendritic cells (cDC2) that traffic from tumor to tdLN and present tumor-derived antigens to CD4⁺ T_conv, but then fail to support antitumor CD4⁺ T_conv differentiation. Regulatory T cell (T_reg) depletion enhanced their capacity to elicit strong CD4⁺ T_conv responses and ensuing antitumor protection. Analogous cDC2 populations were identified in patients, and as in mice, their abundance relative to T_reg predicts protective ICOS⁺ PD-1^lo CD4⁺ T_conv phenotypes and survival. Further, in melanoma patients with low T_reg abundance, intratumoral cDC2 density alone correlates with abundant CD4⁺ T_conv and with responsiveness to anti-PD-1 therapy. Together, this highlights a pathway that restrains cDC2 and whose reversal enhances CD4⁺ T_conv abundance and controls tumor growth.

Quantifying in situ adaptive immune cell cognate interactions in humans

Two-photon excitation microscopy (TPEM) has revolutionized the understanding of adaptive immunity. However, TPEM usually requires animal models and is not amenable to the study of human disease. The recognition of antigen by T cells requires cell contact and is associated with changes in T cell shape. We postulated that by capturing these features in fixed tissue samples, we could quantify in situ adaptive immunity. Therefore, we used a deep convolutional neural network to identify fundamental distance and cell-shape features associated with cognate help (cell-distance mapping (CDM)). In mice, CDM was comparable to TPEM in discriminating cognate T cell-dendritic cell (DC) interactions from non-cognate T cell-DC interactions. In human lupus nephritis, CDM confirmed that myeloid DCs present antigen to CD4+ T cells and identified plasmacytoid DCs as an important antigen-presenting cell. These data reveal a new approach with which to study human in situ adaptive immunity broadly applicable to autoimmunity, infection, and cancer.

Characterization of cell fate probabilities in single-cell data with Palantir

Single-cell RNA sequencing studies of differentiating systems have raised fundamental questions regarding the discrete versus continuous nature of both differentiation and cell fate. Here we present Palantir, an algorithm that models trajectories of differentiating cells by treating cell fate as a probabilistic process and leverages entropy to measure cell plasticity along the trajectory. Palantir generates a high-resolution pseudo-time ordering of cells and, for each cell state, assigns a probability of differentiating into each terminal state. We apply our algorithm to human bone marrow single-cell RNA sequencing data and detect important landmarks of hematopoietic differentiation. Palantir's resolution enables the identification of key transcription factors that drive lineage fate choice and closely track when cells lose plasticity. We show that Palantir outperforms existing algorithms in identifying cell lineages and recapitulating gene expression trends during differentiation, is generalizable to diverse tissue types, and is well-suited to resolving less-studied differentiating systems.

Dissecting CLL through high-dimensional single-cell technologies

We now have the potential to undertake detailed analysis of the inner workings of thousands of cancer cells, one cell at a time, through the emergence of a range of techniques that probe the genome, transcriptome, and proteome combined with the development of bioinformatics pipelines that enable their interpretation. This provides an unprecedented opportunity to better understand the heterogeneity of chronic lymphocytic leukemia and how mutations, activation states, and protein expression at the single-cell level have an impact on disease course, response to treatment, and outcomes. Herein, we review the emerging application of these new techniques to chronic lymphocytic leukemia and examine the insights already attained through this transformative technology.

Negative Co-stimulation Constrains T Cell Differentiation by Imposing Boundaries on Possible Cell States

Co-stimulation regulates T cell activation, but it remains unclear whether co-stimulatory pathways also control T cell differentiation. We used mass cytometry to profile T cells generated in the genetic absence of the negative co-stimulatory molecules CTLA-4 and PD-1. Our data indicate that negative co-stimulation constrains the possible cell states that peripheral T cells can acquire. CTLA-4 imposes major boundaries on CD4⁺ T cell phenotypes, whereas PD-1 subtly limits CD8⁺ T cell phenotypes. By computationally reconstructing T cell differentiation paths, we identified protein expression changes that underlied the abnormal phenotypic expansion and pinpointed when lineage choice events occurred during differentiation. Similar alterations in T cell phenotypes were observed after anti-CTLA-4 and anti-PD-1 antibody blockade. These findings implicate negative co-stimulation as a key regulator and determinant of T cell differentiation and suggest that checkpoint blockade might work in part by altering the limits of T cell phenotypes.

Preferential Infiltration of Unique Vγ9Jγ2-Vδ2 T Cells Into Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is clinically highly aggressive as a result of evolutionary dynamics induced by cross-talk between cancer cells and a heterogeneous group of immune cells in tumor microenvironment. The brain harbors limited numbers of immune cells with few lymphocytes and macrophages; thus, innate-like lymphocytes, such as γδ T cells, have important roles in antitumor immunity. Here, we characterized GBM-infiltrating γδ T cells, which may have roles in regulating the GBM tumor microenvironment and cancer cell gene expression. V(D)J repertoires of tumor-infiltrating and blood-circulating γδ T cells from four patients were analyzed by next-generation sequencing-based T-cell receptor (TCR) sequencing in addition to mutation and immune profiles in four GBM cases. In all tumor tissues, abundant innate and effector/memory lymphocytes were detected, accompanied by large numbers of tumor-associated macrophages and closely located tumor-infiltrating γδ T cells, which appear to have anti-tumor activity. The immune-related gene expression analysis using the TCGA database showed that the signature gene expression extent of γδ T cells were more associated with those of cytotoxic T and Th1 cells and M1 macrophages than those of Th2 cells and M2 macrophages. Although the most abundant γδ T cells were Vγ9Vδ2 T cells in both tumor tissues and blood, the repertoire of intratumoral Vγ9Vδ2 T cells was distinct from that of peripheral blood Vγ9Vδ2 T cells and was dominated by Vγ9Jγ2 sequences, not by canonical Vγ9JγP sequences that are mostly commonly found in blood γδ T cells. Collectively, unique GBM-specific TCR clonotypes were identified by comparing TCR repertoires of peripheral blood and intra-tumoral γδ T cells. These findings will be helpful for the elucidation of tumor-specific antigens and development of anticancer immunotherapies using tumor-infiltrating γδ T cells.

MicroRNA-155 coordinates the immunological landscape within murine melanoma and correlates with immunity in human cancers

miR-155 has recently emerged as an important promoter of antitumor immunity through its functions in T lymphocytes. However, the impact of T cell-expressed miR-155 on immune cell dynamics in solid tumors remains unclear. In the present study, we used single-cell RNA sequencing to define the CD45+ immune cell populations at different time points within B16F10 murine melanoma tumors growing in either wild-type or miR-155 T cell conditional knockout (TCKO) mice. miR-155 was required for optimal T cell activation and reinforced the T cell response at the expense of infiltrating myeloid cells. Further, myeloid cells from tumors growing in TCKO mice were defined by an increase in wound healing genes and a decreased IFN-γ-response gene signature. Finally, we found that miR-155 expression predicted a favorable outcome in human melanoma patients and was associated with a strong immune signature. Moreover, gene expression analysis of The Cancer Genome Atlas (TCGA) data revealed that miR-155 expression also correlates with an immune-enriched subtype in 29 other human solid tumors. Together, our study provides an unprecedented analysis of the cell types and gene expression signatures of immune cells within experimental melanoma tumors and elucidates the role of miR-155 in coordinating antitumor immune responses in mammalian tumors.

Revolutionizing immunology with single-cell RNA sequencing

The immune system is composed of a complex hierarchy of cell types that protect the organism against disease and maintain homeostasis. Identifying heterogeneity of immune cells is the key to understanding the immune system. Advanced single-cell RNA sequencing (scRNA-seq) technologies are revolutionizing our ability to study immunology. By measuring transcriptomes at the single-cell level, scRNA-seq enables identification of cellular heterogeneity in far greater detail than conventional methods. In this review, we introduce the existing scRNA-seq technologies and present their strengths and weaknesses. We also discuss potential applications and future innovations of scRNA-seq in immunology.

New tools for pathology: a user's review of a highly multiplexed method for in situ analysis of protein and RNA expression in tissue

Tumor cell heterogeneity and tumor cell-stromal interactions are being explored as determinants of disease progression and treatment resistance in solid tumor and hematological malignancies. As such, tools simultaneously capable of highly multiplexed profiling of tissues' protein and RNA content, as well as interrogation of rare or single cells, are required to precisely characterize constituent tumor cell populations, infiltrating lymphocytes and stromal elements. Access to spatial relationships will enable more precise characterization of tumors, support patient stratification and may help to identify novel drug targets. Multiple platforms are being developed to address these critical unmet needs. The NanoString digital spatial profiling (DSP) platform enables highly multiplexed, spatial assessment of protein and/or RNA targets in tissues by detecting oligonucleotide barcodes conjugated via a photocleavable linker to primary antibodies or nucleic acid probes. Although this platform enables high-dimensional spatial interrogation of tissue protein and RNA expression, a detailed understanding of its composition, function and chemistry is advisable to guide experimental design and data interpretation. The purpose of this review is to provide an independent, comprehensive description of the DSP technology, including an overview of NanoString's capture and antibody barcode conjugation chemistries, experimental workflow, data output and analysis methods. The DSP technology will be discussed in the context of other highly multiplexed immunohistochemistry methods, including imaging mass cytometry and multiplexed ion beam imaging, to inform potential users of the advantages and limitations of each. Additional issues such as preanalytical variability, sampling and specimen adequacy will be considered with respect to the platforms to inform potential experimental design. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Reactive oxygen species modulate macrophage immunosuppressive phenotype through the up-regulation of PD-L1

The combination of immune checkpoint blockade with chemotherapy is currently under investigation as a promising strategy for the treatment of triple negative breast cancer (TNBC). Tumor-associated macrophages (TAMs) are the most prominent component of the breast cancer microenvironment because they influence tumor progression and the response to therapies. Here we show that macrophages acquire an immunosuppressive phenotype and increase the expression of programmed death ligand-1 (PD-L1) when treated with reactive oxygen species (ROS) inducers such as the glutathione synthesis inhibitor, buthionine sulphoximine (BSO), and paclitaxel. Mechanistically, these agents cause accumulation of ROS that in turn activate NF-κB signaling to promote PD-L1 transcription and the release of immunosuppressive chemokines. Systemic in vivo administration of paclitaxel promotes PD-L1 accumulation on the surface of TAMS in a mouse model of TNBC, consistent with in vitro results. Combinatorial treatment with paclitaxel and an anti-mouse PD-L1 blocking antibody significantly improved the therapeutic efficacy of paclitaxel by reducing tumor burden and increasing the number of tumor-associated cytotoxic T cells. Our results provide a strong rationale for the use of anti-PD-L1 blockade in the treatment of TNBC patients. Furthermore, interrogation of chemotherapy-induced PD-L1 expression in TAMs is warranted to define appropriate patient selection in the use of PD-L1 blockade.

Lymphocyte innateness defined by transcriptional states reflects a balance between proliferation and effector functions

How innate T cells (ITC), including invariant natural killer T (iNKT) cells, mucosal-associated invariant T (MAIT) cells, and γδ T cells, maintain a poised effector state has been unclear. Here we address this question using low-input and single-cell RNA-seq of human lymphocyte populations. Unbiased transcriptomic analyses uncover a continuous ‘innateness gradient’, with adaptive T cells at one end, followed by MAIT, iNKT, γδ T and natural killer cells at the other end. Single-cell RNA-seq reveals four broad states of innateness, and heterogeneity within canonical innate and adaptive populations. Transcriptional and functional data show that innateness is characterized by pre-formed mRNA encoding effector functions, but impaired proliferation marked by decreased baseline expression of ribosomal genes. Together, our data shed new light on the poised state of ITC, in which innateness is defined by a transcriptionally-orchestrated trade-off between rapid cell growth and rapid effector function.

Innate T cells (ITC) contain many subsets and are poised to promptly respond to antigens and pathogens, but how this poised state is maintained is still unclear. Here the authors perform single-cell RNA-seq to align the various ITC subsets along an ‘innateness gradient’ that is associated with changes in proliferation and effector functions.

High-Throughput Automated Single-Cell Imaging Analysis Reveals Dynamics of Glioblastoma Stem Cell Population During State Transition

Cancer stem cells (CSCs) are a heterogeneous and dynamic self-renewing population that stands at the top of tumor cellular hierarchy and contribute to tumor recurrence and therapeutic resistance. As methods of CSC isolation and functional interrogation advance, there is a need for a reliable and accessible quantitative approach to assess heterogeneity and state transition dynamics in CSCs. We developed a high-throughput automated single cell imaging analysis (HASCIA) approach for the quantitative assessment of protein expression with single-cell resolution and applied the method to investigate spatiotemporal factors that influence CSC state transition using glioblastoma (GBM) CSCs (GSCs) as a model system. We were able to validate the quantitative nature of this approach through comparison of the protein expression levels determined by HASCIA to those determined by immunoblotting. A virtue of HASCIA was exemplified by detection of a subpopulation of SOX2-low cells, which expanded in fraction size during state transition. HASCIA also revealed that GSCs were committed to loose stem cell state at an earlier time point than the average SOX2 level decreased. Functional assessment of stem cell frequency in combination with the quantification of SOX2 expression by HASCIA defined a stable cutoff of SOX2 expression level for stem cell state. We also developed an approach to assess local cell density and found that denser monolayer areas possess higher average levels of SOX2, higher cell diversity, and a presence of a sub-population of slowly proliferating SOX2-low GSCs. HASCIA is an open source software that facilitates understanding the dynamics of heterogeneous cell population such as that of GSCs and their progeny. It is a powerful and easy-to-use image analysis and statistical analysis tool available at https://hascia.lerner.ccf.org. © 2019 International Society for Advancement of Cytometry.

Revolutionizing Cancer Immunology: The Power of Next-Generation Sequencing Technologies

It has long been appreciated that tumors are diverse, varying in mutational status, composition of cellular infiltrate, and organizational architecture. For the most part, the information embedded in this diversity has gone untapped due to the limited resolution and dimensionality of assays for analyzing nucleic acid expression in cells. The advent of high-throughput, next-generation sequencing (NGS) technologies that measure nucleic acids, particularly at the single-cell level, is fueling the characterization of the many components that comprise the tumor microenvironment (TME), with a strong focus on immune composition. Understanding the immune and nonimmune components of the TME, how they interact, and how this shapes their functional properties requires the development of novel computational methods and, eventually, the application of systems-based approaches. The continued development and application of NGS technologies holds great promise for accelerating discovery in the cancer immunology field.

Emerging approaches to study cell-cell interactions in tumor microenvironment

Cell-cell interactions are of crucial importance for tissue formation, homeostasis, regeneration processes, and immune response. Recent studies underlined contribution of cell-cell interaction in tumor microenvironment (TME) for tumor progression and metastasis. Cancer cells modify the host cells to tumor-supportive traits, and the modified host cells contribute to tumor progression by interacting with cancer cells and further modifying other normal cells. However, the complex interaction networks of cancer cells and host cells remained largely unknown. Recent advances in high throughput microscopy and single cells-based molecular analyses have unlocked a new era for studying cell-cell interactions in the complex tissue microenvironment at the resolution of a single cell. Here, we review various model systems and emerging experimental approaches that are used to study cell-cell interactions focusing on the studies of TME. We discuss strengths and weaknesses of each model system and each experimental approach, and how upcoming approaches can solve current fundamental questions of cell-cell interactions in TME.

The Myeloid Cell Compartment-Cell by Cell

Myeloid cells are a major cellular compartment of the immune system comprising monocytes, dendritic cells, tissue macrophages, and granulocytes. Models of cellular ontogeny, activation, differentiation, and tissue-specific functions of myeloid cells have been revisited during the last years with surprising results; for example, most tissue macrophages are yolk sac derived, monocytes and macrophages follow a multidimensional model of activation, and tissue signals have a significant impact on the functionality of all these cells. While these exciting results have brought these cells back to center stage, their enormous plasticity and heterogeneity, during both homeostasis and disease, are far from understood. At the same time, the ongoing revolution in single-cell genomics, with single-cell RNA sequencing (scRNA-seq) leading the way, promises to change this. Prevailing models of hematopoiesis with distinct intermediates are challenged by scRNA-seq data suggesting more continuous developmental trajectories in the myeloid cell compartment. Cell subset structures previously defined by protein marker expression need to be revised based on unbiased analyses of scRNA-seq data. Particularly in inflammatory conditions, myeloid cells exhibit substantially vaster heterogeneity than previously anticipated, and work performed within large international projects, such as the Human Cell Atlas, has already revealed novel tissue macrophage subsets. Based on these exciting developments, we propose the next steps to a full understanding of the myeloid cell compartment in health and diseases.

Extensive exploration of T cell heterogeneity in cancers by single cell sequencing

Human T cells are a highly heterogeneous population and can recognize a wide variety of antigens by their T cell receptors (TCRs). Tumor cells display a large repertoire of antigens that serve as potential targets for recognition, thus making T cells in the tumor micro-environment more complicated. Making a connection between TCRs and the transcriptional information of individual T cells will be interesting for investigating clonal expansion within T cell populations under pathologic conditions. Advances in single cell RNA-sequencing (scRNA-seq) have allowed for comprehensive analysis of T cells. In this review, we briefly describe the research progress on tumor micro-environment T cells using single cell RNA sequencing, and then discuss how scRNA-seq can be used to resolve immune system heterogeneity in health and disease. Finally, we point out future directions in this field and potential for immunotherapy.

The molecular landscape of glioma in patients with Neurofibromatosis 1

Neurofibromatosis type 1 (NF1) is a common tumor predisposition syndrome in which glioma is one of the prevalent tumors. Gliomagenesis in NF1 results in a heterogeneous spectrum of low- to high-grade neoplasms occurring during the entire lifespan of patients. The pattern of genetic and epigenetic alterations of glioma that develops in NF1 patients and the similarities with sporadic glioma remain unknown. Here, we present the molecular landscape of low- and high-grade gliomas in patients affected by NF1 (NF1-glioma). We found that the predisposing germline mutation of the NF1 gene was frequently converted to homozygosity and the somatic mutational load of NF1-glioma was influenced by age and grade. High-grade tumors harbored genetic alterations of TP53 and CDKN2A, frequent mutations of ATRX associated with Alternative Lengthening of Telomere, and were enriched in genetic alterations of transcription/chromatin regulation and PI3 kinase pathways. Low-grade tumors exhibited fewer mutations that were over-represented in genes of the MAP kinase pathway. Approximately 50% of low-grade NF1-gliomas displayed an immune signature, T lymphocyte infiltrates, and increased neo-antigen load. DNA methylation assigned NF1-glioma to LGm6, a poorly defined Isocitrate Dehydrogenase 1 wild-type subgroup enriched with ATRX mutations. Thus, the profiling of NF1-glioma defined a distinct landscape that recapitulates a subset of sporadic tumors.

Novel and Alternative Targets Against Breast Cancer Stemness to Combat Chemoresistance

Breast cancer stem cells (BCSCs) play a vital role in tumor progression and metastasis. They are heterogeneous and inherently radio- and chemoresistant. They have the ability to self-renew and differentiate into non-BCSCs. These determinants of BCSCs including the plasticity between the mesenchymal and epithelial phenotypes often leads to minimal residual disease (MRD), tumor relapse, and therapy failure. By studying the resistance mechanisms in BCSCs, a combinatorial therapy can be formulated to co-target BCSCs and bulk tumor cells. This review addresses breast cancer stemness and molecular underpinnings of how the cancer stemness can lead to pharmacological resistance. This might occur through rewiring of signaling pathways and modulated expression of various targets that support survival and self-renewal, clonogenicity, and multi-lineage differentiation into heterogeneous bulk tumor cells following chemotherapy. We explore emerging novel and alternative molecular targets against BC stemness and chemoresistance involving survival, drug efflux, metabolism, proliferation, cell migration, invasion, and metastasis. Strategic targeting of such vulnerabilities in BCSCs may overcome the chemoresistance and increase the longevity of the metastatic breast cancer patients.

Vascular-endothelial response to IDH1 mutant fibrosarcoma secretome and metabolite: implications on cancer microenvironment

Isocitrate dehydrogenases (IDHs) are enzymes involved in the production of α-ketoglutarate (αkg) in normal cellular metabolism. Cells with IDH mutations reduce αkg to 2-hydroxyglutarate (2HG), an oncometabolite, and 2HG directly transforms normal cells to malignant cells through histone demethylation and epigenetic dysregulation. However, whether IDH mutations affect cancer stromal cells is elusive, and little is known whether 2HG may impact the tumor microenvironment. We hypothesized that the IDH mutant cancer secretome and metabolites would stimulate primitive vascular-endothelial genesis. The secretome of IDH1 mutant human fibrosarcoma cells was harvested following medium starvation and was used to treat vascular-endothelial cells using a tube formation assay. GSK864, an allosteric IDH1 inhibitor, was supplemented to the fibrosarcoma secretome to determine its effects on vascular-endothelial tube formation. Exogenous 2HG or as supplemented in the GSK864-treated secretome was applied to further induce vascular-endothelial perturbation. Total vascular-endothelial tube lengths were quantified using NIH/Image J. Two-sided Student's t-tests and Mann-Whitney U tests were used for statistical analysis. The IDH1 mutant fibrosarcoma secretome stimulated vascular-endothelial tube formation by ~138% relative to control. Remarkably, GSK864 attenuated vascular-endothelial tube formation by ~36%, but 2HG not only reversed GSK864 attenuation of tube formation, but also significantly stimulated vascular-endothelial tubes in the GSK864-treated fibrosarcoma secretome. Importantly, 2HG alone augmented vascular-endothelial tube formation that was equivalent to the fibrosarcoma secretome. Thus, 2HG stimulates vascular-endothelial genesis in conjunction with the fibrosarcoma secretome, despite pre-emptive inhibition of IDH1 mutation with GSK864, suggesting that 2HG enables oncogenic angiogenesis via paracrine signaling. Stimulation of vascular-endothelial genesis by 2HG alone, independent of the cancer secretome, suggests that 2HG also activates oncogenic angiogenic pathways in cancer stromal cells. Thus, the IDH mutant cancer secretome stimulates primitive oncogenic angiogenesis through 2HG and/or paracrine pathways. Taken together, these findings suggest novel mechanisms by which the IDH mutant cancer secretome and/or metabolite, specifically 2HG, interacts with the tumor microenvironment by inducing oncogenic angiogenesis in favor of metastasis.

Single-Cell Ssequencing in Cancer: Recent Applications to Immunogenomics and Multi-omics Tools

Tumor heterogeneity, the cellular mosaic of multiple lineages arising from the process of clonal evolution, has continued to thwart multi-omics analyses using traditional bulk sequencing methods. The application of single-cell sequencing, in concert with existing genomics methods, has enabled high-resolution interrogation of the genome, transcriptome, epigenome, and proteome. Applied to cancers, these single-cell multi-omics methods bypass previous limitations on data resolution and have enabled a more nuanced understanding of the evolutionary dynamics of tumor progression, immune evasion, metastasis, and treatment resistance. This review details the growing number of novel single-cell multi-omics methods applied to tumors and further discusses recent discoveries emerging from these approaches, especially in regard to immunotherapy.

Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma

Tumor immune cell compositions play a major role in response to immunotherapy, but the heterogeneity and dynamics of immune infiltrates in human cancer lesions remain poorly characterized. Here, we identify conserved intratumoral CD4 and CD8 T cell behaviors in scRNA-seq data from 25 melanoma patients. We discover a large population of CD8 T cells showing continuous progression from an early effector "transitional" into a dysfunctional T cell state. CD8 T cells that express a complete cytotoxic gene set are rare, and TCR sharing data suggest their independence from the transitional and dysfunctional cell states. Notably, we demonstrate that dysfunctional T cells are the major intratumoral proliferating immune cell compartment and that the intensity of the dysfunctional signature is associated with tumor reactivity. Our data demonstrate that CD8 T cells previously defined as exhausted are in fact a highly proliferating, clonal, and dynamically differentiating cell population within the human tumor microenvironment.

Cancer research in the era of immunogenomics

The most meaningful advancement in cancer treatment in recent years has been the emergence of immunotherapy. Checkpoint inhibitor blockade and adoptive T cell therapy have shown remarkable clinical effects in a wide range of tumour types. Despite these advances, many tumours do not respond to these treatments, which raises the need to further investigate how patients can benefit from immunotherapy. This effort can now take advantage of the recent technological progress in single-cell, high-throughput sequencing and computational efforts. In this review, we will discuss advances in different immunotherapies and the principles of cancer immunogenomics, with an emphasis on the detection of cancer neoantigens with human leucocyte antigen peptidomics, and how these principles can be further used for more efficient clinical output.

Organoid Modeling of the Tumor Immune Microenvironment

In vitro cancer cultures, including three-dimensional organoids, typically contain exclusively neoplastic epithelium but require artificial reconstitution to recapitulate the tumor microenvironment (TME). The co-culture of primary tumor epithelia with endogenous, syngeneic tumor-infiltrating lymphocytes (TILs) as a cohesive unit has been particularly elusive. Here, an air-liquid interface (ALI) method propagated patient-derived organoids (PDOs) from >100 human biopsies or mouse tumors in syngeneic immunocompetent hosts as tumor epithelia with native embedded immune cells (T, B, NK, macrophages). Robust droplet-based, single-cell simultaneous determination of gene expression and immune repertoire indicated that PDO TILs accurately preserved the original tumor T cell receptor (TCR) spectrum. Crucially, human and murine PDOs successfully modeled immune checkpoint blockade (ICB) with anti-PD-1- and/or anti-PD-L1 expanding and activating tumor antigen-specific TILs and eliciting tumor cytotoxicity. Organoid-based propagation of primary tumor epithelium en bloc with endogenous immune stroma should enable immuno-oncology investigations within the TME and facilitate personalized immunotherapy testing.