Journal Articles

'Omics analyses

Genome, transcriptome, proteome, etc. studies that help to understand and improve cancer immunotherapy

Spatial Intratumor Genomic Heterogeneity within Localized Prostate Cancer Revealed by Single-nucleus Sequencing

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BACKGROUND: Prostate adenocarcinoma (PCa) is a complex genetic disease, and the implementation of personalized treatment in PCa faces challenges due to significant inter- and intrapatient tumor heterogeneities. OBJECTIVE: To systematically explore the genomic complexity of tumor cells with different Gleason scores (GSs) in PCa. DESIGN, SETTING, AND PARTICIPANTS: We performed single-cell whole genome sequencing of 17 tumor cells from localized lesions with distinct GS and matched four normal samples from two prostatectomy patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: All classes of genomic alterations were identified, including substitutions, insertions/deletions, copy number alterations, and rearrangements. RESULTS AND LIMITATIONS: Significant spatial, intra- and intertumoral heterogeneities were observed at the cellular level. In the patient 1, all cells shared the same TP53 driver mutation, implying a monoclonal origin of PCa. In the patient 2, only a subpopulation of cells contained the TP53 driver mutation, whereas other cells carried different driver mutations, indicating a typical polyclonal model with separate clonal cell expansions. The tumor cells from different sides of prostate owned various mutation patterns. Considerable neoantigens were predicted among different cells, implying unknown immune editing components helping prostate tumor cells escaping from immune surveillance. CONCLUSIONS: There is a significant spatial genomic heterogeneity even in the same PCa patient. Our study also provides the first genome-wide evidence at single-cell level, supporting that the origin of PCa could be either polyclonal or monoclonal, which has implications for treatment decisions for prostate cancer. PATIENT SUMMARY: We reported the first single-cell whole genomic data of prostate adenocarcinoma (PCa) from different Gleason scores. Identification of these genetic alterations may help understand PCa tumor progression and clonal evolution.

Author Info: (1) Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China; The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China

Author Info: (1) Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China; The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. (2) Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China. (3) Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. (4) Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. (5) Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. (6) Department of Oncology, Beijing Hospital, National Center of Gerontology, Beijing, China. (7) Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. (8) Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. (9) Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China. (10) Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China. (11) The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. (12) The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. (13) The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. (14) Department of Oncology, Beijing Hospital, National Center of Gerontology, Beijing, China. (15) Sun Yat-sen University Cancer Center, Guangzhou, China. (16) Center for Biotherapy, Beijing Hospital, National Center of Gerontology, Beijing, China; State Key Lab of Molecular Oncology, National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: majie4685@bjhmoh.cn. (17) Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China; The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. Electronic address: xiaofei3965@bjhmoh.cn. (18) Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. Electronic address: liuming3222@bjhmoh.cn.

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Single-Cell Proteomics for Cancer Immunotherapy

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Cancer immunotherapy fights against cancer by modulating the immune response and is delivering encouraging results in clinical treatments. However, it is challenging to achieve durable response in all cancer patients during treatment due to the diversity and dynamic nature of immune system as well as inter- and intratumor heterogeneity. A comprehensive assessment of system immunity and tumor microenvironment is crucial for effective and safe cancer therapy, which can potentially be resolved by single-cell proteomic analysis. Single-cell proteomic technologies enable system-wide profiling of protein levels in a number of single cells within the immune system and tumor microenvironment, and thereby provide direct assessment of the functional state of the immune cells and tumor-immune interaction that could be used to evaluate efficacy of immunotherapy and to improve clinical outcome. In this chapter, we summarized current single-cell proteomic technologies and their applications in cancer immunotherapy.

Author Info: (1) Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China. (2) Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China. (3)

Author Info: (1) Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China. (2) Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China. (3) Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China. (4) Minhang Branch, Zhongshan Hospital and Institute of Biomedical Sciences, Fudan University, Shanghai, China; Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai, China. Electronic address: qihuishi@gmail.com. (5) Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China. Electronic address: luyao@dicp.ac.cn.

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Human adaptive immune receptor repertoire analysis-Past, present, and future

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The genes encoding adaptive immune antigen receptors, namely the immunoglobulins expressed in membrane-bound or secreted forms by B cells, and the cell surface T cell receptors, are unique in human biology because they are generated by combinatorial rearrangement of the genomic DNA. The diversity of receptors so generated in populations of lymphocytes enables the human immune system to recognize antigens expressed by pathogens, but also underlies the pathological specificity of autoimmune diseases and the mistargeted immunity in allergies. Several recent technological developments, foremost among them the invention of high-throughput DNA sequencing instruments, have enabled much deeper and thorough evaluation of clones of human B cells and T cells and the antigen receptors they express during physiological and pathogenic immune responses. The evolutionary struggles between host adaptive immune responses and populations of pathogens are now open to greater scrutiny, elucidation of the underlying reasons for successful or failed immunity, and potential predictive modeling, than ever before. Here we give an overview of the foundations, recent progress, and future prospects in this dynamic area of research.

Author Info: (1) Department of Pathology, Stanford University, Stanford, CA, USA. (2) Department of Pathology, Stanford University, Stanford, CA, USA.

Author Info: (1) Department of Pathology, Stanford University, Stanford, CA, USA. (2) Department of Pathology, Stanford University, Stanford, CA, USA.

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Assessing human B cell repertoire diversity and convergence

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A hallmark of the adaptive immune system is the specificity of B cell and T cell responses. Mechanistically, this feature relies on the fact that the two genes that encode B cell and T cell antigen receptors are not germline encoded and instead are assembled from a large number of small gene segments during lymphocyte development. The underlying somatic gene recombination process can generate a quasi-unlimited repertoire of antigen receptors. The high degree of diversity is essential to guarantee recognition of nearly any antigenic structure to protect from the large variety of potential invading pathogens and to keep the balance with commensals. Due to the enormous complexity of the antigen receptor repertoire, our understanding of its actual size and functional convergence at the level of the individual and the population is still limited. A better understanding of the actual degree of diversity could help to predict adaptive immune responses and would have wide implications for the development of preventive and therapeutic measures against infectious and autoimmune diseases as well as cancer. Here, we discuss the recent advances in the field with a specific focus on B cells and the function of antibodies.

Author Info: (1) German Cancer Research Center, B Cell Immunology, Heidelberg, Germany. (2) German Cancer Research Center, B Cell Immunology, Heidelberg, Germany.

Author Info: (1) German Cancer Research Center, B Cell Immunology, Heidelberg, Germany. (2) German Cancer Research Center, B Cell Immunology, Heidelberg, Germany.

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Bohemian T cell receptors: sketching the repertoires of unconventional lymphocytes

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Over the last several decades, novel populations of unconventional T cells have been identified; defined by an invariant (or nearly invariant) T cell receptor (TCR) with a fixed specificity to non-canonical antigens and major histocompatibility (MHC) molecules, they form large, functionally monoclonal populations tasked with surveying for their specific antigens. With residence in both lymphoid and non-lymphoid tissues coupled with their ability to rapidly produce a spectrum of cytokines and effector molecules, the unconventional T cells are poised as some of the first responders to infection/damage and are thought to provide critical coverage before more focused, conventional T cell responses are mobilized. However, new technologies for the measurement and characterization of TCR repertoires have identified an underappreciated amount of TCR diversity in the unconventional T cells. In many cases, the specificities of these diverse TCRs converge on the same or similar antigens as their invariant counterparts, while others have yet to be defined. Here, we will review the current knowledge of the TCR repertoires of unconventional T cells and discuss how repertoires might be used as a framework for their organization, and further our understanding of their role not only during an immune response, but also their contribution in maintaining homeostasis.

Author Info: (1) St. Jude Children's Research Hospital, Memphis, TN, USA. (2) St. Jude Children's Research Hospital, Memphis, TN, USA.

Author Info: (1) St. Jude Children's Research Hospital, Memphis, TN, USA. (2) St. Jude Children's Research Hospital, Memphis, TN, USA.

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Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination

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Despite the extreme diversity of T-cell repertoires, many identical T-cell receptor (TCR) sequences are found in a large number of individual mice and humans. These widely shared sequences, often referred to as "public," have been suggested to be over-represented due to their potential immune functionality or their ease of generation by V(D)J recombination. Here, we show that even for large cohorts, the observed degree of sharing of TCR sequences between individuals is well predicted by a model accounting for the known quantitative statistical biases in the generation process, together with a simple model of thymic selection. Whether a sequence is shared by many individuals is predicted to depend on the number of queried individuals and the sampling depth, as well as on the sequence itself, in agreement with the data. We introduce the degree of publicness conditional on the queried cohort size and the size of the sampled repertoires. Based on these observations, we propose a public/private sequence classifier, "PUBLIC" (Public Universal Binary Likelihood Inference Classifier), based on the generation probability, which performs very well even for small cohort sizes.

Author Info: (1) Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA. (2) Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA. (3) Joseph Henry Laboratories, Princeton University, Princeton

Author Info: (1) Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA. (2) Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA. (3) Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA. (4) Laboratoire de physique statistique, CNRS, Sorbonne Universite, Universite Paris-Diderot, and Ecole Normale Superieure (PSL University), Paris, France. (5) Laboratoire de physique theorique, CNRS, Sorbonne Universite, and Ecole Normale Superieure (PSL University), Paris, France.

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Immunoglobulin gene analysis as a tool for investigating human immune responses

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The human immunoglobulin repertoire is a hugely diverse set of sequences that are formed by processes of gene rearrangement, heavy and light chain gene assortment, class switching and somatic hypermutation. Early B cell development produces diverse IgM and IgD B cell receptors on the B cell surface, resulting in a repertoire that can bind many foreign antigens but which has had self-reactive B cells removed. Later antigen-dependent development processes adjust the antigen affinity of the receptor by somatic hypermutation. The effector mechanism of the antibody is also adjusted, by switching the class of the antibody from IgM to one of seven other classes depending on the required function. There are many instances in human biology where positive and negative selection forces can act to shape the immunoglobulin repertoire and therefore repertoire analysis can provide useful information on infection control, vaccination efficacy, autoimmune diseases, and cancer. It can also be used to identify antigen-specific sequences that may be of use in therapeutics. The juxtaposition of lymphocyte development and numerical evaluation of immune repertoires has resulted in the growth of a new sub-speciality in immunology where immunologists and computer scientists/physicists collaborate to assess immune repertoires and develop models of immune action.

Author Info: (1) Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK. (2) Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK. (3)

Author Info: (1) Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK. (2) Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK. (3) Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK. (4) Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.

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Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing

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Cancer immunotherapies have shown sustained clinical responses in treating non-small-cell lung cancer(1-3), but efficacy varies and depends in part on the amount and properties of tumor infiltrating lymphocytes(4-6). To depict the baseline landscape of the composition, lineage and functional states of tumor infiltrating lymphocytes, here we performed deep single-cell RNA sequencing for 12,346 T cells from 14 treatment-naive non-small-cell lung cancer patients. Combined expression and T cell antigen receptor based lineage tracking revealed a significant proportion of inter-tissue effector T cells with a highly migratory nature. As well as tumor-infiltrating CD8(+) T cells undergoing exhaustion, we observed two clusters of cells exhibiting states preceding exhaustion, and a high ratio of "pre-exhausted" to exhausted T cells was associated with better prognosis of lung adenocarcinoma. Additionally, we observed further heterogeneity within the tumor regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of those activated tumor Tregs, which included IL1R2, correlated with poor prognosis in lung adenocarcinoma. Our study provides a new approach for patient stratification and will help further understand the functional states and dynamics of T cells in lung cancer.

Author Info: (1) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (2) BIOPIC, Beijing Advanced Innovation Centre for Genomics

Author Info: (1) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (2) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (3) Peking-Tsinghua Centre for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China. (4) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (5) Department of Thoracic Surgery, Peking University Third Hospital, Beijing, China. (6) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (7) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (8) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (9) Department of Thoracic Surgery, Peking University Third Hospital, Beijing, China. (10) Peking University Cancer Hospital & Institute, Beijing, China. (11) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (12) Peking-Tsinghua Centre for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China. (13) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (14) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (15) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. (16) Bayer AG, Berlin, Germany. (17) Bayer AG, Berlin, Germany. (18) Department of Thoracic Surgery, Peking University Third Hospital, Beijing, China. yts8966@163.com. (19) BIOPIC, Beijing Advanced Innovation Centre for Genomics, and School of Life Sciences, Peking University, Beijing, China. zemin@pku.edu.cn. Peking-Tsinghua Centre for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China. zemin@pku.edu.cn.

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Gemcitabine alters the proteasome composition and immunopeptidome of tumour cells

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The antigenic makeup of tumour cells can have a profound effect on the progression of cancer and success of immunotherapies. Therefore, one strategy to improve the efficacy of cancer treatments is to augment the antigens displayed by tumours. The present study explores how the recognition of tumour cells may be altered by non-cytotoxic concentrations of gemcitabine (GEM). Testing a panel of chemotherapeutics in human cancer cell lines in vitro, it was found that GEM increased surface expression of HLA-A,B,C and that underlying this were specific increases in beta-2-microglobulin and immunoproteasome subunit proteins. Furthermore, the peptide antigen repertoire displayed on HLA class I was altered, revealing a number of novel antigens, many of which that were derived from proteins involved in the DNA-damage response. Changes in the nature of the peptide antigens eluted from HLA-A,B,C after GEM treatment consisted of amino acid anchor-residue modifications and changes in peptide length which rendered peptides likely to favour alternative HLA-alleles and increased their predicted immunogenicity. Signalling through the MAPK/ERK and NFkappaB/RelB pathways was associated with these changes. These data may explain observations made in previous in vivo studies, advise as to which antigens should be used in future vaccination protocols and reinforce the idea that chemotherapy and immunotherapy could be used in combination.

Author Info: (1) Institute for infection and immunity, St George's, University of London, London, UK. (2) Department of Immunology, Institute of Cell Biology, University of Tubingen, Tubingen

Author Info: (1) Institute for infection and immunity, St George's, University of London, London, UK. (2) Department of Immunology, Institute of Cell Biology, University of Tubingen, Tubingen, Germany. (3) Department of Immunology, Institute of Cell Biology, University of Tubingen, Tubingen, Germany. (4) Institute for infection and immunity, St George's, University of London, London, UK. (5) Institute for infection and immunity, St George's, University of London, London, UK.

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Pan-cancer adaptive immune resistance as defined by the Tumor Inflammation Signature (TIS): results from The Cancer Genome Atlas (TCGA)

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The Tumor Inflammation Signature (TIS) is an investigational use only (IUO) 18-gene signature that measures a pre-existing but suppressed adaptive immune response within tumors. The TIS has been shown to enrich for patients who respond to the anti-PD1 agent pembrolizumab. To explore this immune phenotype within and across tumor types, we applied the TIS algorithm to over 9000 tumor gene expression profiles downloaded from The Cancer Genome Atlas (TCGA). As expected based on prior evidence, tumors with known clinical sensitivity to anti-programmed cell death protein 1 (PD-1) blockade had higher average TIS scores. Furthermore, TIS scores were more variable within than between tumor types, and within each tumor type a subset of patients with elevated scores was identifiable although with different prevalence associated with each tumor type, the latter consistent with the observed clinical responsiveness to anti PD-1 blockade. Notably, TIS scores only minimally correlated with mutation load in most tumors and ranking tumors by median TIS score showed differing association to clinical sensitivity to PD-1/PD-1 ligand 1 (PD-L1) blockade than ranking of the same tumors by mutation load. The expression patterns of the TIS algorithm genes were conserved across tumor types yet appeared to be minimally prognostic in most cancers, consistent with the TIS score serving as a pan-cancer measurement of the inflamed tumor phenotype. Characterization of the prevalence and variability of TIS will lead to increased understanding of the immune status of untreated tumors and may lead to improved indication selection for testing immunotherapy agents.

Author Info: (1) NanoString Technologies Inc, Seattle, WA, USA. (2) NanoString Technologies Inc, Seattle, WA, USA. (3) AbbVie Inc., Redwood City, CA, USA. (4) AbbVie Inc., Redwood

Author Info: (1) NanoString Technologies Inc, Seattle, WA, USA. (2) NanoString Technologies Inc, Seattle, WA, USA. (3) AbbVie Inc., Redwood City, CA, USA. (4) AbbVie Inc., Redwood City, CA, USA. (5) NanoString Technologies Inc, Seattle, WA, USA. (6) NanoString Technologies Inc, Seattle, WA, USA. (7) NanoString Technologies Inc, Seattle, WA, USA. (8) AbbVie Inc., Redwood City, CA, USA. (9) NanoString Technologies Inc, Seattle, WA, USA. acesano@nanostring.com.

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