Seminars in Immunopathology最新文献

{"title":"The role of macrophages in the tumor microenvironment and tumor metabolism.","authors":"Pritam Sadhukhan,&nbsp;Tanguy Y Seiwert","doi":"10.1007/s00281-023-00988-2","DOIUrl":"https://doi.org/10.1007/s00281-023-00988-2","url":null,"abstract":"<p><p>The complexity and plasticity of the tumor microenvironment (TME) make it difficult to fully understand the intratumoral regulation of different cell types and their activities. Macrophages play a crucial role in the signaling dynamics of the TME. Among the different subtypes of macrophages, tumor-associated macrophages (TAMs) are often associated with poor prognosis, although some subtypes of TAMs can at the same time improve treatment responsiveness and lead to favorable clinical outcomes. TAMs are key regulators of cancer cell proliferation, metastasis, angiogenesis, extracellular matrix remodeling, tumor metabolism, and importantly immunosuppression in the TME by modulating various chemokines, cytokines, and growth factors. TAMs have been identified as a key contributor to resistance to chemotherapy and cancer immunotherapy. In this review article, we aim to discuss the mechanisms by which TAMs regulate innate and adaptive immune signaling in the TME and summarize recent preclinical research on the development of therapeutics targeting TAMs and tumor metabolism.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 2","pages":"187-201"},"PeriodicalIF":9.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9681485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CAF-immune cell crosstalk and its impact in immunotherapy.","authors":"Ana Maia,&nbsp;Anna Schöllhorn,&nbsp;Juliane Schuhmacher,&nbsp;Cécile Gouttefangeas","doi":"10.1007/s00281-022-00977-x","DOIUrl":"https://doi.org/10.1007/s00281-022-00977-x","url":null,"abstract":"<p><p>Tumour cells do not exist as isolated entities. Instead, they are surrounded by a variety of cells and extracellular matrix, which form the tumour microenvironment (TME). The interaction between cancer cells and their microenvironment is increasingly acknowledged as essential in dictating the outcome of the patients. The TME includes everything that surrounds tumour cells and is often highjacked by the latter to promote their growth, invasion, and immune escape. Immune cells and cancer-associated fibroblasts (CAFs) are essential components of the TME, and there is increasing evidence that their interaction constitutes a major player not only for tumour progression but also for therapy response.Recent work in the field of immuno-oncology resulted in the development of novel therapies that aim at activating immune cells against cancer cells to eliminate them. Despite their unprecedented success, the lack of response from a large portion of patients highlights the need for further progress and improvement. To achieve its ultimate goal, the interaction between cancer cells and the TME needs to be studied in-depth to allow the targeting of mechanisms that are involved in resistance or refractoriness to therapy. Moreover, predictive and prognostic biomarkers for patient stratification are still missing. In this review, we focus on and highlight the complexity of CAFs within the TME and how their interaction, particularly with immune cells, can contribute to treatment failure. We further discuss how this crosstalk can be further dissected and which strategies are currently used to target them.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 2","pages":"203-214"},"PeriodicalIF":9.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10051836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel immunotherapeutic combinations moving forward: the modulation of the immunosuppressive microenvironment.","authors":"Mads Hald Andersen","doi":"10.1007/s00281-023-00991-7","DOIUrl":"https://doi.org/10.1007/s00281-023-00991-7","url":null,"abstract":"","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 2","pages":"159-161"},"PeriodicalIF":9.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9676104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning cell identity in immunology, neuroscience, and cancer.","authors":"Stephanie Medina, Rebecca A Ihrie, Jonathan M Irish","doi":"10.1007/s00281-022-00976-y","DOIUrl":"10.1007/s00281-022-00976-y","url":null,"abstract":"<p><p>Suspension and imaging cytometry techniques that simultaneously measure hundreds of cellular features are powering a new era of cell biology and transforming our understanding of human tissues and tumors. However, a central challenge remains in learning the identities of unexpected or novel cell types. Cell identification rubrics that could assist trainees, whether human or machine, are not always rigorously defined, vary greatly by field, and differentially rely on cell intrinsic measurements, cell extrinsic tissue measurements, or external contextual information such as clinical outcomes. This challenge is especially acute in the context of tumors, where cells aberrantly express developmental programs that are normally time, location, or cell-type restricted. Well-established fields have contrasting practices for cell identity that have emerged from convention and convenience as much as design. For example, early immunology focused on identifying minimal sets of protein features that mark individual, functionally distinct cells. In neuroscience, features including morphology, development, and anatomical location were typical starting points for defining cell types. Both immunology and neuroscience now aim to link standardized measurements of protein or RNA to informative cell functions such as electrophysiology, connectivity, lineage potential, phospho-protein signaling, cell suppression, and tumor cell killing ability. The expansion of automated, machine-driven methods for learning cell identity has further created an urgent need for a harmonized framework for distinguishing cell identity across fields and technology platforms. Here, we compare practices in the fields of immunology and neuroscience, highlight concepts from each that might work well in the other, and propose ways to implement these ideas to study neural and immune cell interactions in brain tumors and associated model systems.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 1","pages":"3-16"},"PeriodicalIF":7.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9455397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immune biology of NSCLC revealed by single-cell technologies: implications for the development of biomarkers in patients treated with immunotherapy.","authors":"J Wlosik,&nbsp;S Fattori,&nbsp;P Rochigneux,&nbsp;A Goncalves,&nbsp;D Olive,&nbsp;A S Chretien","doi":"10.1007/s00281-022-00973-1","DOIUrl":"https://doi.org/10.1007/s00281-022-00973-1","url":null,"abstract":"<p><p>First-line immunotherapy in non-small-cell lung cancer largely improved patients' survival. PD-L1 testing is required before immune checkpoint inhibitor initiation. However, this biomarker fails to accurately predict patients' response. On the other hand, immunotherapy exposes patients to immune-related toxicity, the mechanisms of which are still unclear. Hence, there is an unmet need to develop clinically approved predictive biomarkers to better select patients who will benefit the most from immune checkpoint inhibitors and improve risk management. Single-cell technologies provide unprecedented insight into the tumor and its microenvironment, leading to the discovery of immune cells involved in immune checkpoint inhibitor response or toxicity. In this review, we will underscore the potential of the single-cell approach to identify candidate biomarkers improving non-small-cell lung cancer patients' care.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 1","pages":"29-41"},"PeriodicalIF":9.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9974692/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9391272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards multiomic analysis of oral mucosal pathologies.","authors":"Jakob Einhaus, Xiaoyuan Han, Dorien Feyaerts, John Sunwoo, Brice Gaudilliere, Somayeh H Ahmad, Nima Aghaeepour, Karl Bruckman, David Ojcius, Christian M Schürch, Dyani K Gaudilliere","doi":"10.1007/s00281-022-00982-0","DOIUrl":"10.1007/s00281-022-00982-0","url":null,"abstract":"<p><p>Oral mucosal pathologies comprise an array of diseases with worldwide prevalence and medical relevance. Affecting a confined space with crucial physiological and social functions, oral pathologies can be mutilating and drastically reduce quality of life. Despite their relevance, treatment for these diseases is often far from curative and remains vastly understudied. While multiple factors are involved in the pathogenesis of oral mucosal pathologies, the host's immune system plays a major role in the development, maintenance, and resolution of these diseases. Consequently, a precise understanding of immunological mechanisms implicated in oral mucosal pathologies is critical (1) to identify accurate, mechanistic biomarkers of clinical outcomes; (2) to develop targeted immunotherapeutic strategies; and (3) to individualize prevention and treatment approaches. Here, we review key elements of the immune system's role in oral mucosal pathologies that hold promise to overcome limitations in current diagnostic and therapeutic approaches. We emphasize recent and ongoing multiomic and single-cell approaches that enable an integrative view of these pathophysiological processes and thereby provide unifying and clinically relevant biological signatures.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 1","pages":"111-123"},"PeriodicalIF":7.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9974703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9098633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Highly multiplexed spatial profiling with CODEX: bioinformatic analysis and application in human disease.","authors":"Wilson Kuswanto,&nbsp;Garry Nolan,&nbsp;Guolan Lu","doi":"10.1007/s00281-022-00974-0","DOIUrl":"https://doi.org/10.1007/s00281-022-00974-0","url":null,"abstract":"<p><p>Multiplexed imaging, which enables spatial localization of proteins and RNA to cells within tissues, complements existing multi-omic technologies and has deepened our understanding of health and disease. CODEX, a multiplexed single-cell imaging technology, utilizes a microfluidics system that incorporates DNA barcoded antibodies to visualize 50 + cellular markers at the single-cell level. Here, we discuss the latest applications of CODEX to studies of cancer, autoimmunity, and infection as well as current bioinformatics approaches for analysis of multiplexed imaging data from preprocessing to cell segmentation and marker quantification to spatial analysis techniques. We conclude with a commentary on the challenges and future developments for multiplexed spatial profiling.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 1","pages":"145-157"},"PeriodicalIF":9.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9936615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiparameter single-cell proteomic technologies give new insights into the biology of ovarian tumors.","authors":"Ionut-Gabriel Funingana,&nbsp;Jacob S Bedia,&nbsp;Ying-Wen Huang,&nbsp;Antonio Delgado Gonzalez,&nbsp;Kenyi Donoso,&nbsp;Veronica D Gonzalez,&nbsp;James D Brenton,&nbsp;Alan Ashworth,&nbsp;Wendy J Fantl","doi":"10.1007/s00281-022-00979-9","DOIUrl":"https://doi.org/10.1007/s00281-022-00979-9","url":null,"abstract":"<p><p>High-grade serous ovarian cancer (HGSOC) is the most lethal gynecological malignancy. Its diagnosis at advanced stage compounded with its excessive genomic and cellular heterogeneity make curative treatment challenging. Two critical therapeutic challenges to overcome are carboplatin resistance and lack of response to immunotherapy. Carboplatin resistance results from diverse cell autonomous mechanisms which operate in different combinations within and across tumors. The lack of response to immunotherapy is highly likely to be related to an immunosuppressive HGSOC tumor microenvironment which overrides any clinical benefit. Results from a number of studies, mainly using transcriptomics, indicate that the immune tumor microenvironment (iTME) plays a role in carboplatin response. However, in patients receiving treatment, the exact mechanistic details are unclear. During the past decade, multiplex single-cell proteomic technologies have come to the forefront of biomedical research. Mass cytometry or cytometry by time-of-flight, measures up to 60 parameters in single cells that are in suspension. Multiplex cellular imaging technologies allow simultaneous measurement of up to 60 proteins in single cells with spatial resolution and interrogation of cell-cell interactions. This review suggests that functional interplay between cell autonomous responses to carboplatin and the HGSOC immune tumor microenvironment could be clarified through the application of multiplex single-cell proteomic technologies. We conclude that for better clinical care, multiplex single-cell proteomic technologies could be an integral component of multimodal biomarker development that also includes genomics and radiomics. Collection of matched samples from patients before and on treatment will be critical to the success of these efforts.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 1","pages":"43-59"},"PeriodicalIF":9.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9974728/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9789357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell technologies uncover intra-tumor heterogeneity in childhood cancers.","authors":"Yu-Chen Lo,&nbsp;Yuxuan Liu,&nbsp;Marte Kammersgaard,&nbsp;Abhishek Koladiya,&nbsp;Timothy J Keyes,&nbsp;Kara L Davis","doi":"10.1007/s00281-022-00981-1","DOIUrl":"https://doi.org/10.1007/s00281-022-00981-1","url":null,"abstract":"<p><p>Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution. This facilitates unraveling the heterogeneity of childhood cancers to identify cell subtypes that are prone to treatment resistance. The rapid accumulation of single-cell data from different modalities necessitates the development of novel computational approaches for processing, visualizing, and analyzing single-cell data. Here, we review single-cell approaches utilized or under development in the context of childhood cancers. We review computational methods for analyzing single-cell data and discuss best practices for their application. Finally, we review the impact of several studies of childhood tumors analyzed with these approaches and future directions to implement single-cell studies into translational cancer research in pediatric oncology.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 1","pages":"61-69"},"PeriodicalIF":9.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10830508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revisiting transplant immunology through the lens of single-cell technologies.","authors":"Arianna Barbetta, Brittany Rocque, Deepika Sarode, Johanna Ascher Bartlett, Juliet Emamaullee","doi":"10.1007/s00281-022-00958-0","DOIUrl":"10.1007/s00281-022-00958-0","url":null,"abstract":"<p><p>Solid organ transplantation (SOT) is the standard of care for end-stage organ disease. The most frequent complication of SOT involves allograft rejection, which may occur via T cell- and/or antibody-mediated mechanisms. Diagnosis of rejection in the clinical setting requires an invasive biopsy as there are currently no reliable biomarkers to detect rejection episodes. Likewise, it is virtually impossible to identify patients who exhibit operational tolerance and may be candidates for reduced or complete withdrawal of immunosuppression. Emerging single-cell technologies, including cytometry by time-of-flight (CyTOF), imaging mass cytometry, and single-cell RNA sequencing, represent a new opportunity for deep characterization of pathogenic immune populations involved in both allograft rejection and tolerance in clinical samples. These techniques enable examination of both individual cellular phenotypes and cell-to-cell interactions, ultimately providing new insights into the complex pathophysiology of allograft rejection. However, working with these large, highly dimensional datasets requires expertise in advanced data processing and analysis using computational biology techniques. Machine learning algorithms represent an optimal strategy to analyze and create predictive models using these complex datasets and will likely be essential for future clinical application of patient level results based on single-cell data. Herein, we review the existing literature on single-cell techniques in the context of SOT.</p>","PeriodicalId":21704,"journal":{"name":"Seminars in Immunopathology","volume":"45 1","pages":"91-109"},"PeriodicalIF":7.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9233634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}