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Cancer is one of the most concerning public health issues and breast cancer is one of the most common cancers in the world. The immune cells within the tumor microenvironment regulate cancer development. In this study, single immune cell data sets were used to identify marker gene sets for exhausted CD8 + T cells (CD8Tex) in breast cancer. Machine learning methods were used to cluster subtypes and establish the prognostic models with breast cancer bulk data using the gene sets to evaluate the impacts of CD8Tex. We analyzed breast cancer overexpressing and survival-associated marker genes and identified CD8Tex hub genes in the protein–protein-interaction network. The relevance of the hub genes for CD8 + T-cells in breast cancer was evaluated. The clinical associations of the hub genes were analyzed using bulk sequencing data and spatial sequencing data. The pan-cancer expression, survival, and immune association of the hub genes were analyzed. We identified biomarker gene sets for CD8Tex in breast cancer. CD8Tex-based subtyping systems and prognostic models performed well in the separation of patients with different immune relevance and survival. CRTAM, CLEC2D, and KLRB1 were identified as CD8Tex hub genes and were demonstrated to have potential clinical relevance and immune therapy impact. This study provides a unique view of the critical CD8Tex hub genes for cancer immune therapy.

BackgroundTumor heterogeneity plays essential roles in developing cancer therapies, including therapies for breast cancer (BC). In addition, it is also very important to understand the relationships between tumor microenvironments and the systematic immune environment.MethodsHere, we performed single-cell, VDJ sequencing and spatial transcriptome analyses on tumor and adjacent normal tissue as well as axillar lymph nodes (LNs) and peripheral blood mononuclear cells (PBMCs) from 8 BC patients.ResultsWe found that myeloid cells exhibited environment-dependent plasticity, where a group of macrophages with both M1 and M2 signatures possessed high tumor specificity spatially and was associated with worse patient survival. Cytotoxic T cells in tumor sites evolved in a separate path from those in the circulatory system. T cell receptor (TCR) repertoires in metastatic LNs showed significant higher consistency with TCRs in tumor than those in nonmetastatic LNs and PBMCs, suggesting the existence of common neo-antigens across metastatic LNs and primary tumor cites. In addition, the immune environment in metastatic LNs had transformed into a tumor-like status, where pro-inflammatory macrophages and exhausted T cells were upregulated, accompanied by a decrease in B cells and neutrophils. Finally, cell interactions showed that cancer-associated fibroblasts (CAFs) contributed most to shaping the immune-suppressive microenvironment, while CD8+ cells were the most signal-responsive cells.ConclusionsThis study revealed the cell structures of both micro- and macroenvironments, revealed how different cells diverged in related contexts as well as their prognostic capacities, and displayed a landscape of cell interactions with spatial information.

Traditionally, diagnostic pathology uses histology representing structural alterations in a disease’s cells and tissues. In many cases, however, it is supplemented by other morphology-based methods such as immunohistochemistry and fluorescent in situ hybridization. Single-cell RNA sequencing (scRNA-seq) is one of the strategies that may help tackle the heterogeneous cells in a disease, but it does not usually provide histologic information. Spatial sequencing is designed to assign cell types, subtypes, or states according to the mRNA expression on a histological section by RNA sequencing. It can provide mRNA expressions not only of diseased cells, such as cancer cells but also of stromal cells, such as immune cells, fibroblasts, and vascular cells. In this review, we studied current methods of spatial transcriptome sequencing based on their technical backgrounds, tissue preparation, and analytic procedures. With the pathology examples, useful recommendations for pathologists who are just getting started to use spatial sequencing analysis in research are provided here. In addition, leveraging spatial sequencing by integration with scRNA-seq is reviewed. With the advantages of simultaneous histologic and single-cell information, spatial sequencing may give a molecular basis for pathological diagnosis, improve our understanding of diseases, and have potential clinical applications in prognostics and diagnostic pathology.

Adamantinomatous craniopharyngioma (ACP) is a clinically aggressive tumor without effective treatment method. Previous studies proposed a paracrine tumorigenesis model, in which oncogenic β-catenin induces senescence in pituitary stem cells and the senescent cells lead the formation of paracrine tumors through secretion of pro-tumorigenic factors. However, there lacks characterization on senescent cells in ACPs. Here, we profiled 12 ACPs with single-cell RNA and TCR-sequencing to elucidate the cellular atlas in ACPs and 3 of them were also subject to spatial sequencing to localize different subpopulations of the tumor cells. In total, we obtained the transcriptome profiles of 70,682 cells. Tumor cells, which were unambiguously identified through the cellular mutation status of the driver CTNNB1 mutations, were clustered into 6 subsets. The whorl-like cluster (WC) cells show distinct molecular features from the other tumor cells and the palisading epithelium (PE) cells consists of a proliferating subset. Other than typical PE and WC, we identified two novel subpopulations of the tumor cells. In one subpopulation, the cells express a high level of cytokines, e.g., FDCSP and S100A8 / A9 , and are enriched with the senescence-associated secretory phenotype (SASP) factors. Hematoxylin and eosin staining reveals that these SASP cells lack an ordered structures and their nuclei are elongated. In the other subpopulation, the cell sizes are small and they are tightly packed together with an unusual high density expressing a high level of mitochondrial genes (median 10.9%). These cells are the origin of the tumor developmental trajectories revealed by RNA velocity and pseudo-time analysis. Single-cell RNA and TCR analysis reveals that some ACPs are infiltrated with clonally expanded cytotoxic T cells. We propose a hypothesis that WC and PE are formed via different negative regulation mechanisms of the overactivated WNT/β-catenin signaling which provides a new understanding on the tumorigenesis of ACPs. The study lays a foundation for future studies on targeting senescent cells in ACPs with senolytic compounds or other therapeutic agents.

Glioblastoma (GBM) is an aggressive form of brain cancer that is highly resistant to therapy due to significant intra‐tumoral heterogeneity. The lack of robust in vitro models to study early tumor progression has hindered the development of effective therapies. Here, this study develops engineered GBM organoids (eGBOs) harboring GBM subtype‐specific oncogenic mutations to investigate the underlying transcriptional regulation of tumor progression. Single‐cell and spatial transcriptomic analyses revealed that these mutations disrupt normal neurodevelopment gene regulatory networks resulting in changes in cellular composition and spatial organization. Upon xenotransplantation into immunodeficient mice, eGBOs form tumors that recapitulate the transcriptional and spatial landscape of human GBM samples. Integrative single‐cell trajectory analysis of both eGBO‐derived tumor cells and patient GBM samples reveal the dynamic gene expression changes in developmental cell states underlying tumor progression. This analysis of eGBOs provides an important validation of engineered cancer organoid models and demonstrates their utility as a model of GBM tumorigenesis for future preclinical development of therapeutics. This study develops engineered glioblastoma organoids to investigate the role of specific mutations in tumor progression. The analytic framework spans single‐cell analysis, spatial transcriptomics, single‐cell trajectory analysis, orthotopic implantation, clinically oriented imaging, and histopathological analysis. The work provides an important proof of concept that engineered tumor organoids can model glioblastoma progression.

Immune-mediated inflammatory diseases (IMIDs), such as inflammatory bowel diseases and inflammatory arthritis (e.g., rheumatoid arthritis, psoriatic arthritis), are marked by increasing worldwide incidence rates. Apart from irreversible damage of the affected tissue, the systemic nature of these diseases heightens the incidence of cardiovascular insults and colitis-associated neoplasia. Only 40–60% of patients respond to currently used standard-of-care immunotherapies. In addition to this limited long-term effectiveness, all current therapies have to be given on a lifelong basis as they are unable to specifically reprogram the inflammatory process and thus achieve a true cure of the disease. On the other hand, the development of various OMICs technologies is considered as “the great hope” for improving the treatment of IMIDs. This review sheds light on the progressive development and the numerous approaches from basic science that gradually lead to the transfer from “bench to bedside” and the implementation into general patient care procedures.

Solid tumours exhibit a well‐defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as ‘seeds’ for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body‐border‐haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments. Some tumours establish immunosuppressive and stromal barriers at their boundaries while enhancing oxidative phosphorylation and lipid metabolism to sustain their invasive potential. Additionally early evolving premalignant clones are able to cross histologic boundaries, possessing some genomic CNV features but not presenting cytomorphic changes. Multiple intratumoural clonal subpopulations infiltrate the blood vessels with a circadian rhythm when undergoing metastasis, while evading immunosurveillance and proliferating in the bloodstream in multiple ways.

Hepatocellular carcinoma (HCC) is one of the most lethal cancers for humans. HCC is highly heterogeneous. In this study, we performed ultra-depth (∼1 million reads per spot) sequencing of 6,320 spatial transcriptomes on a case of HCC. Sixteen distinct spatial expression clusters were identified. Each of these clusters was spatially contiguous and had distinct gene expression patterns. In contrast, benign liver tissues showed minimal heterogeneity in terms of gene expression. Numerous immune cell-enriched spots were identified in both HCC and benign liver regions. Cells adjacent to these immune cell-enriched spots showed significant alterations in their gene expression patterns. Interestingly, the responses of HCC cells to the nearby immune cells were significantly more intense and broader, while the responses of benign liver cells to immune cells were somewhat narrow and muted, suggesting an innate difference in immune cell activities towards HCC cells in comparison with benign liver cells. However, cell-cell interaction analyses showed significant immune evasion by HCC cancer cells. When standard-depth sequencing was performed, significant numbers of genes and pathways that were associated with these changes disappeared. Qualitative differences in some pathways were also found. These results suggest that deep spatial sequencing may help to uncover previously unidentified mechanisms of liver cancer development.

Acute myeloid leukemia (AML) is caused by altered maturation and differentiation of myeloid blasts, as well as transcriptional/epigenetic alterations, all leading to excessive proliferation of malignant blood cells in the bone marrow. Tumor heterogeneity due to the acquisition of new somatic alterations leads to a high rate of resistance to current therapies or reduces the efficacy of hematopoietic stem cell transplantation (HSCT), thus increasing the risk of relapse and mortality. Single-cell RNA sequencing (scRNA-seq) will enable the classification of AML and guide treatment approaches by profiling patients with different facets of the same disease, stratifying risk, and identifying new potential therapeutic targets at the time of diagnosis or after treatment. ScRNA-seq allows the identification of quiescent stem-like cells, and leukemia stem cells responsible for resistance to therapeutic approaches and relapse after treatment. This method also introduces the factors and mechanisms that enhance the efficacy of the HSCT process. Generated data of the transcriptional profile of the AML could even allow the development of cancer vaccines and CAR T-cell therapies while saving valuable time and alleviating dangerous side effects of chemotherapy and HSCT in vivo. However, scRNA-seq applications face various challenges such as a large amount of data for high-dimensional analysis, technical noise, batch effects, and finding small biological patterns, which could be improved in combination with artificial intelligence models. Highlights Tumor heterogeneity and drug resistance reduce therapeutic efficacy in AML treatment. ScRNA-seq improves the accuracy and quality of HSCT, resulting in a durable antitumor response. ScRNA-seq introduces neoantigens, biomarkers and cell subtypes that may contribute to reversing resistance to standard therapies in AML. Combination approaches using scRNA-seq and AI may provide effective AML management in the future.

Evidence demonstrates that sensory neurons respond to pathogenic/allergic infiltration and mediate immune responses, forming an integral part of host defense that becomes hypersensitized during allergy. Our objective was to investigate how asthmatic induction alters the pulmonary neuroimmune transcriptome. We hypothesized that asthmatic induction would upregulate genes in the vagal ganglia (nodose/jugular ganglia), which would be associated with asthmatic immunity, and that these would be clustered, primarily in nodose neurons. Furthermore, lungs would increase transcripts associated with nerve activation, and these would be centered in neural and neuroendocrine-like cells. Standard RNA sequencing, single nucleus-RNA sequencing, and spatial RNA sequencing of vagal ganglia. Standard RNA-sequencing and spatial RNA-sequencing of lungs in naïve and mice that have undergone asthmatic induction with . Bulk RNA-seq revealed that genes related to allergen sensing were increased in asthmatic ganglia nodose/jugular ganglia compared to control ganglia. These genes were associated with nodose clusters as shown by single-nucleus RNA sequencing, and a distinct caudal-to-rostral spatial arrangement was presented as delineated by spatial transcriptomics. The distinct clusters closely match previous identification of nodose neuron clusters. Correspondingly, the lung transcriptome was altered with asthmatic induction such that transcripts associated with neural excitation were upregulated. The spatial distribution of these transcripts was revealed by spatial transcriptomics to illustrate that these were expressed in neuroendocrine-like cells/club cells, and neurons. These results show that the neuroimmune transcriptome is altered in response to asthmatic induction in a cell cluster and spatially distinct manner.