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Spatial transcriptomics technology has been an essential and powerful method for delineating tissue architecture at the molecular level. However, due to the limitations of the current spatial techniques, the cellular information cannot be directly measured but instead spatial spots typically varying from a diameter of 0.2 to 100 µm are characterized. Therefore, it is vital to apply computational strategies for inferring the cellular composition within each spatial spot. The main objective of this review is to summarize the most recent progresses to estimate the exact cellular proportions for each spatial spot, and to prospect the future directions of this field.
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Characterizing the compositional and phenotypic characteristics of tumor-infiltrating B cells (TIBs) is important for advancing our understanding of their role in cancer development. Here, we establish a comprehensive resource of human B cells by integrating single-cell RNA sequencing data of B cells from 649 patients across 19 major cancer types. We demonstrate substantial heterogeneity in their total abundance and subtype composition and observe immunoglobulin G (IgG)-skewness of antibody-secreting cell isotypes. Moreover, we identify stress-response memory B cells and tumor-associated atypical B cells (TAABs), two tumor-enriched subpopulations with prognostic potential, shared in a pan-cancer manner. In particular, TAABs, characterized by a high clonal expansion level and proliferative capacity as well as by close interactions with activated CD4 T cells in tumors, are predictive of immunotherapy response. Our integrative resource depicts distinct clinically relevant TIB subsets, laying a foundation for further exploration of functional commonality and diversity of B cells in cancer.
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Computational deconvolution with single-cell RNA sequencing data as reference is pivotal to interpreting spatial transcriptomics data, but the current methods are limited to cell-type resolution. Here we present Redeconve, an algorithm to deconvolute spatial transcriptomics data at single-cell resolution, enabling interpretation of spatial transcriptomics data with thousands of nuanced cell states. We benchmark Redeconve with the state-of-the-art algorithms on diverse spatial transcriptomics platforms and datasets and demonstrate the superiority of Redeconve in terms of accuracy, resolution, robustness, and speed. Application to a human pancreatic cancer dataset reveals cancer-clone-specific T cell infiltration, and application to lymph node samples identifies differential cytotoxic T cells between IgA+ and IgG+ spots, providing novel insights into tumor immunology and the regulatory mechanisms underlying antibody class switch.
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Perfilación de la Expresión Génica , Transcriptoma , Humanos , Transcriptoma/genética , Algoritmos , Benchmarking , Isotipos de Inmunoglobulinas , Análisis de la Célula IndividualRESUMEN
Spatial transcriptomics technology has revolutionized our understanding of cell types and tissue organization, opening possibilities for researchers to explore transcript distributions at subcellular levels. However, existing methods have limitations in resolution, sensitivity, or speed. To overcome these challenges, we introduce SPRINTseq (Spatially Resolved and signal-diluted Next-generation Targeted sequencing), an innovative in situ sequencing strategy that combines hybrid block coding and molecular dilution strategies. Our method enables fast and sensitive high-resolution data acquisition, as demonstrated by recovering over 142 million transcripts using a 108-gene panel from 453,843 cells from four mouse brain coronal slices in less than 2 d. Using this advanced technology, we uncover the cellular and subcellular molecular architecture of Alzheimer's disease, providing additional information into abnormal cellular behaviors and their subcellular mRNA distribution. This improved spatial transcriptomics technology holds great promise for exploring complex biological processes and disease mechanisms.
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Perfilación de la Expresión Génica , Secuenciación de Nucleótidos de Alto Rendimiento , Animales , Ratones , ARN Mensajero/genética , TranscriptomaRESUMEN
Neoadjuvant immune-checkpoint blockade therapy only benefits a limited fraction of patients with glioblastoma multiforme (GBM). Thus, targeting other immunomodulators on myeloid cells is an attractive therapeutic option. Here, we performed single-cell RNA sequencing and spatial transcriptomics of patients with GBM treated with neoadjuvant anti-PD-1 therapy. We identified unique monocyte-derived tumor-associated macrophage subpopulations with functional plasticity that highly expressed the immunosuppressive SIGLEC9 gene and preferentially accumulated in the nonresponders to anti-PD-1 treatment. Deletion of Siglece (murine homolog) resulted in dramatically restrained tumor development and prolonged survival in mouse models. Mechanistically, targeting Siglece directly activated both CD4+ T cells and CD8+ T cells through antigen presentation, secreted chemokines and co-stimulatory factor interactions. Furthermore, Siglece deletion synergized with anti-PD-1/PD-L1 treatment to improve antitumor efficacy. Our data demonstrated that Siglec-9 is an immune-checkpoint molecule on macrophages that can be targeted to enhance anti-PD-1/PD-L1 therapeutic efficacy for GBM treatment.
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Glioblastoma , Humanos , Animales , Ratones , Glioblastoma/genética , Glioblastoma/terapia , Antígeno B7-H1 , Proteínas de Punto de Control Inmunitario/genética , Proteínas de Punto de Control Inmunitario/uso terapéutico , Linfocitos T CD8-positivos/patología , Inmunoterapia/métodos , Macrófagos/patologíaRESUMEN
OBJECTIVE: A comprehensive immune landscape for HBV infection is pivotal to achieve HBV cure. DESIGN: We performed single-cell RNA sequencing of 2 43 000 cells from 46 paired liver and blood samples of 23 individuals, including six immune tolerant, 5 immune active (IA), 3 acute recovery (AR), 3 chronic resolved and 6 HBV-free healthy controls (HCs). Flow cytometry and histological assays were applied in a second HBV cohort for validation. RESULTS: Both IA and AR were characterised by high levels of intrahepatic exhausted CD8+ T (Tex) cells. In IA, Tex cells were mainly derived from liver-resident GZMK+ effector memory T cells and self-expansion. By contrast, peripheral CX3CR1+ effector T cells and GZMK+ effector memory T cells were the main source of Tex cells in AR. In IA but not AR, significant cell-cell interactions were observed between Tex cells and regulatory CD4+ T cells, as well as between Tex and FCGR3A+ macrophages. Such interactions were potentially mediated through human leukocyte antigen class I molecules together with their receptors CANX and LILRBs, respectively, contributing to the dysfunction of antiviral immune responses. By contrast, CX3CR1+GNLY+ central memory CD8+ T cells were concurrently expanded in both liver and blood of AR, providing a potential surrogate marker for viral resolution. In clinic, intrahepatic Tex cells were positively correlated with serum alanine aminotransferase levels and histological grading scores. CONCLUSION: Our study dissects the coordinated immune responses for different HBV infection phases and provides a rich resource for fully understanding immunopathogenesis and developing effective therapeutic strategies.
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Linfocitos T CD8-positivos , Hígado , Humanos , Hígado/patología , Antivirales , Linfocitos T Reguladores , Análisis de Secuencia de ARN , Virus de la Hepatitis BRESUMEN
In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the single-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful applications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commercial industry.
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SARS-CoV-2 Omicron variant infection generally gives rise to asymptomatic to moderate COVID-19 in vaccinated people. The immune cells can be reprogrammed or "imprinted" by vaccination and infections to generate protective immunity against subsequent challenges. Considering the immune imprint in Omicron infection is unclear, here we delineate the innate immune landscape of human Omicron infection via single-cell RNA sequencing, surface proteome profiling, and plasma cytokine quantification. We found that monocyte responses predominated in immune imprints of Omicron convalescents, with IL-1ß-associated and interferon (IFN)-responsive signatures with mild and moderate symptoms, respectively. Low-density neutrophils increased and exhibited IL-1ß-associated and IFN-responsive signatures similarly. Mild convalescents had increased blood IL-1ß, CCL4, IL-9 levels and PI3+ neutrophils, indicating a bias to IL-1ß responsiveness, while moderate convalescents had increased blood CXCL10 and IFN-responsive monocytes, suggesting durative IFN responses. Therefore, IL-1ß- or IFN-responsiveness of myeloid cells may indicate the disease severity of Omicron infection and mediate post-COVID conditions.
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COVID-19 , Humanos , SARS-CoV-2 , Citocinas , Inmunidad Innata/genéticaRESUMEN
Gallbladder carcinoma (GBC) is the most common biliary tract malignancy with the lowest survival rate, primarily arising from chronic inflammation. To better characterize the progression from inflammation to cancer to metastasis, we performed single-cell RNA sequencing across samples of 6 chronic cholecystitis, 12 treatment-naive GBCs, and 6 matched metastases. Benign epithelial cells from inflamed gallbladders displayed resting, immune-regulating, and gastrointestinal metaplastic phenotypes. A small amount of PLA2G2A+ epithelial cells with copy number variation were identified from a histologically benign sample. We validated significant overexpression of PLA2G2A across in situ GBCs, together with increased proliferation and cancer stemness in PLA2G2A-overexpressing GBC cells, indicating an important role for PLA2G2A during early carcinogenesis. Malignant epithelial cells displayed pervasive cancer hallmarks and cellular plasticity, differentiating into metaplastic, inflammatory, and mesenchymal subtypes with distinct transcriptomic, genomic, and prognostic patterns. Chronic cholecystitis led to an adapted microenvironment characterized by MDSC-like macrophages, CD8+ TRM cells, and CCL2+ immunity-regulating fibroblasts. By contrast, GBC instigated an aggressive and immunosuppressive microenvironment, featured by tumor-associated macrophages, Treg cells, CD8+ TEX cells, and STMN1+ tumor-promoting fibroblasts. Single-cell and bulk RNA-seq profiles consistently showed a more suppressive immune milieu for GBCs with inflammatory epithelial signatures, coupled with strengthened epithelial-immune crosstalk. We further pinpointed a subset of senescence-like fibroblasts (FN1+TGM2+) preferentially enriched in metastatic lesions, which promoted GBC migration and invasion via their secretory phenotype. Collectively, this study provides comprehensive insights into epithelial and microenvironmental reprogramming throughout cholecystitis-propelled carcinogenesis and metastasis, laying a new foundation for the precision therapy of GBC.
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Human genetic variants can influence the severity of symptoms infected with SARS-COV-2. Several genome-wide association studies have identified human genomic risk single nucleotide polymorphisms (SNPs) associated with coronavirus disease 2019 (COVID-19) severity. However, the causal tissues or cell types underlying COVID-19 severity are uncertain. In addition, candidate genes associated with these risk SNPs were investigated based on genomic proximity instead of their functional cellular contexts. Here, we compiled regulatory networks of 77 human contexts and revealed those risk SNPs' enriched cellular contexts and associated risk SNPs with transcription factors, regulatory elements, and target genes. Twenty-one human contexts were identified and grouped into two categories: immune cells and epithelium cells. We further aggregated the regulatory networks of immune cells and epithelium cells. These two aggregated regulatory networks were investigated to reveal their association with risk SNPs' regulation. Two genomic clusters, the chemokine receptors cluster and the oligoadenylate synthetase (OAS) cluster, showed the strongest association with COVID-19 severity, and they had different regulatory programs in immune and epithelium contexts. Our findings were supported by analysis of both SNP array and whole genome sequencing-based genome wide association study (GWAS) summary statistics. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00066-x.
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The tumor microenvironment (TME) is connected to immunotherapy responses, but it remains unclear how cancer cells and host tissues differentially influence the immune composition within TME. Here, we performed single-cell analyses for autologous samples from liver metastasized colorectal cancer to disentangle factors shaping TME. By aligning CD45+ cells across different tissues, we classified exhausted CD8+ T cells (Texs) and activated regulatory T cells as M-type, whose phenotypes were associated with the malignancy, while natural killer and mucosal-associated invariant T cells were defined as N-type, whose phenotypes were associated with the niche. T cell receptor sharing between Texs in primary and metastatic tumors implicated the presence of common peripheral non-exhausted precursors. For myeloid cells, a subset of dendritic cells (DC3s) and SPP1+ macrophages were M-type, and the latter were predominant in liver metastasis, indicating its pro-metastasis role. Our analyses bridge immune phenotypes of primary and metastatic tumors, thereby helping to understand the tumor-specific contexture and identify the pro-metastasis components.
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Neoplasias Colorrectales , Neoplasias Hepáticas , Linfocitos T CD8-positivos , Neoplasias Colorrectales/patología , Humanos , Inmunoterapia , Neoplasias Hepáticas/genética , Microambiente TumoralRESUMEN
The cell-mediated protective and pathogenic immune responses to SARS-CoV-2 infection remain largely elusive. Here we identified 76 distinct cell subsets in the PBMC samples that were associated with various clinical presentations of COVID-19 using scRNA-seq technology coupled with a deep and comprehensive analysis of unique cell surface markers and differentially expressed genes. We revealed that (TRAV1-2+CD8+)MAIT cells and (NCAM1hiCD160+)NK cells significantly enriched in the asymptomatic subjects whereas (LAG3+CD160+CD8+)NKT cells increased in the symptomatic patients. We also observed that (CD68-CSF1R-IL1BhiCD14+)classical monocytes were positively correlated with the disease severity. Moreover, (CD33-HLA-DMA-CD14+)classical monocytes and (CLEC10A-S100A9lo)pDC were associated with the viral persistence. The GO and KEGG analyses identified enriched pathways related to immune responses, inflammation, and apoptosis. These findings may enhance our understanding of the immunopathogenesis of COVID-19 and help develop novel strategies against SARS-CoV-2 infection.
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COVID-19/diagnóstico , COVID-19/inmunología , Células Asesinas Naturales/inmunología , Monocitos/inmunología , Células T Invariantes Asociadas a Mucosa/inmunología , Células T Asesinas Naturales/inmunología , SARS-CoV-2/fisiología , Infecciones Asintomáticas , Femenino , Citometría de Flujo , Humanos , Inmunofenotipificación , Masculino , Persona de Mediana Edad , Índice de Severidad de la Enfermedad , Carga ViralRESUMEN
Liquid-liquid phase separation (LLPS) is an important mechanism that mediates the formation of biomolecular condensates. Despite the immense interest in LLPS, phase-separated proteins verified by experiments are still limited, and identification of phase-separated proteins at proteome-scale is a challenging task. Multivalent interaction among macromolecules is the driving force of LLPS, which suggests that phase-separated proteins may harbor distinct biological characteristics in protein-protein interactions (PPIs). In this study, we constructed an integrated human PPI network (HPIN) and mapped phase-separated proteins into it. Analysis of the network parameters revealed differences of network topology between phase-separated proteins and others. The results further suggested the efficiency when applying topological similarities in distinguishing components of MLOs. Furthermore, we found that affinity purification mass spectrometry (AP-MS) detects PPIs more effectively than yeast-two hybrid system (Y2H) in phase separation-driven condensates. Our work provides the first global view of the distinct network topology of phase-separated proteins in human interactome, suggesting incorporation of PPI network for LLPS prediction in further studies.
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Espectrometría de Masas/métodos , Mapeo de Interacción de Proteínas/métodos , Proteínas/química , Proteínas/metabolismo , Condensados Biomoleculares/química , Fenómenos Biofísicos , Análisis por Conglomerados , Humanos , Proteínas Intrínsecamente Desordenadas/química , Proteínas Intrínsecamente Desordenadas/metabolismo , Orgánulos/metabolismo , Transición de Fase , Técnicas del Sistema de Dos HíbridosRESUMEN
Liver metastasis is associated with immunotherapy resistance, although the underlying mechanisms remain incompletely understood. By applying single cell RNA-sequencing to a concurrent subcutaneous and liver tumor murine model to recapitulate liver metastases, it is identified that subsets within tumor-infiltrating exhausted CD8+ T (Tex) cells and immunosuppressive tumor-associated macrophages (TAMs) display opposite responses to concurrent liver tumors and anti-PD-1 treatment, suggesting a complex immune regulating network. Both angiogenic and interferon-reactive TAMs show increased frequencies in implanted liver tumors, and anti-PD-1 treatment further elevates the frequencies of angiogenic TAMs. Such TAMs frequencies negatively correlate with the proportions of cytotoxic T cell subsets. Further, expression of interferon-stimulated genes in TAMs is dramatically reduced under effective anti-PD-1 treatment, while such tendencies are diminished in mice with implanted liver tumors. Therefore, the study indicates that liver metastases could increase immunosuppressive TAMs frequencies and inhibit Tex responses to PD-1 blockade, resulting in compromised systemic antitumor immunity and limited immunotherapy efficacy.
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Mycosis fungoides (MF), the most common form of cutaneous T-cell lymphoma, undergo large-cell transformation (LCT) in the late stage, manifesting aggressive behavior, resistance to treatments, and poor prognosis, but the mechanisms involved remain unclear. To identify the molecular driver of LCT, we collected tumor samples from 133 MF patients and performed whole-transcriptome sequencing on 49 advanced-stage MF patients, followed by integrated copy number inference and genomic hybridization. Tumors with LCT showed unique transcriptional programs and enriched expressions of genes at chr7q. Paternally expressed gene 10 (PEG10), an imprinted gene at 7q21.3, was ectopically expressed in malignant T cells from LCT, driven by 7q21.3 amplification. Mechanistically, aberrant PEG10 expression increased cell size, promoted cell proliferation, and conferred treatment resistance by a PEG10/KLF2/NF-κB axis in in vitro and in vivo models. Pharmacologically targeting PEG10 reversed the phenotypes of proliferation and treatment resistance in LCT. Our findings reveal new molecular mechanisms underlying LCT and suggest that PEG10 inhibition may serve as a promising therapeutic approach in late-stage aggressive T-cell lymphoma.
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Proteínas Reguladoras de la Apoptosis/genética , Transformación Celular Neoplásica/genética , Proteínas de Unión al ADN/genética , Linfoma Cutáneo de Células T/genética , Proteínas de Unión al ARN/genética , Neoplasias Cutáneas/genética , Animales , Línea Celular Tumoral , Transformación Celular Neoplásica/patología , Femenino , Amplificación de Genes , Regulación Neoplásica de la Expresión Génica , Impresión Genómica , Humanos , Linfoma Cutáneo de Células T/patología , Ratones Endogámicos NOD , Ratones SCID , Micosis Fungoide/genética , Micosis Fungoide/patología , Neoplasias Cutáneas/patologíaRESUMEN
T cells play a central role in cancer immunotherapy, but we lack systematic comparison of the heterogeneity and dynamics of tumor-infiltrating T cells across cancer types. We built a single-cell RNA-sequencing pan-cancer atlas of T cells for 316 donors across 21 cancer types and revealed distinct T cell composition patterns. We found multiple state-transition paths in the exhaustion of CD8+ T cells and the preference of those paths among different tumor types. Certain T cell populations showed specific correlation with patient properties such as mutation burden, shedding light on the possible determinants of the tumor microenvironment. T cell compositions within tumors alone could classify cancer patients into groups with clinical trait specificity, providing new insights into T cell immunity and precision immunotherapy targeting T cells.