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A factor-based analysis of individual human microglia uncovers regulators of an Alzheimer-related transcriptional signature.
Human microglial heterogeneity is only beginning to be appreciated at the molecular level. Here, we present a large, single-cell atlas of expression signatures from 441,088 live microglia broadly sampled across a diverse set of brain regions and neurodegenerative and neuroinflammatory diseases obtained from 161 donors sampled at autopsy or during a neurosurgical procedure. Using single-cell hierarchical Poisson factorization (scHPF), we derived a 23-factor model for continuous gene expression signatures across microglia which capture specific biological processes (e.g., metabolism, phagocytosis, antigen presentation, inflammatory signaling, disease-associated states). Using external datasets, we evaluated the aspects of microglial phenotypes that are encapsulated in various in vitro and in vivo microglia models and identified and replicated the role of two factors in human postmortem tissue of Alzheimer's disease (AD). Further, we derived a complex network of transcriptional regulators for all factors, including regulators of an AD-related factor enriched for the mouse disease-associated microglia 2 (DAM2) signature: ARID5B, CEBPA, MITF, and PPARG. We replicated the role of these four regulators in the AD-related factor and then designed a multiplexed MERFISH panel to assess our microglial factors using spatial transcriptomics. We find that, unlike cells with high expression of the interferon-response factor, cells with high expression of the AD DAM2-like factor are widely distributed in neocortical tissue. We thus propose a novel analytic framework that provides a taxonomic approach for microglia that is more biologically interpretable and use it to uncover new therapeutic targets for AD.
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Precancer Atlas to Drive Precision Prevention Trials.
Cancer development is a complex process driven by inherited and acquired molecular and cellular alterations. Prevention is the holy grail of cancer elimination, but making this a reality will take a fundamental rethinking and deep understanding of premalignant biology. In this Perspective, we propose a national concerted effort to create a Precancer Atlas (PCA), integrating multi-omics and immunity - basic tenets of the neoplastic process. The biology of neoplasia caused by germline mutations has led to paradigm-changing precision prevention efforts, including: tumor testing for mismatch repair (MMR) deficiency in Lynch syndrome establishing a new paradigm, combinatorial chemoprevention efficacy in familial adenomatous polyposis (FAP), signal of benefit from imaging-based early detection research in high-germline risk for pancreatic neoplasia, elucidating early ontogeny in BRCA1-mutation carriers leading to an international breast cancer prevention trial, and insights into the intricate germline-somatic-immunity interaction landscape. Emerging genetic and pharmacologic (metformin) disruption of mitochondrial (mt) respiration increased autophagy to prevent cancer in a Li-Fraumeni mouse model (biology reproduced in clinical pilot) and revealed profound influences of subtle changes in mt DNA background variation on obesity, aging, and cancer risk. The elaborate communication between the immune system and neoplasia includes an increasingly complex cellular microenvironment and dynamic interactions between host genetics, environmental factors, and microbes in shaping the immune response. Cancer vaccines are in early murine and clinical precancer studies, building on the recent successes of immunotherapy and HPV vaccine immune prevention. Molecular monitoring in Barrett's esophagus to avoid overdiagnosis/treatment highlights an important PCA theme. Next generation sequencing (NGS) discovered age-related clonal hematopoiesis of indeterminate potential (CHIP). Ultra-deep NGS reports over the past year have redefined the premalignant landscape remarkably identifying tiny clones in the blood of up to 95% of women in their 50s, suggesting that potentially premalignant clones are ubiquitous. Similar data from eyelid skin and peritoneal and uterine lavage fluid provide unprecedented opportunities to dissect the earliest phases of stem/progenitor clonal (and microenvironment) evolution/diversity with new single-cell and liquid biopsy technologies. Cancer mutational signatures reflect exogenous or endogenous processes imprinted over time in precursors. Accelerating the prevention of cancer will require a large-scale, longitudinal effort, leveraging diverse disciplines (from genetics, biochemistry, and immunology to mathematics, computational biology, and engineering), initiatives, technologies, and models in developing an integrated multi-omics and immunity PCA - an immense national resource to interrogate, target, and intercept events that drive oncogenesis. Cancer Res; 77(7); 1510-41. ©2017 AACR.
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Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses.
Assays linking cellular phenotypes with T cell or B cell antigen receptor sequences are crucial for characterizing adaptive immune responses. Existing methodologies are limited by low sample throughput and high cost. Here, we present INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach that combines molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility.
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Mechanism- and Immune Landscape-Based Ranking of Therapeutic Responsiveness of 22 Major Human Cancers to Next Generation Anti-CTLA-4 Antibodies.
BACKGROUND: CTLA-4 was the first immune checkpoint targeted for cancer therapy and the first target validated by the FDA (Food and Drug Administration) after approval of the anti-CTLA-4 antibody, Ipilimumab. However, clinical response rates to anti-CTLA-4 antibodies are lower while the rates of immunotherapy-related adverse events (irAE) are higher than with anti-PD-1 antibodies. As a result, the effort to target CTLA-4 for cancer immunotherapy has stagnated. To reinvigorate CTLA-4-targeted immunotherapy, we and others have reported that rather than blocking CTLA-4 interaction with its cognate targets, CD80 and CD86, anti-CTLA-4 antibodies achieve their therapeutic responses through selective depletion of regulatory T cells in the tumor microenvironment. Accordingly, we have developed a new generation of anti-CTLA-4 antibodies with reduced irAE and enhanced antibody-dependent cell-mediated cytotoxicity/phagocytosis (ADCC/ADCP). A major unresolved issue is how to select appropriate cancer types for future clinical development. METHODS: We generated a landscape of the immune tumor microenvironment from RNAseq and genomic data of 7279 independent cancer samples belonging to 22 cancer types from The Cancer Genomics Atlas (TCGA) database. Based primarily on genomic and RNAseq data from pre-treatment clinical samples of melanoma patients who were later identified as responders and nonresponders to the anti-CTLA-4 antibody Ipilimumab, we identified 5 ranking components of responsiveness to anti-CTLA-4, including CTLA-4 gene expression, ADCC potential, mutation burden, as well as gene enrichment and cellular composition that favor CTLA-4 responsiveness. The total ranking number was calculated by the sum of 5 independent partitioning values, each comprised of 1-3 components. RESULTS: Our analyses predict metastatic melanoma as the most responsive cancer, as expected. Surprisingly, non-small cell lung carcinoma (NSCLC) is predicted to be highly responsive to anti-CTLA-4 antibodies. Single-cell RNAseq analysis and flow cytometry of human NSCLC-infiltrating T cells supports the potential of anti-CTLA-4 antibodies to selectively deplete intratumoral Treg. CONCLUSIONS: Our in silico and experimental analyses suggest that non-small cell lung carcinoma will likely respond to a new generation of anti-CTLA-4 monoclonal antibodies. Our approach provides an objective ranking of the sensitivity of human cancers to anti-CTLA-4 antibodies. The comprehensive ranking of major cancer types provides a roadmap for clinical development of the next generation of anti-CTLA-4 antibodies.
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Multiphase enhanced computed tomography features captured by delta radiomics reveal prognosis and tumor heterogeneity in patients with hepatocellular carcinoma treated with transarterial chemoembolization.
BACKGROUND: Although transarterial chemoembolization (TACE) is a widely used locoregional therapy for intermediate-stage hepatocellular carcinoma (HCC), there is substantial inter-patient heterogeneity in treatment response. This study aimed to develop a delta radiomic model based on pre-treatment enhanced computed tomography (CT) to predict the prognosis of HCC patients undergoing TACE and to reveal tumor heterogeneity. METHODS: A total of 269 patients treated with TACE between January 2016 and June 2020 were enrolled from two medical centers and divided into three cohorts: a training cohort (n = 126), an internal validation cohort (n = 84), an external test cohort (n = 59). Radiological features of the tumor area were extracted on multiple phases of CT before treatment, and progression-free survival (PFS) was predicted through the least absolute shrinkage and selection operator Cox (LASSO-Cox) regression algorithm. Overall survival (OS) was evaluated using the Kaplan-Meier curve. Genetic and tumor microenvironment differences related to the prognosis of TACE were analyzed in 23 patients with CT from The Cancer Genome Atlas (TCGA). Single-cell data from the comprehensive Gene Expression Omnibus (GEO) public database were used to explore the expression of different genes in cells. RESULTS: The area under the receiver operating characteristic curves of the delta radiomic model for predicting 2-year PFS in TACE-treated patients were 0.812, 0.720, and 0.807 in the training, internal validation, and external test cohorts, respectively. The Rad-score was calculated based on radiomic features selected through LASSO. The Rad-score stratified patients into high- and low-risk groups, with significant differences in OS across all cohorts. The high-risk group had a higher immune score. It is worth noting that in the immune infiltration analysis, there were significant differences in B cells, resting CD4 memory T cells, active natural killer cells, and mast cells among different risk groups. CONCLUSIONS: The delta radiomics model based on multiphase enhanced CT accurately predicts prognosis and reflects tumor heterogeneity in HCC patients treated with TACE, and contributes to treatment planning.
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Focal Adhesion Kinase-Dependent Reprogramming of IFN-γ Signaling through PYK2 Coinhibition Sensitizes Melanoma to Immune Checkpoint Blockade.
Immune checkpoint blockade has transformed melanoma therapy but is frequently limited by acquired resistance. Focal adhesion kinase (FAK) and its homolog PYK2 are nonreceptor tyrosine kinases that coordinate cell-matrix adhesion and cytoskeletal signaling. In this study, we define the distinct roles of FAK (as the principal scaffold) and PYK2 (in a supportive capacity) in IFN-γ-mediated immune checkpoint blockade resistance. Label-free phosphoproteomic profiling revealed that IFN-γ stimulation drives extensive phosphorylation across pathways governing cytoskeletal remodeling, transcriptional regulation, mRNA splicing, and ribosomal RNA biogenesis. Selective FAK inhibition markedly suppressed IFN-γ-induced signal transducer and activator of transcription 1 and PD-L1 upregulation, and the addition of PYK2 blockade achieved maximal suppression, culminating in enhanced CD8+ T-cell-mediated tumor cytotoxicity. In an anti-PD-1-resistant murine melanoma model, high tumoral FAK expression correlated with treatment failure. Analysis of The Cancer Genome Atlas-Skin Cutaneous Melanoma cohort showed that FAK levels associate with immunosuppressive gene signatures, whereas in an independent clinical dataset (GSE91061), patients exhibiting post-treatment downregulation of FAK experienced improved outcomes. Single-cell RNA sequencing distinguished tumor cell-intrinsic FAK expression from PYK2 enrichment in immune subsets. Together, these data position FAK as the dominant driver of IFN-γ-dependent resistance, with PYK2 playing a subsidiary role, and suggest that selective FAK targeting-potentially combined with limited PYK2 inhibition-may overcome immune checkpoint blockade resistance in melanoma.
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Spatial characterization of skin lesions in discoid and systemic lupus erythematosus.
Lupus erythematosus (LE) skin lesions are associated with significant dysregulation of the local immune microenvironment. However, the spatial distribution and interactions between stromal and immune cells within affected tissues remain poorly characterized. In this study, we employed Stereo-seq to construct a single-cell resolution spatial transcriptomic atlas of lesional skin from patients with discoid lupus erythematosus (DLE) and systemic lupus erythematosus (SLE). Our analysis revealed that keratinocyte subpopulations in distinct differentiation states presented cell type-specific profiles of inflammatory mediator expression. Notably, a subset of stress keratinocytes located predominantly at the epidermis-dermis interface mediated the recruitment of T cells and plasma cells, potentially through an IFN-γ-JAK-STAT axis driving CXCL9/10/11-CXCR3 signaling, and these effects were more pronounced in active SLE lesions compared to chronic DLE lesions. Spatial profiling revealed immune cell niches resembling tertiary lymphoid structures (TLS), which were particularly prominent in chronic DLE and SLE lesions. These lupus-associated TLS structures were characterized by the coordinated infiltration of multiple cell subsets, including age-associated B cells, precursors of germinal center B cells, naïve B cells, regulatory T cells, T peripheral helper and/or T follicular helper cells, memory T cells, and CCL14+ vascular endothelial cells, which presented the spatial characteristics of the lymphoid follicle-like structures in chronic LE skin lesions. Collectively, our findings provide a comprehensive spatial characterization of the cellular components and molecular features within LE skin lesions.
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A hypoxia-responsive migrasome-related lncRNA signature predicts prognosis and suggests the MSC-AS1/ITGA5 axis as a potential therapeutic target in head and neck squamous cell carcinoma.
Head and neck squamous cell carcinoma (HNSCC) is an aggressive malignancy associated with dismal prognosis. Migrasomes, a unique class of migration-dependent extracellular vesicles, have emerged as pivotal mediators of intercellular crosstalk within the tumor microenvironment. However, the clinical implications and regulatory mechanisms of migrasome-related long non-coding RNAs (MRLs) in HNSCC remain largely unexplored. Herein, we retrieved transcriptomic and clinical data of HNSCC from The Cancer Genome Atlas (TCGA) and established a prognostic signature using LASSO-Cox regression analysis, which was further internally validated in a randomly split subset of the TCGA cohort as internal validation. We systematically characterized the immune microenvironment and drug sensitivity profiles stratified by this signature, and identified the cellular distribution of core MRLs via single-cell RNA sequencing. Functional experiments were performed in clinical specimens and HNSCC cell lines using RT-qPCR, Western blot, CCK-8, and wound-healing assays. Consequently, a 10-MRL prognostic model was constructed to effectively stratify patients into high- and low-risk groups with significantly divergent overall survival, representing an independent prognostic factor in the context of the available clinical covariates from TCGA. High-risk patients exhibited an immunosuppressive tumor microenvironment and activation of oncogenic pathways (NF-κB, JAK-STAT). Mechanistically, MSC-AS1 was upregulated in HNSCC and facilitated cell proliferation and migration. Hypoxia upregulated the MSC-AS1/ITGA5 axis and increased VEGFA/PD-L1 expression, along with changes in the migrasome-related protein TSPAN4, suggesting a potential association with migrasome-related molecular features, which requires direct experimental validation. Collectively, our findings establish a novel MRL-based signature for prognostic prediction in HNSCC and highlight the hypoxia-responsive MSC-AS1/ITGA5 axis as a promising target for combinatorial therapeutic strategies.
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Serum response factor is essential for endometrial function and prevention of inflammatory fibrosis.
Pregnancy requires a supportive uterine environment facilitated by steroid hormone-regulated differentiation of endometrial stromal fibroblasts into decidual cells and tight control of inflammation. Serum response factor (SRF) is a widely expressed transcription factor essential for mesenchymal cell growth and differentiation with noted roles in hormonal regulation of muscle tissues but little characterization in reproductive organs. Here, we reveal that endometrial SRF is dysregulated in human endometriosis and is critical for female reproductive success in mice through regulation of endometrial stromal and epithelial cells. Immunohistochemical analysis identified decreased endometrial SRF expression in infertile endometriosis patient tissues. RNAi-based SRF knockdown in human endometrial stromal cells resulted in disrupted cytoskeletal structure, viability, and decidual response. Conditional Srf knockout mice (Srfd/d) generated using the PgrCre were infertile with implantation failure, lack of decidual response, and development of severe endometrial fibrosis. Single-cell RNA sequencing identified dramatic changes in Srfd/d endometrial cell populations including large-scale myeloid immune cell infiltration. Srfd/d stromal fibroblasts displayed aberrant cytoskeletal and extracellular matrix gene expression and downregulation of genes important for decidual growth response. Srf-deficient epithelial cells displayed the most prominent dysregulation, strongly overexpressing estrogenic innate inflammatory genes including C3 and Lcn2 and fibrogenic genes Mmp7 and Fbln1, all of which paralleled patterns in human endometriosis patient data that we identified through comparative analysis using a published single-cell atlas. These results demonstrate the profound impact of SRF on endometrial homeostasis with relevance to human endometriosis-related infertility.
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Identification of novel cuproptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of breast cancer patients.
BACKGROUND: Cuproptosis is a new modality of cell death regulation that is currently considered as a new cancer treatment strategy. Nevertheless, the prognostic predictive value of cuproptosis-related lncRNAs in breast cancer (BC) remains unknown. Using cuproptosis-related lncRNAs, this study aims to predict the immune microenvironment and prognosis of BC patients. and develop new therapeutic strategies that target the disease. METHODS: The Cancer Genome Atlas (TCGA) database provided the RNA-seq data along with the corresponding clinical and prognostic information. Univariate and multivariate Cox regression analyses were performed to acquire lncRNAs associated with cuproptosis to establish predictive features. The Kaplan-Meier method was used to calculate the overall survival rate (OS) in the high-risk and low-risk groups. High risk and low risk gene sets were enriched to explore functional discrepancies among risk teams. The mutation data were analyzed using the "MAFTools" r-package. The ties of predictive characteristics and immune status had been explored by single sample gene set enrichment analysis (ssGSEA). Last, the correlation between predictive features and treatment condition in patients with BC was analyzed. Based on prognostic risk models, we assessed associations between risk subgroups and immune scores and immune checkpoints. In addition, drug responses in at-risk populations were predicted. RESULTS: We identified a set of 11 Cuproptosis-Related lncRNAs (GORAB-AS1, AC 079922.2, AL 589765.4, AC 005696.4, Cytor, ZNF 197-AS1, AC 002398.1, AL 451085.3, YTH DF 3-AS1, AC 008771.1, LINC 02446), based on which to construct the risk model. In comparison to the high-risk group, the low-risk patients lived longer (p < 0.001). Moreover, cuproptosis-related lncRNA profiles can independently predict prognosis in BC patients. The AUC values for receiver operating characteristics (ROC) of 1-, 3-, and 5-year risk were 0.849, 0.779, and 0.794, respectively. Patients in the high-risk group had lower OS than those in the low-risk group when they were divided into groups based on various clinicopathological variables. The tumor burden mutations (TMB) correlation analysis showed that high TMB had a worse prognosis than low-TMB, and gene mutations were found to be different in high and low TMB groups, such as PIK3CA (36% versus 32%), SYNE1 (4% versus 6%). Gene enrichment analysis indicated that the differential genes were significantly concentrated in immune-related pathways. The predictive traits were significantly correlated with the immune status of BC patients, according to ssGSEA results. Finally, high-risk patients showed high sensitivity in anti-CD276 immunotherapy and conventional chemotherapeutic drugs such as imatinib, lapatinib, and pazopanib. CONCLUSION: We successfully constructed of a cuproptosis-related lncRNA signature, which can independently predict the prognosis of BC patients and can be used to estimate OS and clinical treatment outcomes in BRCA patients. It will serve as a foundation for further research into the mechanism of cuproptosis-related lncRNAs in breast cancer, as well as for the development of new markers and therapeutic targets for the disease.