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A single-cell atlas of the human substantia nigra reveals cell-specific pathways associated with neurological disorders.
We describe a human single-nuclei transcriptomic atlas for the substantia nigra (SN), generated by sequencing approximately 17,000 nuclei from matched cortical and SN samples. We show that the common genetic risk for Parkinson's disease (PD) is associated with dopaminergic neuron (DaN)-specific gene expression, including mitochondrial functioning, protein folding and ubiquitination pathways. We identify a distinct cell type association between PD risk and oligodendrocyte-specific gene expression. Unlike Alzheimer's disease (AD), we find no association between PD risk and microglia or astrocytes, suggesting that neuroinflammation plays a less causal role in PD than AD. Beyond PD, we find associations between SN DaNs and GABAergic neuron gene expression and multiple neuropsychiatric disorders. Conditional analysis reveals that distinct neuropsychiatric disorders associate with distinct sets of neuron-specific genes but converge onto shared loci within oligodendrocytes and oligodendrocyte precursors. This atlas guides our aetiological understanding by associating SN cell type expression profiles with specific disease risk.
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Characterization of neutrophil extracellular traps related gene pair for predicting prognosis in hepatocellular carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant disease with a high incidence rate, high mortality and poor prognosis. Neutrophil extracellular traps (NETs), as an extracellular reticular structure, promote the development and progression of cancer in the tumor microenvironment, and have a promising prospect as a prognostic indicator. In the present study, we elucidated the prognostic value of NET-related genes. METHODS: The NETs gene pair of The Cancer Genome Atlas cohort was constructed by least absolute shrinkage and selection operator analysis. Samples from the International Cancer Genome Consortium were performed to verify its feasibility. Kaplan-Meier analysis was used to compare the overall survival (OS) rate of the two subgroups. The independent predictors of OS were determined by univariate and multivariate Cox analysis. Furthermore, Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway were analyzed by gene set enrichment analysis. The single sample gene set enrichment analysis method was performed to deplore the relationship of risk score with tumor immune microenvironment. The GSE149614 dataset was applied as single cell RNA level validation. PCR was performed to the detect mRNA expression profiles of NETs-related genes. RESULTS: Our analysis of the NETs-related model provides a promising prospect as a prognostic indicator. The OS of high-risk group patients was significantly reduced. The risk score was an important independent predictor of HCC prognosis. The Nomogram model suggested a favorable classification performance. The drug resistance and sensitivity of tumor cells to chemotherapeutics was significantly correlated with the prognostic gene expression. The immune status of the two risk groups showed a marked difference. CONCLUSIONS: The novel prognostic gene pair and immune landscape could predict the prognosis of HCC patients and provide a new understanding of immunotherapy in HCC.
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The Identification of a Tumor Infiltration CD8+ T-Cell Gene Signature That Can Potentially Improve the Prognosis and Prediction of Immunization Responses in Papillary Renal Cell Carcinoma.
BACKGROUND: CD8+ T cells, vital effectors pertaining to adaptive immunity, display close relationships to the immunization responses to kill tumor cells. Understanding the effect exerted by tumor infiltration CD8+ T cells in papillary renal cell carcinoma (papRCC) is critical for assessing the prognosis process and responses to immunization therapy in cases with this disease. MATERIALS AND APPROACHES: The single-cell transcriptome data of papRCC were used for screening CD8+ T-cell-correlated differentially expressed genes to achieve the following investigations. On that basis, a prognosis gene signature associated with tumor infiltration CD8+ T cell was built and verified with The Cancer Genome Atlas data set. Risk scores were determined for papRCC cases and categorized as high- or low-risk groups. The prognosis significance for risk scores was assessed with multiple-variate Cox investigation and Kaplan-Meier survival curves. In addition, the possible capability exhibited by the genetic profiles of cases to assess the response to immunization therapy was further explored. RESULTS: Six hundred twenty-one cell death-inhibiting RNA genes were screened using single-cell RNA sequencing. A gene signature consisting of seven genes (LYAR, YBX1, PNRC1, TCF25, MYL12B, MINOS1, and LINC01420) was then identified, and this collective was considered to be an independent prognosis indicator that could strongly assess overall survival in papRCC. In addition, the data allowed papRCC cases to fall to cohorts at high and low risks, exhibiting a wide range of clinically related features as well as different CD8+ T-cell immunization infiltration and immunization therapy responses. CONCLUSIONS: Our work provides a possible explanation for the limited response of current immunization checkpoint-inhibiting elements for combating papRCC. Furthermore, the researchers built a novel genetic signature that was able to assess the prognosis and immunotherapeutic response of cases. This may also be considered as a promising therapeutic target for the disease.
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Molecular profiling of skin cells identifies distinct cellular signatures in radiation-induced skin injury across various stages in the murine dataset.
BACKGROUND: Radiation-induced skin injury (RISI) commonly manifests in cancer patients undergoing radiotherapy (RT). However, a universally accepted standard for treating radiation injury has not yet been established. Our objective was to provide a detailed molecular overview of skin pre- and post-radiation therapy, aiming to enhance our understanding of the subclusters and molecular mechanisms contributing to radiodermatitis. METHODS: C57BL/6 mice were subjected to a single fraction (20 Gy) of RT targeting the right dorsal skin. We then employed integrated single-cell RNA sequencing (scRNA-seq) to analyze skin samples from mice at 7 and 30 days after radiation exposure, as well as from non-irradiated mice. The Seurat analysis pipeline, Cellchat, SCP, and ssGSEA were used to define the cell types and mechanisms involved in radiation-induced skin injury. Reverse transcription polymerase chain reaction (RT-PCR), multiplex immunofluorescent staining, and other datasets (GSE130183, GSE193564, and GSE193807) were used to validate our findings. RESULTS: Thirty-two distinct cell clusters encompassing 71,412 cells were identified. We discovered that cycling keratinocytes (KCs), with the BMP signaling pathway enriched, could activate the Wnt pathway, as well as the SMAD pathways, driving the wound healing and fibrosis processes in RISI. Terminally differentiated secretory-papillary fibroblasts (Fibs) are capable of attracting immune cells, which contributes to the pathogenesis of RISI. Lymphatic endothelial cells (ECs) with pro-inflammatory properties play a critical role in the pathogenesis of RISI by facilitating leukocyte migration. Our analysis also highlighted enhanced ligand-receptor interactions, notably the interactions between chemokines like CXCL10, CCL2, and ACKR1, across subclusters of inflammatory KCs, Fibs, ECs, and immune cells, underscoring their pivotal role in leukocyte recruitment in RISI. CONCLUSIONS: Cycling KCs, secretory-papillary Fibs, and lymphatic ECs play critical roles in RISI progression. Targeting the interactions of these subclusters with immune cells might help improve the severity of RISI. Furthermore, our study provides a valuable resource for understanding the interactions among immune cells in the context of RISI.
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A single-cell atlas of non-haematopoietic cells in human lymph nodes and lymphoma reveals a landscape of stromal remodelling.
The activities of non-haematopoietic cells (NHCs), including mesenchymal stromal cells and endothelial cells, in lymphomas are reported to underlie lymphomagenesis. However, our understanding of lymphoma NHCs has been hampered by unexplained NHC heterogeneity, even in normal human lymph nodes (LNs). Here we constructed a single-cell transcriptome atlas of more than 100,000 NHCs collected from 27 human samples, including LNs and various nodal lymphomas, and it revealed 30 distinct subclusters, including some that were previously unrecognized. Notably, this atlas was useful for comparative analyses with lymphoma NHCs, which revealed an unanticipated landscape of subcluster-specific changes in gene expression and interaction with malignant cells in follicular lymphoma NHCs. This facilitates our understanding of stromal remodelling in lymphoma and highlights potential clinical biomarkers. Our study largely updates NHC taxonomy in human LNs and analysis of disease status, and provides a rich resource and deeper insights into LN and lymphoma biology to advance lymphoma management and therapy.
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Aged hippocampal single-cell atlas screening unveils disrupted neuroglial system in postoperative cognitive impairment.
Glia-neuron interaction is a crucial feature in aged hippocampus during the occurrence of postoperative cognitive impairment. However, the regulatory effects of microglia, astrocytes, and oligodendrocytes in this glia-neuron interaction, the potential mechanisms and gene targets are still to be elucidated. Here, single-cell RNA sequencing was performed to detect the perioperative genomic expression characteristics of neuroglial system in the hippocampus of aged mice, and to investigate the potential cross-cellular mechanisms and valuable treatment options for glia-neuron interaction-related cognitive impairment. We found that postoperative neurons and glia cells exhibited protein dysmetabolism and mitochondrial electron misrouting. Impaired autophagy and circadian rhythm worsened microglia activation/neuroinflammation, and exacerbated these metabolic alterations. Reactive microglia also aggravated astrocyte and oligodendrocyte cytotoxicity through the PGD2/DP and complement pathways, altering glutamate level and synaptic function via the "tripartite synapses" model, and affecting neuronal myelination. Ligand-receptor communication also indicated these synaptic and axonal dysfunctions via enhanced MDK and PTN pathways. Additionally, we found that anesthetic dexmedetomidine hold therapeutic potential within the disrupted neuroglial system. It enhanced neuronal metabolic rebalance (Atf3-related) and reduced neuroinflammation from a multicellular perspective, therefore improving postoperative cognitive impairment. Together, our study proposes an aged hippocampal cell atlas and provides insights into the role of disrupted glia-neuron cycle in postoperative cognitive impairment. Our findings also elucidate the therapeutic potential and mechanism of dexmedetomidine intervention.
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Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer.
Background: Ground-glass opacity (GGO)-associated cancers are increasingly prevalent, exhibiting unique clinical and molecular features that suggest the need for a distinct treatment strategy. However, the metabolic characteristics and vulnerabilities of GGO-associated lung cancers remain unexplored. Methods: We conducted metabolomic and transcriptomic analyses on 40 pairs of GGO-associated lung cancer tissues and adjacent normal tissues. By integrating data from TCGA database and single-cell RNA sequencing, we aimed to identify aberrant metabolic pathways, establish a metabolite-associated gene signature, and pinpoint key metabolic genes. The physiological effect of key genes was detected in vitro and vivo assays. Results: We identified a 30-gene metabolite-associated signature and discovered aberrant metabolic pathways for GGO-associated lung cancer at both metabolic and transcriptional levels. Patients with this signature displayed specific prognostic and molecular features. Cox regression analysis, based on the Cancer Genome Atlas Program (TCGA) data, further narrowed down the metabolite-related gene signature, resulting in a 5-gene signature. Confirmed by single-cell RNA sequencing (GSE203360), the 5-gene signature was mainly expressed in cancer cells of GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential expression of these genes between GGO and adjacent normal tissue obtained from pulmonary surgery. Finally, our integrative analysis unveiled aberrant histidine metabolism at both the multi-omics and single-cell levels. Moreover, we identified MAOB as a key metabolic gene, demonstrating its ability to suppress cell proliferation, migration, and invasion in LUAD cell lines, both in vitro and in vivo. Conclusions: We identified a specific metabolite-associated gene signature and identified aberrant histidine metabolism in GGO-associated lung cancer from multiple perspectives. Notably, MAOB, a crucial component in histidine metabolism, demonstrated a significant inhibitory effect on the proliferation and metastasis of LUAD, indicating its potential significance in pathogenesis and therapeutic interventions.
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Single-cell and spatial transcriptomics identify COL6A3 as a prognostic biomarker in undifferentiated pleomorphic sarcoma.
Undifferentiated pleomorphic sarcoma (UPS) and related tumors are the most common type of soft tissue sarcoma. However, this spectrum of tumors has different etiologies with varying rates of metastasis and survival. Two dermal-based neoplasms in this class of pleomorphic sarcomas, atypical fibroxanthoma (AFX) and pleomorphic dermal sarcoma (PDS), are challenging to differentiate at initial biopsy but vary significantly in prognosis. We performed single-cell transcriptomics on five AFX and PDS biopsy specimens as well as both single-cell and spatial transcriptomics on one PDS excision specimen to better characterize these tumors. The top differential genes between AFX and PDS were predictive of overall survival in 17 other cancers included in the Human Protein Atlas. Of these genes, COL6A3 and BGN predicted overall survival and metastasis-free survival in independent cohorts of 46 and 38 UPS tumors, respectively. COL6A3 was most predictive of overall survival in UPS patients and outperformed an established sarcoma prognostic gene panel at predicting metastasis in UPS.
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Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types.
The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8887 TCGA, and 1261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n = 1261) including our lung cancer cohort (n = 497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.
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The emergence of transcriptional identity in somatosensory neurons.
More than twelve morphologically and physiologically distinct subtypes of primary somatosensory neuron report salient features of our internal and external environments1-4. It is unclear how specialized gene expression programs emerge during development to endow these subtypes with their unique properties. To assess the developmental progression of transcriptional maturation of each subtype of principal somatosensory neuron, we generated a transcriptomic atlas of cells traversing the primary somatosensory neuron lineage in mice. Here we show that somatosensory neurogenesis gives rise to neurons in a transcriptionally unspecialized state, characterized by co-expression of transcription factors that become restricted to select subtypes as development proceeds. Single-cell transcriptomic analyses of sensory neurons from mutant mice lacking transcription factors suggest that these broad-to-restricted transcription factors coordinate subtype-specific gene expression programs in subtypes in which their expression is maintained. We also show that neuronal targets are involved in this process; disruption of the prototypic target-derived neurotrophic factor NGF leads to aberrant subtype-restricted patterns of transcription factor expression. Our findings support a model in which cues that emanate from intermediate and final target fields promote neuronal diversification in part by transitioning cells from a transcriptionally unspecialized state to transcriptionally distinct subtypes by modulating the selection of subtype-restricted transcription factors.