Single-cell transcriptomics reveals heterogeneous progression and EGFR activation in pancreatic adenosquamous carcinoma

Pancreatic adenosquamous carcinoma (PASC) — a rare pathological pancreatic cancer (PC) type — has a poor prognosis due to high malignancy. To examine the heterogeneity of PASC, we performed single-cell RNA sequencing (scRNA-seq) profiling with sample tissues from a healthy donor pancreas, an intraductal papillary mucinous neoplasm, and a patient with PASC. Of 9,887 individual cells, ten cell subpopulations were identified, including myeloid, immune, ductal, fibroblast, acinar, stellate, endothelial, and cancer cells. Cancer cells were divided into five clusters. Notably, cluster 1 exhibited stem-like phenotypes expressing UBE2C, ASPM, and TOP2A. We found that S100A2 is a potential biomarker for cancer cells. LGALS1, NPM1, RACK1, and PERP were upregulated from ductal to cancer cells. Furthermore, the copy number variations in ductal and cancer cells were greater than in the reference cells. The expression of EREG, FCGR2A, CCL4L2, and CTSC increased in myeloid cells from the normal pancreas to PASC. The gene sets expressed by cancer-associated fibroblasts were enriched in the immunosuppressive pathways. We demonstrate that EGFR-associated ligand-receptor pairs are activated in ductal-stromal cell communications. Hence, this study revealed the heterogeneous variations of ductal and stromal cells, defined cancer-associated signaling pathways, and deciphered intercellular interactions following PASC progression.     

Single-cell RNA sequencing reveals transcriptional profiles of monocytes in HBV-infected pregnant women during mid-pregnancy

There is a growing body of evidence that innate immunity also plays an important role in the progression of hepatitis B virus (HBV) infection. However, there is less study on systematically elucidating the characteristics of innate immunity in HBV-infected pregnant women. We compared the features of peripheral blood mononuclear cells in three healthy pregnant women and three HBV-infected pregnant women by single-cell RNA sequencing. 10 DEGs were detected between groups and monocytes were the main expression source of most of the DEGs, which involved in the inflammatory response, apoptosis and immune regulation. Meanwhile, qPCR and ELISA were performed to verify above genes. Monocytes displayed immune response defect, reflecting poor ability of response to IFN. In addition, eight clusters were identified in monocytes. We identified molecular drivers in monocytes subpopulations.TNFSF10+ monocytes, MT1G+ monocytes and TUBB1+ monocytes were featured with different gene expression pattern and biological function.TNFSF10+ monocytes and MT1G+ monocytes were characterized by high levels of inflammation response.TNFSF10+ monocytes, MT1G+ monocytes and TUBB1+ monocytes showed decreased response to IFN. Our results dissects alterations in monocytes related to the immune response of HBV-infected pregnant women and provides a rich resource for fully understanding immunopathogenesis and developing effective preventing HBV intrauterine infection strategies.     

Single-cell analysis reveals metastatic cell heterogeneity in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is one of the leading causes of cancer-related death worldwide. Tumour metastasis and heterogeneity lead to poor survival outcomes and drug resistance in patients with metastatic RCC (mRCC). In this study, we aimed to assess intratumoural heterogeneity (ITH) in mRCC cells by performing a combined analysis of bulk data and single-cell RNA-sequencing data, and develop novel biomarkers for prognosis prediction on the basis of the potential molecular mechanisms underlying tumorigenesis. Eligible single-cell cohorts related to mRCC were acquired using the Gene Expression Omnibus (GEO) dataset to identify potential mRCC subpopulations. We then performed gene set variation analysis to understand the differential function in primary RCC and mRCC samples. Subsequently, we applied weighted correlation network analysis to identify coexpressing gene modules that were related to the external trait of metastasis. Protein-protein interactions were used to screen hub subpopulation-difference (sub-dif) markers (ACTG1, IL6, CASP3, ACTB and RAP1B) that might be involved in the regulation of RCC metastasis and progression. Cox regression analysis revealed that ACTG1 was a protective factor (HR < 1), whereas the other four genes (IL6, CASP3, ACTB and RAP1B) were risk factors (HR > 1). Kaplan-Meier survival analysis suggested the potential prognostic value of these sub-dif markers. The expression of sub-dif markers in mRCC was further evaluated in clinical samples by immunohistochemistry (IHC). Additionally, the genetic features of sub-dif marker expression patterns, such as genetic variation profiles, correlations with tumour-infiltrating lymphocytes (TILs), and targeted signalling pathway activities, were assessed in bulk RNA-seq datasets. In conclusion, we established novel subpopulation markers as key prognostic factors affecting EMT-related signalling pathway activation in mRCC, which could facilitate the implementation of a treatment for mRCC patients.     

Single-cell RNA sequencing analysis to characterize cells and gene expression landscapes in atrial septal defect

This study aimed to characterize the cells and gene expression landscape in atrial septal defect (ASD). We performed single-cell RNA sequencing of cells derived from cardiac tissue of an ASD patient. Unsupervised clustering analysis was performed to identify different cell populations, followed by the investigation of the cellular crosstalk by analysing ligand-receptor interactions across cell types. Finally, differences between ASD and normal samples for all cell types were further investigated. An expression matrix of 18,411 genes in 6487 cells was obtained and used in this analysis. Five cell types, including cardiomyocytes, endothelial cells, smooth muscle cells, fibroblasts and macrophages were identified. ASD showed a decreased proportion of cardiomyocytes and an increased proportion of fibroblasts. There was more cellular crosstalk among cardiomyocytes, fibroblasts and macrophages, especially between fibroblast and macrophage. For all cell types, the majority of the DEGs were downregulated in ASD samples. For cardiomyocytes, there were 199 DEGs (42 upregulated and 157 downregulated) between ASD and normal samples. PPI analysis showed that cardiomyocyte marker gene FABP4 interacted with FOS, while FOS showed interaction with NPPA. Cell trajectory analysis showed that FABP4, FOS, and NPPA showed different expression changes along the pseudotime trajectory. Our results showed that single-cell RNA sequencing provides a powerful tool to study DEG profiles in the cell subpopulations of interest at the single-cell level. These findings enhance the understanding of the underlying mechanisms of ASD at both the cellular and molecular level and highlight potential targets for the treatment of ASD.     

单细胞测序技术及其在乳腺癌研究中的应用

乳腺癌是起源于乳腺各级导管和乳腺上皮细胞,由增生到不典型增生而逐步发展成原位癌、早期浸润癌至浸润性癌的一种恶性肿瘤。传统高通量测序技术对乳腺癌的研究主要是鉴定与乳腺癌发生发展相关的"驱动基因",但是对于乳腺癌基因组结构变化以及亚克隆的鉴定等存在一定的局限性,并且忽略了乳腺癌肿瘤细胞之间的异质性。近年来兴起的单细胞测序技术是以单个细胞为研究对象,对基因拷贝和基因表达等数据进行分析,探究乳腺癌的细胞组成、细胞状态和细胞命运,绘制乳腺癌生态系统图谱,对临床患者进行精准分层,为实现个体化治疗提供支持。同时,还可以揭示乳腺癌与T细胞、巨噬细胞等免疫细胞间的相关性,为发现乳腺癌新的治疗靶点、免疫检查点等提供参考。本文对单细胞测序技术及其在乳腺癌研究中的应用和研究进展进行了综述,以期为单细胞测序技术的进一步发展提供参考,同时为理解乳腺癌的发病机制和免疫治疗提供基础支持。     

单细胞转录组测序技术在心脏发育、疾病以及医学中的 应用

单细胞转录组测序(Single-cell RNA sequencing,scRNA-seq)可以在单细胞水平描绘出每个细胞同一基因的表达量在不同细胞间的表达水平差异,使得在单细胞水平重新认识各种组织器官成为可能.目前对心脏的测序研究正从传统的普通转录组水平过渡到单细胞水平,对小鼠和人的心脏的测序陆续地发表出来.概述了s...     

Single-cell transcriptome profiling reveals intratumoural heterogeneity and malignant progression in retinoblastoma

Retinoblastoma is a childhood retinal tumour that is the most common primary malignant intraocular tumour. However, it has been challenging to identify the cell types associated with genetic complexity. Here, we performed single-cell RNA sequencing on 14,739 cells from two retinoblastoma samples to delineate the heterogeneity and the underlying mechanism of retinoblastoma progression. Using a multiresolution network-based analysis, we identified two major cell types in human retinoblastoma. Cell trajectory analysis yielded a total of 5 cell states organized into two main branches, and the cell cycle-associated cone precursors were the cells of origin of retinoblastoma that were required for initiating the differentiation and malignancy process of retinoblastoma. Tumour cells differentiation reprogramming trajectory analysis revealed that cell-type components of multiple tumour-related pathways and predominantly expressed UBE2C were associated with an activation state in the malignant progression of the tumour, providing a potential novel “switch gene” marker during early critical stages in human retinoblastoma development. Thus, our findings improve our current understanding of the mechanism of retinoblastoma progression and are potentially valuable in providing novel prognostic markers for retinoblastoma.Subject terms: Eye cancer, Differentiation, Prognostic markers     

单细胞RNA测序技术在病毒研究中的应用

单细胞RNA测序(single-cell RNA sequencing, scRNA-seq)技术已经成为不同领域中研究细胞异质性的有效工具。在病毒研究领域中,利用该技术分析病毒和细胞的转录组,可以在单细胞水平上检测病毒感染的动态变化,了解病毒与细胞间复杂的相互作用。本文简述了scRNA-seq技术,着重介绍病毒感染宿主细胞后scRNA-seq研究的最新进展,同时也描述了细胞周期、基因表达、细胞状态等细胞异质性对病毒感染过程的影响,以及病毒变异对其本身感染过程的影响。此外,本文还分析了scRNA-seq在研究病毒–宿主互作动态变化方面具有的独特优势,及其在病毒研究领域中广阔的应用前景,为揭示病毒的感染与致病机制、抗病毒靶标的开发等提供参考。     

Single-cell transcriptomics analysis reveals intratumoral heterogeneity and identifies a gene signature associated with prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) tumors exhibit high heterogeneity. However, current understanding of tumor cell heterogeneity of HCC and the association with prognosis remains very limited. In the present study, we collected and examined tumor tissue from one HCC patient by single-cell RNA sequencing (scRNA-seq). We identified 5753 cells and 16 clusters including hepatocytes/cancer cells, T cells, macrophages, endothelial cells, fibroblasts, NK cells, neutrophils, and B cells. In six tumor cell subclusters, we identified a cluster of proliferative tumor cells associated with poor prognosis. We downloaded scRNA-seq data of {"type":"entrez-geo","attrs":{"text":"GSE125449","term_id":"125449"}}GSE125449 from the NCBI-GEO as validation dataset, and found that a cluster of hepatocytes exhibited high proliferation activity in HCC. Furthermore, we identified a gene signature related to the proliferation of HCC cells. This gene signature is efficient to classify HCC patients into two groups with distinct prognosis in both TCGA and ICGC database cohorts. Our results reveal the intratumoral heterogeneity of HCC at single cell level and identify a gene signature associated with HCC prognosis.     

Single-cell multiome sequencing clarifies enteric glial diversity and identifies an intraganglionic population poised for neurogenesis

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Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.