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• Editorial

  Investigating the biology of yeast aging by single-cell RNA-seq

  Relevance score: 5.225523

  Yi Zhang, Xiannian Zhang, Brian K. Kennedy

  Keywords: single-cell RNA-seq, yeast aging, cell-to-cell heterogeneity, iron transport, mitochondrial dysfunction

  Published in Aging on August 14, 2023

• Research Paper Volume 14, Issue 7 pp 3276-3292

  An immune subtype-related prognostic signature of hepatocellular carcinoma based on single-cell sequencing analysis

  Relevance score: 5.715112

  Jiaheng Xie, Liang Chen, Qingmei Sun, Haobo Li, Wei Wei, Dan Wu, Yiming Hu, Zhechen Zhu, Jingping Shi, Ming Wang

  Keywords: hepatocellular carcinoma, single-cell sequencing analysis, differential expression analysis, immune microenvironment, prognostic model

  Published in Aging on April 12, 2022

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  Hepatocellular carcinoma (HCC) is one of the most common cancers in the world and is often associated with a poor prognosis. The main reason for this poor prognosis is that inconspicuous early symptoms lead to delayed diagnosis. Treatment options for advanced HCC remain limited and ineffective. In this context, the exploration of the immune microenvironment in HCC becomes attractive. In this study, we divided HCC into immune cell and non-immune cell subtypes, by single-cell sequencing analysis of GEO dataset GSE146115. We found differentially expressed genes in the two subtypes, which we used to construct a prognostic model for HCC through Cox and Lasso regressions. Our prognostic model can accurately evaluate the prognosis of HCC patients, and provide a reference for the design of immunotherapy for HCC.

• Research Paper Volume 13, Issue 23 pp 24943-24962

  Impact of chemotherapy and immunotherapy on the composition and function of immune cells in COVID-19 convalescent with gynecological tumors

  Relevance score: 6.7237115

  Tianyu Qin, Ensong Guo, Funian Lu, Yu Fu, Si Liu, Rourou Xiao, Xue Wu, Chen Liu, Chao He, Zizhuo Wang, Xu Qin, Dianxing Hu, Lixin You, Fuxia Li, Xi Li, Xiaoyuan Huang, Ding Ma, Xiaoyan Xu, Bin Yang, Junpeng Fan

  Keywords: COVID-19, tumor, chemotherapy, ICIs, single cell sequencing

  Published in Aging on December 4, 2021

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  Ongoing pandemic and potential resurgence of Coronavirus disease 2019 (COVID-19) has prompted urgent efforts to investigate the immunological memory of convalescent patients, especially in patients with active cancers. Here we performed single-cell RNA sequencing in peripheral blood samples of 3 healthy donors (HDs), 4 COVID-19 patients (Covs) and 4 COVID-19 patients with active gynecological tumor (TCs) pre- and post- anti-tumor treatment. All Covs patients had recovered from their acute infection. Interestingly, the molecular features of PBMCs in TCs are similar to that in Covs, suggesting that convalescent COVID-19 with gynecologic tumors do not have major immunological changes and may be protected against reinfection similar to COVID-19 patients without tumors. Moreover, the chemotherapy given to these patients mainly caused neutropenia, while having little effect on the proportion and functional phenotype of T and B cells, and T cell clonal expansion. Notably, anti-PD-L1 treatment massively increased cytotoxic scores of NK cells, and T cells, and facilitated clonal expansion of T cells in these patients. It is likely that T cells could protect patients from SARS-CoV-2 virus reinfection and anti-PD-L1 treatment can enhance the anti-viral activity of the T cells.

• Research Paper Volume 13, Issue 21 pp 24432-24448

  Immune cell and TCR/BCR repertoire profiling in systemic lupus erythematosus patients by single-cell sequencing

  Relevance score: 6.7237115

  Fengping Zheng, Huixuan Xu, Cantong Zhang, Xiaoping Hong, Dongzhou Liu, Donge Tang, Zuying Xiong, Yong Dai

  Keywords: SLE, single-cell sequencing, immune cells, TCR, BCR

  Published in Aging on November 12, 2021

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  The immune cells and the repertoire of T cells and B cells play an important role in the pathogenesis of systemic lupus erythematosus (SLE). Exploring their expression and distribution in SLE can help us better understand this lethal autoimmune disease. In this study, we used a single-cell 5’ RNA sequence and single-cell T cell receptor (TCR)/B cell receptor (BCR) to study the immune cells and the repertoire from ten SLE patients and the paired normal controls (NC). The results showed that 9732 cells correspondence to 12 cluster immune cell types were identified in NC, whereas 11042 cells correspondence to 16 cluster immune cell types were identified in SLE. The results demonstrated that neutrophil, macrophage, and dendritic cells were accumulated in SLE by annotating the immune cell types. Besides, the bioinformatics analysis of differentially expressed genes (DEGs) in these cell types indicates their role in inflammation response. In addition, patients with SLE showed increased TCR and BCR clonotypes compared with the healthy controls. Furthermore, patients with SLE showed biased usage of TCR and BCR V(D)J genes. Taken together, we characterized the transcriptome and TCR/BCR immune repertoire profiles of SLE patients, which may provide a new avenue for the diagnosis and treatment of SLE.

• Research Paper Volume 13, Issue 16 pp 20511-20533

  A comprehensive transcriptomic analysis of alternate interferon signaling pathways in peripheral blood mononuclear cells in rheumatoid arthritis

  Relevance score: 4.361276

  Liang Han, Shenghao Tu, Pan Shen, Jiahui Yan, Yao Huang, Xin Ba, Tingting Li, Weiji Lin, Huihui Li, Kun Yu, Jing Guo, Ying Huang, Kai Qin, Yu Wang, Zhe Chen

  Keywords: rheumatoid arthritis (RA), type I interferon, interferon-γ (IFN-γ), single-cell sequencing (SCS), peripheral blood mononuclear cells (PBMCs)

  Published in Aging on August 25, 2021

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  Interferon (IFN) signaling pathways play crucial roles in the pathogenesis of rheumatoid arthritis (RA). Prior studies have mainly studied mixed alterations in the IFN signaling pathway in RA, but these studies have not been sufficient to elucidate how imbalanced IFN signaling subtly influences immune cells. Single-cell RNA (scRNA) sequencing makes it possible to better understand the alternations in the interferon signaling pathways in RA. In the present study, we found that IFN signaling pathways were activated in natural killer (NK) cells, monocytes, T cells, B cells, and most immune cell subclasses in RA. We then explored and analyzed the connections between abnormal IFN signaling pathways and cellular functional changes in RA. Single-Cell rEgulatory Network Inference and Clustering (SCENIC) analysis and gene regulatory network (GRN) construction were also performed to identify key transcription factors in RA. Finally, we also investigated altered IFN signaling pathways in multiple RA peripheral blood samples, which indicated that abnormal IFN signaling pathways were universally observed in RA. Our study contributes to a better understanding of the delicate and precise regulation of IFN signaling in the immune system in RA. Furthermore, common alternations in IFN signaling pathway-related transcription factors could help to identify novel therapeutic targets for RA treatment.

• Research Paper Volume 13, Issue 16 pp 20629-20650

  A systematic dissection of human primary osteoblasts in vivo at single-cell resolution

  Relevance score: 6.382531

  Yun Gong, Junxiao Yang, Xiaohua Li, Cui Zhou, Yu Chen, Zun Wang, Xiang Qiu, Ying Liu, Huixi Zhang, Jonathan Greenbaum, Liang Cheng, Yihe Hu, Jie Xie, Xuecheng Yang, Yusheng Li, Yuntong Bai, Yu-Ping Wang, Yiping Chen, Li-Jun Tan, Hui Shen, Hong-Mei Xiao, Hong-Wen Deng

  Keywords: single-cell RNA sequencing, osteoblasts, cellular heterogeneity, bone formation

  Published in Aging on August 24, 2021

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  Human osteoblasts are multifunctional bone cells, which play essential roles in bone formation, angiogenesis regulation, as well as maintenance of hematopoiesis. However, the categorization of primary osteoblast subtypes in vivo in humans has not yet been achieved. Here, we used single-cell RNA sequencing (scRNA-seq) to perform a systematic cellular taxonomy dissection of freshly isolated human osteoblasts from one 31-year-old male with osteoarthritis and osteopenia after hip replacement. Based on the gene expression patterns and cell lineage reconstruction, we identified three distinct cell clusters including preosteoblasts, mature osteoblasts, and an undetermined rare osteoblast subpopulation. This novel subtype was found to be the major source of the nuclear receptor subfamily 4 group A member 1 and 2 (NR4A1 and NR4A2) in primary osteoblasts, and the expression of NR4A1 was confirmed by immunofluorescence staining on mouse osteoblasts in vivo. Trajectory inference analysis suggested that the undetermined cluster, together with the preosteoblasts, are involved in the regulation of osteoblastogenesis and also give rise to mature osteoblasts. Investigation of the biological processes and signaling pathways enriched in each subpopulation revealed that in addition to bone formation, preosteoblasts and undetermined osteoblasts may also regulate both angiogenesis and hemopoiesis. Finally, we demonstrated that there are systematic differences between the transcriptional profiles of human and mouse osteoblasts, highlighting the necessity for studying bone physiological processes in humans rather than solely relying on mouse models. Our findings provide novel insights into the cellular heterogeneity and potential biological functions of human primary osteoblasts at the single-cell level.

• Research Paper Volume 13, Issue 12 pp 16485-16499

  Cell landscape atlas for patients with chronic thromboembolic pulmonary hypertension after pulmonary endarterectomy constructed using single-cell RNA sequencing

  Relevance score: 5.6447825

  Ran Miao, Xingbei Dong, Juanni Gong, Yidan Li, Xiaojuan Guo, Jianfeng Wang, Qiang Huang, Ying Wang, Jifeng Li, Suqiao Yang, Tuguang Kuang, Jun Wan, Min Liu, Zhenguo Zhai, Jiuchang Zhong, Yuanhua Yang

  Keywords: chronic thromboembolic pulmonary hypertension, single-cell RNA sequencing, gene ontology enrichment analysis

  Published in Aging on June 21, 2021

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  This study aimed to construct an atlas of the cell landscape and comprehensively characterize the cellular repertoire of the pulmonary endarterectomized tissues of patients with chronic thromboembolic pulmonary hypertension (CTEPH). Five pulmonary endarterectomized tissues were collected. 10× Genomics single-cell RNA sequencing was performed, followed by the identification of cluster marker genes and cell types. Gene Ontology (GO) enrichment analysis was conducted. Seventeen cell clusters were characterized, corresponding to 10,518 marker genes, and then classified into eight cell types, including fibroblast/smooth muscle cell, endothelial cell, T cell/NK cell, macrophage, mast cell, cysteine rich secretory protein LCCL domain containing 2 (CRISPLD2)+ cell, cancer stem cell, and undefined. The specific marker genes of fibroblast/smooth muscle cell, endothelial cell, T cell/NK cell, macrophage, mast cell, and cancer stem cell were significantly enriched for multiple functions associated with muscle cell migration, endothelial cell migration, T cell activation, neutrophil activation, erythrocyte homeostasis, and tissue remodeling, respectively. No functions were significantly enriched for the marker gene of CRISPLD2+ cell. Our study, for the first time, provides an atlas of the cell landscape of the pulmonary endarterectomized tissues of CTEPH patients at single-cell resolution, which may serve as a valuable resource for further elucidation of disease pathophysiology.

• Research Paper Volume 13, Issue 11 pp 15595-15619

  Single-cell RNA sequencing of human femoral head in vivo

  Relevance score: 5.4270673

  Xiang Qiu, Ying Liu, Hui Shen, Zun Wang, Yun Gong, Junxiao Yang, Xiaohua Li, Huixi Zhang, Yu Chen, Cui Zhou, Wanqiang Lv, Liang Cheng, Yihe Hu, Boyang Li, Wendi Shen, Xuezhen Zhu, Li-Jun Tan, Hong-Mei Xiao, Hong-Wen Deng

  Keywords: single-cell RNA sequencing, bone cell, immune cell, bone metabolism, cell-cell communication

  Published in Aging on June 10, 2021

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  The homeostasis of bone metabolism depends on the coupling and precise regulation of various types of cells in bone tissue. However, the communication and interaction between bone tissue cells at the single-cell level remains poorly understood. Thus, we performed single-cell RNA sequencing (scRNA-seq) on the primary human femoral head tissue cells (FHTCs). Nine cell types were identified in 26,574 primary human FHTCs, including granulocytes, T cells, monocytes, B cells, red blood cells, osteoblastic lineage cells, endothelial cells, endothelial progenitor cells (EPCs) and plasmacytoid dendritic cells. We identified serine protease 23 (PRSS23) and matrix remodeling associated protein 8 (MXRA8) as novel bone metabolism-related genes. Additionally, we found that several subtypes of monocytes, T cells and B cells were related to bone metabolism. Cell-cell communication analysis showed that collagen, chemokine, transforming growth factor and their ligands have significant roles in the crosstalks between FHTCs. In particular, EPCs communicated with osteoblastic lineage cells closely via the "COL2A1-ITGB1" interaction pair. Collectively, this study provided an initial characterization of the cellular composition of the human FHTCs and the complex crosstalks between them at the single-cell level. It is a unique starting resource for in-depth insights into bone metabolism.

• Research Paper Volume 13, Issue 8 pp 11646-11664

  Two reactive behaviors of chondrocytes in an IL-1β-induced inflammatory environment revealed by the single-cell RNA sequencing

  Relevance score: 6.820061

  Chenghao Gao, Hongxu Pu, Qian Zhou, Tenghui Tao, Hui Liu, Xuying Sun, Ximiao He, Jun Xiao

  Keywords: chondrocyte, inflammation, osteoarthritis, IL-1beta, single-cell RNA sequencing

  Published in Aging on April 20, 2021

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  Objective: To investigate the heterogeneous responses of in vitro expanded chondrocytes, which were cultured in an interleukin (IL)-1β -induced inflammatory environment.

  Method: Human articular chondrocytes were expanded, in vitro, for 13 days and treated with IL-1β for 0, 24, and 48 h. Cells were collected and subjected to single-cell RNA sequencing. Multiple bioinformatics tools were used to determine the signatures that define chondrocyte physiology.

  Results: Two major cell clusters with distinct expression patterns were identified at the initial phase and were with heterogeneous variation that coincides with inflammation progress. They transformed into two terminal cell clusters one of which exhibited OA-phenotype and proinflammatory characteristics through two paths, “response-to-inflammation” and “atypical response-to-inflammation”, respectively. The involved cell clusters exhibited intrinsic relationship with cell types within native cartilage from OA patients. Genes controlling cell transformation to OA-phenotype were relating to the tumor necrosis factor (TNF) signaling pathway via NFKB, up-regulated KRAS signaling and the IL2/STAT5 signaling pathway and pathways relating to apoptosis and reactive oxygen species.

  Conclusion: The in vitro expanded chondrocytes under IL-1β-induced inflammatory progression behave heterogeneously. One of the initial cell clusters could transform into a proinflammatory subpopulation through a termed response-to-inflammation path, which may serve as the core target to alleviate OA progression.

• Research Paper Volume 13, Issue 5 pp 6565-6591

  Phenotyping of immune and endometrial epithelial cells in endometrial carcinomas revealed by single-cell RNA sequencing

  Relevance score: 5.225523

  Yu-e Guo, Yiran Li, Bailian Cai, Qizhi He, Guofang Chen, Mengfei Wang, Kai Wang, Xiaoping Wan, Qin Yan

  Keywords: single-cell RNA sequencing, endometrial carcinoma, immune microenvironment, macrophage activation model, endometrial epithelial cells

  Published in Aging on January 10, 2021

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  Tumors are complex ecosystems harboring multiple cell types which might play a critical role in tumor progression and treatment response. The endometrial epithelial cell identities and immune microenvironment of endometrial carcinoma (ECC) are poorly characterized. In this study, a cellular map of endometrial carcinoma was generated by profiling 30,780 cells isolated from tumor and paratumor tissues from five patients using single-cell RNA sequencing. 7 cell types in lymphocytes, 7 types in myeloid cells and 3 types in endometrial epithelial cells were identified. Distinct CD8⁺ T cell states and different monocyte-macrophage populations were discovered, among which exhausted CD8⁺ T cells and macrophages were preferentially enriched in tumor. Both CD8⁺ T cells and macrophages comport with continuous activation model. Gene expression patterns examination and gene ontology enrichment analysis of endometrial epithelial cells revealed 3 subtypes: stem-like cells, secretory glandular cells and ciliated cells. Overall, our study presents a view of endometrial carcinoma at single-cell resolution that reveals the characteristics of endometrial epithelial cells in the endometrium, and provides a cellular landscape of the tumor immune microenvironment.

• Research Paper Volume 12, Issue 24 pp 25337-25355

  Single cell sequencing reveals cell populations that predict primary resistance to imatinib in chronic myeloid leukemia

  Relevance score: 5.406

  Weilong Zhang, Beibei Yang, Linqian Weng, Jiangtao Li, Jiefei Bai, Ting Wang, Jingwen Wang, Jin Ye, Hongmei Jing, Yuchen Jiao, Xixi Chen, Hui Liu, Yi-Xin Zeng

  Keywords: chronic myeloid leukemia, peripheral immune structure, single cell sequencing, TKI resistance, stem cells

  Published in Aging on November 23, 2020

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  The treatment of chronic myeloid leukemia (CML), a disease caused by t(9;22)(q34;q11) reciprocal translocation, has advanced largely through the use of targeted tyrosine kinase inhibitors (TKIs). To identify molecular differences that might distinguish TKI responders from non-responders, we performed single cell RNA sequencing on cells (n = 41,723 cells) obtained from the peripheral blood of four CML patients at different stages of treatment to generate single cell expression profiles. Analysis of our single cell expression profiles in conjunction with those previously obtained from the bone marrow of additional CML patients and healthy donors (total = 69,263 cells) demonstrated that imatinib treatment significantly altered leukocyte population compositions in both responders and non-responders, and affected the expression profiles of multiple cell populations, including non-neoplastic cell types. Notably, in imatinib poor-responders, patient-specific pre-treatment unique stem/progenitor cells became enriched in peripheral blood compared to the responders. These results indicate that resistance to TKIs might be intrinsic in some CML patients rather than acquired, and that non-neoplastic immune cell types may also play vital roles in dispersing the responsiveness of patients to TKIs. Furthermore, these results demonstrated the potential utility of peripheral blood as a diagnostic tool in the TKI sensitivity of CML patients.

• Research Paper Volume 12, Issue 21 pp 21559-21581

  Single-cell transcriptome analysis demonstrates inter-patient and intra-tumor heterogeneity in primary and metastatic lung adenocarcinoma

  Relevance score: 6.336181

  Yafei Liu, Guanchao Ye, Lan Huang, Chunyang Zhang, Yinliang Sheng, Bin Wu, Lu Han, Chunli Wu, Bo Dong, Yu Qi

  Keywords: lung adenocarcinoma, single cell RNA sequencing, tumour heterogeneity, chemoresistance

  Published in Aging on November 10, 2020

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  In this study, we performed single-cell transcriptome data analysis of fifty primary and metastatic lung adenocarcinoma (LUAD) samples from the GSE123902 and GSE131907 datasets to determine the landscape of inter-patient and intra-tumoral heterogeneity. The gene expression profiles and copy number variations (CNV) showed significant heterogeneity in the primary and metastatic LUAD samples. We observed upregulation of pathways related to translational initiation, endoplasmic reticulum stress, exosomes, and unfolded protein response in the brain metastasis samples as compared to the primary tumor samples. Pathways related to exosomes, cell adhesion and metabolism were upregulated and the epithelial-to-mesenchymal-transition (EMT) pathway was downregulated in brain metastasis samples from chemotherapy-treated LUAD patients as compared to those from the untreated LUAD patients. Tumor cell subgroups in the brain metastasis samples showed differential expression of genes related to type II alveolar cells, chemoresistance, glycolysis and oxidative phosphorylation (metabolic reprogramming), and EMT. Thus, single-cell transcriptome analysis demonstrated intra-patient and intra-tumor heterogeneity in the regulation of pathways related to tumor progression, chemoresistance and metabolism in the primary and metastatic LUAD tissues. Moreover, our study demonstrates that single cell transcriptome analysis is a potentially useful tool for accurate diagnosis and personalized targeted treatment of LUAD patients.

• Research Paper Volume 12, Issue 3 pp 2747-2763

  Single-cell RNA sequencing of immune cells in gastric cancer patients

  Relevance score: 6.6367106

  Kai Fu, Bingqing Hui, Qian Wang, Chen Lu, Weihong Shi, Zhigang Zhang, Dawei Rong, Betty Zhang, Zhaofeng Tian, Weiwei Tang, Hongyong Cao, Xuehao Wang, Ziyi Chen

  Keywords: gastric cancer, single-cell RNA sequencing, immunotherapy, exhausted

  Published in Aging on February 10, 2020

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  Cancer immunotherapy has achieved positive clinical responses in the treatment of various cancers, including gastric cancer (GC). In this study, we characterized the heterogeneity of T cells isolated from GC patients at the single-cell level using single-cell RNA sequencing. We identified different immune cell subtypes and their heterogeneous transcription factors and depicted their developmental trajectories. In particular, we focused on exhausted CD8⁺ cells and Tregs and discovered that, as compared to control, the IRF8 transcription factor was downregulated in CD8⁺ tumour-infiltrating lymphocytes (TILs) from GC tissues, and that GC patients with lower IRF8 levels in blood CD8⁺ T cells tended to be a at a more advanced disease stage. These findings provide a theoretical basis for targeted immune therapy in GC.

  

  Overview of the study design. (A) ScRNA-seq was performed on immune cells isolated from GC preoperational peripheral blood samples and GC tissues and corresponding adjacent non-tumor tissues. 10 cell clusters in tissues and 9 cell clusters in peripheral blood were identified based on CD45 isolation. (B) Each immune cell subtype, their heterogeneous transcription factors, and their developmental trajectories. (C) Correlation between the expression of specific genes and clinical significance.

  
  
  

  

  The transcription factor IRF8 was associated with CD8⁺ T cells in GC. (A) Heat map displaying the top 50 genes differentially expressed in CD8⁺ exhausted T cells from tissues. (B and C) Pathway analysis for CD8⁺ exhausted T cells. (D) Trajectory analysis for CD8⁺ T cells in tissues. (E). Trajectory analysis for CD8⁺ T cells in blood. (F) Expression of IRF8 in CD8⁺TILs from GC tissues and normal tissues. (G) Expression of IRF8 in peripheral blood CD8⁺ T cells from GC patients. (H) TGCA analysis of IRF8 in GC prognosis. (I). Pathway and disease analysis of IRF8.

  
  
  

  

  Identification of genes uniquely associated with Treg function in GC. (A) Heat map displaying the top 50 genes differentially expressed in Tregs from tissues. (B and C) Pathway analysis for different genes in Tregs. (D) Trajectory analysis for Tregs in tissues. (E) Expression of various molecules in Tregs. (F) STRING analysis of RBPJ. (G) Single-cell analysis using CancerSEA. (H) Top 20 differentially expressed TFs in cancers as shown by Cistrome DB Toolkit for RBPJ. (I) GEPIA analyses showing the association between RBPJ and LAG3.

  
  
  

  

  Gene signature of B cells and pathway analysis. (A) The expression analysis of functional molecules in B cell cluster in T vs N. (B) The expression analysis of functional molecules in B cell cluster in PB vs HB. (C) Pathway analysis of in B cell cluster in T vs N. (D) Pathway analysis of in B cell cluster in PB vs HB. (E) The expression analysis of functional molecules in B cell cluster in T vs N. (F) The expression analysis of functional molecules in B cell cluster in PB vs HB.

  
  
  

  

  More inhibitory receptors and fewer activated receptors are secreted by NK cells in response to GC. (A). Expression analysis of functional molecules in the NK cell cluster in T vs N. (B). Expression analysis of functional molecules in the NK cell cluster in PB vs HB. (C). Pathway analysis of functional molecules in the NK cell cluster in T vs N. (D). Pathway analysis of functional molecules in the NK cell cluster in PB vs HB. (E). Expression analysis of functional molecules in the NK cell cluster in T vs N. (F). Expression analysis of functional molecules in the NK cell cluster in PB vs HB.

  
  
  

  

  Different DC subtypes and their interactions in GC. (A) Expression analysis of functional molecules in the DC cell cluster in T vs N. (B) Expression analysis of functional molecules in the DC cell cluster in PB vs HB. (C) Pathway analysis of functional molecules in the DC cell cluster in T vs N. (D) Pathway analysis of functional molecules in the DCB cell cluster in PB vs HB. (E) Expression analysis of functional molecules in the DC cell cluster in T vs N. (F) Expression analysis of functional molecules in the DC cell cluster in PB vs HB.

  
  
  

• Research Paper Volume 11, Issue 22 pp 10183-10202

  Development and validation of a metastasis-associated prognostic signature based on single-cell RNA-seq in clear cell renal cell carcinoma

  Relevance score: 6.0092664

  Chuanjie Zhang, Hongchao He, Xin Hu, Ao Liu, Da Huang, Yang Xu, Lu Chen, Danfeng Xu

  Keywords: single-cell RNA-seq, metastasis-associated genes, progression, tumor mutation burden, TCGA

  Published in Aging on November 20, 2019

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  Single-cell RNA sequencing (scRNA-seq) was recently adopted for deciphering intratumoral heterogeneity across cell sub-populations, including clear cell renal cell carcinoma (ccRCC). Here, we characterized the single-cell expression profiling of 121 cell samples and found 44 metastasis-associated marker genes. Accordingly, we trained and validated 17 pivotal metastasis-associated genes (MAGs) in 626 patients incorporating internal and external cohorts to evaluate the model for predicting overall survival (OS) and progression-free survival (PFS). Correlation analysis revealed that the MAGs correlated significantly with several risk clinical characteristics. Moreover, we conducted Cox regression analysis integrating these independent clinical variables into a MAGs nomogram with superior accuracy in predicting progression events. We further revealed the differential landscape of somatic tumor mutation burden (TMB) between two nomogram-score groups and observed that TMB was also a prognostic biomarker; patients with high MAGs-nomogram scores suffered from a higher TMB, potentially leading to worse prognosis. Last, higher MAGs-nomogram scores correlated with the upregulation of oxidative phosphorylation, the Wnt signaling pathway, and MAPK signaling crosstalk in ccRCC. Overall, we constructed the robust MAGs through scRNA-seq and validated the model in a large patient population, which was valuable for prognostic stratification and providing potential targets against metastatic ccRCC.

  

  Characterization of single-cell RNA sequencing from 121 cells and screening of marker genes. (A, B) Quality control of scRNA-seq for three cell sub-populations. We filtered out the cells with poor quality and analyzed the positive associations between detected gene counts and sequencing depth. (C) we identified the gene symbols with significant difference across cells and drawn the characteristic variance diagram. (D, E) The principal component analysis (PCA), a linear dimensionality reduction method, was ultilized to identify the significantly available dimensions of data sets with estimated P value. Accordingly, we classified the cell groups into three categories. (F) Based on available significant components from PCA, we conducted another nonlinear dimensionality reduction, TSNE algorithm, to successfully divided the cells into two clusters, in accordance with actual cell types. (G) Differential analysis with logFC =0.5 and adjPval =0.05 was constructed between two clusters to identify significant marker genes and we exhibited the top 20 in heatmap package. (H) Cell annotations and trajectory analysis revealed the tendency curve from primary RCC to metastatic ones, indicating the genomic alternations between them.

  
  
  

  

  Identification of prognostic metastasis associated genes. (A, B) We conducted the LASSO method based on glmnet package and identified the 17 prognostic genes in TCGA training cohort, where the optimal cutoff value was -4 and the minimum account of genes was 17. © Meanwhile, we also illustrated the significantly differential expressions of 17 prognostic genes in two clusters via bubble plot.

  
  
  

  

  Internal and external validation of MAGs to determine its clinical predictive value. (A, C) The AUCs of ROC curves were 0.763 and 0.803 in predicting 3-year OS events in training and testing cohorts, respectively. (B, D) Besides, Kaplan-Meier analysis indicated that patients with high MAGs-score suffered significantly worse OS outcomes (P = 2.904e-08), which was validated consistently in testing cohort with P = 1.031e-10. (E, F) In addition, we also proved our findings in an independent ICGC cohort and observed the similar statistical results. (G–I) We further integrated MAGs signature with survival analysis in the total TCGA-KIRC cohort and distribution plots suggested that high MAGs risk scores correlated with more dead and recurrence/progression cases.

  
  
  

  

  Correlation analysis between MAGs with other clinical variables and predictive efficiency of MAGs in PFS. (A–E) Kruskal-Wallis test revealed that increasing MAGs-score correlated with higher T stages (P = 7.586e-09), higher positive rate of lymph nodes (P = 0.005), advanced metastatic stages (P = 1.572e-06), poor pathological stages (P = 1.699e-08) and progressive tumor grades (P = 1.643e-11). (F, G) Moreover, the MAGs signature possessed superior significance in 5-year PFS prediction with AUC = 0.752 in total TCGA-KIRC cohort and patients with high MAGs-score suffered more hazards in tumor recurrence or progression with log-rank test of P = 0. (H, I) Correlation analysis of MAGs with T, M stages in ICGC validation cohort.

  
  
  

  

  Construction and assessment of MAGs-nomogram for predicting progression. (A) Univariate- and multivariate Cox regression analysis for screening appropriate and significant features into final nomogram model. (B) Ultilizing the glm regression algorithm, the MAGs-nomogram incorporating these four variables was developed and the TCGA-KIRC cohort was classified into high and low groups according to the median of MAGs-nomogram scores. (C) Calibration curve was drawn to depict the well curve fitting between predicted 1-year or 3-year progression events and actual observed outcomes. (D, E) Meanwhile, the AUCs of MAGs-nomogram in predicting 1-year and 3-year progression outcomes were up to 0.848 and 0.837, respectively. Survival analysis also suggested that the MAGs-nomogram was determined to be a significant predictor in PFS of ccRCC with P = 0.

  
  
  

  

  Differential landscape of somatic mutation burden between high and low MAGs-nomogram levels. (A) The mutational landscape reflected that mutated events occurred more frequently in high Nomogram-score group than that in low group. Besides, the Chi-square test revealed that VHL, PBRM1, SETD2 and BAP1 especially harbored more mutants compared with that in low risk group. (B) Wilcoxon rank-sum test suggested that the MAGs-nomogram risk scores were significantly higher in high TMB group than that in low TMB group (P = 2.875e-05). (C, D) Additionally, we found that higher TMB levels were associated with more risks of progression events with P = 0.01 and worse OS outcomes with P = 0.035.

  
  
  

  

  GSEA results revealed the significantly enriched biological processes between two nomogram-score levels.

  
  
  

• Research Paper Volume 11, Issue 18 pp 7707-7722

  Single-cell RNA-seq reveals RAD51AP1 as a potent mediator of EGFRvIII in human glioblastomas

  Relevance score: 7.494157

  Qixue Wang, Yanli Tan, Chuan Fang, Junhu Zhou, Yunfei Wang, Kai Zhao, Weili Jin, Ye Wu, Xiaomin Liu, Xing Liu, Chunsheng Kang

  Keywords: glioblastoma, heterogenous, EGFRvIII, single-cell sequencing, RAD51AP1

  Published in Aging on September 18, 2019

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  Recent advances in single-cell RNA sequencing (scRNA-seq) have endowed researchers with the ability to detect and analyze the transcriptomes of individual cancer cells. In the present study, 16,128 tumor cells from EGFR wild-type and EGFRvIII mutant cells were profiled by scRNA-seq. Analyses of scRNA-seq data from both U87MG and U87MG-EGFRvIII libraries revealed inherent heterogeneity in gene expression and biological processes. The cells stably expressing EGFRvIII showed enhanced transcriptional activities and a relatively homogeneous pattern, which manifested as less diverse distributions, gene expression levels and functional annotations compared with those of cells expressing the nonmutated version. Moreover, the differentially expressed genes between the U87MG and U87MG-EGFRvIII groups were mainly enriched in DNA replication, DNA repair and angiogenesis. We compared scRNA-seq data with bulk RNA-seq and EGFRvIII xenograft RNA-seq data. RAD51AP1 was shown to be upregulated in all three databases. Further analysis of RAD51AP1 revealed that it is an independent prognostic factor of glioma. Knocking down RAD51AP1 significantly inhibited tumor volume in an intracranial EGFRvIII-positive GBM model and prolonged survival time. Collectively, our microfluidic-based scRNA-seq driven by a single genetic event revealed a previously unappreciated implication of EGFRvIII in the heterogeneity of GBM and identified RAD51AP1 as an oncogene in glioma.

  

  Single-cell analyses of U87MG and U87MG-EGFRvIII cells. U87MG-EGFRvIII cells were less heterogeneous than U87MG cells. (A) Clustering analyses reveal ten subsets with cluster-specific genes and functions. The pie chart shows the percentage of each cluster. (B) The clustering results of U87MG-EGFRvIII cells (k=10) and the percentage of each cluster. (C) The clustering results with k values from two to ten. (D) The heatmap shows the gene expression of every single cell.

  
  
  

  

  Comparison of single-cell libraries from U87MG and U87MG-EGFRvIII cells. (A) The distribution of U87MG cells. (B) The distribution of U87MG-EGFRvIII cells. (C) The biological process annotations of differential genes that were upregulated in EGFRvIII cells. (D) Graph-based clustering revealed 15 clusters in 16,128 cells. (E) Distributions of each cluster in the U87MG and U87MG-EGFRvIII libraries. (F) The expression levels of cluster-specific genes.

  
  
  

  

  Gene Ontology (GO) analysis of EGFRvIII-related cluster-specific genes and biological processes (cluster 1, cluster 3, and cluster 6).

  
  
  

  

  RAD51AP1 is upregulated in EGFRvIII-positive cells. The volcano plot was constructed to profile the differentially expressed genes observed in GES46028 (A) and scRNA-seq data (B). (C) A heatmap was employed to profile the differentially expressed genes observed in U87MG/U87MG-EGFRvIII RNA-seq data. A Venn diagram was used to profile the common upregulated (D) and downregulated (E) genes in three databases. (F) The EGFRvIII, r-H2A.x, RAD51AP1 and Ki-67 expression levels in multipoint samples from two patients were examined by IHC staining.

  
  
  

  

  The expression level of RAD51AP1 correlated with the GBM clinical grade and patient survival rate. (A–D) ssGSEA was employed to evaluate the expression pattern of RAD51AP1 in the CGGA, TCGA and GSE16011 databases. (E–H) Kaplan-Meier survival curves were plotted to show the survival times at different RAD51AP1 expression levels.

  
  
  

  

  RAD51AP1 is an oncogene in glioma. (A) RAD51AP1 highly coincides with EGFRvIII in scRNA-seq data. (B) GSEA was performed to estimate RAD51AP1 expression in gliomas of different clinical grades. (C) Uni- and multivariable Cox analyses were performed to evaluate the role of RAD51AP1 in gliomas in the CGGA database, while GO and KEGG analyses were employed to profile the pathways of RAD51AP1-related genes in the CGGA database.

  
  
  

  

  Target knocking down RAD51AP1 inhibited the progression of the EGFRvIII-positive intracranial GBM model. (A) The tumor volumes at the indicated times were evaluated by bioluminescence imaging. (B) Survival rates of mice bearing U87-EGFRvIII and EGFRvIII-siRAD51AP1 tumors. (C) Immunohistochemistry analysis was performed to detect Ki-67 and CD34 expression.

  
  
  

• Research Paper pp undefined-undefined

  Single cell sequencing analysis constructed the N7-methylguanosine (m7G)-related prognostic signature in uveal melanoma

  Relevance score: 5.8806953

  Jiaheng Xie, Liang Chen, Yuan Cao, Chenfeng Ma, Wenhu Zhao, JinJing Li, Wen Yao, Yiming Hu, Ming Wang, Jingping Shi

  Keywords: uveal melanoma, N7-Methylguanosine, single cell sequencing analysis, PAG1, immune microenvironment

  Published in Aging on Invalid Date

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  Background: Uveal melanoma is a highly malignant tumor in the eye. Its recurrence and metastasis are common, and the prognosis is poor.

  Methods: The transcriptome data of UVM was downloaded from TCGA database, and the single cell sequencing dataset GSE139829 was downloaded from GEO database. Weighted co-expression network analysis was used to explore the modules associated with m7G. Lasso regression was used to construct M⁷G-related prognostic signature. Immune infiltration analysis was used to explore the significance of the model in the tumor immune microenvironment. Finally, cell assays were used to explore the function of key genes in the MUM-2B and OCM-1 cell lines of UVM.

  Results: The prognostic signature was constructed by Cox regression and Lasso regression. Patients could be divided into high-risk group and low-risk group by this signature, and the high-risk group had worse prognosis (P<0.05). Cell experiments showed that the proliferation, invasion and migration ability of UVM cell lines were significantly decreased after the knockdown of PAG1, a key gene in signature, which proved that PAG1 might be a potential target of UVM.

  Conclusions: Our study explored the significance of m⁷G in UVM, provided biomarkers for its diagnosis and treatment.

• Research Paper pp undefined-undefined

  Construction and validation of an oxidative-stress-related risk model for predicting the prognosis of osteosarcoma

  Relevance score: 6.7237115

  Hanning Wang, Juntan Li, Xu Li

  Keywords: osteosarcoma, prognosis, immune microenvironment, single cell sequencing, nomogram

  Published in Aging on Invalid Date

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  Background: Osteosarcoma is the most common bone malignancy in teenagers, and warrants effective measures for diagnosis and prognosis. Oxidative stress (OS) is the key driver of several cancers and other diseases.

  Methods: The TARGET-osteosarcoma database was employed as the training cohort and GSE21257 and GSE39055 was applied for external validation. The patients were classified into the high- and low-risk groups based on the median risk score of each sample. ESTIMATE and CIBERSORT were applied for the evaluation of tumor microenvironment immune infiltration. GSE162454 of single-cell sequencing was employed for analyzing OS-related genes.

  Results: Based on the gene expression and clinical data of 86 osteosarcoma patients in the TARGET database, we identified eight OS-related genes, including MAP3K5, G6PD, HMOX1, ATF4, ACADVL, MAPK1, MAPK10, and INS. In both the training and validation sets, the overall survival of patients in the high-risk group was significantly worse than that in the low-risk group. The ESTIMATE algorithm revealed that patients in the high-risk group had higher tumor purity but lower immune score and stromal score. In addition, the CIBERSORT algorithm showed that the M0 and M2 macrophages were the predominant infiltrating cells in osteosarcoma. Based on the expression analysis of immune checkpoint, CD274(PDL1), CXCL12, BTN3A1, LAG3, and IL10 were identified as potential immune therapy targets. Analysis of the single cell sequencing data also revealed the expression patterns of OS-related genes in different cell types.

  Conclusions: An OS-related prognostic model can accurately provide the prognosis of osteosarcoma patients, and may help identify suitable candidates for immunotherapy.

• Research Paper pp undefined-undefined

  Significance of liquid-liquid phase separation(LLPS)-related genes in breast cancer: a multi-omics analysis

  Relevance score: 5.6447825

  Jiaheng Xie, Liang Chen, Dan Wu, Shengxuan Liu, Shengbin Pei, Qikai Tang, Yue Wang, Mengmeng Ou, Zhechen Zhu, Shujie Ruan, Ming Wang, Jingping Shi

  Keywords: breast cancer, liquid-liquid phase separation, single cell sequencing analysis, bioinformatics, PGAM1

  Published in Aging on Invalid Date

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  Currently, the role of liquid-liquid phase separation (LLPS) in cancer has been preliminaries explained. However, the significance of LLPS in breast cancer is unclear. In this study, single cell sequencing datasets GSE188600 and GSE198745 for breast cancer were downloaded from the GEO database. Transcriptome sequencing data for breast cancer were downloaded from UCSC database. We divided breast cancer cells into high-LLPS group and low-LLPS group by downdimension clustering analysis of single-cell sequencing data set, and obtained differentially expressed genes between the two groups. Subsequently, weighted co-expression network analysis (WGCNA) was performed on transcriptome sequencing data, and the module genes most associated with LLPS were obtained. COX regression and Lasso regression were performed and the prognostic model was constructed. Subsequently, survival analysis, principal component analysis, clinical correlation analysis, and nomogram construction were used to evaluate the significance of the prognostic model. Finally, cell experiments were used to verify the function of the model’s key gene, PGAM1. We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1. By calculating LLPS-related risk scores, breast cancer patients could be divided into high-risk and low-risk groups, with the high-risk group having a significantly worse prognosis. Cell experiments showed that the activity, proliferation, invasion and healing ability of breast cancer cell lines were significantly decreased after knockdown of the key gene PGAM1 in the model. Our study provides a new idea for prognostic stratification of breast cancer and provides a novel marker: PGAM1.

• Research Paper pp undefined-undefined

  Single-cell sequencing analysis reveals the relationship between tumor microenvironment cells and oxidative stress in breast cancer bone metastases

  Relevance score: 5.4270673

  Minmin Zhang, Xiao Chai, Li Wang, Ke Mo, Wenyang Chen, Xiangtao Xie

  Keywords: breast cancer bone metastasis, oxidative stress, apoptosis, bone remodeling, single cell RNA sequencing

  Published in Aging on Invalid Date

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  Bone metastasis (BM) is one of the main manifestations of advanced breast cancer (BC), causing complications such as pathological fractures, which seriously affects the quality of life of patients and even leads to death. In our study, a global single-cell landscape of the tumor microenvironment was constructed using single cell RNA sequencing data from BM. BC cells were found to be reduced in the BM, while mesenchymal stem cells (MSCs), Fibroblasts and other cells were significantly more abundant in the BM. The subpopulations of these cells were further identified, and the pathways, developmental trajectories and transcriptional regulation of different subpopulations were discussed. The results suggest that with the development of BM, BC cells were vulnerable to oxidative damage, showing a high level of oxidative stress, which played a key role in cell apoptosis. Fibroblasts were obviously involved in the biological processes (BPs) related to ossification and bone remodeling, and play an important role in tumor cell inoculation to bone marrow and growth. MSC subpopulations were significantly enriched in a number of BPs associated with bone growth and development and oxidative stress and may serve as key components of BC cells homing and adhesion to the ecological niche of BM. In conclusion, our research results describe the appearance of tumor microenvironment cell subpopulations in breast cancer patients, reveal the important role of some cells in the balance of BM bone remodeling and the imbalance of BM development, and provide potential therapeutic targets for BM.

• Research Paper pp undefined-undefined

  Single-cell landscape and spatial transcriptomic analysis reveals macrophage infiltration and glycolytic metabolism in kidney renal clear cell carcinoma

  Relevance score: 5.225523

  Chen-Yueh Wen, Jui-Hu Hsiao, Yen-Dun Tony Tzeng, Renin Chang, Yi-Ling Tsang, Chen-Hsin Kuo, Chia-Jung Li

  Keywords: PGAM1, glycolytic metabolism, immune infiltration, single cell-RNA sequencing, kidney renal clear cell carcinoma

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  The present study investigates the clinical relevance of glycolytic factors, specifically PGAM1, in the tumor microenvironment of kidney renal clear cell carcinoma (KIRC). Despite the established role of glycolytic metabolism in cancer pathophysiology, the prognostic implications and key targets in KIRC remain elusive. We analyzed GEO and TCGA datasets to identify DEGs in KIRC and studied their relationship with immune gene expression, survival, tumor stage, gene mutations, and infiltrating immune cells. We explored Pgam1 gene expression in different kidney regions using spatial transcriptomics after mouse kidney injury analysis. Single-cell RNA-sequencing was used to assess the association of PGAM1 with immune cells. Findings were validated with tumor specimens from 60 KIRC patients, correlating PGAM1 expression with clinicopathological features and prognosis using bioinformatics and immunohistochemistry. We demonstrated the expression of central gene regulators in renal cancer in relation to genetic variants, deletions, and tumor microenvironment. Mutations in these hub genes were positively associated with distinct immune cells in six different immune datasets and played a crucial role in immune cell infiltration in KIRC. Single-cell RNA-sequencing revealed that elevated PGAM1 was associated with immune cell infiltration, specifically macrophages. Furthermore, pharmacogenomic analysis of renal cancer cell lines indicated that inactivation of PGAM1 was associated with increased sensitivity to specific small-molecule drugs. Altered PGAM1 in KIRC is associated with disease progression and immune microenvironment. It has diagnostic and prognostic implications, indicating its potential in precision medicine and drug screening.