Characterizing dedifferentiation of thyroid cancer by integrated analysis

Understanding of dedifferentiation, an indicator of poo prognosis for patients with thyroid cancer, has been hampered by imprecise and incomplete characterization of its heterogeneity and its attributes. Using single-cell RNA sequencing, we explored the landscape of thyroid cancer at single-cell resolution with 46,205 cells and delineated its dedifferentiation process and suppressive immune microenvironment. The developmental trajectory indicated that anaplastic thyroid cancer (ATC) cells were derived from a small subset of papillary thyroid cancer (PTC) cells. Moreover, a potential functional role of CREB3L1 on ATC development was revealed by integrated analyses of copy number alteration and transcriptional regulatory network. Multiple genes in differentiation-related pathways (e.g., EMT) were involved as the downstream targets of CREB3L1, increased expression of which can thus predict higher relapse risk of PTC. Collectively, our study provided insights into the heterogeneity and molecular evolution of thyroid cancer and highlighted the potential driver role of CREB3L1 in its dedifferentiation process.

Download Full-text

Screening Driving Transcription Factors in the Processing of Gastric Cancer

Gastroenterology Research and Practice ◽

10.1155/2016/8431480 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 5

Author(s):

Guangzhong Xu ◽

Kai Li ◽

Nengwei Zhang ◽

Bin Zhu ◽

Guosheng Feng

Keyword(s):

Gastric Cancer ◽

Transcription Factors ◽

Regulatory Network ◽

Target Genes ◽

Transcriptional Regulatory Network ◽

Expression Profiles ◽

Functional Enrichment ◽

Regulatory Mechanisms ◽

Integrated Analysis ◽

Transcriptional Regulatory

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer.Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed.Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer.Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.

Download Full-text

The role of chemotherapy and latest emerging target therapies in anaplastic thyroid cancer

OncoTargets and Therapy ◽

10.2147/ott.s46545 ◽

2013 ◽

pp. 1231 ◽

Cited By ~ 31

Author(s):

Nerina Denaro ◽

Lo Nigro ◽

E g Russi ◽

Merlano

Keyword(s):

Thyroid Cancer ◽

Anaplastic Thyroid Cancer ◽

Target Therapies

Download Full-text

Integrated Analysis of Thyroid Cancer Public Datasets Reveals Role of Post-Transcriptional Regulation on Tumor Progression by Targeting of Immune System Mediators

PLoS ONE ◽

10.1371/journal.pone.0141726 ◽

2015 ◽

Vol 10 (11) ◽

pp. e0141726 ◽

Cited By ~ 11

Author(s):

Murilo V. Geraldo ◽

Edna T. Kimura

Keyword(s):

Transcriptional Regulation ◽

Thyroid Cancer ◽

Immune System ◽

Tumor Progression ◽

Integrated Analysis ◽

Public Datasets ◽

Post Transcriptional Regulation

Download Full-text

Identification of pathogenic genes and transcription factors in respiratory syncytial virus

BMC Pediatrics ◽

10.1186/s12887-020-02480-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Lei Li ◽

Yong An Ni ◽

Zhenfeng Song ◽

Zhi Yi ◽

Fang Wang

Keyword(s):

Transcription Factors ◽

Respiratory Syncytial Virus ◽

Respiratory Infections ◽

Transcriptional Regulatory Network ◽

Enrichment Analysis ◽

Microarray Dataset ◽

Integrated Analysis ◽

Pathogenic Genes ◽

Transcriptional Regulatory ◽

Syncytial Virus

Abstract Background Respiratory syncytial virus (RSV) is a major cause of acute lower respiratory infections in children, especially bronchiolitis. Our study aimed to identify the key genes and upstream transcription factors in RSV. Methods To screen for RSV pathogenic genes, an integrated analysis was performed using the RSV microarray dataset in GEO. Functional annotation and potential pathways for differentially expressed genes (DEGs) were further explored by GO and KEGG enrichment analysis. We constructed the RSV-specific transcriptional regulatory network to identify key transcription factors for DEGs in RSV. Results From three GEO datasets, we identified 1059 DEGs (493 up-regulated and 566 down-regulated genes, FDR < 0.05 and |Combined.ES| > 0.8) between RSV patients and normal controls. GO and KEGG analysis revealed that ‘response to virus’ (FDR = 7.13E-15), ‘mitochondrion’ (FDR = 1.39E-14) and ‘Asthma’ (FDR = 1.28E-06) were significantly enriched pathways for DEGs. The expression of IFI27, IFI44, IFITM3, FCER1A, and ISG15 were shown to be involved in the pathogenesis of RSV. Conclusions We concluded that IFI27, IFI44, IFITM3, FCER1A, and ISG15 may play a role in RSV. Our finding may contribute to the development of new potential biomarkers, reveal the underlying pathogenesis and also identify novel therapeutic targets for RSV.

Download Full-text

Identification of KLF6/PSGs and NPY-Related USF2/CEACAM Transcriptional Regulatory Networks via Spinal Cord Bulk and Single-Cell RNA-Seq Analysis

Disease Markers ◽

10.1155/2021/2826609 ◽

2021 ◽

Vol 2021 ◽

pp. 1-21

Author(s):

Xinbing Liu ◽

Wei Gao ◽

Wei Liu

Keyword(s):

Spinal Cord ◽

Single Cell ◽

Regulatory Networks ◽

Single Cell Analysis ◽

Transcriptional Regulatory Network ◽

Transcriptional Regulator ◽

Cell Analysis ◽

Rna Seq ◽

Transcriptional Regulatory Networks ◽

Transcriptional Regulatory

Background. To further understand the development of the spinal cord, an exploration of the patterns and transcriptional features of spinal cord development in newborn mice at the cellular transcriptome level was carried out. Methods. The mouse single-cell sequencing (scRNA-seq) dataset was downloaded from the GSE108788 dataset. Single-cell RNA-Seq (scRNA-Seq) was conducted on cervical and lumbar spinal V2a interneurons from 2 P0 neonates. Single-cell analysis using the Seurat package was completed, and marker mRNAs were identified for each cluster. Then, pseudotemporal analysis was used to analyze the transcription changes of marker mRNAs in different clusters over time. Finally, the functions of these marker mRNAs were assessed by enrichment analysis and protein-protein interaction (PPI) networks. A transcriptional regulatory network was then constructed using the TRRUST dataset. Results. A total of 949 cells were screened. Single-cell analysis was conducted based on marker mRNAs of each cluster, which revealed the heterogeneity of neonatal mouse spinal cord neuronal cells. Functional analysis of pseudotemporal trajectory-related marker mRNAs suggested that pregnancy-specific glycoproteins (PSGs) and carcinoembryonic antigen cell adhesion molecules (CEACAMs) were the core mRNAs in cluster 3. GSVA analysis then demonstrated that the different clusters had differences in pathway activity. By constructing a transcriptional regulatory network, USF2 was identified to be a transcriptional regulator of CEACAM1 and CEACAM5, while KLF6 was identified to be a transcriptional regulator of PSG3 and PSG5. This conclusion was then validated using the Genotype-Tissue Expression (GTEx) spinal cord transcriptome dataset. Conclusions. This study completed an integrated analysis of a single-cell dataset with the utilization of marker mRNAs. USF2/CEACAM1&5 and KLF6/PSG3&5 transcriptional regulatory networks were identified by spinal cord single-cell analysis.

Download Full-text

Single-cell Transcriptomic Analysis Reveals the Cellular Heterogeneity of Mesenchymal Stem Cells

10.1101/2021.11.24.469676 ◽

2021 ◽

Author(s):

Chen Zhang ◽

Xueshuai Han ◽

Jingkun Liu ◽

Lei Chen ◽

Ying Lei ◽

...

Keyword(s):

Stem Cells ◽

Mesenchymal Stem Cells ◽

Single Cell ◽

Ex Vivo ◽

Developmental Trajectory ◽

Cellular Heterogeneity ◽

Multipotent Progenitor Cells ◽

Definition Of

Ex vivo-expanded mesenchymal stem cells (MSCs) have been demonstrated to be a heterogeneous mixture of cells exhibiting varying proliferative, multipotential, and immunomodulatory capacities. However, the exact characteristics of MSCs remain largely unknown. By single-cell RNA sequencing of 61,296 MSCs derived from bone marrow and Wharton's jelly, we revealed five distinct subpopulations. The developmental trajectory of these five MSC subpopulations were mapped, revealing a differentiation path from stem-like active proliferative cells (APCs) to multipotent progenitor cells, followed by the branching into two paths - adipogenesis or osteochondrogenesis - and subsequent differentiation into unipotent prechondrocytes. The stem-like APCs, expressing the perivascular mesodermal progenitor markers CSPG4/MCAM/NES, uniquely exhibited strong proliferation and stemness signatures. Remarkably, the prechondrocyte subpopulation specifically expressed immunomodulatory genes and was able to suppress activated CD3+ T cell proliferation in vitro, supporting the role of this population in immunoregulation. In summary, our analysis mapped the heterogeneous subpopulations of MSCs and identified two subpopulations with potential functions in self-renewal and immunoregulation. Our findings advance the definition of MSCs by identifying the specific functions of its heterogeneous cellular composition, allowing for more specific and effective MSC application through the purification of its functional subpopulations.

Download Full-text

Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Mouse Brain Vasculature

BioMed Research International ◽

10.1155/2021/7643209 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Wei-Wei Lin ◽

Lin-Tao Xu ◽

Yi-Sheng Chen ◽

Ken Go ◽

Chenyu Sun ◽

...

Keyword(s):

Single Cell ◽

Mouse Brain ◽

Regulatory Network ◽

Regulatory Networks ◽

Transcriptional Regulatory Network ◽

Rna Seq ◽

Brain Vasculature ◽

Transcriptional Regulatory ◽

Cell Transcriptome ◽

Single Cell Transcriptome

Background. The critical role of vascular health on brain function has received much attention in recent years. At the single-cell level, studies on the developmental processes of cerebral vascular growth are still relatively few. Techniques for constructing gene regulatory networks (GRNs) based on single-cell transcriptome expression data have made significant progress in recent years. Herein, we constructed a single-cell transcriptional regulatory network of mouse cerebrovascular cells. Methods. The single-cell RNA-seq dataset of mouse brain vessels was downloaded from GEO (GSE98816). This cell clustering was annotated separately using singleR and CellMarker. We then used a modified version of the SCENIC method to construct GRNs. Next, we used a mouse version of SEEK to assess whether genes in the regulon were coexpressed. Finally, regulatory module analysis was performed to complete the cell type relationship quantification. Results. Single-cell RNA-seq data were used to analyze the heterogeneity of mouse cerebrovascular cells, whereby four cell types including endothelial cells, fibroblasts, microglia, and oligodendrocytes were defined. These subpopulations of cells and marker genes together characterize the molecular profile of mouse cerebrovascular cells. Through these signatures, key transcriptional regulators that maintain cell identity were identified. Our findings identified genes like Lmo2, which play an important role in endothelial cells. The same cell type, for instance, fibroblasts, was found to have different regulatory networks, which may influence the functional characteristics of local tissues. Conclusions. In this study, a transcriptional regulatory network based on single-cell analysis was constructed. Additionally, the study identified and profiled mouse cerebrovascular cells using single-cell transcriptome data as well as defined TFs that affect the regulatory network of the mouse brain vasculature.

Download Full-text

Role of Advanced Glycation End-Products and Other Ligands for AGE Receptors in Thyroid Cancer Progression

Journal of Clinical Medicine ◽

10.3390/jcm10184084 ◽

2021 ◽

Vol 10 (18) ◽

pp. 4084

Author(s):

Agnieszka Bronowicka-Szydełko ◽

Łukasz Kotyra ◽

Łukasz Lewandowski ◽

Andrzej Gamian ◽

Irena Kustrzeba-Wójcicka

Keyword(s):

Thyroid Cancer ◽

Cancer Progression ◽

Advanced Glycation End Products ◽

Intracellular Signaling ◽

Anaplastic Thyroid Cancer ◽

Carbonyl Stress ◽

Advanced Glycation ◽

Glycation End Products ◽

End Products

To date, thyroid cancers (TCs) remain a clinical challenge owing to their heterogeneous nature. The etiopathology of TCs is associated not only with genetic mutations or chromosomal rearrangements, but also non-genetic factors, such as oxidative-, nitrosative-, and carbonyl stress-related alterations in tumor environment. These factors, through leading to the activation of intracellular signaling pathways, induce tumor tissue proliferation. Interestingly, the incidence of TCs is often coexistent with various simultaneous mutations. Advanced glycation end-products (AGEs), their precursors and receptors (RAGEs), and other ligands for RAGEs are reported to have significant influence on carcinogenesis and TCs progression, inducing gene mutations, disturbances in histone methylation, and disorders in important carcinogenesis-related pathways, such as PI3K/AKT/NF-kB, p21/MEK/MPAK, or JAK/STAT, RAS/ERK/p53, which induce synthesis of interleukins, growth factors, and cytokines, thus influencing metastasis, angiogenesis, and cancer proliferation. Precursors of AGE (such as methylglyoxal (MG)) and selected ligands for RAGEs: AS1004, AS1008, and HMGB1 may, in the future, become potential targets for TCs treatment, as low MG concentration is associated with less aggressive anaplastic thyroid cancer, whereas the administration of anti-RAGE antibodies inhibits the progression of papillary thyroid cancer and anaplastic thyroid cancer. This review is aimed at collecting the information on the role of compounds, engaged in glycation process, in the pathogenesis of TCs. Moreover, the utility of these compounds in the diagnosis and treatment of TCs is thoroughly discussed. Understanding the mechanism of action of these compounds on TCs pathogenesis and progression may potentially be the grounds for the development of new treatment strategies, aiming at quality-of-life improvements.

Download Full-text