scholarly journals Autophagy Regulatory Genes MET and RIPK2 Play a Prognostic Role in Pancreatic Ductal Adenocarcinoma: A Bioinformatic Analysis Based on GEO and TCGA

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xingyu Li ◽  
Zhiqiang Li ◽  
Hongwei Zhu ◽  
Xiao Yu
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Differentially Expressed Genes ◽  
Clinical Application ◽  
Regulatory Genes ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Ductal Adenocarcinoma ◽  
Rna Seq

Pancreatic ductal adenocarcinoma is a common malignant tumor with a poor prognosis. Autophagy activity changes in both cancer cells and microenvironment and affects the progression of pancreatic ductal adenocarcinoma. The purpose of this study was to predict the prognostic autophagy regulatory genes and their role in the regulation of autophagy in pancreatic ductal adenocarcinoma. We draw conclusions based on gene expression data from different platforms: GSE62165 and GSE85916 from the array platform, TCGA from the bulk RNA-seq platform, and GSE111672 from the single-cell RNA-seq platform. At first, we detected differentially expressed genes in pancreatic ductal adenocarcinoma compared with normal pancreatic tissue based on GSE62165. Then, we screened prognostic genes based on GSE85916 and TCGA. Furthermore, we constructed a risk signature composed of the prognostic differentially expressed genes. Finally, we predicted the probable role of these genes in regulating autophagy and the types of cell expressing these genes. According to our screening criteria, there were only two genes: MET and RIPK2, selected into the development of the risk signature. However, evaluated by log-rank tests, receiver operating characteristic curves, and calibration curves, the risk signature was worth considering its clinical application because of good sensitivity, specificity, and stability. Besides, we predicted that both MET and RIPK2 promote autophagy in pancreatic ductal adenocarcinoma by gene set enrichment analysis. Analysis of single-cell RNA-seq data from GSE111672 revealed that both MET and RIPK2 were expressed in cancer cells while RIPK2 was also expressed in monocytes and neutrophils. After comprehensive analysis, we found that both MET and RIPK2 are related to the prognosis of pancreatic ductal adenocarcinoma and provided some associated clues for clinical application and basic experiment research.

scholarly journals Bioinformatics-based Screening of Key Genes for Saponin Metabolism in Quinoa

2021 ◽  
Author(s):  
Chengang Guo ◽  
Zhimin wei ◽  
Wei Lyu ◽  
Yanlou Geng
Keyword(s):  
Differentially Expressed Genes ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Hierarchical Cluster ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Differential Analysis ◽  
Rna Seq ◽  
Protein Coding ◽  
Key Genes

Abstract Quinoa saponins have complex, diverse and evident physiologic activities. However, the key regulatory genes for quinoa saponin metabolism are not yet well studied. The purpose of this study was to explore genes closely related to quinoa saponin metabolism. In this study, the significantly differentially expressed genes in yellow quinoa were firstly screened based on RNA-seq technology. Then, the key genes for saponin metabolism were selected by gene set enrichment analysis (GSEA) and principal component analysis (PCA) statistical methods. Finally, the specificity of the key genes was verified by hierarchical clustering. The results of differential analysis showed that 1654 differentially expressed genes were achieved after pseudogenes deletion. Therein, there were 142 long non-coding genes and 1512 protein-coding genes. Based on GSEA analysis, 116 key candidate genes were found to be significantly correlated with quinoa saponin metabolism. Through PCA dimension reduction analysis, 57 key genes were finally obtained. Hierarchical cluster analysis further demonstrated that these key genes can clearly separate the four groups of samples. The present results could provide references for the breeding of sweet quinoa and would be helpful for the rational utilization of quinoa saponins.

scholarly journals Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution

2019 ◽  
Author(s):  
Abdel Nasser Hosein ◽  
Huocong Huang ◽  
Zhaoning Wang ◽  
Kamalpreet Parmar ◽  
Wenting Du ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Ductal Adenocarcinoma ◽  
Cell Populations ◽  
Specific Cell ◽  
Cell Heterogeneity ◽  
Mesenchymal Transition

AbstractBackground & AimsPancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death with limited therapeutic options available. This highlights the need for improved understanding of the biology of PDA progression. The progression of PDA is a highly complex and dynamic process featuring changes in cancer cells and stromal cells; however, a comprehensive characterization of PDA cancer cell and stromal cell heterogeneity during disease progression is lacking. In this study, we aimed to profile cell populations and understand their phenotypic changes during PDA progression.MethodsWe employed single-cell RNA sequencing technology to agnostically profile cell heterogeneity during different stages of PDA progression in genetically engineered mouse models.ResultsOur data indicate that an epithelial-to-mesenchymal transition of cancer cells accompanies tumor progression. We also found distinct populations of macrophages with increasing inflammatory features during PDA progression. In addition, we noted the existence of three distinct molecular subtypes of fibroblasts in the normal mouse pancreas, which ultimately gave rise to two distinct populations of fibroblasts in advanced PDA, supporting recent reports on intratumoral fibroblast heterogeneity. Our data also suggest that cancer cells and fibroblasts are dynamically regulated by epigenetic mechanisms.ConclusionThis study systematically outlines the landscape of cellular heterogeneity during the progression of PDA. It strongly improves our understanding of the PDA biology and has the potential to aid in the development of therapeutic strategies against specific cell populations of the disease.

scholarly journals Author Correction: Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma

Cell Research ◽  
2019 ◽  
Vol 29 (9) ◽  
pp. 777-777
Author(s):  
Junya Peng ◽  
Bao-Fa Sun ◽  
Chuan-Yuan Chen ◽  
Jia-Yi Zhou ◽  
Yu-Sheng Chen ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Malignant Progression ◽  
Ductal Adenocarcinoma ◽  
Rna Seq

scholarly journals Using RNA-Seq to Investigate Immune-Metabolism Features in Immunocompromised Patients With Sepsis

2021 ◽  
Vol 8 ◽  
Author(s):  
Po-Liang Cheng ◽  
Hsin-Hua Chen ◽  
Yu-Han Jiang ◽  
Tzu-Hung Hsiao ◽  
Chen-Yu Wang ◽  
...  
Keyword(s):  
T Cell ◽  
Differentially Expressed Genes ◽  
Cell Function ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Immunocompromised Patients ◽  
Rna Seq ◽  
Cell Repertoire ◽  
Tertiary Referral Centre ◽  
Immunocompetent Patients

Objective: Sepsis is life threatening and leads to complex inflammation in patients with immunocompromised conditions, such as cancer, and receiving immunosuppressants for autoimmune diseases and organ transplant recipients. Increasing evidence has shown that RNA-Sequencing (RNA-Seq) can be used to define subendotype in patients with sepsis; therefore, we aim to use RNA-Seq to identify transcriptomic features among immunocompromised patients with sepsis.Methods: We enrolled patients who were admitted to medical intensive care units (ICUs) for sepsis at a tertiary referral centre in central Taiwan. Whole blood on day-1 and day-8 was obtained for RNA-Seq. We used Gene Set Enrichment Analysis (GSEA) to identify the enriched pathway of day-8/day-1 differentially expressed genes and MiXCR to determine the diversity of T cell repertoire.Results: A total of 18 immunocompromised subjects with sepsis and 18 sequential organ failure assessment (SOFA) score-matched immunocompetent control subjects were enrolled. The ventilator-day, ICU-stay, and hospital-day were similar between the two groups, whereas the hospital mortality was higher in immunocompromised patients than those in immunocompetent patients (50.0 vs. 5.6%, p < 0.01). We found that the top day-8/day-1 upregulated genes in the immunocompetent group were mainly innate immunity and inflammation relevant genes, namely, PRSS33, HDC, ALOX15, FCER1A, and OLR1, whereas a blunted day-8/day-1 dynamic transcriptome was found among immunocompromised patients with septic. Functional pathway analyses of day-8/day-1 differentially expressed genes identified the upregulated functional biogenesis and T cell-associated pathways in immunocompetent patients recovered from sepsis, whereas merely downregulated metabolism-associated pathways were found in immunocompromised patients with septic. Moreover, we used MiXCR to identify a higher diversity of T cell receptor (TCR) in immunocompetent patients both on day-1 and on day-8 than those in immunocompromised patients.Conclusions: Using RNA-Seq, we found compromised T cell function, altered metabolic signalling, and decreased T cell diversity among immunocompromised patients with septic, and more mechanistic studies are warranted to elucidate the underlying mechanism.

scholarly journals Single-cell analysis of pancreatic ductal adenocarcinoma identifies a novel fibroblast subtype associated with poor prognosis but better immunotherapy response

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Yu Wang ◽  
Yiyi Liang ◽  
Haiyan Xu ◽  
Xiao Zhang ◽  
Tiebo Mao ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Single Cell Analysis ◽  
Treatment Options ◽  
Objective Response ◽  
Complete Response ◽  
Ductal Adenocarcinoma

AbstractThe current pathological and molecular classification of pancreatic ductal adenocarcinoma (PDAC) provides limited guidance for treatment options, especially for immunotherapy. Cancer-associated fibroblasts (CAFs) are major players of desmoplastic stroma in PDAC, modulating tumor progression and therapeutic response. Using single-cell RNA sequencing, we explored the intertumoral heterogeneity among PDAC patients with different degrees of desmoplasia. We found substantial intertumoral heterogeneity in CAFs, ductal cancer cells, and immune cells between the extremely dense and loose types of PDACs (dense-type, high desmoplasia; loose-type, low desmoplasia). Notably, no difference in CAF abundance was detected, but a novel subtype of CAFs with a highly activated metabolic state (meCAFs) was found in loose-type PDAC compared to dense-type PDAC. MeCAFs had highly active glycolysis, whereas the corresponding cancer cells used oxidative phosphorylation as a major metabolic mode rather than glycolysis. We found that the proportion and activity of immune cells were much higher in loose-type PDAC than in dense-type PDAC. Then, the clinical significance of the CAF subtypes was further validated in our PDAC cohort and a public database. PDAC patients with abundant meCAFs had a higher risk of metastasis and a poor prognosis but showed a dramatically better response to immunotherapy (64.71% objective response rate, one complete response). We characterized the intertumoral heterogeneity of cellular components, immune activity, and metabolic status between dense- and loose-type PDACs and identified meCAFs as a novel CAF subtype critical for PDAC progression and the susceptibility to immunotherapy.

scholarly journals Single-cell mapper (scMappR): using scRNA-seq to infer the cell-type specificities of differentially expressed genes

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Dustin J Sokolowski ◽  
Mariela Faykoo-Martinez ◽  
Lauren Erdman ◽  
Huayun Hou ◽  
Cadia Chan ◽  
...  
Keyword(s):  
Single Cell ◽  
Differentially Expressed Genes ◽  
Cell Types ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Kidney Regeneration ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Cost Constraints ◽  
Mouse Tissues

Abstract RNA sequencing (RNA-seq) is widely used to identify differentially expressed genes (DEGs) and reveal biological mechanisms underlying complex biological processes. RNA-seq is often performed on heterogeneous samples and the resulting DEGs do not necessarily indicate the cell-types where the differential expression occurred. While single-cell RNA-seq (scRNA-seq) methods solve this problem, technical and cost constraints currently limit its widespread use. Here we present single cell Mapper (scMappR), a method that assigns cell-type specificity scores to DEGs obtained from bulk RNA-seq by leveraging cell-type expression data generated by scRNA-seq and existing deconvolution methods. After evaluating scMappR with simulated RNA-seq data and benchmarking scMappR using RNA-seq data obtained from sorted blood cells, we asked if scMappR could reveal known cell-type specific changes that occur during kidney regeneration. scMappR appropriately assigned DEGs to cell-types involved in kidney regeneration, including a relatively small population of immune cells. While scMappR can work with user-supplied scRNA-seq data, we curated scRNA-seq expression matrices for ∼100 human and mouse tissues to facilitate its stand-alone use with bulk RNA-seq data from these species. Overall, scMappR is a user-friendly R package that complements traditional differential gene expression analysis of bulk RNA-seq data.

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