scholarly journals Dissecting the Single-Cell Transcriptome Network in Superficial/Deep Tumor Tissues of Diffuse Gastric Cancer

2021 ◽  
Author(s):  
Yili Ren ◽  
Beibei Zhang ◽  
Chenkai Xu ◽  
Lei Zhang
Keyword(s):  
Gastric Cancer ◽  
Survival Analysis ◽  
Single Cell ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Cell Subpopulation ◽  
Diffuse Gastric Cancer ◽  
Normal Tissues ◽  
Tumor Tissues

Abstract Background and purpose: Gastric cancer is a type of highly heterogeneous malignant tumor and the prognosis of gastric cancer is hard to be improved due to limited knowledge on the molecular mechanism of heterogeneity. Single-cell sequencing technology is recently widely used for the investigation of both inter-tumoral heterogeneity and intra-tumoral heterogeneity. The present study aims to explore the potential oncogene by analyzing the single-cell data in the GSE167297 dataset.Methods: The GSE167297 dataset was downloaded from the GEO database, followed by quality control to remove data with lower quality. The division on cell subtypes was determined by the characteristic marker expressed in each cell subpopulation. Wilcoxon rank-sum test was used to screen out differentially expressed genes. Survival analysis was performed to evaluate the prognostic value of G-protein subunit g 11 (GNG11) gene which was significantly overexpressed in deep tumor tissues of diffuse gastric cancer.Results: In both normal tissues and tumor tissues, subtypes of immune cells and stromal cells were identified, with a higher proportion of infiltrated macrophages observed in deep tumor tissues. EPCAM was found significantly highly expressed in a cell subpopulation from gastric tumor tissues. 515 differentially expressed genes (| log2FC | > 2 and FDR < 1e-5) were screened out between normal tissues and tumor tissues. 86 differentially expressed genes (| log2FC | > 1 and FDR < 0.01) were screened out between superficial and deep tumor tissues, in which GNG11 was most highly expressed in deep tumor tissues (mean expression value: 0.1247, FC value: 52.2109). Disease-specific survival analysis on GNG11 results showed that the HR [95%CI] in the constructed univariate Cox proportional risk model was 4.419 [1.399-13.96] and the P-value in the log-rank test was 0.0056.Conclusion: Differentially expression profiles were provided both extratumorally and intratumorally, indicating a higher infiltration of macrophages in deep tumor tissues. Additionally,GNG11 was screened out to be a significant risk factor in STAD patients.

scholarly journals Genomic Expression Profiling of Colorectal Cancer in Silico

2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Hub Genes ◽  
Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

scholarly journals Comprehensive Analysis of the Expression Profiles of Long Non-Coding RNAs with Associated ceRNA Network Involved in the Colon Cancer Staging and Progression

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Meini Wu ◽  
Wenliang Li ◽  
Fengchang Huang ◽  
Jing Sun ◽  
Kang ping Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Expression Profiles ◽  
Comprehensive Analysis ◽  
Differentially Expressed ◽  
Stage Iii ◽  
Aberrant Expression ◽  
Normal Tissues ◽  
Cerna Network ◽  
Tumor Tissues ◽  
Non Coding Rnas

AbstractLong non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) to compete with microRNAs (miRNAs) in cancer occurrence and development. However, the differential expression of RNAs and their ceRNA network during the development of colon cancer (CC) remains unclear. This study was aimed at comprehensive analysis of the lncRNAs and their ceRNA networks associated with CC. Whole transcriptome sequencing was performed on colorectal and adjacent normal tissues at different pathological stages. Forty-nine lncRNAs were differently expressed between the CC tissues and their adjacent normal tissues at all stages. Aberrant expression of lncRNA CDKN2B-AS1 and lncRNA MIR4435-2HG was confirmed by TCGA database. Moreover, 14 lncRNAs were differentially expressed between early and advance stages of the tumor tissues, and 117 miRNAs were specifically expressed in stage III & IV. Weighted gene co-expression network analysis of 17105 differently expressed mRNAs revealed that the mRNAs shown in module pink, midnight blue, black, and light cyan were related to TNM and pathological stage, and that these mRNAs were enriched in cancer related functions and pathways. As DElncRNA showed a trend of change similar to that of the DEmRNA and opposite to that of DEmiRNA, ceRNA network was constructed with 3 DEmiRNAs, 5 DElncRNAs, and 130 DEmRNAs. Real time PCR revealed that expression of MEG3 was decreased in the tumor tissues belonging to stage III and IV as compared to that in stage I. Moreover, hsa-miR-324-5p was upregulated, while FGFR3, PLCB4, and IKBKB were downregulated in the tumor tissues as compared to that in the adjacent normal tissues. Thus, this study revealed differentially expressed lncRNA between different stages of CC as well as suggested that lncRNA CDKN2B-AS1, MIR4435-2HG, and MEG3 may act as diagnostic biomarkers for the development of CC.

scholarly journals Gene Expression Analysis of Human Papillomavirus-Associated Colorectal Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Qiancheng Qiu ◽  
Yazhen Li ◽  
Zhiqiang Fan ◽  
Fen Yao ◽  
Wenjun Shen ◽  
...  
Keyword(s):  
Human Papillomavirus ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Target Genes ◽  
Hpv Infection ◽  
Differentially Expressed ◽  
Noncancerous Tissue ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Taqman Array

Purpose. Human papillomavirus (HPV) antigens had been found in colorectal cancer (CRC) tissue, but little evidence demonstrates the association of HPV with oncogene mutations in CRC. We aim to elucidate the mutated genes that link HPV infection and CRC carcinogenesis. Methods. Cancerous and adjacent noncancerous tissues were obtained from CRC patients. HPV antigen was measured by using the immunohistochemical (IHC) technique. The differentially expressed genes (DEGs) in HPV-positive and HPV-negative tumor tissues were measured by using TaqMan Array Plates. The target genes were validated with the qPCR method. Results. 15 (31.9%) cases of CRC patients were observed to be HPV positive, in which HPV antigen was expressed in most tumor tissues rather than in adjacent noncancerous tissues. With TaqMan Array Plates analyses, we found that 39 differentially expressed genes (DEGs) were upregulated, while 17 DEGs were downregulated in HPV-positive CRC tissues compared with HPV-negative tissues. Four DEGs (MMP-7, MYC, WNT-5A, and AXIN2) were upregulated in tumor vs. normal tissues, or adenoma vs. normal tissue in TCGA, which was overlapped with our data. In the confirmation test, MMP-7, MYC, WNT-5A, and AXIN2 were upregulated in cancerous tissue compared with adjacent noncancerous tissue. MYC, WNT-5A, and AXIN2 were shown to be upregulated in HPV-positive CRC tissues when compared to HPV-negative tissues. Conclusion. HPV-encoding genome may integrate into the tumor genomes that involved in multiple signaling pathways. Further genomic and proteomic investigation is necessary for obtaining a more comprehensive knowledge of signaling pathways associated with the CRC carcinogenesis.

Calreticulin is Differentially Expressed in Invasive Ductal Carcinoma: A Comparative Study

2019 ◽  
Vol 16 (2) ◽  
pp. 148-155
Author(s):  
Asma Tariq ◽  
Rana Muhammad Mateen ◽  
Iram Fatima ◽  
Muhammad Waheed Akhtar
Keyword(s):  
Invasive Ductal Carcinoma ◽  
Tumor Tissue ◽  
Ductal Carcinoma ◽  
Tissue Level ◽  
Differentially Expressed ◽  
Breast Cancer Patients ◽  
Two Dimensional Gel Electrophoresis ◽  
Normal Tissues ◽  
Tumor Tissues ◽  
Grade Ii

Objective: The aim of the present study was to build protein profiles of untreated breast cancer patients of invasive ductal carcinoma grade II at tissue level in Pakistani population and to compare 2-D profiles of breast tumor tissues with matched normal tissues in order to evaluate for variations of proteins among them. Materials & Methods: Breast tissue profiles were made after polytron tissue lysis and rehydrated proteins were further characterized by using two-dimensional gel electrophoresis. On the basis of isoelectric point (pI) and molecular weight, proteins were identified by online tool named Siena 2-D database and their identification was further confirmed by using MALDI-TOF. Results: Among identified spots, 10 proteins were found to be differentially expressed i.e.; COX5A, THIO, TCTP, HPT, SODC, PPIA, calreticulin (CRT), HBB, albumin and serotransferrin. For further investigation, CRT was selected. The level of CRT in tumors was found to be significantly higher than in normal group (p < 0.05). The increased expression of CRT level in tumor was statistically significant (p = 0.010) at a 95% confidence level (p < 0.05) as analyzed by Mann-Whitney. CRT was found distinctly expressed in high amount in tumor tissue as compared to their matched normal tissues. Conclusion: It has been concluded that CRT expression could discriminate between normal tissue and tumor tissue so it might serve as a possible candidate for future studies in cancer diagnostic markers.

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

scholarly journals EPEN-22. SINGLE-CELL RNA SEQUENCING IDENTIFIES UPREGULATION OF IKZF1 IN PFA2 MYELOID SUBPOPULATION DRIVING AN ANTI-TUMOR PHENOTYPE

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii312-iii312
Author(s):  
Andrea Griesinger ◽  
Eric Prince ◽  
Andrew Donson ◽  
Kent Riemondy ◽  
Timothy Ritzman ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
T Cell Activation ◽  
Expression Profiles ◽  
Myeloid Cells ◽  
Cell Subset ◽  
Lineage Tracing ◽  
Machine Learning Techniques ◽  
Cell Subpopulation ◽  
Immune Gene

Abstract We have previously shown immune gene phenotype variations between posterior fossa ependymoma subgroups. PFA1 tumors chronically secrete IL-6, which pushes the infiltrating myeloid cells to an immune suppressive function. In contrast, PFA2 tumors have a more immune activated phenotype and have a better prognosis. The objective of this study was to use single-cell(sc) RNAseq to descriptively characterize the infiltrating myeloid cells. We analyzed approximately 8500 cells from 21 PFA patient samples and used advanced machine learning techniques to identify distinct myeloid and lymphoid subpopulations. The myeloid compartment was difficult to interrupt as the data shows a continuum of gene expression profiles exist within PFA1 and PFA2. Through lineage tracing, we were able to tease out that PFA2 myeloid cells expressed more genes associated with an anti-viral response (MHC II, TNF-a, interferon-gamma signaling); while PFA1 myeloid cells had genes associated with an immune suppressive phenotype (angiogenesis, wound healing, IL-10). Specifically, we found expression of IKZF1 was upregulated in PFA2 myeloid cells. IKZF1 regulates differentiation of myeloid cells toward M1 or M2 phenotype through upregulation of either IRF5 or IRF4 respectively. IRF5 expression correlated with IKZF1, being predominately expressed in the PFA2 myeloid cell subset. IKZF1 is also involved in T-cell activation. While we have not completed our characterization of the T-cell subpopulation, we did find significantly more T-cell infiltration in PFA2 than PFA1. Moving forward these studies will provide us with valuable information regarding the molecular switches involved in the tumor-immune microenvironment and to better develop immunotherapy for PFA ependymoma.

scholarly journals Single-Cell Expression Landscape of SARS-CoV-2 Receptor ACE2 and Host Proteases in Normal and Malignant Lung Tissues from Pulmonary Adenocarcinoma Patients

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1250
Author(s):  
Guangchun Han ◽  
Ansam Sinjab ◽  
Kieko Hara ◽  
Warapen Treekitkarnmongkol ◽  
Patrick Brennan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Single Cell ◽  
Cancer Patients ◽  
Expression Profiles ◽  
Lung Cells ◽  
Alveolar Type ◽  
Specific Expression ◽  
Lung Cancer Patients ◽  
Normal Tissues ◽  
Cell Expression

The novel coronavirus SARS-CoV-2 is the causative agent of the COVID-19 pandemic. Severely symptomatic COVID-19 is associated with lung inflammation, pneumonia, and respiratory failure, thereby raising concerns of elevated risk of COVID-19-associated mortality among lung cancer patients. Angiotensin-converting enzyme 2 (ACE2) is the major receptor for SARS-CoV-2 entry into lung cells. The single-cell expression landscape of ACE2 and other SARS-CoV-2-related genes in pulmonary tissues of lung cancer patients remains unknown. We sought to delineate single-cell expression profiles of ACE2 and other SARS-CoV-2-related genes in pulmonary tissues of lung adenocarcinoma (LUAD) patients. We examined the expression levels and cellular distribution of ACE2 and SARS-CoV-2-priming proteases TMPRSS2 and TMPRSS4 in 5 LUADs and 14 matched normal tissues by single-cell RNA-sequencing (scRNA-seq) analysis. scRNA-seq of 186,916 cells revealed epithelial-specific expression of ACE2, TMPRSS2, and TMPRSS4. Analysis of 70,030 LUAD- and normal-derived epithelial cells showed that ACE2 levels were highest in normal alveolar type 2 (AT2) cells and that TMPRSS2 was expressed in 65% of normal AT2 cells. Conversely, the expression of TMPRSS4 was highest and most frequently detected (75%) in lung cells with malignant features. ACE2-positive cells co-expressed genes implicated in lung pathobiology, including COPD-associated HHIP, and the scavengers CD36 and DMBT1. Notably, the viral scavenger DMBT1 was significantly positively correlated with ACE2 expression in AT2 cells. We describe normal and tumor lung epithelial populations that express SARS-CoV-2 receptor and proteases, as well as major host defense genes, thus comprising potential treatment targets for COVID-19 particularly among lung cancer patients.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

scholarly journals Expression profiles of differentially expressed genes affecting fecundity in goat ovarian tissues

2015 ◽  
Vol 14 (4) ◽  
pp. 18743-18752 ◽  
Author(s):  
Y.H. Ling ◽  
Q. Quan ◽  
H. Xiang ◽  
L. Zhu ◽  
M.X. Chu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Differentially Expressed

Long-Living Budding Yeast Cell Subpopulation Induced by Ethanol/Acetate and Respiration

2019 ◽  
Vol 75 (8) ◽  
pp. 1448-1456 ◽  
Author(s):  
Young-Yon Kwon ◽  
Seung-Soo Kim ◽  
Han-Jun Lee ◽  
Seo-Hyeong Sheen ◽  
Kyoung Heon Kim ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Budding Yeast ◽  
Gradient Centrifugation ◽  
Carbon Sources ◽  
Cell Types ◽  
Glucose Sensing ◽  
Differentially Expressed ◽  
Cell Subpopulation ◽  
Genes Encoding ◽  
Cell Transcriptome

Abstract Budding yeast generate heterogeneous cells that can be separated into two distinctive cell types: short-living low-density and long-living high-density (HD) cells by density gradient centrifugation. We found that ethanol and acetate induce formation of HD cells, and mitochondrial respiration is required. From their transcriptomes and metabolomes, we found upregulated differentially expressed genes in HD cells involved in the RGT2/RGT1 glucose sensing pathway and its downstream genes encoding hexose transporters. For HD cells, we determined an abundance of various carbon sources including glucose, lactate, pyruvate, trehalose, mannitol, mannose, and galactose. Other upregulated differentially expressed genes in HD cells were involved in the TORC1–SCH9 signaling pathway and its downstream genes involved in cytoplasmic translation. We also measured an abundance of free amino acids in HD cells including valine, proline, isoleucine, and glutamine. These characteristics of the HD cell transcriptome and metabolome may be important conditions for maintaining a long-living phenotype.

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