1.Knockdown of IGF2BP2 inhibits colorectal cancer cell proliferation, migration and promotes tumor immunity by down-regulating MYC expression.
Tianyue LIU ; Chenying HAN ; Chenchen HU ; Siyi MAO ; Yuanjie SUN ; Shuya YANG ; Kun YANG
Chinese Journal of Cellular and Molecular Immunology 2023;39(4):303-310
		                        		
		                        			
		                        			Objective To investigate the effect of insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) on the proliferation, migration and tumor immune microenvironment of colorectal cancer cells and its possible molecular mechanism. Methods The Cancer Genome Atlas (TCGA) database was used to analyze the expression levels of IGF2BP2 and MYC in colorectal cancer and adjacent tissues. The expression of IGF2BP2 in HCT-116 and SW480 human colorectal cancer cells was silenced by RNA interference (RNAi), and the silencing effect was detected by quantitative real-time PCR. After knocking down IGF2BP2, colony formation assay, CCK-8 assay and 5-ethynyl-2'-deoxyuridine (EdU) assay were employed to detect cell colony formation and proliferation ability. TranswellTM assay was used to detect cell migration ability. Quantitative real-time PCR was used to detect the mRNA expression of IGF2BP2, MYC, tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β) and interleukin-10 (IL-10). The protein expression of IGF2BP2 and MYC was detected by western blot. The binding ability of IGF2BP2 and MYC in HCT-116 cells was detected by quantitative real-time PCR after RNA immunoprecipitation. Results The results of TCGA database showed that the expression of IGF2BP2 and MYC in colorectal cancer tissues was significantly higher than that in adjacent tissues, and the survival time of colorectal cancer patients with high expression of IGF2BP2 was shorter. After silencing IGF2BP2, the viability, proliferation and migration of HCT-116 and SW480 cells were decreased. The mRNA expression of MYC, TGF-β and IL-10 in IGF2BP2 knockdown group was significantly decreased, while the expression of TNF-α mRNA was increased. The expression of MYC protein and the stability of MYC mRNA were significantly decreased. RIP-qPCR results showed that IGF2BP2 could bind to MYC mRNA. Conclusion Knockdown of IGF2BP2 inhibits colorectal cancer cell proliferation, migration and promotes tumor immunity by down-regulating MYC expression.
		                        		
		                        		
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Cell Line, Tumor
		                        			;
		                        		
		                        			Cell Movement/genetics*
		                        			;
		                        		
		                        			Cell Proliferation/genetics*
		                        			;
		                        		
		                        			Colorectal Neoplasms/metabolism*
		                        			;
		                        		
		                        			Gene Expression Regulation, Neoplastic
		                        			;
		                        		
		                        			Interleukin-10/metabolism*
		                        			;
		                        		
		                        			RNA, Messenger
		                        			;
		                        		
		                        			RNA-Binding Proteins/metabolism*
		                        			;
		                        		
		                        			Transforming Growth Factor beta/genetics*
		                        			;
		                        		
		                        			Tumor Microenvironment/immunology*
		                        			;
		                        		
		                        			Tumor Necrosis Factor-alpha/metabolism*
		                        			;
		                        		
		                        			Proto-Oncogene Proteins c-myc/metabolism*
		                        			
		                        		
		                        	
2.A human circulating immune cell landscape in aging and COVID-19.
Yingfeng ZHENG ; Xiuxing LIU ; Wenqing LE ; Lihui XIE ; He LI ; Wen WEN ; Si WANG ; Shuai MA ; Zhaohao HUANG ; Jinguo YE ; Wen SHI ; Yanxia YE ; Zunpeng LIU ; Moshi SONG ; Weiqi ZHANG ; Jing-Dong J HAN ; Juan Carlos Izpisua BELMONTE ; Chuanle XIAO ; Jing QU ; Hongyang WANG ; Guang-Hui LIU ; Wenru SU
Protein & Cell 2020;11(10):740-770
		                        		
		                        			
		                        			Age-associated changes in immune cells have been linked to an increased risk for infection. However, a global and detailed characterization of the changes that human circulating immune cells undergo with age is lacking. Here, we combined scRNA-seq, mass cytometry and scATAC-seq to compare immune cell types in peripheral blood collected from young and old subjects and patients with COVID-19. We found that the immune cell landscape was reprogrammed with age and was characterized by T cell polarization from naive and memory cells to effector, cytotoxic, exhausted and regulatory cells, along with increased late natural killer cells, age-associated B cells, inflammatory monocytes and age-associated dendritic cells. In addition, the expression of genes, which were implicated in coronavirus susceptibility, was upregulated in a cell subtype-specific manner with age. Notably, COVID-19 promoted age-induced immune cell polarization and gene expression related to inflammation and cellular senescence. Therefore, these findings suggest that a dysregulated immune system and increased gene expression associated with SARS-CoV-2 susceptibility may at least partially account for COVID-19 vulnerability in the elderly.
		                        		
		                        		
		                        		
		                        			Adult
		                        			;
		                        		
		                        			Aged
		                        			;
		                        		
		                        			Aged, 80 and over
		                        			;
		                        		
		                        			Aging
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Betacoronavirus
		                        			;
		                        		
		                        			CD4-Positive T-Lymphocytes
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Cell Lineage
		                        			;
		                        		
		                        			Chromatin Assembly and Disassembly
		                        			;
		                        		
		                        			Coronavirus Infections
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Cytokine Release Syndrome
		                        			;
		                        		
		                        			etiology
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Cytokines
		                        			;
		                        		
		                        			biosynthesis
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			Disease Susceptibility
		                        			;
		                        		
		                        			Flow Cytometry
		                        			;
		                        		
		                        			methods
		                        			;
		                        		
		                        			Gene Expression Profiling
		                        			;
		                        		
		                        			Gene Expression Regulation, Developmental
		                        			;
		                        		
		                        			Gene Rearrangement
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Immune System
		                        			;
		                        		
		                        			cytology
		                        			;
		                        		
		                        			growth & development
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Immunocompetence
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			Inflammation
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Mass Spectrometry
		                        			;
		                        		
		                        			methods
		                        			;
		                        		
		                        			Middle Aged
		                        			;
		                        		
		                        			Pandemics
		                        			;
		                        		
		                        			Pneumonia, Viral
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Sequence Analysis, RNA
		                        			;
		                        		
		                        			Single-Cell Analysis
		                        			;
		                        		
		                        			Transcriptome
		                        			;
		                        		
		                        			Young Adult
		                        			
		                        		
		                        	
3.Expression of MHCⅠ genes in different tissues of Rana dybowskii under the stress of Aeromonas hydrophila.
Ruofei BIAN ; Xiao XU ; Yufen LIU ; Peng LIU ; Wenge ZHAO
Chinese Journal of Biotechnology 2020;36(7):1323-1333
		                        		
		                        			
		                        			The aim of this study was to investigate the expression of MHCⅠ gene in different tissues of Rana dybowskii under the stress of Aeromonas hydrophila (Ah), and to provide evidence for revealing the anti-infective immune response mechanism of amphibians. The experimental animal model of Aeromonas hydrophila infection was first constructed, and the pathological changes were observed by HE staining. The MHCⅠ gene α1+α2 peptide binding region of Rana dybowskii was cloned by RT-PCR and analyzed by bioinformatics. Real-time PCR was used to detect the transcription level of MHCⅠ in different tissues under Ah stress. After Ah infection, the skin, liver and muscle tissues showed signs of cell structure disappearance and texture disorder. The MHCⅠ gene α1+α2 peptide binding region fragment was 494 bp, encoding 164 amino acids, and homology with amphibians. Above 77%, the homology with mammals was as low as 14.96%, indicating that the α1+α2 region of MHC gene was less conserved among different species. The results of real-time PCR show that the liver, spleen and kidney of the experimental group were under Ah stress. The transcript levels of MHCⅠ gene in skin and muscle tissues were higher than those in the control group at 72 h, but the time to peak of each tissue was different (P<0.01), indicating that the response time of MHCⅠ gene in different tissues was different under Ah stress. This study provides a reference for further exploring the immune function of MHC molecules in anti-infection.
		                        		
		                        		
		                        		
		                        			Aeromonas hydrophila
		                        			;
		                        		
		                        			Animals
		                        			;
		                        		
		                        			Gene Expression Profiling
		                        			;
		                        		
		                        			Gene Expression Regulation
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Gram-Negative Bacterial Infections
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Liver
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Ranidae
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			microbiology
		                        			;
		                        		
		                        			Skin
		                        			;
		                        		
		                        			metabolism
		                        			
		                        		
		                        	
4.Transcriptome and Regulatory Network Analyses of CD19-CAR-T Immunotherapy for B-ALL.
Qiong ZHANG ; Hui HU ; Si-Yi CHEN ; Chun-Jie LIU ; Fei-Fei HU ; Jianming YU ; Yaohui WU ; An-Yuan GUO
Genomics, Proteomics & Bioinformatics 2019;17(2):190-200
		                        		
		                        			
		                        			Chimeric antigen receptor (CAR) T cell therapy has exhibited dramatic anti-tumor efficacy in clinical trials. In this study, we reported the transcriptome profiles of bone marrow cells in four B cell acute lymphoblastic leukemia (B-ALL) patients before and after CD19-specific CAR-T therapy. CD19-CAR-T therapy remarkably reduced the number of leukemia cells, and three patients achieved bone marrow remission (minimal residual disease negative). The efficacy of CD19-CAR-T therapy on B-ALL was positively correlated with the abundance of CAR and immune cell subpopulations, e.g., CD8 T cells and natural killer (NK) cells, in the bone marrow. Additionally, CD19-CAR-T therapy mainly influenced the expression of genes linked to cell cycle and immune response pathways, including the NK cell mediated cytotoxicity and NOD-like receptor signaling pathways. The regulatory network analyses revealed that microRNAs (e.g., miR-148a-3p and miR-375), acting as oncogenes or tumor suppressors, could regulate the crosstalk between the genes encoding transcription factors (TFs; e.g., JUN and FOS) and histones (e.g., HIST1H4A and HIST2H4A) involved in CD19-CAR-T therapy. Furthermore, many long non-coding RNAs showed a high degree of co-expression with TFs or histones (e.g., FOS and HIST1H4B) and were associated with immune processes. These transcriptome analyses provided important clues for further understanding the gene expression and related mechanisms underlying the efficacy of CAR-T immunotherapy.
		                        		
		                        		
		                        		
		                        			Adult
		                        			;
		                        		
		                        			Antigens, CD19
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Bone Marrow
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			CD8-Positive T-Lymphocytes
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Gene Expression Regulation, Leukemic
		                        			;
		                        		
		                        			Gene Regulatory Networks
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Immunotherapy, Adoptive
		                        			;
		                        		
		                        			Male
		                        			;
		                        		
		                        			MicroRNAs
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Middle Aged
		                        			;
		                        		
		                        			Precursor Cell Lymphoblastic Leukemia-Lymphoma
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			therapy
		                        			;
		                        		
		                        			RNA, Long Noncoding
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Receptors, Antigen, T-Cell
		                        			;
		                        		
		                        			Transcription Factors
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Transcriptome
		                        			;
		                        		
		                        			genetics
		                        			
		                        		
		                        	
5.Hesperetin derivative-12 (HDND-12) regulates macrophage polarization by modulating JAK2/STAT3 signaling pathway.
Ling-Na KONG ; Xiang LIN ; Cheng HUANG ; Tao-Tao MA ; Xiao-Ming MENG ; Chao-Jie HU ; Qian-Qian WANG ; Yan-Hui LIU ; Qing-Ping SHI ; Jun LI
Chinese Journal of Natural Medicines (English Ed.) 2019;17(2):122-130
		                        		
		                        			
		                        			Macrophages show significant heterogeneity in function and phenotype, which could shift into different populations of cells in response to exposure to various micro-environmental signals. These changes, also termed as macrophage polarization, of which play an important role in the pathogenesis of many diseases. Numerous studies have proved that Hesperidin (HDN), a traditional Chinese medicine, extracted from fruit peels of the genus citrus, play key roles in anti-inflammation, anti-tumor, anti-oxidant and so on. However, the role of HDN in macrophage polarization has never been reported. Additional, because of its poor water solubility and bioavailability. Our laboratory had synthesized many hesperidin derivatives. Among them, hesperidin derivatives-12 (HDND-12) has better water solubility and bioavailability. So, we evaluated the role of HDND-12 in macrophage polarization in the present study. The results showed that the expression of Arginase-1 (Arg-1), interleukin-10 (IL-10), transforming growth factor β (TGF-β) were up-regulated by HDND-12, whereas the expression of inducible Nitric Oxide Synthase (iNOS) was down-regulated in LPS- and IFN-γ-treated (M1) RAW264.7 cells. Moreover, the expression of p-JAK2 and p-STAT3 were significantly decreased after stimulation with HDND-12 in M1-like macrophages. More importantly, when we taken AG490 (inhibitor of JAK2/STAT3 signaling), the protein levels of iNOS were significantly reduced in AG490 stimulation group compare with control in LPS, IFN-γ and HDND-12 stimulation cells. Taken together, these findings indicated that HDND-12 could prevent polarization toward M1-like macrophages, at least in part, through modulating JAK2/STAT3 pathway.
		                        		
		                        		
		                        		
		                        			Animals
		                        			;
		                        		
		                        			Cytokines
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Enzyme Inhibitors
		                        			;
		                        		
		                        			pharmacology
		                        			;
		                        		
		                        			Gene Expression Regulation
		                        			;
		                        		
		                        			drug effects
		                        			;
		                        		
		                        			Hesperidin
		                        			;
		                        		
		                        			chemistry
		                        			;
		                        		
		                        			pharmacology
		                        			;
		                        		
		                        			Inflammation
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Janus Kinase 2
		                        			;
		                        		
		                        			antagonists & inhibitors
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Macrophages
		                        			;
		                        		
		                        			drug effects
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Medicine, Chinese Traditional
		                        			;
		                        		
		                        			Mice
		                        			;
		                        		
		                        			Molecular Structure
		                        			;
		                        		
		                        			Phosphorylation
		                        			;
		                        		
		                        			drug effects
		                        			;
		                        		
		                        			RAW 264.7 Cells
		                        			;
		                        		
		                        			STAT3 Transcription Factor
		                        			;
		                        		
		                        			antagonists & inhibitors
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Signal Transduction
		                        			;
		                        		
		                        			drug effects
		                        			
		                        		
		                        	
6.Expression of PD1 and BTLA on the CD8+ T Cell and γδT Cell Subsets in Peripheral Blood of Non-Small Cell Lung Cancer Patients.
Yi BAO ; Juan-Fen MO ; Jia-Yuan WU ; Chen-Xi CAO
Chinese Medical Sciences Journal 2019;34(4):248-255
		                        		
		                        			
		                        			Objective To investigate the expression and regulation of programmed cell death protein 1 (PD1), B lymphocyte and T lymphocyte attenuator (BTLA) in peripheral blood of patients with non-small cell lung cancer (NSCLC); to examine the correlation of the mRNA levels between PD and BTLA in NSCLC. Methods Flow cytometry was used to detect the expression of PD1 and BTLA on the surfaces of CD8+ T cells and γδ+ T cells in the peripheral blood samples collected from 32 in-patients with stage IV NSCLC and 30 healthy individuals. We compared the expression of PD1 and BTLA on the surfaces of γδ+ T cells in the NSCLC patients with bone metastasis before and after the treatment of zoledronic acid. The correlations of PD1 and BTLA, as well as their ligands were analyzed using Pearson correlation analysis with the cBioPortal data platform. Results The frequency of PD1 on the surfaces of CD8+ T cells was significantly higher than that of the γδT cells in both healthy controls (t=2.324, P=0.024) and NSCLC patients(t=2.498, P=0.015). The frequency of PD1 on CD8+ T cells, rather than on γδ+ T cells, was significantly upregulated in advanced NSCLC patients compared with that in healthy controls (t=4.829, P<0.001). The PD1+ BTLA+γδT cells of the healthy controls were significantly lower than that of the NSCLC patients (t=2.422, P=0.0185). No differences in percentage of PD1+γδ+ and BTLA+γδ+ T cells were observed in 7 NSCLC patients with bone metastasis before and after zoledronic acid treatment. PD1 was positively correlated with BTLA in both lung adenocarcinoma (r=0.54; P<0.05) and lung squamous cell carcinoma (r=0.78; P<0.05). Conclusions The upregulation of co-inhibitory molecules occurs on the surfaces of both CD8+ T cells and γδT cells in advanced NSCLC, suggesting that these molecules were involved in regulating the inactivation of CD8+ T cells and γδ+ T cells, immune escape and tumor invasion.
		                        		
		                        		
		                        		
		                        			Bone Neoplasms/secondary*
		                        			;
		                        		
		                        			CD8-Positive T-Lymphocytes
		                        			;
		                        		
		                        			Carcinoma, Non-Small-Cell Lung/immunology*
		                        			;
		                        		
		                        			Case-Control Studies
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Gene Expression Regulation, Neoplastic
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Ligands
		                        			;
		                        		
		                        			Lung Neoplasms/immunology*
		                        			;
		                        		
		                        			Lymphocyte Subsets/immunology*
		                        			;
		                        		
		                        			Male
		                        			;
		                        		
		                        			Middle Aged
		                        			;
		                        		
		                        			Programmed Cell Death 1 Receptor/metabolism*
		                        			;
		                        		
		                        			RNA, Messenger/metabolism*
		                        			;
		                        		
		                        			Receptors, Antigen, T-Cell, gamma-delta
		                        			;
		                        		
		                        			Receptors, Immunologic/metabolism*
		                        			
		                        		
		                        	
7.IL-2 and IL-15 dependent thymic development of Foxp3-expressing regulatory T lymphocytes.
Cécile APERT ; Paola ROMAGNOLI ; Joost P M VAN MEERWIJK
Protein & Cell 2018;9(4):322-332
		                        		
		                        			
		                        			Immunosuppressive regulatory T lymphocytes (Treg) expressing the transcription factor Foxp3 play a vital role in the maintenance of tolerance of the immune-system to self and innocuous non-self. Most Treg that are critical for the maintenance of tolerance to self, develop as an independent T-cell lineage from common T cell precursors in the thymus. In this organ, their differentiation requires signals from the T cell receptor for antigen, from co-stimulatory molecules, as well as from cytokine-receptors. Here we focus on the cytokines implicated in thymic development of Treg, with a particular emphasis on the roles of interleukin-2 (IL-2) and IL-15. The more recently appreciated involvement of TGF-β in thymic Treg development is also briefly discussed. Finally, we discuss how cytokine-dependence of Treg development allows for temporal, quantitative, and potentially qualitative modulation of this process.
		                        		
		                        		
		                        		
		                        			Animals
		                        			;
		                        		
		                        			Cell Differentiation
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			Cytokines
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Forkhead Transcription Factors
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Gene Expression Regulation
		                        			;
		                        		
		                        			Immune Tolerance
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			Interleukin-15
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Interleukin-2
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Mice
		                        			;
		                        		
		                        			Receptors, Antigen, T-Cell
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			T-Lymphocytes, Regulatory
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Transforming Growth Factor beta
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			
		                        		
		                        	
8.Analysis of differential expression of tight junction proteins in cultured oral epithelial cells altered by Porphyromonas gingivalis, Porphyromonas gingivalis lipopolysaccharide, and extracellular adenosine triphosphate.
Wei GUO ; Peng WANG ; Zhong-Hao LIU ; Ping YE
International Journal of Oral Science 2018;10(1):e8-e8
		                        		
		                        			
		                        			Tight junctions (TJs) are the most apical intercellular junctions of epithelial cells formed by occludin, claudins, junctional adhesion molecules (JAMs), and zonula occludens (ZO). Tight junction proteins can sense the presence of bacteria and regulate the transcription of target genes that encode effectors and regulators of the immune response. The aim of this study was to determine the impact of TJ proteins in response to Porphyromonas gingivalis (P. gingivalis), P. gingivalis lipopolysaccharide (P. gingivalis LPS), and extracellular adenosine triphosphate (ATP) in the oral epithelial cell culture model. Quantified real time-polymerase chain reaction (RT-PCR), immunoblots, and immunostaining were performed to assess the gene and protein expression in TJs. It was found that P. gingivalis infection led to transient upregulation of the genes encoding occludin, claudin-1, and claudin-4 but not JAM-A, claudin-15, or ZO-1, while P. gingivalis LPS increased claudin-1, claudin-15, and ZO-1 and decreased occludin, JAM-A, and claudin-4. Tight junction proteins showed significant upregulation in the above two groups when cells were pretreated with ATP for 3 h. The findings indicated that P. gingivalis induced the host defence responses at an early stage. P. gingivalis LPS exerted a more powerful stimulatory effect on the disruption of the epithelial barrier than P. gingivalis. ATP stimulation enhanced the reaction of TJ proteins to P. gingivalis invasion and LPS destruction of the epithelium.International Journal of Oral Science (2018) 10, e8; doi:10.1038/ijos.2017.51; published online 10 January 2018.
		                        		
		                        		
		                        		
		                        			Adenosine Triphosphate
		                        			;
		                        		
		                        			pharmacology
		                        			;
		                        		
		                        			Cells, Cultured
		                        			;
		                        		
		                        			Epithelial Cells
		                        			;
		                        		
		                        			cytology
		                        			;
		                        		
		                        			Gene Expression
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Immunoblotting
		                        			;
		                        		
		                        			Lipopolysaccharides
		                        			;
		                        		
		                        			pharmacology
		                        			;
		                        		
		                        			Mouth Mucosa
		                        			;
		                        		
		                        			cytology
		                        			;
		                        		
		                        			Porphyromonas gingivalis
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Real-Time Polymerase Chain Reaction
		                        			;
		                        		
		                        			Tight Junction Proteins
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Up-Regulation
		                        			
		                        		
		                        	
9.The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling.
Johana A LUNA CORONELL ; Khulan SERGELEN ; Philipp HOFER ; István GYURJÁN ; Stefanie BREZINA ; Peter HETTEGGER ; Gernot LEEB ; Karl MACH ; Andrea GSUR ; Andreas WEINHÄUSEL
Genomics, Proteomics & Bioinformatics 2018;16(1):73-84
		                        		
		                        			
		                        			Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 "CRC genes." These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology.
		                        		
		                        		
		                        		
		                        			Adult
		                        			;
		                        		
		                        			Aged
		                        			;
		                        		
		                        			Aged, 80 and over
		                        			;
		                        		
		                        			Biomarkers, Tumor
		                        			;
		                        		
		                        			genetics
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Case-Control Studies
		                        			;
		                        		
		                        			Colonic Neoplasms
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			metabolism
		                        			;
		                        		
		                        			Computational Biology
		                        			;
		                        		
		                        			methods
		                        			;
		                        		
		                        			Computer Simulation
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Gene Expression Profiling
		                        			;
		                        		
		                        			Gene Expression Regulation, Neoplastic
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Immunoglobulin G
		                        			;
		                        		
		                        			immunology
		                        			;
		                        		
		                        			Male
		                        			;
		                        		
		                        			Middle Aged
		                        			;
		                        		
		                        			Protein Array Analysis
		                        			;
		                        		
		                        			methods
		                        			
		                        		
		                        	
10.The role of miR-492 in the regulation of OK blood group antigen expression on red blood cells.
Luyi YE ; Chen WANG ; Qixiu YANG ; Ziyan ZHU
Chinese Journal of Medical Genetics 2017;34(5):680-683
OBJECTIVETo investigate whether miR-492 is involved in the post-transcriptional regulation of OK blood group antigen expression on red blood cells.
METHODSTwo 3'-UTR fragments of the BSG gene were synthesized with a chemical method, which respectively encompassed the BSG rs8259 TT or BSG rs8259 AA sites. The fragments were added with Xho I and Not I restriction enzyme cutting sites at both ends and cloned into a pUC57 vector, which in turn was constructed into a psiCHECK-2 vector and verified by sequencing. K562 cells were transfected with various combinations of miR-492 mimic and constructed psiCHECK2-BSG-T or psiCHECK2-BSG-A recombinant plasmid. A blank control group was set up. Each transfection experiment was repeated three times. The activity of Renilla reniformis luciferase was determined and normalized with that of firefly luciferase, and detected with a dual-luciferase reporter assay system. The data were subjected to statistical analysis.
RESULTSThe sequencing results confirmed that the recombinant psiCHECK2 plasmids containing the BSG rs8259 TT or rs8259 AA sites were constructed successfully. The results of dual-luciferase report gene detection showed that the miR-492 mimic could significantly inhibit psiCHECK2-BSG-T at a concentration over 100 nmol/L. However, it could not inhibit psiCHECK-BSG-A.
CONCLUSIONmiR-492 may be involved in the regulation of OK antigen expression on red blood cells with the BSG rs8259 TT genotype.
Basigin ; genetics ; Blood Group Antigens ; genetics ; Erythrocytes ; immunology ; Gene Expression Regulation ; Genotype ; Humans ; MicroRNAs ; physiology
            
Result Analysis
Print
Save
E-mail