E-cigarette use results in suppression of immune and inflammatory-response genes in nasal epithelial cells similar to cigarette smoke

Exposure to cigarette smoke is known to result in impaired host defense responses and immune suppressive effects. However, the effects of new and emerging tobacco products, such as e-cigarettes, on the immune status of the respiratory epithelium are largely unknown. We conducted a clinical study collecting superficial nasal scrape biopsies, nasal lavage, urine, and serum from nonsmokers, cigarette smokers, and e-cigarette users and assessed them for changes in immune gene expression profiles. Smoking status was determined based on a smoking history and a 3- to 4-wk smoking diary and confirmed using serum cotinine and urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) levels. Total RNA from nasal scrape biopsies was analyzed using the nCounter Human Immunology v2 Expression panel. Smoking cigarettes or vaping e-cigarettes resulted in decreased expression of immune-related genes. All genes with decreased expression in cigarette smokers ( n = 53) were also decreased in e-cigarette smokers. Additionally, vaping e-cigarettes was associated with suppression of a large number of unique genes ( n = 305). Furthermore, the e-cigarette users showed a greater suppression of genes common with those changed in cigarette smokers. This was particularly apparent for suppressed expression of transcription factors, such as EGR1, which was functionally associated with decreased expression of 5 target genes in cigarette smokers and 18 target genes in e-cigarette users. Taken together, these data indicate that vaping e-cigarettes is associated with decreased expression of a large number of immune-related genes, which are consistent with immune suppression at the level of the nasal mucosa.

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PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

Scientific Reports ◽

10.1038/s41598-021-95698-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kota Fujisawa ◽

Mamoru Shimo ◽

Y.-H. Taguchi ◽

Shinya Ikematsu ◽

Ryota Miyata

Keyword(s):

Gene Expression ◽

Feature Extraction ◽

Target Genes ◽

Gene Selection ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Principal Component ◽

Data Set ◽

Immune Related Genes ◽

Unsupervised Feature Extraction

AbstractCoronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

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A Comprehensive Genomic Approach Using Gain of Function Cell Models, Patient Specimens and ChIP-on-CHIP Technologies Identifies PLZF-RARα Target Genes with Potential Roles in t(11;17) Associated APL.

Blood ◽

10.1182/blood.v110.11.3168.3168 ◽

2007 ◽

Vol 110 (11) ◽

pp. 3168-3168

Author(s):

Jonathan D. Licht ◽

Kim L. Rice ◽

Itsaso Hormaeche ◽

Julia Meyer ◽

Ken I. Mills ◽

...

Keyword(s):

Cell Growth ◽

Target Genes ◽

Expression Profiles ◽

Defense Responses ◽

Myeloid Differentiation ◽

Small Subset ◽

U937 Cells ◽

Gain Of Function ◽

Cell Functions ◽

On Chip

Abstract The t(11;17)(q23;q21) translocation involves the production of reciprocal fusion proteins PLZF-RARα and RARα-PLZF, which mediate malignant transformation by binding to and dysregulating RARα/RXR and PLZF target genes, respectively. In order to investigate the molecular basis for PLZF-RARα induced leukemogenesis, we used a gain of function model in which PLZF-RARα was ectopically expressed in U937 leukemia cells. After demonstrating in our system that PLZF-RARα is capable of inducing a G1 cell cycle arrest and inhibiting cell growth and myeloid differentiation, we sought to identify genes directly bound and transcriptionally regulated by PLZF-RARα. Chromatin from U937PLZF-RARα expressing cells (+10nM RA) was immunoprecipitated using PLZF antibodies, amplified by ligation-mediated PCR and biological triplicates were hybridized to NimbleGen 2.7kB promoter arrays, which represent 24,275 human promoters. We identified 1797 genes that are directly bound by PLZF-RARα in at least 2 out of 3 arrays, and the majority of these genes (89%) are also bound in the absence of exogenously added RA. Quantitative real time PCR using primary ChIP samples was used to validate ChIP-on-CHIP results and all genes tested to date (n=11) were confirmed as direct targets of PLZF-RARα. Ontological analyses of genes identified by ChIP-on-CHIP revealed enrichment for genes involved in myeloid cell functions including immune, inflammatory and defense responses, in addition to genes involved in apoptosis and signal transduction pathways. Furthermore, genes encoding nuclear proteins were also highly enriched and these included previously identified RARα/RXR target genes (ie. CEBPε, RARβ2, PRAM1, NFE-2), which are likely targeted by the PLZF-RARα oncoprotein, as well as novel PLZF-RARα targets, many of which have roles in blood cell development and have been implicated in leukemia (ie. RUNX1, MLL2, MCL1, PIM1, FANCB). Of these 1797 genes, a significant percentage (22%) are also transcriptionally regulated by PLZF-RARα (>1.5 fold, p<0.05). To identify genes specific to the PLZF-RARα fusion generated in t(11;17) APL, we compared gene expression profiles of 26 PML-RARα and 4 PLZF-RARα expressing APL patient blasts. A comparison of differentially expressed genes in the patient specimens with those both directly bound and regulated by PLZF-RARα in U937 cells, identified a small subset of genes including RUNX1, KLF10, a transcriptional regulator and inhibitor of cell growth, as well as ID1 and ID2, whose expression level has been shown to correlate with myeloid differentiation. Although the expression of these genes was variable in PML-RARα blasts, expression was consistently lower in PLZF-RARα APL blasts (>2 fold, p<0.03). In U937 cells, PLZF-RARα repressed RUNX1, KLF10 and ID1 in the absence of exogenous RA. Intriguingly, RUNX1, KLF10 and ID2 were also identified as direct target genes of PLZF in the KG1a cell line and were transcriptionally regulated by PLZF in U937 cells, suggesting that PLZF and PLZF-RARα may co-regulate a subset of target genes. Given the roles of RUNX1, KLF10, ID1 and ID2 in myeloid differentiation and growth inhibition, these genes may represent PLZF-RARα specific targets that potentially contribute to the pathogenesis of t(11;17) APL.

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Systematic Characterization of Novel Immune Gene Signatures Predicts Prognostic Factors in Hepatocellular Carcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.686664 ◽

2021 ◽

Vol 9 ◽

Author(s):

Dafeng Xu ◽

Yu Wang ◽

Jincai Wu ◽

Yuliang Zhang ◽

Zhehao Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Risk Score ◽

Cox Regression ◽

Expression Profiles ◽

Gene Signature ◽

Clinical Samples ◽

Immune Gene ◽

Cox Regression Analysis ◽

Immune Related Genes ◽

Cancer Tissues

Background: The prognosis of patients with hepatocellular carcinoma (HCC) is negatively affected by the lack of effective prognostic indicators. The change of tumor immune microenvironment promotes the development of HCC. This study explored new markers and predicted the prognosis of HCC patients by systematically analyzing immune characteristic genes.Methods: Immune-related genes were obtained, and the differentially expressed immune genes (DEIGs) between tumor and para-cancer samples were identified and analyzed using gene expression profiles from TCGA, HCCDB, and GEO databases. An immune prognosis model was also constructed to evaluate the predictive performance in different cohorts. The high and low groups were divided based on the risk score of the model, and different algorithms were used to evaluate the tumor immune infiltration cell (TIIC). The expression and prognosis of core genes in pan-cancer cohorts were analyzed, and gene enrichment analysis was performed using clusterProfiler. Finally, the expression of the hub genes of the model was validated by clinical samples.Results: Based on the analysis of 730 immune-related genes, we identified 64 common DEIGs. These genes were enriched in the tumor immunologic related signaling pathways. The first 15 genes were selected using RankAggreg analysis, and all the genes showed a consistent expression trend across multi-cohorts. Based on lasso cox regression analysis, a 5-gene signature risk model (ATG10, IL18RAP, PRKCD, SLC11A1, and SPP1) was constructed. The signature has strong robustness and can stabilize different cohorts (TCGA-LIHC, HCCDB18, and GSE14520). Compared with other existing models, our model has better performance. CIBERSORT was used to assess the landscape maps of 22 types of immune cells in TCGA, GSE14520, and HCCDB18 cohorts, and found a consistent trend in the distribution of TIIC. In the high-risk score group, scores of Macrophages M1, Mast cell resting, and T cells CD8 were significantly lower than those of the low-risk score group. Different immune expression characteristics, lead to the different prognosis. Western blot demonstrated that ATG10, PRKCD, and SPP1 were highly expressed in cancer tissues, while IL18RAP and SLC11A1 expression in cancer tissues was lower. In addition, IL18RAP has a highly positive correlation with B cell, macrophage, Neutrophil, Dendritic cell, CD8 cell, and CD4 cell. The SPP1, PRKCD, and SLC11A1 genes have the strongest correlation with macrophages. The expression of ATG10, IL18RAP, PRKCD, SLC11A1, and SPP1 genes varies among different immune subtypes and between different T stages.Conclusion: The 5-immu-gene signature constructed in this study could be utilized as a new prognostic marker for patients with HCC.

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Construction of a novel immune gene-based model for prognosis prediction of colorectal cancer

10.21203/rs.3.rs-279544/v1 ◽

2021 ◽

Author(s):

Bin Xie ◽

jie lin

Keyword(s):

Gene Expression ◽

Cox Regression ◽

Expression Profiles ◽

Colon Adenocarcinoma ◽

Gene Set Enrichment Analysis ◽

Immune Gene ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Risk Of Death ◽

Immune Related Genes

Abstract Background Colon adenocarcinoma (COAD) is the third leading cause of cancer-related death. Although surgical treatment and chemotherapy of COAD have made significant progress, its immunotherapy also has great potential, nowadays. Methods Gene expression profiles and clinical data of COAD patients were obtained from The Cancer Genome Atlas_Colon Adenocarcinoma (TCGA_COAD) and Gene Expression Omnibus (GEO) databases, which were further detected for immune-related genes. Immune-related genes were downloaded from Immunology Database and Analysis Portal (ImmPort). LASSO Cox regression analysis was utilized to analyze the immune-related prognostic signature. The prognostic value of the signature was validated by ROC curve. To further detected the potential pathway about immune-related genes in COAD patients, Gene Set Enrichment Analysis (GESA) was used to identify the most significant pathways. Results Finally, a total of 436 immune-related mRNA were identified. Eleven prognosis-related genes were selected to establish an immune-related prognostic signature, which divided patients into high and low risk groups. Several biological processes, such as immune response was enriched. Moreover, our prognosis model has better performance in predicting the 1-, 3-, 5- and 8-years overall survival (OS) for patients from the TCGA and GEO cohort. Also, the complicated signature obtained by combining immune-related signatures with clinical factors provides a more accurate OS predicting compared with individual molecular signatures. Conclusion We have established a prognostic signature consisting of 11 immune-related genes, which may be potential biomarkers for identifying COAD with a high risk of death. Then, the possibility including immunotherapy in personalized COAD treatment was evaluated.

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Identification of molecular subtyping system and four-gene prognostic signature with immune-related genes for uveal melanoma

Experimental Biology and Medicine ◽

10.1177/15353702211053801 ◽

2021 ◽

pp. 153537022110538

Author(s):

Fei Xia ◽

Zhilong Yu ◽

Aijun Deng ◽

Guohong Gao

Keyword(s):

Uveal Melanoma ◽

Expression Profiles ◽

Gene Set Enrichment Analysis ◽

Enrichment Score ◽

Immune Gene ◽

Cox Regression Analysis ◽

Immune Genes ◽

Gene Modules ◽

Melanoma Patients ◽

Immune Related Genes

Immunotherapy is the most promising treatment for uveal melanoma patients with metastasis. Tumor microenvironment plays an essential role in tumor progression and greatly affects the efficacy of immunotherapy. This research constructed an immune-related subtyping system and discovered immune prognostic genes to further understand the immune mechanism in uveal melanoma. Immune-related genes were determined from literature. Gene expression profiles of uveal melanoma were clustered using consensus clustering based on immune-related genes. Subtypes were further divided by applying immune landscape, and weighted correlation network analysis was performed to construct immune gene modules. Univariate Cox regression analysis was conducted to generate a prognostic model. Enriched immune cells were determined after gene set enrichment analysis. Three major immune subtypes (IS1, IS2, and IS3) were identified, and IS2 could be further divided into IS2A and IS2B. The subtypes were closely associated with uveal melanoma prognosis. IS3 group had the most favorable prognosis and was sensitive to PD-1 inhibitor. Immune genes in IS1 group showed an overall higher expression than IS3 group. Six immune gene modules were identified, and the enrichment score of immune genes varied within immune subtypes. Four immune prognostic genes ( IL32, IRF1, SNX20, and VAV1) were found to be closely related to survival. This novel immune subtyping system and immune landscape provide a new understanding of immunotherapy in uveal melanoma. The four prognostic genes can predict prognosis of uveal melanoma patients and contribute to new development of targeted drugs.

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Na,K-ATPase is a target of cigarette smoke and reduced expression predicts poor patient outcome of smokers with lung cancer

AJP Lung Cellular and Molecular Physiology ◽

10.1152/ajplung.00384.2010 ◽

2012 ◽

Vol 302 (11) ◽

pp. L1150-L1158 ◽

Cited By ~ 11

Author(s):

Thu P. Huynh ◽

Vei Mah ◽

Valerie B. Sampson ◽

David Chia ◽

Michael C. Fishbein ◽

...

Keyword(s):

Atpase Activity ◽

Lung Adenocarcinoma ◽

Cigarette Smoke ◽

Smoking Status ◽

Immunohistochemical Analysis ◽

Tumor Grade ◽

Smoking History ◽

Lung Carcinogenesis ◽

Lung Malignancies

Diminished Na,K-ATPase expression has been reported in several carcinomas and has been linked to tumor progression. However, few studies have determined whether Na,K-ATPase function and expression are altered in lung malignancies. Because cigarette smoke (CS) is a major factor underlying lung carcinogenesis and progression, we investigated whether CS affects Na,K-ATPase activity and expression in lung cell lines. Cells exposed to CS in vitro showed a reduction of Na,K-ATPase activity. We detected the presence of reactive oxygen species (ROS) in cells exposed to CS before Na,K-ATPase inhibition, and neutralization of ROS restored Na,K-ATPase activity. We further determined whether Na,K-ATPase expression correlated with increasing grades of lung adenocarcinoma and survival of patients with smoking history. Immunohistochemical analysis of lung adenocarcinoma tissues revealed reduced Na,K-ATPase expression with increasing tumor grade. Using tissue microarray containing lung adenocarcinomas of patients with known smoking status, we found that high expression of Na,K-ATPase correlated with better survival. For the first time, these data demonstrate that CS is associated with loss of Na,K-ATPase function and expression in lung carcinogenesis, which might contribute to disease progression.

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Analysis of Immune Gene Expression in Seabass (Lates calcarifer) Immunized with Inactivated Vaccine against Similar Damselfish Virus

Indian Journal of Animal Research ◽

10.18805/ijar.b-3813 ◽

2020 ◽

Author(s):

P. Sivasankar ◽

K. Riji John ◽

M. Rosalind George ◽

M. Mohamed Mansoor ◽

P. Magesh Kumar ◽

...

Keyword(s):

Immune Response ◽

Expression Profiles ◽

Disease Outbreaks ◽

Viral Disease ◽

Immune Gene ◽

Lates Calcarifer ◽

Virus Challenge ◽

Immune Genes ◽

Viral Vaccine ◽

Immune Related Genes

Background: Control of viral disease outbreaks in aquaculture and minimizing the loss of production can be achieved by development of effective vaccines. Efficacy of these vaccines can be improved by using adjuvants, immunostimulants or vaccine carriers. In this study, inactivated similar damselfish virus (SRDV) vaccine was prepared and expression profiles of immune related genes against virus challenge of the vaccine were investigated in seabass (Lates calcarifer). Methods: Formalin-inactivated virus vaccine was developed to assess its immune responses to SRDV challenge in fish. The immune response was induced by intra-peritoneal injection with inactivated viral vaccine added Quil-A® adjuvant. The transcriptional levels of immune genes IRF-7 and IL-10 were evaluated in the spleen and kidney of seabass from different groups by quantitative real-time RT-PCR assays. Result: Expression profiles of both genes (IRF-7 and IL-10) in the kidney and spleen of seabass immunized with vaccine added adjuvant were up-regulated at 48 hpi of the virus. In comparison, spleen of seabass immunized with vaccine added adjuvant showed highest expression profiles than kidney. The current study provides evidence for the presence of expression profiles of immune-related genes during the SRDV infection. The study also strongly suggests that Quil-A® adjuvant enhances the immune response of the vaccine candidates.

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Using Nicalert Strips to Validate Smoking Status in Pregnant Cigarette Smokers

PsycEXTRA Dataset ◽

10.1037/e707702011-001 ◽

2011 ◽

Author(s):

Diann E. Gaalema ◽

Stephen T. Higgins ◽

Matthew P. Bradstreet ◽

Sarah H. Heil ◽

Ira Bernstein

Keyword(s):

Smoking Status ◽

Cigarette Smokers

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Does Active Smoking Influence the Second Trimester Biochemical Markers Concentrations?

Revista de Chimie ◽

10.37358/rc.17.10.5862 ◽

2017 ◽

Vol 68 (10) ◽

pp. 2234-2236

Author(s):

Dan Navolan ◽

Florin Birsasteanu ◽

Adrian Carabineanu ◽

Octavian Cretu ◽

Diana Liana Badiu ◽

...

Keyword(s):

Pregnant Woman ◽

Pregnant Women ◽

Cigarette Smoke ◽

Chorionic Gonadotropin ◽

Reference Values ◽

Biochemical Markers ◽

Smoking Status ◽

Active Smoking ◽

Second Trimester ◽

Harmful Effects

Cigarette smoke contains over 7000 different substances some of them exerting harmful effects on embryo and pregnant woman. Nowadays 15 % of adult people and around 10-15% of pregnant women smoke. Previous studies showed that cigarette smoke compounds could exert pharmacodinamic effects and influence some of the second trimester biochemical markers concentration. Therefore there is a need to adjust the reference values of second trimester markers depending of the smoker status. The aim of our study was to analyse which of the markers are influenced by smoking and whether the software used to calculate the risk for aneuploidies is able to counterbalance this influence. Alpha-fetoprotein (AFP), chorionic gonadotropin hormone (hCG) and free estriol (uE3) values were measured in second trimester sera of 1242 pregnant women: 1089 non-smokers and 153 smokers. Only hCG second trimester values were influenced by smoking whereas AFP and uE3 values were not. The correction of medians according to the smoking status was able to counterbalance this effect.

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Genome-wide transcriptome profiling uncovers differential miRNAs and lncRNAs in ovaries of Hu sheep at different developmental stages

Scientific Reports ◽

10.1038/s41598-021-85245-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Samina Shabbir ◽

Prerona Boruah ◽

Lingli Xie ◽

Muhammad Fakhar-e-Alam Kulyar ◽

Mohsin Nawaz ◽

...

Keyword(s):

Target Genes ◽

Expression Profiles ◽

Ovarian Follicle ◽

Follicular Development ◽

Differentially Expressed ◽

Ovary Development ◽

Estrogen Metabolism ◽

Genome Wide ◽

Micro Rnas ◽

Hu Sheep

AbstractOvary development is an important determinant of the procreative capacity of female animals. Here, we performed genome-wide sequencing of long non-coding RNAs (lncRNAs) and mRNAs on ovaries of 1, 3 and 8 months old Hu sheep to assess their expression profiles and roles in ovarian development. We identified 37,309 lncRNAs, 45,404 messenger RNAs (mRNAs) and 330 novel micro RNAs (miRNAs) from the transcriptomic analysis. Six thousand, seven hundred and sixteen (6716) mRNAs and 1972 lncRNAs were significantly and differentially expressed in ovaries of 1 month and 3 months old Hu sheep (H1 vs H3). These mRNAs and target genes of lncRNAs were primarily enriched in the TGF-β and PI3K-Akt signalling pathways which are closely associated with ovarian follicular development and steroid hormone biosynthesis regulation. We identified MSTRG.162061.1, MSTRG.222844.7, MSTRG.335777.1, MSTRG.334059.16, MSTRG.188947.6 and MSTRG.24344.3 as vital genes in ovary development by regulating CTNNB1, CCNA2, CDK2, CDC20, CDK1 and EGFR expressions. A total of 2903 mRNAs and 636 lncRNAs were differentially expressed in 3 and 8 months old ovaries of Hu sheep (H3 vs H8); and were predominantly enriched in PI3K-Akt, progesterone-mediated oocyte maturation, estrogen metabolism, ovulation from the ovarian follicle and oogenesis pathways. These lncRNAs were also found to regulate FGF7, PRLR, PTK2, AMH and INHBA expressions during follicular development. Our result indicates the identified genes participate in the development of the final stages of follicles and ovary development in Hu sheep.

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