scholarly journals Cigarette smoke alters the transcriptome of non-involved lung tissue in lung adenocarcinoma patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Giulia Pintarelli ◽  
Sara Noci ◽  
Davide Maspero ◽  
Angela Pettinicchio ◽  
Matteo Dugo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Cigarette Smoke ◽  
Lung Tissue ◽  
Gene Networks ◽  
Lung Parenchyma ◽  
Fold Change ◽  
Differentially Expressed ◽  
Significant Gene ◽  
Never Smokers

Abstract Alterations in the gene expression of organs in contact with the environment may signal exposure to toxins. To identify genes in lung tissue whose expression levels are altered by cigarette smoking, we compared the transcriptomes of lung tissue between 118 ever smokers and 58 never smokers. In all cases, the tissue studied was non-involved lung tissue obtained at lobectomy from patients with lung adenocarcinoma. Of the 17,097 genes analyzed, 357 were differentially expressed between ever smokers and never smokers (FDR < 0.05), including 290 genes that were up-regulated and 67 down-regulated in ever smokers. For 85 genes, the absolute value of the fold change was ≥2. The gene with the smallest FDR was MYO1A (FDR = 6.9 × 10−4) while the gene with the largest difference between groups was FGG (fold change = 31.60). Overall, 100 of the genes identified in this study (38.6%) had previously been found to associate with smoking in at least one of four previously reported datasets of non-involved lung tissue. Seven genes (KMO, CD1A, SPINK5, TREM2, CYBB, DNASE2B, FGG) were differentially expressed between ever and never smokers in all five datasets, with concordant higher expression in ever smokers. Smoking-induced up-regulation of six of these genes was also observed in a transcription dataset from lung tissue of non-cancer patients. Among the three most significant gene networks, two are involved in immunity and inflammation and one in cell death. Overall, this study shows that the lung parenchyma transcriptome of smokers has altered gene expression and that these alterations are reproducible in different series of smokers across countries. Moreover, this study identified a seven-gene panel that reflects lung tissue exposure to cigarette smoke.

scholarly journals Uncovering Driver DNA Methylation Events in Nonsmoking Early Stage Lung Adenocarcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Xindong Zhang ◽  
Lin Gao ◽  
Zhi-Ping Liu ◽  
Songwei Jia ◽  
Luonan Chen
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Methylation Data ◽  
Driver Genes ◽  
Differential Network Analysis ◽  
Differential Network ◽  
Aberrant Dna Methylation ◽  
Never Smokers

As smoking rates decrease, proportionally more cases with lung adenocarcinoma occur in never-smokers, while aberrant DNA methylation has been suggested to contribute to the tumorigenesis of lung adenocarcinoma. It is extremely difficult to distinguish which genes play key roles in tumorigenic processes via DNA methylation-mediated gene silencing from a large number of differentially methylated genes. By integrating gene expression and DNA methylation data, a pipeline combined with the differential network analysis is designed to uncover driver methylation genes and responsive modules, which demonstrate distinctive expressions and network topology in tumors with aberrant DNA methylation. Totally, 135 genes are recognized as candidate driver genes in early stage lung adenocarcinoma and top ranked 30 genes are recognized as driver methylation genes. Functional annotation and the differential network analysis indicate the roles of identified driver genes in tumorigenesis, while literature study reveals significant correlations of the top 30 genes with early stage lung adenocarcinoma in never-smokers. The analysis pipeline can also be employed in identification of driver epigenetic events for other cancers characterized by matched gene expression data and DNA methylation data.

scholarly journals hnRNP U is differentially expressed in whole blood from patients with sepsis.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Whole Blood ◽  
Differentially Expressed ◽  
Significant Differential Expression ◽  
Hnrnp U ◽  
Significant Gene ◽  
Nuclear Ribonucleoprotein ◽  
Microarray Datasets

We probed published and public microarray datasets (1, 2) to discover the most significant gene expression changes in the blood of patients with sepsis. We identified significant differential expression of the heterogenous nuclear ribonucleoprotein hnRNP U in whole blood from patients with sepsis.

scholarly journals The interleukin-18 receptor is differentially expressed in the blood during sepsis.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Differentially Expressed ◽  
Interleukin 18 ◽  
Genes Encoding ◽  
Significant Gene ◽  
Microarray Datasets

We probed published and public microarray datasets (1, 2) to discover the most significant gene expression changes in the blood of patients with sepsis. We found significant induction expression of IL18RAP and IL18R1, genes encoding subunits of the interleukin-18 receptor, in whole blood from patients with sepsis.

scholarly journals DDX19B is differentially expressed in the brains of patients with psychotic disorders.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Gene Expression ◽  
Prefrontal Cortex ◽  
Microarray Data ◽  
Schizoaffective Disorder ◽  
Dorsolateral Prefrontal Cortex ◽  
Psychotic Disorders ◽  
Differentially Expressed ◽  
Dorsolateral Prefrontal ◽  
Significant Gene

We used public and published microarray data (1, 2) to identify the most significant gene expression changes in the brains of patients with psychotic disorders. We DDX19B as differentially expressed in the dorsolateral prefrontal cortex of patients with schizophrenia and schizoaffective disorder. In neurons of the dorsolateral prefrontal cortex from patients with psychotic disorders, DDX19B expression was significantly decreased.

Age-related differences in gene expression in colorectal cancer (CRC).

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 654-654
Author(s):  
Raphael M Byrne ◽  
Rebecca Ruhl ◽  
Christian Lanciault ◽  
Sudarshan Anand ◽  
Abhinav Nellore ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Rna Sequencing ◽  
Young Patients ◽  
Young Group ◽  
Fold Change ◽  
Differentially Expressed ◽  
Mouse Tumor ◽  
Sequencing Data ◽  
Old Patients

654 Background: Colorectal cancer (CRC) in young patients is increasing in incidence and is associated with worse outcomes than CRC in older patients. While distinct molecular subtypes of CRC have been recently characterized, it is unclear whether there are molecular differences between the tumors of young and old patients. We sought to identify differences in gene expression of CRC between these two groups. Our discovery analysis identified a gene signature of several differentially expressed RNAs, from which we validated PEG10. The PEG10 gene on chromosome 7q21.3 has been implicated in liver, gallbladder, thyroid, and blood cancers, and is thought to play a role in cancer cell survival and regulation of apoptosis. In hepatocellular carcinoma, increased PEG10 expression has been associated with younger patient age. Methods: RNA sequencing data was obtained from The Cancer Genome Atlas (TCGA) and analyzed for differences in gene expression between patients ≤ 45 years old and those ≥ 65 years old. The identified differentially expressed genes were then validated with qPCR using human CRC tissue from patients ≤ 45 years old and those ≥ 65 years old. Results: RNA sequencing data from patients ≤ 45 years old (n = 29) and patients ≥ 65 years old (n = 299) identified seven genes with increased expression in younger patients: ZNF334 (log2 [fold change] = 2.30), DSC3 (1.78), PEG10 (1.67), CACNA1I (1.54), PKIA (1.33), MAP9 (1.27), and EPHX3 (1.17) (p < 0.07). Validation with qPCR for PEG10 was most promising, and was performed on both young (n = 10, mean age = 39) and old patient samples ( n= 8, mean age = 72). Two cancers (20%) in the young group received radiation treatment and five (50%) received chemotherapy. One cancer (12.5%) in the old group received radiation and two (25%) received chemotherapy. PEG10 had increased expression in the young group with log2 [fold change] = 3.16 (p < 0.02). Conclusions: We have identified a potentially unique gene expression signature for CRC in young patients, which includes PEG10. Functional analysis of PEG10 and other genes is underway using in vitro cell culture, archived human tumor tissue, and mouse tumor models.

scholarly journals Gene expression in blood reflects smoking exposure among cancer-free women in the Norwegian Women and Cancer (NOWAC) postgenome cohort

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nikita Baiju ◽  
Torkjel M. Sandanger ◽  
Pål Sætrom ◽  
Therese H. Nøst
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Smoking Status ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
P Value ◽  
Smoking Exposure ◽  
Former Smokers ◽  
Never Smokers ◽  
Free Women

AbstractActive smoking has been linked to modulated gene expression in blood. However, there is a need for a more thorough understanding of how quantitative measures of smoking exposure relate to differentially expressed genes (DEGs) in whole-blood among ever smokers. This study analysed microarray-based gene expression profiles from whole-blood samples according to smoking status and quantitative measures of smoking exposure among cancer-free women (n = 1708) in the Norwegian Women and Cancer postgenome cohort. When compared with never smokers and former smokers, current smokers had 911 and 1082 DEGs, respectively and their biological functions could indicate systemic impacts of smoking. LRRN3 was associated with smoking status with the lowest FDR-adjusted p-value. When never smokers and all former smokers were compared, no DEGs were observed, but LRRN3 was differentially expressed when never smokers were compared with former smokers who quit smoking ≤ 10 years ago. Further, LRRN3 was positively associated with smoking intensity, pack-years, and comprehensive smoking index score among current smokers; and negatively associated with time since cessation among former smokers. Consequently, LRRN3 expression in whole-blood is a molecular signal of smoking exposure that could supplant self-reported smoking data in further research targeting blood-based markers related to the health effects of smoking.

scholarly journals The NER proteins are differentially expressed in ever smokers and in never smokers with lung adenocarcinoma

2009 ◽  
Vol 20 (7) ◽  
pp. 1257-1263 ◽  
Author(s):  
D. Planchard ◽  
J. Domont ◽  
E. Taranchon ◽  
I. Monnet ◽  
J. Tredaniel ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Differentially Expressed ◽  
Never Smokers

Altered expression of a limited number of genes contributes to cardiac decompensation during chronic ventricular tachypacing in dogs

2007 ◽  
Vol 29 (1) ◽  
pp. 76-83 ◽  
Author(s):  
Caroline Ojaimi ◽  
Khaled Qanud ◽  
Thomas H. Hintze ◽  
Fabio A. Recchia
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Decompensated Heart Failure ◽  
Left Ventricular ◽  
Fold Change ◽  
Differentially Expressed ◽  
Altered Expression ◽  
Cardiac Decompensation ◽  
Number Of Genes ◽  
End Stage

Our aim was to determine the changes in the gene expression profile occurring during the transition from compensated dysfunction (CD) to decompensated heart failure (HF) in pacing-induced dilated cardiomyopathy. Twelve chronically instrumented dogs underwent left ventricular pacing at 210 beats/min for 3 wk and at 240 beats thereafter, and four normal dogs were used as control. The transition from CD to HF occurred between the 3rd and 4th wk of pacing, with end-stage HF at 28 ± 1 days. RNA was extracted from left ventricular tissue at control and 3 and 4 wk of pacing ( n = 4) and tested with the Affymetrix Canine Array. We found 509 genes differentially expressed in CD vs. control ( P ≤ 0.05, fold change ≥±2), with 362 increasing and 147 decreasing; 526 genes were differentially expressed in HF vs. control ( P ≤ 0.05; fold change ≥±2), with 439 increasing and 87 decreasing. To better understand the transition, we compared gene alterations at 3 vs. 4 wk pacing and found that only 30 genes differed ( P ≤ 0.05; fold change of ±2). We conclude that a number of processes including normalization of gene regulation during decompensation, appearance of new upregulated genes and maintenance of gene expression all contribute to the transition to overt heart failure with an unexpectedly small number of genes differentially regulated.

scholarly journals Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

2021 ◽  
Author(s):  
Timo Benedikt Trefzer ◽  
Marc A. Schneider ◽  
Katharina Jechow ◽  
Lorenz Robert Chua ◽  
Thomas Muley ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Lung Tissue ◽  
Significant Proportion ◽  
Cellular Heterogeneity ◽  
Tobacco Smoke Exposure ◽  
Smoking History ◽  
Normal Lung Tissue ◽  
Normal Lung ◽  
Never Smokers

Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

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