scholarly journals Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3484
Author(s):  
Jisun Lim ◽  
Yeon Bi Han ◽  
Soo Young Park ◽  
Soyeon Ahn ◽  
Hyojin Kim ◽  
...  

Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.

Nano LIFE ◽  
2019 ◽  
Vol 09 (01n02) ◽  
pp. 1940002
Author(s):  
Jichen Xu ◽  
Xianchun Zong ◽  
Qianshu Ren ◽  
Hongyu Wang ◽  
Lijuan Zhao ◽  
...  

The aim of this paper is to identify key genes in lung adenocarcinoma (LUAD) through weighted gene co-expression network analysis (WGCNA), and to further understand the molecular mechanism of LUAD. 107 gene expression profiles were downloaded from GSE10072 in the GEO database. We performed rigorous processing of the initial gene expression profile data. Subsequently, we used WGCNA to identify disease-driven modules and enforced functional enrichment analysis. The key genes were defined as the most connected genes in the driver module and were validated using the GSE75037 and TCGA database. GSE10072 removed 41 unpaired lung samples and 4 outliers. By analyzing the 62 samples using WGCNA, we obtained 26 modules and identified the brown and magenta modules as the driving modules for the LUAD. We found that the “Cell cycle”, “Oocyte meiosis” and “Progesterone-mediated oocyte maturation” pathways may be related to the occurrence of LUAD. GSE75037 removed 8 outlier and obtained 2909 differentially expressed genes (DEGs), 26 genes (9 genes in the brown module, 17 genes in the magenta module) overlap with key genes in the driver module. The results of the survival analysis suggest that 19 genes were significantly correlated with the patient’s survival time, including KPNA2, FEN1, RRM2, TOP2A, CENPF, MCM4, BIRC5, MELK, MAD2L1, CCNB1, CCNA2, KIF11, CDKN3, NUSAP1, CEP55, AURKA, NEK2, KIF14 and CDCA8, which may be potential biomarkers or therapeutic targets for LUAD. In this study, we provide a theoretical basis for further understanding the biological mechanism of LUAD through bioinformatics analysis of LUAD.


2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A954-A955
Author(s):  
Jacob Kaufman ◽  
Doug Cress ◽  
Theresa Boyle ◽  
David Carbone ◽  
Neal Ready ◽  
...  

BackgroundLKB1 (STK11) is a commonly disrupted tumor suppressor in NSCLC. Its loss promotes an immune exclusion phenotype with evidence of low expression of interferon stimulated genes (ISG) and decreased microenvironment immune infiltration.1 2 Clinically, LKB1 loss induces primary immunotherapy resistance.3 LKB1 is a master regulator of a complex downstream kinase network and has pleiotropic effects on cell biology. Understanding the heterogeneous phenotypes associated with LKB1 loss and their influence on tumor-immune biology will help define and overcome mechanisms of immunotherapy resistance within this subset of lung cancer.MethodsWe applied multi-omic analyses across multiple lung adenocarcinoma datasets2 4–6 (>1000 tumors) to define transcriptional and genetic features enriched in LKB1-deficient lung cancer. Top scoring phenotypes exhibited heterogeneity across LKB1-loss tumors, and were further interrogated to determine association with increased or decreased markers of immune activity. Further, immune cell-types were estimated by Cibersort to identify effects of LKB1 loss on the immune microenvironment. Key conclusions were confirmed by blinded pathology review.ResultsWe show that LKB1 loss significantly affects differentiation patterns, with enrichment of ASCL1-expressing tumors with putative neuroendocrine differentiation. LKB1-deficient neuroendocrine tumors had lower expression of Interferon Stimulated Genes (ISG), MHC1 and MHC2 components, and immune infiltration compared to LKB1-WT and non-neuroendocrine LKB1-deficient tumors (figure 1).The abundances of 22 immune cell types assessed by Cibersort were compared between LKB1-deficient and LKB1-WT tumors. We observe skewing of immune microenvironmental composition by LKB1 loss, with lower abundance of dendritic cells, monocytes, and macrophages, and increased levels of neutrophils and plasma cells (table 1). These trends were most pronounced among tumors with neuroendocrine differentiation, and were concordant across three independent datasets. In a confirmatory subset of 20 tumors, plasma cell abundance was assessed by a blinded pathologist. Pathologist assessment was 100% concordant with Cibersort prediction, and association with LKB1 loss was confirmed (P=0.001).Abstract 909 Figure 1Immune-associated Gene Expression Profiles Affected by Neuroendocrine Differentiation within LKB1-Deficient Lung Adenocarcinomas. Gene expression profiles corresponding to five immune-associated phenotypes are shown with bars indicating average GEP scores for tumors grouped according to LKB1 and neuroendocrine status as indicated. P-values represent results from Student’s T-test between groups as indicated.Abstract 909 Table 1LKB1 Loss Affects Composition of Immune Microenvironment. Values indicate log10 P-values comparing LKB1-loss to LKB1-WT tumors. Positive (red) indicates increased abundance in LKB1 loss. Negative (blue) indicates decreased abundance.ConclusionsWe conclude that tumor differentiation patterns strongly influence the immune microenvironment and immune exclusion characteristics of LKB1-deficient tumors. Neuroendocrine differentiation is associated with the strongest immune exclusion characteristics and should be evaluated clinically for evidence of immunotherapy resistance. A novel observation of increased plasma cell abundance is observed across multiple datasets and confirmed by pathology. Causal mechanisms linking differentiation status to immune activity is not well understood, and the functional role of plasma cells in the immune biology of LKB1-deficient tumors is undefined. These questions warrant further study to inform precision immuno-oncology treatments for these patients.AcknowledgementsThis work was funded by SITC AZ Immunotherapy in Lung Cancer grant (SPS256666) and DOD Lung Cancer Research Program Concept Award (LC180633).ReferencesSkoulidis F, Byers LA, Diao L, et al. Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discov 2015;5:860–77.Schabath MB, Welsh EA, Fulp WJ, et al. Differential association of STK11 and TP53 with KRAS mutation-associated gene expression, proliferation and immune surveillance in lung adenocarcinoma. Oncogene 2016;35:3209–16.Skoulidis F, Goldberg ME, Greenawalt DM, et al. STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discovery 2018;8:822-835.Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 2014;511:543–50.Chitale D, Gong Y, Taylor BS, et al. An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR-mutant tumors. Oncogene 2009;28:2773–83.Shedden K, Taylor JM, Enkemann SA, et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med 2008;14:822–7.


2021 ◽  
Author(s):  
Zimeng Wei ◽  
Min Zhao ◽  
Linnan Zang

Abstract Background Lung adenocarcinoma (LUAD) is the main histological subtype of lung cancer. However, the molecular mechanism underlying LUAD is not yet clearly defined, but elucidating this process in detail would be of great significance for clinical diagnosis and treatment. Methods Gene expression profiles were retrieved from Gene Expression Omnibus database (GEO), and the common differentially expressed genes (DEGs) were identified by online GEO2R analysis tool. Subsequently, the enrichment analysis of function and signaling pathways of DEGs in LUAD were performed by gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomics (KEGG) analysis. The protein-protein interaction (PPI) networks of the DEGs were established through the Search Tool for the Retrieval of Interacting Genes (STRING) database and hub genes were screened by plug-in CytoHubba in Cytoscape. Afterwards, we detected the expression of hub genes in LUAD and other cancers via GEPIA, Oncomine and HPA databases. Finally, Kaplan-Meier plotter were performed to analyze the prognosis efficacy of hub genes. Results 74 up-regulated and 238 down-regulated DEGs were identified. As for the up-regulated DEGs, KEGG analysis results revealed they were mainly enrolled in protein digestion and absorption. However, the down-regulated DEGs were primarily enriched in cell adhesion molecules. Subsequently, 9 hub genes: KIAA0101, CDCA7, TOP2A, CDC20, ASPM, TPX2, CENPF, UBE2T and ECT2, were identified and showed higher expression in both LUAD and other cancers. Finally, all these hub genes were found significantly related to the prognosis of LUAD (p < 0.05). Conclusions Our results screened out the hub genes and pathways that were related to the development and prognosis of LUAD, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of LUAD.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xiao-Yang Liao ◽  
Wei-Wen Wang ◽  
Zheng-Hui Yang ◽  
Jun Wang ◽  
Hang Lin ◽  
...  

To complement the molecular pathways contributing to Parkinson’s disease (PD) and identify potential biomarkers, gene expression profiles of two regions of the medulla were compared between PD patients and control. GSE19587 containing two groups of gene expression profiles [6 dorsal motor nucleus of the vagus (DMNV) samples from PD patients and 5 from controls, 6 inferior olivary nucleus (ION) samples from PD patients and 5 from controls] was downloaded from Gene Expression Omnibus. As a result, a total of 1569 and 1647 differentially expressed genes (DEGs) were, respectively, screened in DMNV and ION with limma package ofR. The functional enrichment analysis by DAVID server (the Database for Annotation, Visualization and Integrated Discovery) indicated that the above DEGs may be involved in the following processes, such as regulation of cell proliferation, positive regulation of macromolecule metabolic process, and regulation of apoptosis. Further analysis showed that there were 365 common DEGs presented in both regions (DMNV and ION), which may be further regulated by eight clusters of microRNAs retrieved with WebGestalt. The genes in the common DEGs-miRNAs regulatory network were enriched in regulation of apoptosis process via DAVID analysis. These findings could not only advance the understandings about the pathogenesis of PD, but also suggest potential biomarkers for this disease.


2021 ◽  
Author(s):  
Supantha Dey ◽  
Harpreet Kaur ◽  
Elia Brodsky ◽  
Mohit Mazumder

Malaria is a life-threatening disease, and Africa is still one of the most affected endemic regions despite years of policy to limit infection and transmission rates. Further, studies into the variable efficacy of the vaccine are needed to provide a better understanding of protective immunity. Thus, the current study is designed to delineate the effect of the different vaccination doses on the transcriptional profiles of subjects to determine its efficacy and understand the molecular mechanisms underlying the protection this vaccine provides. Here, we used gene expression profiles of pre and post-vaccination patients after various doses of RTS,S based on 275 and 583 samples collected from the GEO datasets. At first, exploratory data analysis based Principal component analysis (PCA) shown the distinct pattern of different doses. Subsequently, differential gene expression analysis using edgeR revealed the significantly (FDR <0.005) 158 down-regulated and 61 upregulated genes between control vs. Controlled Human Malaria Infection (CHMI) samples. Further, enrichment analysis of significant genes using Annotation and GAGE tools delineate the involvement of CCL8, CXCL10, CXCL11, XCR1, CSF3, IFNB1, IFNE, IL12B, IL22, IL6, IL27, etc., genes which found to be upregulated after earlier doses but downregulated after the 3rd dose in cytokine-chemokine pathways. Notably, we identified 13 cytokine genes whose expression significantly varied during three doses. Eventually, these findings give insight into the dual role of cytokine responses in malaria pathogenesis and variations in their expression patterns after various doses of vaccination involved in protection.


Cells ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1103 ◽  
Author(s):  
Arthur C. Oliveira ◽  
Luiz A. Bovolenta ◽  
Lucas Alves ◽  
Lucas Figueiredo ◽  
Amanda O. Ribeiro ◽  
...  

MicroRNAs (miRNAs) are non-coding RNAs that regulate a wide range of biological pathways by post-transcriptionally modulating gene expression levels. Given that even a single miRNA may simultaneously control several genes enrolled in multiple biological functions, one would expect that these tiny RNAs have the ability to properly sort among distinctive cellular processes to drive protein production. To test this hypothesis, we scrutinized previously published microarray datasets and clustered protein-coding gene expression profiles according to the intensity of fold-change levels caused by the exogenous transfection of 10 miRNAs (miR-1, miR-7, miR-9, miR-124, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a) in a human cell line. Through an in silico functional enrichment analysis, we discovered non-randomic regulatory patterns, proper of each cluster identified. We demonstrated that miRNAs are capable of equivalently modulate the expression signatures of target genes in regulatory clusters according to the biological function they are assigned to. Moreover, target prediction analysis applied to ten vertebrate species, suggest that such miRNA regulatory modus operandi is evolutionarily conserved within vertebrates. Overall, we discovered a complex regulatory cluster-module strategy driven by miRNAs, which relies on the controlled intensity of the repression over distinct targets under specific biological contexts. Our discovery helps to clarify the mechanisms underlying the functional activity of miRNAs and makes it easier to take the fastest and most accurate path in the search for the functions of miRNAs in any distinct biological process of interest.


2020 ◽  
Author(s):  
Zhijun Meng ◽  
Jia Gao ◽  
Hongping Liang ◽  
Caihong Liu ◽  
Jianli Zhao ◽  
...  

Abstract Background Atherosclerosis is the leading cause of cardiovascular disease worldwide for which lacks effective prevention and therapeutic strategy. Therefore, clinical indicators for early diagnosis and screening are in great need. The present study aimed to elucidate the key genetic signatures and pathways identifying the key candidate biomarker in atherosclerosis by integrative bioinformatics analysis combining with experimental assay. Methods The gene expression profiles (GSE30169, GSE6584) were achieved from the Gene Expression Omnibus database. Functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to examine the biological functions of identified differentially expressed genes (DEGs). A protein-protein interaction (PPI) network was mapped using Cytoscape software. Results 91 DEGs were identified, including 68 up-regulated genes and 23 down-regulated genes. Functional enrichment analysis indicated that DEGs genes were significantly enriched in ferroptosis, TNF signaling pathway, IL-17 signaling pathway. 12 nodes with the highest degrees were selected as hub genes. CCL2, CXCL1, IL6, and DUSP1 can serve as a sensitive diagnostic indicator for the early stage of atherosclerosis; CEBPB and HMOX1 can serve as a diagnostic indicator for diabetic atherosclerosis; TRIB3 is a sensitive marker indicating atherosclerosis risks in diabetic women group.Conclusions In conclusion, we have identified key candidate genes that indicate the diagnosis of patients with atherosclerosis, and these genes may serve as potential therapeutic or drug development targets for atherosclerosis.


2020 ◽  
pp. 1-10
Author(s):  
Min Wei ◽  
Sijun Meng ◽  
Sufang Shi ◽  
Lijun Liu ◽  
Xujie Zhou ◽  
...  

<b><i>Introduction:</i></b> Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis. It involves both genetic and environmental factors, among which DNA methylation, the most studied epigenetic modification, was shown to play a role. Here, we assessed genome-wide DNA methylation and gene expression profiles in 2 pairs of IgAN-discordant monozygotic (MZ) twins, in order to characterize methylation changes and their potential influences on gene expression in IgAN. <b><i>Methods:</i></b> Genome-wide DNA methylation and gene expression profiles were evaluated in peripheral blood mononuclear cells obtained from 2 IgAN-discordant MZ twins. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were detected, and an integrated analysis was performed. Finally, functional enrichment analysis was done for DMR-associated genes and DEGs. <b><i>Results:</i></b> Totally 521 DMRs were detected for 2 IgAN-discordant MZ twins. Among them, 9 DMRs were found to be mapped to genes that differentially expressed in 2 MZ twins, indicating the potential regulatory mechanisms of expression for these 9 genes (<i>MNDA</i>, <i>DYSF</i>, <i>IL1R2</i>, <i>TLR6</i>, <i>TREML2</i>, <i>TREM1</i>, <i>IL32</i>, <i>S1PR5</i>, and <i>ADGRE3</i>) in IgAN. Biological process analysis of them showed that they were mostly involved in the immune system process. Functional enrichment analysis of DEGs and DMR-associated genes both identified multiple pathways relevant to inflammatory and immune responses. And DMR-associated genes were significantly enriched in terms related to T-cell function. <b><i>Conclusions:</i></b> Our findings indicate that changes in DNA methylation patterns were involved in the pathogenesis of IgAN. Nine target genes detected in our study may provide new ideas for the exploration of molecular mechanisms of IgAN.


BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Baojie Wu ◽  
Shuyi Xi

Abstract Background This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis. Methods Three gene expression profiles (GSE63514, GSE64217 and GSE138080) were screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the GEO2R and Venn diagram tools. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Gene set enrichment analysis (GSEA) was performed to analyze the three gene expression profiles. Moreover, a protein–protein interaction (PPI) network of the DEGs was constructed, and functional enrichment analysis was performed. On this basis, hub genes from critical PPI subnetworks were explored with Cytoscape software. The expression of these genes in tumors was verified, and survival analysis of potential prognostic genes from critical subnetworks was conducted. Functional annotation, multiple gene comparison and dimensionality reduction in candidate genes indicated the clinical significance of potential targets. Results A total of 476 DEGs were screened: 253 upregulated genes and 223 downregulated genes. DEGs were enriched in 22 biological processes, 16 cellular components and 9 molecular functions in precancerous lesions and cervical cancer. DEGs were mainly enriched in 10 KEGG pathways. Through intersection analysis and data mining, 3 key KEGG pathways and related core genes were revealed by GSEA. Moreover, a PPI network of 476 DEGs was constructed, hub genes from 12 critical subnetworks were explored, and a total of 14 potential molecular targets were obtained. Conclusions These findings promote the understanding of the molecular mechanism of and clinically related molecular targets for cervical cancer.


2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Li Teng ◽  
Laiwan Chan

SummaryTraditional analysis of gene expression profiles use clustering to find groups of coexpressed genes which have similar expression patterns. However clustering is time consuming and could be diffcult for very large scale dataset. We proposed the idea of Discovering Distinct Patterns (DDP) in gene expression profiles. Since patterns showing by the gene expressions reveal their regulate mechanisms. It is significant to find all different patterns existing in the dataset when there is little prior knowledge. It is also a helpful start before taking on further analysis. We propose an algorithm for DDP by iteratively picking out pairs of gene expression patterns which have the largest dissimilarities. This method can also be used as preprocessing to initialize centers for clustering methods, like K-means. Experiments on both synthetic dataset and real gene expression datasets show our method is very effective in finding distinct patterns which have gene functional significance and is also effcient.


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