LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

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Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis

BioMed Research International ◽

10.1155/2018/2381680 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 12

Author(s):

Wei Gu ◽

Ying Sun ◽

Xiong Zheng ◽

Jin Ma ◽

Xiao-Ying Hu ◽

...

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Microarray Analysis ◽

Cancer Progression ◽

Pathway Analysis ◽

Bioinformatics Analysis ◽

Malignant Tumors ◽

Expression Profiles ◽

Circular Rnas ◽

Target Mrnas

Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar’s home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network.

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Identification of Potential Biomarkers in Synovial Tissue of Rheumatoid Arthritis via Integrated Microarray Analysis. Identification of Biomarkers of Rheumatoid Arthritis

10.21203/rs.3.rs-700226/v1 ◽

2021 ◽

Author(s):

Li Tao ◽

ChaoLiang Xiong ◽

Li Xue

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Pathway Analysis ◽

Expression Profiles ◽

Diagnostic Value ◽

Functional Enrichment ◽

Venn Diagram ◽

Ppi Network ◽

Hub Genes ◽

Gene Markers

Abstract Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovitis and subsequent destruction of cartilage and bone. This study aimed to explore RA-related gene markers and the underlying molecular mechanism.Material and Methods: The expression profiles of GSE77298, GSE55235 and GSE12021 were obtained from the Gene Expression Omnibus database. Then, the differential gene expression analysis was conducted between GSE77298 and GSE55235 datasets. Limma package and a Venn diagram were utilized to screen the overlapping differentially expressed genes (DEGs), and Functional enrichment and pathway analysis were performed by using DAVID database. Subsequently, a protein-protein interaction (PPI) network was established, and candidate hub genes were recognized by using STRING and Cytoscape software. Finally, another dataset (GSE12021) was used for the validation of diagnostic value of the candidate hub genes and to identify real hub genes by using receiver operating characteristic (ROC) curves.Results: A total of 385 DEGs were detected, which include 19 downregulated genes and 366 upregulated genes. GO and KEGG pathway analysis showed that DEGs was mainly enriched in various immune and inflammatory response-related functions and pathways. The PPI network was composed of 374 nodes and 767 edges. A total of 8 real hub genes (HLA-DRA, HLA-DRB1, LCK, VAV1, HLA-DPA1, HLA-DPB1, C3AR1 and CD3D) which displayed an excellent diagnostic value for RA were identified.Conclusion: these findings may provide novel and reliable biomarkers for RA, which have some interesting implications for early diagnosis, prognosis and targeted therapy.

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NCAPG is a Potential Biomarker for Prognosis of Treatment in Children with High-risk Neuroblastoma

10.21203/rs.3.rs-572272/v1 ◽

2021 ◽

Author(s):

Meng Fu ◽

Wei Wu ◽

Yunxia Sun ◽

Rui Zhao ◽

Hao Li ◽

...

Keyword(s):

Gene Expression ◽

High Risk ◽

Prognostic Model ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Luciferase Reporter ◽

Migration And Invasion ◽

Lasso Regression ◽

Pediatric Tumor ◽

Potential Biomarker

Abstract Background High-risk neuroblastoma, as a lethal pediatric tumor, has unfavorable clinical outcomes, and accounts for ~15% of childhood cancer‐related mortality. However, the biomarkers for treatment prognosis have remained largely elusive. The present study sought to identify potential genes associated with the progression and prognosis of high-risk neuroblastoma. Methods The gene expression profiles of neuroblastoma were downloaded from the Gene Expression omnibus (GEO) database, and samples from GSE62564 and GSE16476 were applied as the training set and validation set, respectively. Bioinformatic analysis were performed by R. Subsequently, the biological functions of key gene were investigated by transwell, western blot, and flow cytometry analysis. miRNA that regulated the expression of key gene were predicted and the bind site were validated by luciferase reporter analysis and Q-PCR in children with high-risk neuroblastoma. Results Analysis shown that 120 differentially expressed genes (DEGs) in the blue module were identified to be significantly related to high-risk neuroblastoma by weighted correlation network analysis (WGCNA). After MCODE and Cytohubba algorithm analyses, 26 genes were recognized as hub genes. Subsequently, univariate COX and LASSO regression analyses identified a six-gene signature (NCAPG, UBE2C, MELK, CCNA2, KIF15, and BIRC5) and constructed a prognostic model. The expression of these six genes in high-risk neuroblastoma children was significantly higher than that in non-high-risk neuroblastoma children. These signature genes and the prognostic model demonstrated strong prognostic capability using Kaplan-Meier (KM) curves. Subsequently, NCAPG was selected as key gene and the results indicated that knockdown NCAPG suppressed the migration and invasion, increased the apoptosis rate and decreased the Bcl-2 level in neuroblastoma cells. In addition, the luciferase reporter analysis method showed that miR-495-3p can negatively regulate the expression of NCAPG. Q-PCR indicated that miR-495-3p highly expressed in children with high-risk neuroblastoma. Conclusion Our findings identified that miR-495-3p/ NCAPG could serve as prognostic biomarkers of high-risk neuroblastoma and may advance the understanding of the molecular pathogenesis.

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Systematic Analysis of Long Noncoding RNA and mRNA in Granulosa Cells during the Hen Ovulatory Cycle

Animals ◽

10.3390/ani11061533 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1533

Author(s):

Liang Li ◽

Xun Deng ◽

Silu Hu ◽

Zhifu Cui ◽

Zifan Ning ◽

...

Keyword(s):

Gene Expression ◽

Noncoding Rna ◽

Expression Profiles ◽

Functional Enrichment ◽

Differentially Expressed ◽

Follicle Development ◽

Ovulatory Cycle ◽

Lh Surge ◽

Study Gene Expression ◽

Three Stages

Long non-coding RNAs (lncRNAs) and mRNAs are temporally expressed during chicken follicle development. However, follicle transcriptome studies in chickens with timepoints relating to changes in luteinizing hormone (LH) levels are rare. In this study, gene expression in Rohman layers was investigated at three distinct stages of the ovulatory cycle: zeitgeber time 0 (ZT0, 9:00 a.m.), zeitgeber time 12 (ZT12, 9:00 p.m.), and zeitgeber time 20 (ZT20, 5:00 a.m.) representing the early, middle, and LH surge stages, respectively, of the ovulatory cycle. Gene expression profiles were explored during follicle development at ZT0, ZT12, and ZT20 using Ribo-Zero RNA sequencing. The three stages were separated into two major stages, including the pre-LH surge and the LH surge stages. A total of 12,479 mRNAs and 7528 lncRNAs were identified among the three stages, and 4531, 523 differentially expressed genes (DEGs) and 2367, 211 differentially expressed lncRNAs (DELs) were identified in the ZT20 vs. ZT12, and ZT12 vs. ZT0, comparisons. Functional enrichment analysis revealed that genes involved in cell proliferation and metabolism processes (lipid-related) were mainly enriched in the ZT0 and ZT12 stages, respectively, and genes related to oxidative stress, steroids regulation, and inflammatory process were enriched in the ZT20 stage. These findings provide the basis for further investigation of the specific genetic and molecular functions of follicle development in chickens.

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Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis

PeerJ ◽

10.7717/peerj.7619 ◽

2019 ◽

Vol 7 ◽

pp. e7619 ◽

Cited By ~ 2

Author(s):

Chuanfei Li ◽

Feng Qin ◽

Hao Hong ◽

Hui Tang ◽

Xiaoling Jiang ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Liver Cancer ◽

Expression Profiles ◽

Core Gene ◽

Functional Enrichment ◽

Potential Core ◽

Potential Biomarker ◽

Cancer Tissues ◽

Core Genes

Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment.

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Integrated analysis of DNA methylation and gene expression profiles identified S100A9 as a potential biomarker in ulcerative colitis

Bioscience Reports ◽

10.1042/bsr20202384 ◽

2020 ◽

Vol 40 (12) ◽

Author(s):

Shasha Su ◽

Wenjie Kong ◽

Jing Zhang ◽

Xinguo Wang ◽

Hongmei Guo

Keyword(s):

Gene Expression ◽

Ulcerative Colitis ◽

Dna Methylation ◽

Expression Profiles ◽

Osteoclast Differentiation ◽

Functional Enrichment ◽

Functional Network ◽

Integrated Analysis ◽

Genome Wide ◽

Potential Biomarker

Abstract Ulcerative colitis (UC) is a prevalent relapsing-remitting inflammatory bowel disease whose pathogenetic mechanisms remain elusive. In the present study, colonic biopsies samples from three UC patients treated in the Traditional Chinese Medicine Hospital and three healthy controls were obtained. The genome-wide mRNA and lncRNA expression of the samples were profiled through Agilent gene expression microarray. Moreover, the genome-wide DNA methylation dataset of normal and UC colon tissues was also downloaded from GEO for a collaborative analysis. Differential expression of lncRNA (DELs) and mRNAs (DEMs) in UC samples compared with healthy samples were identified by using limma Bioconductor package. Differentially methylated promoters (DMPs) in UC samples compared with controls were obtained through comparing the average methylation level of CpGs located at promoters by using t-test. Functional enrichment analysis was performed by the DAVID. STRING database was applied to the construction of gene functional interaction network. As a result, 2090 DEMs and 1242 DELs were screened out in UC samples that were closely associated with processes related to complement and coagulation cascades, osteoclast differentiation vaccinia, and hemorrhagic diseases. A total of 90 DEMs and 72 DELs were retained for the construction of functional network for the promoters of their corresponding genes were identified as DMPs. S100A9, HECW2, SOD3 and HIX0114733 showed high interaction degrees in the functional network, and expression of S100A9 was confirmed to be significantly elevated in colon tissues of UC patients compared with that of controls by qRT-PCR that was consistent with gene microarray analysis. These indicate that S100A9 could potentially be used as predictive biomarkers in UC.

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Identification of unique gene expression signatures in colon cancer stroma using microarray technology.

Journal of Clinical Oncology ◽

10.1200/jco.2011.29.4_suppl.447 ◽

2011 ◽

Vol 29 (4_suppl) ◽

pp. 447-447

Author(s):

S. X. Wang ◽

J. Wang ◽

E. Ozhegov ◽

R. Srinivasan ◽

O. O. Olowokure ◽

...

Keyword(s):

Gene Expression ◽

Colon Cancer ◽

Pathway Analysis ◽

Tumor Invasion ◽

Expression Profiles ◽

Expression Patterns ◽

Tumor Stroma ◽

Gene Signature ◽

Specific Gene ◽

Study Gene Expression

447 Background: Microarrays are widely used to study gene expression patterns in cancer. In colorectal cancer, it has proven useful to predict recurrence. The majority of expression profiles are generated from the cancer itself. Given the increasing evidence of importance of the microenvironment for tumor invasion, progression and metastasis, we explored tumor stroma gene signature using microarrays. Methods: Four formalin-fixed paraffin embedded (FFPE) colon cancer specimen carrying a pathological stage of T3-4/N0-2 were retrieved. Tumor stroma and normal stroma were separated using microdissection technology. Random sampling was used to minimize sampling bias. Total RNA was extracted, amplified, and labeled using Nugene FFPE kit, with array analysis using Affymetrix Human Gene 1.0. Eight samples, four normal stroma and four tumor stroma, were analyzed and compared. Array data were balanced and analyzed using standard software. To identify gene signature differences in tumor vs normal stroma, ComparativeMarker analysis and unsupervised cluster analysis were carried out. Results: We identified a 969 Affymetrix probe set as a signature that is highly expressed in tumor stroma. The top 117 genes were further analyzed to carry out a pathway analysis. We found a strong signature evident in tumor stroma, and much of this signature comprised the genes of the extracellular matrix. The pathway analysis revealed evidence of the generalized IGF1/TGFbeta/CTGF/activin mediated effect on the stroma, raising the possibility that some of this derives from, or is accompanied by, angiotensin receptor signaling. Through literature search, we found that several upregulated genes (e.g., FAP) were reported to be associated with stroma activation in vitro and in vivo. Conclusions: In this study, we successfully applied microarrays to study reactive colon tumor stroma in FFPE samples. We identified a specific gene signature reflecting stromal reaction to tumor invasion. We further identified the potential pathway that was activated in the reactive tumor stroma. We provide evidence that microarrays are useful in stroma analysis and may help identify new stromal pathways with potential diagnostic and therapeutic value. No significant financial relationships to disclose.

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Dysregulations of MicroRNA and Gene Expression in Chronic Venous Disease

Journal of Clinical Medicine ◽

10.3390/jcm9051251 ◽

2020 ◽

Vol 9 (5) ◽

pp. 1251 ◽

Cited By ~ 2

Author(s):

Daniel P. Zalewski ◽

Karol P. Ruszel ◽

Andrzej Stępniewski ◽

Dariusz Gałkowski ◽

Jacek Bogucki ◽

...

Keyword(s):

Gene Expression ◽

Mononuclear Cells ◽

Varicose Veins ◽

Expression Profiles ◽

Lower Limbs ◽

Chronic Venous Disease ◽

Venous Disease ◽

Operating Characteristics ◽

Potential Biomarker ◽

Pathologic Features

Chronic venous disease (CVD) is a vascular disease of lower limbs with high prevalence worldwide. Pathologic features include varicose veins, venous valves dysfunction and skin ulceration resulting from dysfunction of cell proliferation, apoptosis and angiogenesis. These processes are partly regulated by microRNA (miRNA)-dependent modulation of gene expression, pointing to miRNA as a potentially important target in diagnosis and therapy of CVD progression. The aim of the study was to analyze alterations of miRNA and gene expression in CVD, as well as to identify miRNA-mediated changes in gene expression and their potential link to CVD development. Using next generation sequencing, miRNA and gene expression profiles in peripheral blood mononuclear cells of subjects with CVD in relation to healthy controls were studied. Thirty-one miRNAs and 62 genes were recognized as potential biomarkers of CVD using DESeq2, Uninformative Variable Elimination by Partial Least Squares (UVE-PLS) and ROC (Receiver Operating Characteristics) methods. Regulatory interactions between potential biomarker miRNAs and genes were projected. Functional analysis of microRNA-regulated genes revealed terms closely related to cardiovascular diseases and risk factors. The study shed new light on miRNA-dependent regulatory mechanisms involved in the pathology of CVD. MicroRNAs and genes proposed as CVD biomarkers may be used to develop new diagnostic and therapeutic methods.

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975. Why Sex Make a Difference in HIV Clinical Course? Bioinformatics Analysis of Differential Expressed Gene in Females and Males with HIV Disease

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1161 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S516-S517

Author(s):

Kulachanya Suwanwongse ◽

Nehad Shabarek

Keyword(s):

Gene Expression ◽

Bioinformatics Analysis ◽

Underlying Mechanism ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Gender Inequalities ◽

Hiv Disease ◽

Go Analysis ◽

Hiv Progression ◽

Pathway Analyses

Abstract Background Human immunodeficiency virus (HIV) disease progression are different among genders, in which women usually progress to acquired immunodeficiency syndrome (AIDS) faster than men. The mechanisms resulting in the gender biases of HIV progression are unclear. We conducted a bioinformatics analysis of differentially expressed genes (DEGs) in women and men with HIV disease to understand the sex-based differences in HIV pathogenesis. Methods We obtained microarray data from the Gene Expression Omnibus (GEO) database using our pre-defined search strategy and analyzed data using the GEO2R platform. The t-test was done to compare DEGs between females and males with HIV diseases. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was implemented to systematically extract biological features and processes of retrieving DEGs via gene ontology (GO) analysis. A Systemic search was performed to evaluate each DEG function and its possible association with HIV. Results One gene expression profiling data were retrieved: GSE 140713, composed of 40 males and 10 females with HIV1 infected samples. A GEO2R analysis yielded 19 DEGs (Table 1). The GO analysis result was demonstrated in Tables 2 and 3. Following a systemic search, we found two DEGs, which have previous studies reported an association with HIV: DDX3X (20 studies) and PDS5 (1 study). We proposed DDX3X (t 5.3, p 0.0037) is responsible for gender inequalities of HIV progression because of: 1. DDX3X is needed in the HIV1 life cycle. 2. Several studies confirmed a positive correlation between DDX3X expression and HIV1 replication. 3. Our study found an up-regulated DDX3X expression in women corresponded to the fact that women progress to AIDS faster than men. 4. Our GO analysis showed female up-regulated genes were enriched in positive regulation of the gene expression pathway, which can be explained by DDX3X and its underlying mechanism. Table 1: DEGs in women and men with HIV1 disease Table 2: GO functional enrichment pathway analyses of overall retrieving DEGs Table 3: GO functional enrichment pathway analyses of down- and up-regulated clusters of DEGs Conclusion Aberrant DDX3X expression may contribute to sex-based differences in HIV disease. Drugs modifying DDX3X gene expression will be beneficial in the treatment of HIV especially resolving the HIV drug resistance problem because current anti-HIV drugs target viral components posed the risk of viral mutation. Disclosures All Authors: No reported disclosures

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The role of salivary vesicles as a potential inflammatory biomarker to detect traumatic brain injury in mixed martial artists

Scientific Reports ◽

10.1038/s41598-021-87180-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Rani Matuk ◽

Mandy Pereira ◽

Janette Baird ◽

Mark Dooner ◽

Yan Cheng ◽

...

Keyword(s):

Gene Expression ◽

Traumatic Brain Injury ◽

Brain Injury ◽

Head Injury ◽

Injury Severity ◽

Expression Profiles ◽

High Impact ◽

Impact Mechanism ◽

Inflammatory Biomarker ◽

Potential Biomarker

AbstractTraumatic brain injury (TBI) is of significant concern in the realm of high impact contact sports, including mixed martial arts (MMA). Extracellular vesicles (EVs) travel between the brain and oral cavity and may be isolated from salivary samples as a noninvasive biomarker of TBI. Salivary EVs may highlight acute neurocognitive or neuropathological changes, which may be particularly useful as a biomarker in high impact sports. Pre and post-fight samples of saliva were isolated from 8 MMA fighters and 7 from controls. Real-time PCR of salivary EVs was done using the TaqMan Human Inflammatory array. Gene expression profiles were compared pre-fight to post-fight as well as pre-fight to controls. Largest signals were noted for fighters sustaining a loss by technical knockout (higher impact mechanism of injury) or a full match culminating in referee decision (longer length of fight), while smaller signals were noted for fighters winning by joint or choke submission (lower impact mechanism as well as less time). A correlation was observed between absolute gene information signals and fight related markers of head injury severity. Gene expression was also significantly different in MMA fighters pre-fight compared to controls. Our findings suggest that salivary EVs as a potential biomarker in the acute period following head injury to identify injury severity and can help elucidate pathophysiological processes involved in TBI.

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