310 poster The differentially expressed genes by radiotherapy in the patients with uterine cervical cancer

2001 ◽  
Vol 58 ◽  
pp. S85
Keyword(s):  
Cervical Cancer ◽  
Differentially Expressed Genes ◽  
Uterine Cervical Cancer ◽  
Differentially Expressed

scholarly journals Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer

2021 ◽  
Vol 11 (5) ◽  
pp. 363
Author(s):  
Arafat Rahman Oany ◽  
Mamun Mia ◽  
Tahmina Pervin ◽  
Salem Ali Alyami ◽  
Mohammad Ali Moni
Keyword(s):  
Cervical Cancer ◽  
Systems Biology ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Profile Analysis ◽  
Target Identification ◽  
Regulatory Genes ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Potential Biomarkers

Nowadays, cervical cancer (CC) is treated as the leading cancer among women throughout the world. Despite effective vaccination and improved surgery and treatment, CC retains its fatality rate of about half of the infected population globally. The major screening biomarkers and therapeutic target identification have now become a global concern. In the present study, we have employed systems biology approaches to retrieve the potential biomarkers and pathways from transcriptomic profiling. Initially, we have identified 76 of each up-regulated and down-regulated gene from a total of 4643 differentially expressed genes. The up-regulatory genes mainly concentrate on immune-inflammatory responses, and the down-regulatory genes are on receptor binding and gamma-glutamyltransferase. The involved pathways associated with these genes were also assessed through pathway enrichment, and we mainly focused on different cancer pathways, immunoresponse, and cell cycle pathways. After the subsequent enrichment of these genes, we have identified 12 hub genes, which play a crucial role in CC and are verified by expression profile analysis. From our study, we have found that genes LILRB2 and CYBB play crucial roles in CC, as reported here for the first time. Furthermore, the survivability of the hub genes was also assessed, and among them, finally, CXCR4 has been identified as one of the most potential differentially expressed genes that might play a vital role in the survival of CC patients. Thus, CXCR4 could be used as a prognostic and/or diagnostic biomarker and a drug target for CC.

scholarly journals Identification of differentially-expressed genes by DNA methylation in cervical cancer

2015 ◽  
Vol 9 (4) ◽  
pp. 1691-1698 ◽  
Author(s):  
HEUN-SIK LEE ◽  
JUN HO YUN ◽  
JUNGHEE JUNG ◽  
YOUNG YANG ◽  
BONG-JO KIM ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Dna Methylation ◽  
Differentially Expressed Genes ◽  
Differentially Expressed

Weighted gene co-expression network analysis combined with machine learning to identify prognostic biomarkers for cervical squamous cell carcinoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e17000-e17000
Author(s):  
Yimin Li ◽  
Mei Lan ◽  
Xinhao Peng ◽  
Zijian Zhang ◽  
Jin Yi Lang
Keyword(s):  
Machine Learning ◽  
Cervical Cancer ◽  
High Risk ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Differentially Expressed ◽  
Prognostic Biomarkers ◽  
Cox Regression Analysis ◽  
Testing Set

e17000 Background: Cervical cancer represents the fourth most frequently diagnosed malignancy affecting women all over the world. However, effective prognostic biomarkers are still limited for accurate identifying high-risk patients. Here, we provide a co-expression network and machine learning-based signature to predict the survival of cervical cancer. Methods: Utilizing expression profiles of The Cancer Genome Atlas datasets, we identified differentially expressed genes (DEGs) and the most significantly module by differential expression analysis and Weighted Gene Co-expression Network Analysis, respectively. The candidate genes was obtained by combining the both results. Then the prognostic classifier was constructed by LASSO COX regression analysis and validated in testing set. Finally, survival receiver operating characteristic and Cox proportional hazards analysis was used to assess the performance of prognostic prediction. Results: We identified 190 differentially expressed genes (DEGs) between cervical squamous cell cancer(CSCC) and normal samples in purple module. Next we built a 8-mRNA-based signature, and determined a optimal cutoff value with sensitivity of 0.889 and specificity of 0.785. Patients were classified into high-risk and low-risk group with significantly different overall survival(training set: p < 0.0001; testing set: p = 0.039). Furthermore, the prognostic classifier was an independent and powerful prognostic biomarker for OS (HR = 7.05, 95% CI: 2.52-19.71, p < 0.001). Conclusions: The prognostic classifier is a promising predictor of CSCC patients, the novel co-expression network and machine learning-based strategy described in the study may have a broad application in precision medicine.

scholarly journals Effect of hyperoside on cervical cancer cells and transcriptome analysis of differentially expressed genes

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Weikang Guo ◽  
Hui Yu ◽  
Lu Zhang ◽  
Xiuwei Chen ◽  
Yunduo Liu ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cell Proliferation ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Control Group ◽  
Rna Seq ◽  
Network Construction ◽  
Target Network ◽  
Key Genes

Abstract Background Hyperoside (Hy) is a plant-derived quercetin 3-d-galactoside that exhibits inhibitory activities on various tumor types. The objective of the current study was to explore Hy effects on cervical cancer cell proliferation, and to perform a transcriptome analysis of differentially expressed genes. Methods Cervical cancer HeLa and C-33A cells were cultured and the effect of Hy treatment was determined using the Cell Counting Kit-8 (CCK-8) assay. After calculating the IC50 of Hy in HeLa and C-33A cells, the more sensitive to Hy treatment cell type was selected for RNA-Seq. Differentially expressed genes (DEGs) were identified by comparing gene expression between the Hy and control groups. Candidate genes were determined through DEG analysis, protein interaction network (PPI) construction, PPI module analysis, transcription factor (TF) prediction, TF-target network construction, and survival analysis. Finally, the key candidate genes were verified by RT-qPCR and western blot. Results Hy inhibited HeLa and C33A cell proliferation in a dose- and time-dependent manner, as determined by the CCK-8 assay. Treatment of C-33A cells with 2 mM Hy was selected for the subsequent experiments. Compared with the control group, 754 upregulated and 509 downregulated genes were identified after RNA-Seq. After functional enrichment, 74 gene ontology biological processes and 43 Kyoto Encyclopedia of Genes and Genomes pathways were obtained. According to the protein interaction network (PPI), PPI module analysis, TF-target network construction, and survival analysis, the key genes MYC, CNKN1A, PAX2, TFRC, ACOX2, UNC5B, APBA1, PRKACA, PEAR1, COL12A1, CACNA1G, PEAR1, and CCNA2 were detected. RT-qPCR was performed on the key genes, and Western blot was used to verify C-MYC and TFRC. C-MYC and TFRC expressions were lower and higher than the corresponding values in the control group, respectively, in accordance with the results from the RNA-Seq analysis. Conclusion Hy inhibited HeLa and C-33A cell proliferation through C-MYC gene expression reduction in C-33A cells and TFRC regulation. The results of the current study provide a theoretical basis for Hy treatment of cervical cancer.

Identifying a cervical cancer survival signature based on mRNA expression and genome-wide copy number variations

2021 ◽  
pp. 153537022110535
Author(s):  
Nan Li ◽  
Kai Yu ◽  
Zhong Lin ◽  
Dingyuan Zeng
Keyword(s):  
Cervical Cancer ◽  
Overall Survival ◽  
Differentially Expressed Genes ◽  
Risk Score ◽  
Copy Number ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Prognostic Signature ◽  
Immune Score

Cervical cancer mortality is the second highest in gynecological cancers. This study developed a new model based on copy number variation data and mRNA data for overall survival prediction of cervical cancer. Differentially expressed genes from The Cancer Genome Atlas dataset detected by univariate Cox regression analysis were further simplified to six by least absolute shrinkage and selection operator (Lasso) and stepwise Akaike information criterion (stepAIC). The study developed a six-gene signature, which was further verified in independent dataset. Association between immune infiltration and risk score was investigated by immune score. The relation between the signature and functional pathways was examined by gene set enrichment analysis. Ninety-nine differentially expressed genes were detected, and C11orf80, FOXP3, GSN, HCCS, PGAM5, and RIBC2 were identified as key genes to construct a six-gene signature. The prognostic signature showed a significant correlation with overall survival (hazard ratio, HR = 3.45, 95% confidence interval (CI) = 2.08–5.72, p <  0.00001). Immune score showed a negative correlation with the risk score calculated by the signature ( p <  0.05). Four immune-related pathways were closely associated with risk score ( p <  0.0001). The six-gene prognostic signature was an effective tool to predict overall survival of cervical cancer. In conclusion, the newly identified six genes may be considered as new drug targets for cervical cancer treatment.

scholarly journals Microarray screening of differentially expressed genes after up-regulating miR-205 or down-regulating miR-141 in cervical cancer cells

2019 ◽  
Author(s):  
Xingyu Fang ◽  
Tingting Yao
Keyword(s):  
Cervical Cancer ◽  
Hela Cell ◽  
Cancer Cells ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Siha Cell ◽  
Differentially Expressed ◽  
Down Regulation ◽  
Siha Cells ◽  
Cervical Cancer Cells

AbstractCervical cancer is one of the most common gynecological malignancies. However,studies on the expression and molecular mechanism of miR-205 and miR-141 in CC are insufficient recently. Expression profile microarray with 21329 Oligo DNA were used to detect the expression of mRNAs in miR-205 up-regulated or miR-141 down-regulated HeLa and SiHa cells and mRNAs in normal HeLa and SiHa cells. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed to assess the potential pathways of miR-205 in SiHa cell.Compared with normal HeLa cell, there were 38 differentially expressed genes (DEGs) in miR-205 up-regulated HeLa cell. Nine were up-regulation genes and 29 were down-regulation genes. There were 23 DEGs in miR-141 down-regulated HeLa cell. One was up-regulated and 22 were down-regulated. Compared with normal SiHa cell, there were 128 DEGs in miR-205 up-regulated SiHa cell. One hundred and three were up-regulation genes and 25 were down-regulation genes. There were 80 DEGs in miR-141 down-regulated SiHa cell. Forty two were up-regulation genes and 28 were down-regulation genes. For miR-205 up-regulated SiHa cell, GO outcome showed that “ubiquitin-protein ligase activity”, “MAP kinase phosphatase activity”, were the most enriched terms (P < 0.05). And in KEGG analysis, “Cell cycle” was notably enriched, and Smad4 in this pathway was up-regulated (P < 0.05). Expression profile microarray technology can effectively screen out DEGs in cervical cancer cells after up-regulating miR-205 or down-regulating miR-141. Which may enable us to understand the pathogenesis and lay an important foundation for the prevention and treatment of cervical cancer.

scholarly journals Identification of crucial aberrantly methylated and differentially expressed genes related to cervical cancer using an integrated bioinformatics analysis

2020 ◽  
Vol 40 (5) ◽  
Author(s):  
Xiaoling Ma ◽  
Jinhui Liu ◽  
Hui Wang ◽  
Yi Jiang ◽  
Yicong Wan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Functional Analysis ◽  
Estrogen Receptor ◽  
Differentially Expressed Genes ◽  
Bioinformatics Analysis ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Venn Diagram ◽  
Hub Genes

Abstract Methylation functions in the pathogenesis of cervical cancer. In the present study, we applied an integrated bioinformatics analysis to identify the aberrantly methylated and differentially expressed genes (DEGS), and their related pathways in cervical cancer. Data of gene expression microarrays (GSE9750) and gene methylation microarrays (GSE46306) were gained from Gene Expression Omnibus (GEO) databases. Hub genes were identified by ‘limma’ packages and Venn diagram tool. Functional analysis was conducted by FunRich. Search Tool for the Retrieval of Interacting Genes Database (STRING) was used to analyze protein–protein interaction (PPI) information. Gene Expression Profiling Interactive Analysis (GEPIA), immunohistochemistry staining, and ROC curve analysis were conducted for validation. Gene Set Enrichment Analysis (GSEA) was also performed to identify potential functions.We retrieved two upregulated-hypomethylated oncogenes and eight downregulated-hypermethylated tumor suppressor genes (TSGs) for functional analysis. Hypomethylated and highly expressed genes (Hypo-HGs) were significantly enriched in cell cycle and autophagy, and hypermethylated and lowly expressed genes (Hyper-LGs) in estrogen receptor pathway and Wnt/β-catenin signaling pathway. Estrogen receptor 1 (ESR1), Erythrocyte membrane protein band 4.1 like 3 (EPB41L3), Endothelin receptor B (EDNRB), Inhibitor of DNA binding 4 (ID4) and placenta-specific 8 (PLAC8) were hub genes. Kaplan–Meier method was used to evaluate survival data of each identified gene. Lower expression levels of ESR1 and EPB41L3 were correlated with a shorter survival time. GSEA results showed that ‘cell adhesion molecules’ was the most enriched item. This research inferred the candidate genes and pathways that might be used in the diagnosis, treatment, and prognosis of cervical cancer.

scholarly journals Molecular Differences Between Squamous Cell Carcinoma and Adenocarcinoma Cervical Cancer Subtypes: Potential Prognostic Biomarkers

2021 ◽  
Author(s):  
Alma Campos-Parra ◽  
Milagros Perez-Quintanilla ◽  
Antonio Daniel Martínez-Gutierrez ◽  
Delia Pérez-Montiel ◽  
Oliver Millan-Catalan ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Ras Signaling ◽  
Mexican Mestizo

Abstract Purpose Cervical cancer (CC) remains a health problem. Persistent infection by high-risk papillomavirus (HR-HPV) is the main cause of this disease. The most frequently diagnosed histological types of CC are squamous cell carcinoma (SCC) and adenocarcinoma (ADC). Clinically, the prognosis of both types is controversial. Our aim was to search for a molecular profile that distinguishes each histological subtype and predicts the prognosis of one or both subtypes would be of great benefit to these patients. Methods The transcriptome of CC patients from The Cancer Genome Atlas (TCGA) was analyzed using the DESeq2 package to obtain the differentially expressed genes between ADC and SCC. The differentially expressed genes obtained from the TCGA database were validated with an online, publicly available transcriptome dataset (GSE56303) containing data for a Mexican-Mestizo independent cohort. The global biological pathways involving differentially expressed genes between SSC and ADC were obtained by performing an analysis using the Webgestalt platform. In addition, associations of the differentially expressed genes with Overall Survival (OS) were assessed. Results The molecular profile of 70 altered transcripts between ADC and SCC patients from the TCGA cohort was determined. These transcripts were also deregulated in the Mexico-Mestizo cohort with the same Log2FoldChange values. The molecular pathways involved were IL-17, JAK/STAT and Ras signaling. Higher GABRB2 and TSPAN8 expression and lower TMEM40 expression were associated with better OS in the Mexican-Mestizo cohort. Conclusion We were able to detect molecular differences between the ADC and SCC subtypes of CC; however, further studies are required to define the appropriate prognostic biomarker for each histological type.

Sign in / Sign up

Export Citation Format

Share Document