Identification of Hub Gene in Cervical Cancer by Weighted Gene Co-Expression Network Analysis

Abstract Background:Cervical cancer(CC) is one of the most common malignant tumors in gynecology. Both its incidence and mortality are high. Despite advances in screening, diagnosis, prevention, and treatment, CC is still one of the leading causes of cancer-related death in women. However, in the pathogenesis of CC, the exact molecular mechanism is still unclear. It may be a multi-gene, multi-factor, multi-step, and multi-stage complex process. Hence, the pathogenesis and molecular mechanism of CC are the keys to effective treatment of it. In this study, we tried to identify candidate biomarkers for cervical cancer through weighted gene co-expression network analysis (WGCNA). Methods: The gene expression profile of CESC was downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were analyzed by the Limma package, and the gene co-expression module was constructed by WGCNA. Use the online website STRING to construct the protein interaction network of genes in significant modules, and then use Cytoscape analysis to find the 10 most important node degree genes. Results: Among these 10 genes, SOX9 expression was associated with the prognosis of cervical cancer patients. Immunohistochemical results from the online website human protein atlas showed that SOX9 protein expression was significantly higher in cervical cancer tissues than in normal cervical tissues. After collecting cancerous and paracancerous tissue specimens from 16 patients with cervical cancer, Q-PCR showed that the mRNA expression levels of SOX9 in cervical cancer tissues were significantly greater than those in normal adjacent tissues. Conclusions: The elevated expression of SOX9 is significantly related to the disease-free survival and overall survival of cervical cancer. Therefore, the SOX9 gene could be used as an indicator of cervical cancer diagnosis and prognosis.

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Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis

Technology in Cancer Research & Treatment ◽

10.1177/1533033820963578 ◽

2020 ◽

Vol 19 ◽

pp. 153303382096357

Author(s):

Xiaoyong Gong ◽

Bobin Ning

Keyword(s):

Prostate Cancer ◽

Network Analysis ◽

Cox Regression ◽

Characteristic Curve ◽

Interaction Network ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Normal Prostate ◽

Cox Regression Analysis ◽

Incidence And Mortality

Prostate cancer (PCa) is a highly malignant tumor, with increasing incidence and mortality rates worldwide. The aim of this study was to identify the prognostic lncRNAs and construct an lncRNA signature for PCa diagnosis by the interaction network between lncRNAs and protein-coding genes (PCGs). The differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) between PCa and normal prostate tissues were screened from The Cancer Genome Atlas (TCGA) database. The DEPCGs were functionally annotated in terms of the enriched pathways. Weighted gene co-expression network analysis (WGCNA) of 104 PCa samples identified 15 co-expression modules, of which the Turquoise module was negatively correlated with cancer and included 5 key lncRNAs and 47 PCGs. KEGG pathway analyses of the core 47 PCGs showed significant enrichment in classic PCa-related pathways, and overlapped with the enriched pathways of the DEPCGs. LINC00857, LINC00900, LINC00908, LINC00900, SNHG3 and FENDRR were significantly associated with the survival of PCa and have not been reported previously. Finally, Multivariable Cox regression analysis was used to establish a prognostic risk formula, and the patients were accordingly stratified into the low- and high-risk groups. The latter had significantly worse OS compared to the low-risk group (P < 0.01), and the area under the receiver operating characteristic curve (ROC) of 14-year OS was 0.829. The accuracy of our prediction model was determined by calculating the corresponding concordance index (C-index) and risk curves. In conclusion, we established a 5-lncRNA prognostic signature that provides insights into the biological and clinical relevance of lncRNAs in PCa.

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Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network

Bioscience Reports ◽

10.1042/bsr20200295 ◽

2020 ◽

Vol 40 (4) ◽

Author(s):

Zihao Xu ◽

Zilong Wu ◽

Jiatang Xu ◽

Jingtao Zhang ◽

Bentong Yu

Keyword(s):

Lung Adenocarcinoma ◽

Target Genes ◽

Characteristic Curve ◽

Interaction Network ◽

Mapk Signaling ◽

The Cancer Genome Atlas ◽

Circular Rnas ◽

Node Degree ◽

Protein Protein Interaction ◽

Cancer Tissues

Abstract Lung adenocarcinoma (LUAD) remains the leading cause of cancer-related deaths worldwide. Increasing evidence suggests that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can regulate target gene expression and participate in tumor genesis and progression. However, hub driving genes and regulators playing a potential role in LUAD progression have not been fully elucidated yet. Based on data from The Cancer Genome Atlas database, 2837 differentially expressed genes, 741 DE-regulators were screened by comparing cancer tissues with paracancerous tissues. Then, 651 hub driving genes were selected by the topological relation of the protein–protein interaction network. Also, the target genes of DE-regulators were identified. Moreover, a key gene set containing 65 genes was obtained from the hub driving genes and target genes intersection. Subsequently, 183 hub regulators were selected based on the analysis of node degree in the ceRNA network. Next, a comprehensive analysis of the subgroups and Wnt, mTOR, and MAPK signaling pathways was conducted to understand enrichment of the subgroups. Survival analysis and a receiver operating characteristic curve analysis were further used to screen for the key genes and regulators. Furthermore, we verified key molecules based on external database, LRRK2, PECAM1, EPAS1, LDB2, and HOXA11-AS showed good results. LRRK2 was further identified as promising biomarker associated with CNV alteration and various immune cells’ infiltration levels in LUAD. Overall, the present study provided a novel perspective and insight into hub driving genes and regulators in LUAD, suggesting that the identified signature could serve as an independent prognostic biomarker.

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Screening of cervical cancer-related hub genes based on comprehensive bioinformatics analysis

Cancer Biomarkers ◽

10.3233/cbm-203262 ◽

2021 ◽

pp. 1-13

Author(s):

Simei Tu ◽

Hao Zhang ◽

Xiaocheng Yang ◽

Wen Wen ◽

Kangjing Song ◽

...

Keyword(s):

Gene Expression ◽

Cervical Cancer ◽

Molecular Mechanisms ◽

Disease Free Survival ◽

The Cancer Genome Atlas ◽

Mrna Levels ◽

Hub Genes ◽

Normal Tissues ◽

Significant Difference ◽

Core Genes

BACKGROUND: Since the molecular mechanisms of cervical cancer (CC) have not been completely discovered, it is of great significance to identify the hub genes and pathways of this disease to reveal the molecular mechanisms of cervical cancer. OBJECTIVE: The study aimed to identify the biological functions and prognostic value of hub genes in cervical cancer. METHODS: The gene expression data of CC patients were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The core genes were screened out by differential gene expression analysis and weighted gene co-expression network analysis (WGCNA). R software, the STRING online tool and Cytoscape software were used to screen out the hub genes. The GEPIA public database was used to further verify the expression levels of the hub genes in normal tissues and tumour tissues and determine the disease-free survival (DFS) rates of the hub genes. The protein expression of the survival-related hub genes was identified with the Human Protein Atlas (HPA) database. RESULTS: A total of 64 core genes were screened, and 10 genes, including RFC5, POLE3, RAD51, RMI1, PALB2, HDAC1, MCM4, ESR1, FOS and E2F1, were identified as hub genes. Compared with that in normal tissues, RFC5, POLE3, RAD51,RMI1, PALB2, MCM4 and E2F1 were all significantly upregulated in cervical cancer, ESR1 was significantly downregulated in cervical cancer, and high RFC5 expression in CC patients was significantly related to OS. In the DFS analysis, no significant difference was observed in the expression level of RFC5 in cervical cancer patients. Finally, RFC5 protein levels verified by the HPA database were consistently upregulated with mRNA levels in CC samples. CONCLUSIONS: RFC5 may play important roles in the occurrence and prognosis of CC. It could be further explored and validated as a potential predictor and therapeutic target for CC.

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The Prognostic Significance of MAFK and its Methylation in Cervical Cancer

10.21203/rs.3.rs-582069/v1 ◽

2021 ◽

Author(s):

Mengjun Zhang ◽

Hao Li ◽

Yuan Liu ◽

Siyu Hou ◽

Ping Cui ◽

...

Keyword(s):

Cervical Cancer ◽

Prognostic Significance ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Aberrant Methylation ◽

Cancer Data ◽

Drug Candidates ◽

Cancer Genome Atlas ◽

Cancer Tissues

Abstract Background: The purpose of this study was to determine the value of MAFK as a biomarker of cervical cancer prognosis and to explore its methylation and possible cellular signaling pathways. Methods: We analyzed the cervical cancer data of The Cancer Genome Atlas (TCGA) through bioinformatics, including MAFK expression, methylation, prognosis and genome enrichment analysis. Results: MAFK expression was higher in cervical cancer tissues and was negatively correlated with the methylation levels of five CpG sites. MAFK is an independent prognostic factor of cervical cancer and is involved in the Nod-like receptor signaling pathway. CMap analysis screened four drug candidates for cervical cancer treatment. Conclusions: We confirmed that MAFK is a novel prognostic biomarker for cervical cancer and aberrant methylation may also affect MAFK expression and carcinogenesis. This study provides a new molecular target for the prognostic evaluation and treatment of cervical cancer.

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Fractionation-Dependent Radiosensitization by Molecular Targeting of Nek1

Cells ◽

10.3390/cells9051235 ◽

2020 ◽

Vol 9 (5) ◽

pp. 1235

Author(s):

Isabel Freund ◽

Stephanie Hehlgans ◽

Daniel Martin ◽

Michael Ensminger ◽

Emmanouil Fokas ◽

...

Keyword(s):

Cervical Cancer ◽

Disease Free Survival ◽

The Cancer Genome Atlas ◽

Cell Cycle Distribution ◽

Checkpoint Activation ◽

Distant Failure ◽

Nsg Mice ◽

Cancer Genome Atlas ◽

Multivariable Analyses

NIMA (never-in-mitosis gene A)-related kinase 1 (Nek1) is shown to impact on different cellular pathways such as DNA repair, checkpoint activation, and apoptosis. Its role as a molecular target for radiation sensitization of malignant cells, however, remains elusive. Stably transduced doxycycline (Dox)-inducible Nek1 shRNA HeLa cervix and siRNA-transfected HCT-15 colorectal carcinoma cells were irradiated in vitro and 3D clonogenic radiation survival, residual DNA damage, cell cycle distribution, and apoptosis were analyzed. Nek1 knockdown (KD) sensitized both cell lines to ionizing radiation following a single dose irradiation and more pronounced in combination with a 6 h fractionation (3 × 2 Gy) regime. For preclinical analyses we focused on cervical cancer. Nek1 shRNA HeLa cells were grafted into NOD/SCID/IL-2Rγc−/− (NSG) mice and Nek1 KD was induced by Dox-infused drinking water resulting in a significant cytostatic effect if combined with a 6 h fractionation (3 × 2 Gy) regime. In addition, we correlated Nek1 expression in biopsies of patients with cervical cancer with histopathological parameters and clinical follow-up. Our results indicate that elevated levels of Nek1 were associated with an increased rate of local or distant failure, as well as with impaired cancer-specific and overall survival in univariate analyses and for most endpoints in multivariable analyses. Finally, findings from The Cancer Genome Atlas (TCGA) validation cohort confirmed a significant association of high Nek1 expression with a reduced disease-free survival. In conclusion, we consider Nek1 to represent a novel biomarker and potential therapeutic target for drug development in the context of optimized fractionation intervals.

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A 17-Gene Signature Predicted Prognosis in Renal Cell Carcinoma

Disease Markers ◽

10.1155/2020/8352809 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Fan Li ◽

Weifeng Hu ◽

Wei Zhang ◽

Guohao Li ◽

Yonglian Guo

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Malignant Tumors ◽

Prognostic Significance ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Prognostic Indicators ◽

Incidence And Mortality ◽

Tcga Dataset

Renal cell carcinoma (RCC), which was one of the most common malignant tumors in urinary system, had gradually increased incidence and mortality in recent years. Although significant advances had been made in molecular and biology research on the pathogenesis of RCC, effective treatments and prognostic indicators were still lacking. In order to predict the prognosis of RCC better, we identified 17 genes that were associated with the overall survival (OS) of RCC patients from The Cancer Genome Atlas (TCGA) dataset and a 17-gene signature was developed. Through SurvExpress, we analyzed the expression differences of the 17 genes and their correlation with the survival of RCC patients in five datasets (ZHAO, TCGA, KIPAN, KIRC, and KIRP), and then evaluated the survival prognostic significance of the 17-gene signature for RCC. Our results showed that the 17-gene signature had a predictive prognostic value not only in single pathologic RCC, but also in multiple pathologic types of RCC. In conclusion, the 17-gene signature model was related to the survival of RCC patients and could help predict the prognosis with significant clinical implications.

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Screening and Identifying m6A Regulators as an Independent Prognostic Biomarker in Pancreatic Cancer Based on The Cancer Genome Atlas Database

BioMed Research International ◽

10.1155/2021/5573628 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Bi Lin ◽

Yangyang Pan ◽

Dinglai Yu ◽

Shengjie Dai ◽

Hongwei Sun ◽

...

Keyword(s):

Pancreatic Cancer ◽

Cox Regression ◽

Malignant Tumors ◽

Expression Profiles ◽

Tumor Therapy ◽

Disease Free Survival ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas ◽

Genome Atlas

Background. Pancreatic cancer is one of the most malignant tumors of the digestive system, and its treatment has rarely progressed for the last two decades. Studies on m6A regulators for the past few years have seemingly provided a novel approach for malignant tumor therapy. m6A-related factors may be potential biomarkers and therapeutic targets. This research is focused on the gene characteristics and clinical values of m6A regulators in predicting prognosis in pancreatic cancer. Methods. In our study, we obtained gene expression profiles with copy number variation (CNV) data and clinical characteristic data of 186 patients with pancreatic cancer from The Cancer Genome Atlas (TCGA) portal. Then, we determined the alteration of m6a regulators and their correlation with clinicopathological features using the log-rank tests, Cox regression model, and chi-square test. Additionally, we validated the prognostic value of m6A regulators in the International Cancer Genome Consortium (ICGC). Results. The results suggested that pancreatic cancer patients with ALKBH5 CNV were associated with worse overall survival and disease-free survival than those with diploid genes. Additionally, upregulation of the writer gene ALKBH5 had a positive correlation with the activation of AKT pathways in the TCGA database. Conclusion. Our study not only demonstrated genetic characteristic changes of m6A-related genes in pancreatic cancer and found a strong relationship between the changes of ALKBH5 and poor prognosis but also provided a novel therapeutic target for pancreatic cancer therapy.

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Correlation between Breast Ultrasound Microcalcification and the Prognosis of Breast Cancer

Journal of Healthcare Engineering ◽

10.1155/2021/6835963 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Shanshan Xue ◽

Qiaoling Zhao ◽

Minghui Tai ◽

Ning Li ◽

Yun Liu

Keyword(s):

Breast Cancer ◽

Malignant Tumors ◽

Survey Methods ◽

Breast Ultrasound ◽

Inflammatory Factors ◽

Breast Cancer Patients ◽

Incidence And Mortality ◽

Ultrasound Technology ◽

Breast Microcalcification ◽

Cancer Tissues

Breast cancer is a common gynecological disease, and its incidence and mortality are higher than those of other common malignant tumors. Breast ultrasound technology is a new surgical method, which has the advantages of reducing postoperative complications, improving the quality of life of patients, and improving the prognosis of patients. Breast microcalcification is a new method for the treatment of tumors. Its mechanism is that the proliferation of breast cancer cell walls increases the inflammatory factors in the cancer tissues and enhances the formation of tumors and peripheral vascular thrombosis. Breast microcalcification in the treatment of breast cancer patients will have a more significant impact compared to ordinary antibiotics alone. For this reason, the microcalcification performance of breast ultrasound is worthy of study, and related research on prognosis is also indispensable. The purpose of this study is to improve the understanding of the ultrasound manifestations of breast cancer microcalcification and the prognosis of breast cancer. This article mainly applied statistical analysis as well as experimental and survey methods to conduct breast ultrasound examination on 100 patients and analyzed the ultrasound manifestations of breast cancer MCs from three aspects: location, shape, and distribution. The experimental results show that there is no correlation between the location and distribution of breast cancer MCs and the diameter of the cancer foci, but there is a certain correlation between the morphology (non-gravel-like calcification) and the diameter of the cancer foci (>5 cm). Among them, HER-2 overexpression accounted for 11.9% in the grit-like MCs group and 51% in the non-grit-like MCs group.

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Predictive Proteomic Signature for the Prognosis of Cervical Cancer

10.21203/rs.3.rs-327396/v1 ◽

2021 ◽

Author(s):

Xiaoyu Ji ◽

Guangdi Chu ◽

Jinwen Jiao ◽

Teng Lv ◽

Yulong Chen ◽

...

Keyword(s):

Cervical Cancer ◽

Regression Analysis ◽

Cox Regression ◽

Predictive Ability ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Cox Regression Analysis ◽

Incidence And Mortality

Abstract Objective: Cervical cancer (CC) is one of the most common types of malignant female cancer, and its incidence and mortality are not optimistic. Protein panels can be a powerful prognostic factor for many types of cancer. The purpose of our study was to investigate a proteomic panel to predict survival of patients with common CC. Methods and results: The protein expression and clinicopathological data of CC were downloaded from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA) database, respectively. We selected the prognosis-related proteins (PRPs) by univariate Cox regression analysis and found that the results of functional enrichment analysis were mainly related to apoptosis. We used Kaplan–Meier(K-M) analysis and multivariable Cox regression analysis further to screen PRPs to establish a prognostic model, including BCL2, SMAD3, and 4EBP1-pT70. The signature was verified to be independent predictors of OS by Cox regression analysis and the Area Under Curves. Nomogram and subgroup classification were established based on the signature to verify its clinical application. Furthermore, we looked for the co-expressed proteins of three-protein panel as potential prognostic proteins.Conclusion: A proteomic signature independently predicted OS of CC patients, and the predictive ability was better than the clinicopathological characteristics. This signature can help improve prediction for clinical outcome and provides new targets for CC treatment.

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A pan-cancer analysis based on weighted gene co-expression network analysis identifies the biomarker utility of lamin B1 in human tumors

Cancer Biomarkers ◽

10.3233/cbm-203247 ◽

2021 ◽

pp. 1-17

Author(s):

Youwei Hua ◽

Zhihui He ◽

Xu Zhang

Keyword(s):

Network Analysis ◽

Disease Free Survival ◽

The Cancer Genome Atlas ◽

Free Survival ◽

Lamin B1 ◽

Cancer Genome Atlas ◽

Mrna Binding ◽

Functional Mechanisms ◽

Pan Cancer

Emerging evidence has revealed a relationship between lamin B1 (LMNB1) and several cancers such as cervical cancer, liver cancer, and prostate cancer. But no systematic pan-cancer analysis is available. Little is known about the clinical significance and biomarker utility of LMNB1. In this study, we first revealed the key role of LMNB1 in esophageal carcinoma (ESCA) through weighted gene co-expression network analysis (WGCNA) and disease-free survival (DFS) analysis. Based on this result and the datasets of the cancer genome atlas (TCGA), we explored the biomarker utility of LMNB1 across thirty-three tumors. We found that LMNB1 was highly expressed in most of the cancers and significant associations existed between LMNB1 expression and prognosis of cases of nearly half of the cancers. We also found that LMNB1 expression was associated with the infiltration level of Macrophages M1 and T cells CD4 memory activated in some cancers. Moreover, LMNB1 was mainly involved in the functional mechanisms of MRNA binding, olfactory transduction, and gene silencing. Our study first provides a pan-cancer study of LMNB1, thereby offering a relatively comprehensive understanding of the biomarker utility of LMNB1 across thirty-three tumors.

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