Identification of Novel Genes and Associated Drugs in Cervical Cancer by Bioinformatics Methods

Wang, Dan; Liu, Yanling; Cheng, Shuyu; Liu, Guoyan

doi:10.12659/msm.934799

Cited by 5 publications

(2 citation statements)

References 51 publications

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“…This finding reports for the first time that CAPG may play a significant role in the survival of cervical cancer. Although MAD2L1 [ 67 ], TOP2A [ 68 ], AURKA [ 69 ], and ASPM [ 68 ] were reported in various research findings, they may play a remarkable role in the survival of cervical cancer. By contrast, NDC80 and CAPG are a novel targets in the survival of cervical cancer.…”

Section: Resultsmentioning

confidence: 99%

Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer

Hasan

Islam

et al. 2023

Journal of Genetic Engineering and Biotechnology

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Background In today’s society, cancer has become a big concern. The most common cancers in women are breast cancer (BC), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). CC is a type of cervix cancer that is the fourth most common cancer in women and the fourth major cause of death. Results This research uses a network approach to discover genetic connections, functional enrichment, pathways analysis, microRNAs transcription factors (miRNA-TF) co-regulatory network, gene-disease associations, and therapeutic targets for CC. Three datasets from the NCBI’s GEO collection were considered for this investigation. Then, using a comparison approach between the datasets, 315 common DEGs were discovered. The PPI network was built using a variety of combinatorial statistical approaches and bioinformatics tools, and the PPI network was then utilized to identify hub genes and critical modules. Conclusion Furthermore, we discovered that CC has specific similar links with the progression of different tumors using Gene Ontology terminology and pathway analysis. Transcription factors-gene linkages, gene-disease correlations, and the miRNA-TF co-regulatory network were revealed to have functional enrichments. We believe the candidate drugs identified in this study could be effective for advanced CC treatment.

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Section: Resultsmentioning

confidence: 99%

Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer

Hasan

Islam

et al. 2023

Journal of Genetic Engineering and Biotechnology

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“…Big data produced from high-throughput RNA-seq and microarrays have been proven to be a powerful aid in oncology research, facilitating the hunting for novel biomarkers in a time-effective manner, which is how expression profiling and molecular investigations have improved the management of gynecological tumors [20][21][22]. Only two studies revealed the mitochondrial function of CKS2 in the aggressive development of chemo radioresistant cervical cancer and the adverse impact of CKS2 high expression on the progression-free survival of cervical cancer patients [23,24].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Expression Profiling and Molecular Basis of CDC28 Protein Kinase Regulatory Subunit 2 in Cervical Cancer

Qin

Luo

Xiao

et al. 2022

International Journal of Genomics

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More and more evidence suggests the oncogenic function of overexpressed CDC28 protein kinase regulatory subunit 2 (CKS2) in various human cancers. However, CKS2 has rarely been studied in cervical cancer. Herein, taking advantage of massive genetics data from multicenter RNA-seq and microarrays, we were the first group to perform tissue microarrays for CKS2 in cervical cancer. We were also the first to evaluate the clinical significance of CKS2 with large samples (980 cervical cancer cases and 422 noncancer cases). We further excavated the mechanism of the tumor-promoting activities of CKS2 in cervical cancer through analysis of genetic mutation profiles, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) significant enrichment of genes coexpressed with CKS2. According to the results, expression data from multilevels unanimously supported the overexpression of CKS2 in cervical cancer. Patients with cervical cancer in stage II from inhouse microarrays had significantly higher expression of CKS2, and CKS2 overexpression had an adverse impact on the disease-free survival status of cervical cancer patients in GSE44001. Both mutation types of mRNA high and mRNA low appeared in cervical cancer cases from the TCGA Firehose project. Gene coexpressed with CKS2 participated in pathways including the cell cycle, estrogen signaling pathway, and DNA replication. In summary, upregulated CKS2 is closely associated with the malignant clinical development of cervical cancer and might serve as a valuable therapeutic target in cervical cancer.

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Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnostic model

Zhang,

Chen,

Deng

2024

J Cancer Res Clin Oncol

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Purpose This study aims to utilize bioinformatics methods to systematically screen and identify susceptibility genes for cervical cancer, as well as to construct and validate an mitophagy-related genes (MRGs) diagnostic model. The objective is to increase the understanding of the disease’s pathogenesis and improve early diagnosis and treatment. Method We initially collected a large amount of genomic data, including gene expression profile and single nucleotide polymorphism (SNP) data, from the control group and Cervical cancer (CC) patients. Through bioinformatics analysis, which employs methods such as differential gene expression analysis and pathway enrichment analysis, we identified a set of candidate susceptibility genes associated with cervical cancer. Results MRGs were extracted from single-cell RNA sequencing data, and a network graph was constructed on the basis of intercellular interaction data. Furthermore, using machine learning algorithms, we constructed a clinical prognostic model and validated and optimized it via extensive clinical data. Through bioinformatics analysis, we successfully identified a group of genes whose expression significantly differed during the development of CC and revealed the biological pathways in which these genes are involved. Moreover, our constructed clinical prognostic model demonstrated excellent performance in the validation phase, accurately predicting the clinical prognosis of patients. Conclusion This study delves into the susceptibility genes of cervical cancer through bioinformatics approaches and successfully builds a reliable clinical prognostic model. This study not only helps uncover potential pathogenic mechanisms of cervical cancer but also provides new directions for early diagnosis and treatment of the disease.

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Identification of Novel Genes and Associated Drugs in Cervical Cancer by Bioinformatics Methods

Cited by 5 publications

References 51 publications

Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer

Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer

Comprehensive Expression Profiling and Molecular Basis of CDC28 Protein Kinase Regulatory Subunit 2 in Cervical Cancer

Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnostic model

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