Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis
Background: Cervical cancer (CC) is the second most common type of malignant tumor survival rate is low in advanced stage, metastatic, and recurrent CC patients. This study aimed at identifying potential genes and drugs for CC diagnosis and targeting therapies. Methods: Three GEO mRNA microarray dat...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2020-12-01
|
| Series: | Technology in Cancer Research & Treatment |
| Online Access: | https://doi.org/10.1177/1533033820980112 |
| _version_ | 1818661703940833280 |
|---|---|
| author | Hui-Zhu Qiu MM Ji Huang MB Cheng-Cheng Xiang MM Rong Li MM Er-Dong Zuo MM Yuan Zhang MM Li Shan MM Xu Cheng MM |
| author_facet | Hui-Zhu Qiu MM Ji Huang MB Cheng-Cheng Xiang MM Rong Li MM Er-Dong Zuo MM Yuan Zhang MM Li Shan MM Xu Cheng MM |
| author_sort | Hui-Zhu Qiu MM |
| collection | DOAJ |
| description | Background: Cervical cancer (CC) is the second most common type of malignant tumor survival rate is low in advanced stage, metastatic, and recurrent CC patients. This study aimed at identifying potential genes and drugs for CC diagnosis and targeting therapies. Methods: Three GEO mRNA microarray datasets of CC tissues and non-cancerous tissues were analyzed for differentially expressed genes (DEGs) by limma package. GO (Gene Ontologies) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used to explore the relationships between the DEGs. Protein-protein interaction (PPI) of these genes was established by the STRING database. MCODE was used for screening significant modules in the PPI networks to select hub genes. Biochemical mechanisms of the hub genes were investigated with Metascape. GEPIA database was used for validating the core genes. According to these DEGs, molecular candidates for CC were recognized from the CMAP database. Results: We identified 309 overlapping DEGs in the 2 tissue-types. Pathway analysis revealed that the DEGs were involved in cell cycle, DNA replication, and p53 signaling. PPI networks between overlapping DEGs showed 68 high-connectivity DEGs that were chosen as hub genes. The GEPIA database showed that the expression levels of RRM2, CDC45, GINS2, HELLS, KNTC1, MCM2, MYBL2, PCNA, RAD54 L, RFC4, RFC5, TK1, TOP2A, and TYMS in CC tissues were significantly different from those in the healthy tissues and were significantly relevant to the OS of CC. We found 10 small molecules from the CMAP database that could change the trend of gene expression in CC tissues, including piperlongumine and chrysin. Conclusions: The 14 DEGs identified in this study could serve as novel prognosis biomarkers for the detection and forecasting of CC. Small molecule drugs like piperlongumine and chrysin could be potential therapeutic drugs for CC treatment. |
| first_indexed | 2024-12-17T04:49:17Z |
| format | Article |
| id | doaj.art-6c595f871c1140509db8e33af8e06f54 |
| institution | Directory Open Access Journal |
| issn | 1533-0338 |
| language | English |
| last_indexed | 2024-12-17T04:49:17Z |
| publishDate | 2020-12-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Technology in Cancer Research & Treatment |
| spelling | doaj.art-6c595f871c1140509db8e33af8e06f542022-12-21T22:02:57ZengSAGE PublishingTechnology in Cancer Research & Treatment1533-03382020-12-011910.1177/1533033820980112Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics AnalysisHui-Zhu Qiu MM0Ji Huang MB1Cheng-Cheng Xiang MM2Rong Li MM3Er-Dong Zuo MM4Yuan Zhang MM5Li Shan MM6Xu Cheng MM7 Department of Hematology and Oncology, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, China Department of Pharmacy, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, China Department of Hematology and Oncology, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, China Department of Hematology and Oncology, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, China Department of Hematology and Oncology, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, China Department of Hematology and Oncology, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, China Department of Hematology and Oncology, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, China Department of Hematology and Oncology, Soochow University Affiliated Taicang Hospital (The First People’s Hospital of Taicang), Jiangsu, ChinaBackground: Cervical cancer (CC) is the second most common type of malignant tumor survival rate is low in advanced stage, metastatic, and recurrent CC patients. This study aimed at identifying potential genes and drugs for CC diagnosis and targeting therapies. Methods: Three GEO mRNA microarray datasets of CC tissues and non-cancerous tissues were analyzed for differentially expressed genes (DEGs) by limma package. GO (Gene Ontologies) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used to explore the relationships between the DEGs. Protein-protein interaction (PPI) of these genes was established by the STRING database. MCODE was used for screening significant modules in the PPI networks to select hub genes. Biochemical mechanisms of the hub genes were investigated with Metascape. GEPIA database was used for validating the core genes. According to these DEGs, molecular candidates for CC were recognized from the CMAP database. Results: We identified 309 overlapping DEGs in the 2 tissue-types. Pathway analysis revealed that the DEGs were involved in cell cycle, DNA replication, and p53 signaling. PPI networks between overlapping DEGs showed 68 high-connectivity DEGs that were chosen as hub genes. The GEPIA database showed that the expression levels of RRM2, CDC45, GINS2, HELLS, KNTC1, MCM2, MYBL2, PCNA, RAD54 L, RFC4, RFC5, TK1, TOP2A, and TYMS in CC tissues were significantly different from those in the healthy tissues and were significantly relevant to the OS of CC. We found 10 small molecules from the CMAP database that could change the trend of gene expression in CC tissues, including piperlongumine and chrysin. Conclusions: The 14 DEGs identified in this study could serve as novel prognosis biomarkers for the detection and forecasting of CC. Small molecule drugs like piperlongumine and chrysin could be potential therapeutic drugs for CC treatment.https://doi.org/10.1177/1533033820980112 |
| spellingShingle | Hui-Zhu Qiu MM Ji Huang MB Cheng-Cheng Xiang MM Rong Li MM Er-Dong Zuo MM Yuan Zhang MM Li Shan MM Xu Cheng MM Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis Technology in Cancer Research & Treatment |
| title | Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis |
| title_full | Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis |
| title_fullStr | Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis |
| title_full_unstemmed | Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis |
| title_short | Screening and Discovery of New Potential Biomarkers and Small Molecule Drugs for Cervical Cancer: A Bioinformatics Analysis |
| title_sort | screening and discovery of new potential biomarkers and small molecule drugs for cervical cancer a bioinformatics analysis |
| url | https://doi.org/10.1177/1533033820980112 |
| work_keys_str_mv | AT huizhuqiumm screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis AT jihuangmb screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis AT chengchengxiangmm screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis AT ronglimm screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis AT erdongzuomm screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis AT yuanzhangmm screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis AT lishanmm screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis AT xuchengmm screeninganddiscoveryofnewpotentialbiomarkersandsmallmoleculedrugsforcervicalcancerabioinformaticsanalysis |