Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients
Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics a...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-02-01
|
| Series: | International Journal of Molecular Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1422-0067/22/5/2442 |
| _version_ | 1797416952480661504 |
|---|---|
| author | Qun Wang Aurelia Vattai Theresa Vilsmaier Till Kaltofen Alexander Steger Doris Mayr Sven Mahner Udo Jeschke Helene Hildegard Heidegger |
| author_facet | Qun Wang Aurelia Vattai Theresa Vilsmaier Till Kaltofen Alexander Steger Doris Mayr Sven Mahner Udo Jeschke Helene Hildegard Heidegger |
| author_sort | Qun Wang |
| collection | DOAJ |
| description | Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (<i>APOD</i>, <i>TFRC</i>, <i>GRN</i>, <i>CSK</i>, <i>HDAC1</i>, <i>NFATC4</i>, <i>BMP6</i>, <i>IL17RD</i>, <i>IL3RA</i>, and <i>LEPR</i>) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets. |
| first_indexed | 2024-03-09T06:11:48Z |
| format | Article |
| id | doaj.art-a7d3bef8edad4f8aab5c4d67257988bc |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T06:11:48Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-a7d3bef8edad4f8aab5c4d67257988bc2023-12-03T11:58:08ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-02-01225244210.3390/ijms22052442Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer PatientsQun Wang0Aurelia Vattai1Theresa Vilsmaier2Till Kaltofen3Alexander Steger4Doris Mayr5Sven Mahner6Udo Jeschke7Helene Hildegard Heidegger8Department of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, GermanyDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, GermanyDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, GermanyDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, GermanyKlinik für Innere Medizin I, Technische Universität München, 80333 Munich, GermanyDepartment of Pathology, LMU Munich, 80377 Munich, GermanyDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, GermanyDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, GermanyDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, GermanyCervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (<i>APOD</i>, <i>TFRC</i>, <i>GRN</i>, <i>CSK</i>, <i>HDAC1</i>, <i>NFATC4</i>, <i>BMP6</i>, <i>IL17RD</i>, <i>IL3RA</i>, and <i>LEPR</i>) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.https://www.mdpi.com/1422-0067/22/5/2442cervical cancertumor immunebioinformatics analysisTCGAKEGG |
| spellingShingle | Qun Wang Aurelia Vattai Theresa Vilsmaier Till Kaltofen Alexander Steger Doris Mayr Sven Mahner Udo Jeschke Helene Hildegard Heidegger Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients International Journal of Molecular Sciences cervical cancer tumor immune bioinformatics analysis TCGA KEGG |
| title | Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients |
| title_full | Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients |
| title_fullStr | Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients |
| title_full_unstemmed | Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients |
| title_short | Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients |
| title_sort | immunogenomic identification for predicting the prognosis of cervical cancer patients |
| topic | cervical cancer tumor immune bioinformatics analysis TCGA KEGG |
| url | https://www.mdpi.com/1422-0067/22/5/2442 |
| work_keys_str_mv | AT qunwang immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT aureliavattai immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT theresavilsmaier immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT tillkaltofen immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT alexandersteger immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT dorismayr immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT svenmahner immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT udojeschke immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients AT helenehildegardheidegger immunogenomicidentificationforpredictingtheprognosisofcervicalcancerpatients |