Constructed competitive endogenous RNA network and patterns of immune infiltration revealing the prognostic signature for cervical cancer
Abstract
Aim: To investigate the relationship between potential abnormal epigenetic modification and immune cell infiltration in patients with cervical carcinoma. Materials & methods: RNA expression profiles from The Cancer Genome Atlas database were used to explore the relationship between key biomarkers and tumor-infiltrating immune cells and for clinical specimen validation. Results: Two nomogram models were developed, one with specific ceRNA and the other based on biological markers of related tumor-infiltrating immune cells. Moreover, a key biomarker (RIPOR2), which was significantly relevant to CD8 T cells. Conclusion: RIPOR2 and CD8 T cells play a crucial role in the development and progression of cervical carcinoma, suggesting their potential as markers for guiding future therapeutic strategies.
Graphical abstract
Papers of special note have been highlighted as: •• of considerable interest
References
- 1. Epidemiological/Disease and Economic Burdens of Cervical Cancer in 2010-2014: Are Younger Women at Risk?. Healthcare (Basel). 11(1), 144 2023).
- 2. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 71(3), 209–249 (2021).
- 3. . Cervical cancer: prevention and early detection. Semin. Oncol. Nurs. 33(2), 172–183 (2017).
- 4. . Cervical cancer: prevention and treatment. Discov. Med. 14(75), 125–131 (2012).
- 5. . Long noncoding RNAs biomarker-based cancer assessment. J. Cell. Physiol. 234(10), 16971–16986 (2019).
- 6. . A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell 146(3), 353–358 (2011). •• The hypothesis of a competitive endogenous RNA network was proposed for the first time.
- 7. . ceRNA cross-talk in cancer: when ce-bling rivalries go awry. Cancer Discov. 3(10), 1113–1121 (2013).
- 8. Integrated analysis of a competing endogenous RNA network revealing a prognostic signature for cervical cancer. Front. Oncol. 8, 368 (2018).
- 9. Construction of an immune-related gene signature for prediction of prognosis in patients with cervical cancer. Int. Immunopharmacol. 88, 106882 (2020).
- 10. . The prognostic landscape of tumor-infiltrating immune cells in cervical cancer. Biomed. Pharmacother. 120, 109444 (2019).
- 11. . Profiling tumor infiltrating immune cells with CIBERSORT. Methods Mol. Biol. 1711, 243–259 (2018).
- 12. . edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1), 139–140 (2010).
- 13. . Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B Stat. Methodol. 57(1), 289–300 (1995).
- 14. GDCRNATools: an R/Bioconductor package for integrative analysis of lncRNA, miRNA and mRNA data in GDC. Bioinformatics 34(14), 2515–2517 (2018). •• Provides methodological validation for the current experiment.
- 15. . Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27(3), 431–432 (2011).
- 16. . Nomograms in oncology: more than meets the eye. Lancet Oncol. 16(4), e173–e180 (2015).
- 17. CellMarker: a manually curated resource of cell markers in human and mouse. Nucleic Acids Res. 47(D1), D721–D728 (2019).
- 18. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2(5), 401–404 (2012).
- 19. DriverDBv3: a multi-omics database for cancer driver gene research. Nucleic Acids Res. 48(D1), D863–D870 (2020).
- 20. Human Genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348(6235), 648–660 (2015).
- 21. . GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 45(W1), W98–W102 (2017).
- 22. SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis. PLOS ONE 8(9), e74250 (2013).
- 23. . MethSurv: a web tool to perform multivariable survival analysis using DNA methylation data. Epigenomics 10(3), 277–288 (2018).
- 24. Interactive online consensus survival tool for esophageal squamous cell carcinoma prognosis analysis. Oncol. Lett. 18(2), 1199–1206 (2019).
- 25. H-score of 11β-hydroxylase and aldosterone synthase in the histopathological diagnosis of adrenocortical tumors. Endocrine 65(3), 683–691 (2019).
- 26. . Cornulin as a prognosticator for lymph node involvement in cutaneous squamous cell carcinoma. Cureus 14(12), e33130 (2022).
- 27. . A Perl toolkit for LIMS development. Source Code Biol. Med. 3, 4 (2008).
- 28. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12(5), 453–457 (2015).
- 29. The BRAF pseudogene functions as a competitive endogenous RNA and induces lymphoma in vivo. Cell 161(2), 319–332 (2015).
- 30. circTP63 functions as a ceRNA to promote lung squamous cell carcinoma progression by upregulating FOXM1. Nat. Commun. 10(1), 3200 (2019).
- 31. Functions and mechanisms of tumor necrosis factor-α and noncoding RNAs in bone-invasive pituitary adenomas. Clin. Cancer Res. 24(22), 5757–5766 (2018).
- 32. . The multilayered complexity of ceRNA crosstalk and competition. Nature 505(7483), 344–352 (2014).
- 33. . Novel insights for lncRNA MAGI2-AS3 in solid tumors. Biomed. Pharmacother. 137, 111429 (2021).
- 34. . Identification and verification of a novel MAGI2-AS3/miRNA-374-5p/FOXO1 network associated with HBV-related HCC. Cells 11(21), 3466 (2022).
- 35. RIPOR2 expression decreased by HPV-16 E6 and E7 oncoproteins: an opportunity in the search for prognostic biomarkers in cervical cancer. Cells 11(23), 3942 (2022).
- 36. . PL48: a novel gene associated with cytotrophoblast and lineage-specific HL-60 cell differentiation. Gene 185(2), 153–157 (1997).
- 37. Fam65b is a new transcriptional target of FOXO1 that regulates RhoA signaling for T lymphocyte migration. J. Immunol. 190(2), 748–755 (2013).
- 38. Rescue of exhausted CD8 T cells by PD-1-targeted therapies is CD28-dependent. Science 355(6332), 1423–1427 (2017).
- 39. . Harnessing CD8(+)CD28(-) regulatory T cells as a tool to treat autoimmune disease. Cells 10(11), 2973 (2021).