Purpose
To assign functional properties to gene expression profiles of cervical cancer stages and identify clinically relevant biomarker genes.
Experimental design
Microarray samples of 24 normal and 102 cervical cancer biopsies from four publicly available studies were pooled and evaluated. High-quality microarrays were normalized using the CONOR package from the Bioconductor project. Gene expression profiling was performed using variance-component analysis for accessing most reliable probes, which were subsequently processed by gene set enrichment analysis.
Results
Of 22.277 probes that were subject to variance-component analysis, eleven probes had low heterogeneity, that is, a W/T ratio between 0.18 and 0.38. Seven of these probes are induced in all cervical cancer stages: they are GINS1, PAK2, DTL, AURKA, PRKDC, NEK2 and CEP55. The other four probes are induced in normal cervix: P11, EMP1, UPK1A and HSPC159. We performed GSEA of 9.873 probes exhibiting less variability, that is, having a W/T ratio of <0.75. Repeatedly, significant gene expression signatures were found that are related to treatment using angiocidin and darapladib. Additionally, expression signatures from immunological disease signatures were found, for example graft versus host disease and acute kidney rejection. Another finding comprises a gene expression signature in stage IB2 that refers to MT1-MMP-dependent migration and invasion. This gene signature is accompanied by gene expression signatures which refer to ECM receptor-mediated interactions.
Conclusion
Analysis of cervical cancer patient gene expression data reveals a novel perspective on HPV-mediated transcription processes. This novel point of view contains a better understanding and even might provide improvements to cancer therapy.