Cervical cancer is the third most common and fourth most fatal type of cancer among women. Our study aims in the elucidation of the molecular mechanisms underlying malignant transformation of the cervical epithelium. To achieve this goal, we used state-of-the-art proteomics techniques.
The pattern of the total cell extract of cervical cancer cell lines HeLa (HPV18+), SiHa (HPV16+), and C-33A (HPV-), was compared to normal cervical keratinocytes (HCK1T). The peptides extracted from each sample after in-gel tryptic digestion, were analyzed by Liquid Chromatography coupled to high resolution mass spectrometry (LC-MS/MS). Bioinformatics analysis was performed on the results utilizing various platforms and databases (e.g. Ingenuity Pathway Analysis, Cytoscape). Validation of the in vitro results was performed with Multiple Reaction Monitoring – Mass Spectrometry (MRM-MS), a highly sensitive and selective, targeted proteomics approach for peptide quantitation. Clinical validation was performed with immunohistochemistry.
The proteomics analysis yielded a high number of identifications for each cell line (~2500-3500 proteins), with a satisfying reproducibility among biological replicates. Moreover, the comparison between each cancer cell line and the normal keratinocytes resulted in ~900-1400 statistically significant (p<0.05, Mann Whitney) differences in the proteome. The total number of differentially expressed proteins was analyzed by bioinformatics tools in order to investigate the biological processes and molecular pathways that contribute to carcinogenesis and metastasis in the cervical epithelium. Two transcription factors, p53 and c-Myc, that are known to regulate cervical carcinogenesis, were predicted to control a significant number of differentially expressed proteins in our dataset. Actin cytoskeleton signaling, which plays an important role in carcinogenesis and metastasis, is a prominent pathway predicted by Ingenuity Pathway Analysis based on the proteomics results. Other pathways and proteins potentially involved in the pathology of cervical cancer identified from this analysis included translation and Eukaryotic Initiation Factor 2 (eIF2). Interesting molecules, that appear to have key roles in cervical cancer, based on this analysis, were chosen and further validated by MRM-MS and Immunohistochemistry in cervical cancer cell lines and clinical samples.
This systems biology approach provided new insights in cervical cancer pathology and led to the discovery of potential biomarkers and pharmacological targets.