Expression profiling of cervical cancers in I ndian women at different stages to identify gene signatures during progression of the disease

Cervical cancer is the second most common cancer among women worldwide, with developing countries accounting for >80% of the disease burden. Although in the West, active screening has been instrumental in reducing the incidence of cervical cancer, disease management is hampered due to lack of biomarkers for disease progression and defined therapeutic targets. Here we carried out gene expression profiling of 29 cervical cancer tissues from I ndian women, spanning International Federation of Gynaecology and Obstetrics ( FIGO ) stages of the disease from early lesion (IA and IIA) to progressive stages (IIB and IIIA–B), and identified distinct gene expression signatures. Overall, metabolic pathways, pathways in cancer and signaling pathways were found to be significantly upregulated, while focal adhesion, cytokine–cytokine receptor interaction and WNT signaling were downregulated. Additionally, we identified candidate biomarkers of disease progression such as SPP 1, proliferating cell nuclear antigen ( PCNA ), STK 17A, and DUSP 1 among others that were validated by quantitative real‐time polymerase chain reaction ( qRT ‐ PCR ) in the samples used for microarray studies as well in an independent set of 34 additional samples. Integrative analysis of our results with other cervical cancer profiling studies could facilitate the development of multiplex diagnostic markers of cervical cancer progression. Cervical cancer is the leading cause of cancer deaths among women in I ndia, yet it remains poorly characterized at molecular level. This study provides one of the largest molecular profiling efforts from this region involving cervical cancer tissues from well‐defined clinical stages to identify molecular signatures of disease progression, as well as identify novel biomarkers distinguishing early and advanced disease. We expect this study to serve as a template for larger studies, including those based on high‐throughput sequencing, to help develop robust biomarkers of disease progression and potentially identify actionable therapeutic targets.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101800/1/cam4152.pd