Integrated Omics Analysis Of HPV And Cervical Cancer

Cervical cancer is one of the most common female reproductive system cancers. There are more than500thousand new cases of cervical cancer worldwide every year.80%of these cases are from developing country. According the data from2011Yearbook of Health Statistics released in NHFPC’s website, the cervical cancer’s morbidity was15.1/100thousand people in China,2010, which was on the rise compared with previous years. Epidemiological studies have shown that high-risk human papilloma virus (HPV) infection is an important factor to induce cervical cancer. Papillomavirus is a small DNA virus that proliferates on skin and mucous membrane. Human papillomavirus (HPV) can be divided into two major categories by clinical analysis, high risk and low risk. High risk HPV, or oncogenic HPV, is carcinogenic. More than12types of high-risk type HPV have been identified. And HPV16and HPV18are associated with about70%of cervical cancer caused by HPV. Although previous research has shown a correlation between the high-risk HPV infection and cervical cancer, there is a lack of macro understanding of high-risk HPV effects on the host cell. With sequencing technology and high resolution mass spectrometry technology becoming increasingly mature, we have the opportunity to comprehensively understand the carcinogenic mechanism of HPV through high-throughput sequencing and total protein spectrum analysis. In this study, we combined the above two new techniques with other molecular biology techniques and obtained transcriptome and proteome data.Objective:To collect the transcriptome and proteome information of cervical cancer tissue or HPV expressing cells, find the difference between cancer sample and the normal control, and test the relationship between HPV infection and the difference.Methods:1. RNA-sequencing of the HPV oncogene E7expressing cells:We prepared RNA from NIKS cells containing a vector or expressing HPV16-E7ncogene,performed sequencing and quantified the data.2. Bioinformatics analysis of RNA-seq results:We selected the protein-coding genes that have obvious expression differences in E7expressing cells and vector control cells, clustered these genes by GO (Gene Ontology), then verified the results of RNA-seq by Real time PCR.3. Preparation of Protein samples from cervical cancer cell lines:We prepared total protein extracts from cervical cancer cell lines SiHa and HeLa, then collected the enzymolysis products by FASP method.4.Proteome analysis of cervical cancer cell lines:We made the LCMS analysis of the peptides from the above two cell lines respectivelymand conducted label-free quantification of the mass spectrometry data。Then we performed bioinformatics analysis of the quantification data. Results:1. We identified236genes that have obviously different expression levels between E7cells and control cells by RNA-sequencing. Among them,150genes have high-level expression in E7cells and86genes have low-level expression in E7cells.2. According the GO clustering, we found38%of the high-level expression genes are related to cell cycle,30%are related to DNA metabolism;15%of the low-level expression genes are related with cell proliferation regulation,14%are related with homeostasis of the cell.3. We identified2373unique proteins in HeLa and SiHa cell lines by LCMS analysis.1401of the identified-proteins in HeLa cells meet the requirement that peptides false positive rate is below0.05.In SiHa cells while1620of the identified-proteins meet this requirement.4. We identified787proteins that are differentially expressed between HeLa and SiHa cells that are statistically significant.401of them are over expressed in HeLa cells and386of them are reduced in HeLa cells.10.8%of the high-level expressed proteins are related with energy metabolism;14.3%of the low-level expressed proteins are related with apoptosis.Conclusions: 1. HPV oncogene E7promotes cell proliferation and cell metabolism, which may be important for cervical carcinogenesis.2. The adenocarcinoma and squamous carcinoma caused by HPV infection have obvious expression differences. These differences may be the important reasons of adenocarcinoma’s poor prognosis.