Screening of biomarkers in cervical squamous cell carcinomas via gene expression profiling

Chen,Bing; Li,Chundong; Zhang,Lei; Lv,Jiahui; Tong,Ying

doi:10.3892/mmr.2015.4322

Screening of biomarkers in cervical squamous cell carcinomas via gene expression profiling

Authors:
- Bing Chen
- Chundong Li
- Lei Zhang
- Jiahui Lv
- Ying Tong
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Affiliations: Department of Gynaecology and Obstetrics, General Hospital of The Air Force, Beijing 100142, P.R. China
Published online on: September 14, 2015 https://doi.org/10.3892/mmr.2015.4322
Pages: 6985-6989

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Abstract

In the present study, gene expression profiles of high-grade squamous intraepithelial lesions (HSIL) and invasive cervical squamous cell carcinomas (CSCC) were analyzed using bioinformatic tools to identify key genes and potential biomarkers. Analyses of differentially expressed genes (DEGs) were performed for HSIL vs. normal control and invasive CSCC vs. normal control tissues using the Limma package in R. Pathway enrichment analysis was performed using KOBAS. A protein‑protein interaction (PPI) network for the DEGs in invasive CSCC was constructed using String. Functional enrichment analysis was performed for the DEGs in the PPI network using DAVID. Relevant small molecules were predicted using Cmap. A total of 633 and 881 DEGs were identified in HSIL and invasive CSCC, respectively, and the two groups had 305 DEGs in common. Genes associated with the mitogen-activated protein kinase signaling pathway were enriched in the HSIL, while cell cycle-associated genes were over‑represented in invasive CSCC. The PPI network, containing 72 upregulated genes and 434 edges, was illustrated. Functional enrichment analysis showed that the cell cycle was the most significant gene ontology term. A total of six small molecules associated with the pathology of CSCC were identified, including the anti-cancer drug piperlongumine, which showed a negative correlation. The findings of the present study not only enhanced the current understanding of the pathogenesis of CSCC, but may also be a basis for the development of novel therapies.

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1	Armstrong EP: Prophylaxis of cervical cancer and related cervical disease: A review of the cost-effectiveness of vaccination against oncogenic HPV types. J Manag Care Pharm. 16:217–230. 2010.PubMed/NCBI
2	Steward BW and Wild CP: World Cancer Report. World Health Organization; Geneva: 2014
3	Chaturvedi AK: Beyond cervical cancer: Burden of other HPV-related cancers among men and women. J Adolesc Health. 46(4 Suppl): S20–S26. 2010. View Article : Google Scholar : PubMed/NCBI
4	Schiffman M, Castle PE, Jeronimo J, Rodriguez AC and Wacholder S: Human papillomavirus and cervical cancer. Lancet. 370:890–907. 2007. View Article : Google Scholar : PubMed/NCBI
5	Gadducci A, Barsotti C, Cosio S, Domenici L and Riccardo Genazzani A: Smoking habit, immune suppression, oral contraceptive use and hormone replacement therapy use and cervical carcinogenesis: A review of the literature. Gynecol Endocrinol. 27:597–604. 2011. View Article : Google Scholar : PubMed/NCBI
6	Uren A, Fallen S, Yuan H, Usubütün A, Küçükali T, Schlegel R and Toretsky JA: Activation of the canonical wnt pathway during genital keratinocyte transformation: A model for cervical cancer progression. Cancer Res. 65:6199–6206. 2005. View Article : Google Scholar : PubMed/NCBI
7	Duarte I, Santos A, Sousa H, Catarino R, Pinto D, Matos A, Pereira D, Moutinho J, Canedo P, Machado JC and Medeiros R: G-308A TNF-alpha polymorphism is associated with an increased risk of invasive cervical cancer. Biochem Biophys Res Commun. 334:588–592. 2005. View Article : Google Scholar : PubMed/NCBI
8	Chan D, Yu S, Chiu PM, Yao KM, Liu VW, Cheung AN and Ngan HY: Over-expression of FOXM1 transcription factor is associated with cervical cancer progression and pathogenesis. J Pathol. 215:245–252. 2008. View Article : Google Scholar : PubMed/NCBI
9	Murphy N, Ring M, Heffron CC, King B, Killalea AG, Hughes C, Martin CM, McGuinness E, Sheils O and O'Leary JJ: p16INK4A, CDC6 and MCM5: Predictive biomarkers in cervical preinvasive neoplasia and cervical cancer. J Clin Pathol. 58:525–534. 2005. View Article : Google Scholar : PubMed/NCBI
10	Song JY, Lee JK, Lee NW, Jung HH, Kim SH and Lee KW: Microarray analysis of normal cervix, carcinoma in situ and invasive cervical cancer: Identification of candidate genes in pathogenesis of invasion in cervical cancer. Int J Gynecol Cancer. 18:1051–1059. 2008. View Article : Google Scholar : PubMed/NCBI
11	Zhai Y, Kuick R, Nan B, Ota I, Weiss SJ, Trimble CL, Fearon ER and Cho KR: Gene expression analysis of preinvasive and invasive cervical squamous cell carcinomas identifies HOXC10 as a key mediator of invasion. Cancer Res. 67:10163–10172. 2007. View Article : Google Scholar : PubMed/NCBI
12	Fujita A, Sato JR, Rodrigues LO, Ferreira CE and Sogayar MC: Evaluating different methods of microarray data normalization. BMC bioinformatics. 7:4692006. View Article : Google Scholar : PubMed/NCBI
13	Smyth GK: Limma: Linear models for microarray data. Bioinformatics and computational biology solutions using R and Bioconductor. Springer; pp. 397–420. 2005, View Article : Google Scholar
14	Benjamini Y and Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological). 289–300. 1995.
15	Szekely GJ and Rizzo ML: Hierarchical clustering via joint between-within distances: Extending Ward's minimum variance method. Journal of Classification. 22:151–183. 2005. View Article : Google Scholar
16	Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, Kong L, Gao G, Li CY and Wei L: KOBAS 2.0: A web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 39(Web Server Issue): W316–W322. 2011. View Article : Google Scholar : PubMed/NCBI
17	Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork P, et al: The STRING database in 2011: Functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 39(Database Issue): D561–D568. 2011. View Article : Google Scholar :
18	Smoot ME, Ono K, Ruscheinski J, Wang PL and Ideker T: Cytoscape 2.8: New features for data integration and network visualization. Bioinformatics. 27:431–432. 2011. View Article : Google Scholar :
19	Huang da W, Sherman BT and Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 4:44–57. 2008. View Article : Google Scholar
20	Evan GI and Vousden KH: Proliferation, cell cycle and apoptosis in cancer. Nature. 411:342–348. 2001. View Article : Google Scholar : PubMed/NCBI
21	Catania A, Urban S, Yan E, Hao C, Barron G and Allalunis-Turner J: Expression and localization of cyclin-dependent kinase 5 in apoptotic human glioma cells. Neuro Oncol. 3:89–98. 2001.PubMed/NCBI
22	Kong EH, Kim YJ, Kim YJ, Cho HJ, Yu SN, Kim KY, Chang JH and Ahn SC: Piplartine induces caspase-mediated apoptosis in PC-3 human prostate cancer cells. Oncol Rep. 20:785–792. 2008.PubMed/NCBI
23	Bezerra DP, Militão GC, de Castro FO, Pessoa C, de Moraes MO, Silveira ER, Lima MA, Elmiro FJ and Costa-Lotufo LV: Piplartine induces inhibition of leukemia cell proliferation triggering both apoptosis and necrosis pathways. Toxicology In Vitro. 21:1–8. 2007. View Article : Google Scholar
24	Kim EK and Choi EJ: Pathological roles of MAPK signaling pathways in human diseases. Biochim Biophys Acta. 1802:396–405. 2010. View Article : Google Scholar : PubMed/NCBI
25	Wagner EF and Nebreda AR: Signal integration by JNK and p38 MAPK pathways in cancer development. Nat Rev Cancer. 9:537–549. 2009. View Article : Google Scholar : PubMed/NCBI
26	Kastan MB and Bartek J: Cell-cycle checkpoints and cancer. Nature. 432:316–323. 2004. View Article : Google Scholar : PubMed/NCBI
27	Hayward DG, Clarke RB, Faragher AJ, Pillai MR, Hagan IM and Fry AM: The centrosomal kinase Nek2 displays elevated levels of protein expression in human breast cancer. Cancer Res. 64:7370–7376. 2004. View Article : Google Scholar : PubMed/NCBI
28	Hayward DG and Fry AM: Nek2 kinase in chromosome instability and cancer. Cancer Lett. 237:155–166. 2006. View Article : Google Scholar
29	Chen Y, Lu B, Yang Q, Fearns C, Yates JR III and Lee JD: Combined integrin phosphoproteomic analyses and small interfering RNA-based functional screening identify key regulators for cancer cell adhesion and migration. Cancer Res. 69:3713–3720. 2009. View Article : Google Scholar : PubMed/NCBI
30	Bonte D, Lindvall C, Liu H, Dykema K, Furge K and Weinreich M: Cdc7-Dbf4 kinase overexpression in multiple cancers and tumor cell lines is correlated with p53 inactivation. Neoplasia. 10:920–931. 2008. View Article : Google Scholar : PubMed/NCBI
31	Cho-Rok J, Yoo J, Jang YJ, Kim S, Chu IS, Yeom YI, Choi JY and Im DS: Adenovirus-mediated transfer of siRNA against PTTG1 inhibits liver cancer cell growth in vitro and in vivo. Hepatology. 43:1042–1052. 2006. View Article : Google Scholar : PubMed/NCBI
32	Ito T, Shimada Y, Kan T, David S, Cheng Y, Mori Y, Agarwal R, Paun B, Jin Z, Olaru A, et al: Pituitary tumor-transforming 1 increases cell motility and promotes lymph node metastasis in esophageal squamous cell carcinoma. Cancer Res. 68:3214–3224. 2008. View Article : Google Scholar : PubMed/NCBI
33	Malinowski DP: Multiple biomarkers in molecular oncology. I. Molecular diagnostics applications in cervical cancer detection. Expert Rev Mol Diagn. 7:117–131. 2007. View Article : Google Scholar : PubMed/NCBI
34	Liu JM, Pan F, Li L, Liu QR, Chen Y, Xiong XX, Cheng K, Yu SB, Shi Z, Yu AC and Chen XQ: Piperlongumine selectively kills glioblastoma multiforme cells via reactive oxygen species accumulation dependent JNK and p38 activation. Biochem Biophys Res Commun. 437:87–93. 2013. View Article : Google Scholar : PubMed/NCBI
35	Jarvius M, Fryknäs M, D'Arcy P, Sun C, Rickardson L, Gullbo J, Haglund C, Nygren P, Linder S and Larsson R: Piperlongumine induces inhibition of the ubiquitin-proteasome system in cancer cells. Biochem Biophys Res Commun. 431:117–123. 2013. View Article : Google Scholar : PubMed/NCBI
36	Ginzburg S, Golovine KV, Makhov PB, Uzzo RG, Kutikov A and Kolenko VM: Piperlongumine inhibits NF-κB activity and attenuates aggressive growth characteristics of prostate cancer cells. Prostate. 74:177–186. 2014. View Article : Google Scholar :