The current methods available for screening and detecting cervical squamous cell carcinoma (CSCC) have insufficient sensitivity and specificity. As a result, many patients suffered from erroneous and missed diagnosis. Because CSCC is usually asymptomatic at potentially curative stages, identification of biomarkers is an urgent need for the early detection of CSCC. Comparative proteomics based on two-dimensional differential in-gel electrophoresis (2D-DIGE) was employed to quantitatively analyze plasma proteins of healthy Uyghur women and with early stage cervical carcinoma. The 2D-DIGE image were analyzed statistically using DeCyder™ 2D software. The statistical analysis of proteomic data revealed that 43 protein spots showed significantly different expression (ratio > 1.5, P < 0.01). A further identification of these protein spots by MALDI-TOF-MS found out 16 different proteins. Bioinformatic analysis within the framework of Ingenuity Pathway Analysis (IPA@) showed that 10 plasma proteins as candidate biomarker were screened, mainly including lipid metabolism-related proteins (APOA4, APOA1, APOE), complement (EPPK1, CFHR1), metabolic enzymes (CP, F2, MASP2), glycoprotein (CLU), and immune function-related proteins (IGK@). Networks involved in lipid metabolism, molecular transport, and small molecule biochemistry were dysfunctional in CSCC. Acute phase response signaling and JAK/Stat signaling and IL-4 signaling, etc., were identified as the canonical pathways that are overrepresented in CSCC. Furthermore, the expression of three proteins (APOA1, APOE, CLU) were validated using ELISA in plasma of patients with different stage cervical lesion. With the combined proteomic and bioinformatic approach, this study was successful in identifying biomarker signatures for cervical cancer and might provide new insights into the mechanism of CSCC progression, potentially leading to the design of novel diagnostic and therapeutic strategies.
This is a preview of subscription content, access via your institution.
Liu KJ, Liu JW, LI XR, et al. Epidemiology study of risk factors on Uigur and Han cervical cancer in Xinjiang. J Xinjiang Med Univ. 2008;31:1335–8.
Suzuke L, Peng YH, Zhou K, et al. The analysis of pathogenetic tendency of cervical cancer in various ethnic women in Xinjiang. J Xinjiang Med Univ. 2006;29:569–71.
Zhang GQ, LIU KJ, Lai XJ, et al. Distribution of malignant tumor patients in hospital from 1989 to 2002 in the Affiliated Tumor Hospital of Xinjiang Medical University. J Xinjiang Med Univ. 2003;26:393–5.
Zhang SQ, Yakup K, Abliz G, et al. The study of the relationships between HPV multiple infection and cervical cancer of Uygur Women in Xinjiang. J Xinjiang Med Univ. 2009;32:525–8.
Lynge E, Rygaard C, Baillet MV, et al. Cervical cancer screening at crossroads. APMIS. 2014;122(8):667–73.
Kim HS. Correction: primary, secondary, and tertiary prevention of cervical cancer. J Gynecol Oncol. 2014;25(3):261.
Garbis SD, Townsend PA. Proteomics of human prostate cancer biospecimens: the global, systems-wide perspective for protein markers with potential clinical utility. Expert Rev Proteomics. 2013;10(4):337–54.
Nair M, Sandhu SS, Sharma AK. Prognostic and predictive biomarkers in cancer. Curr Cancer Drug Targets. 2014.
Baker ES, Liu T, Petyuk VA, et al. Mass spectrometry for translational proteomics: progress and clinical implications. Genome Med. 2012;4(8):63.
Lihong H, Linlin G, Yiping G, et al. Proteomics approaches for identification of tumor relevant protein targets in pulmonary squamous cell carcinoma by 2D-DIGE-MS. PLoS One. 2014;9(4):e95121.
Pressey JG, Pressey CS, Robinson G, et al. 2D-difference gel electrophoretic proteomic analysis of a cell culture model of alveolar rhabdomyosarcoma. J Proteome Res. 2011;10(2):624–36.
Righetti PG, Boschetti E, Lomas L, Citterio A. Protein Equalizer Technology: the quest for a “democratic proteome”. Proteomics. 2006;6:3980–92.
Sihlbom C, Kanmert I, Bahr HV, Davidsson P. Evaluation of the combination of bead technology with SELDI-TOF-MS and 2-D DIGE for detection of plasma proteins. J Proteome Res. 2008;7(9):4191–8.
Yadav AK, Bhardwaj G, Basak T. A systematic analysis of eluted fraction of plasma post immunoaffinity depletion: implications in biomarker discovery. PLoS ONE. 2011;6(9):e24442.
Hanash S. A call for a fresh new look at the plasma proteome. Proteomics Clin Appl. 2012;6(9–10):443–6.
Matsubara J, Honda K, Ono M, et al. Identification of adipophilin as a potential plasma biomarker for colorectal cancer using label-free quantitative mass spectrometry and protein microarray. Cancer Epidemiol Biomarkers Prev. 2011;20(10):2195–203.
Zhou C, Simpson KL, Lancashire LJ, et al. Statistical considerations of optimal study design for human plasma proteomics and biomarker discovery. J Proteome Res. 2012;11(4):2103–13.
Lin YW, Lai HC, Lin CY, et al. Plasma proteomic profiling for detecting and differentiating in situ and invasive carcinomas of the uterine cervix. Int J Gynecol Cancer. 2006;16(3):1216–24.
Xia T, Zheng ZG, Gao Y, et al. [Application of SELDI-TOF serum proteome profiling in cervical squamous cell carcinoma]. Ai Zheng. 2008;27(3):279–82.
Looi ML, Karsani SA, Rahman MA, et al. Plasma proteome analysis of cervical intraepithelial neoplasia and cervical squamous cell carcinoma. Biosci. 2009;34(6):917–25.
Dae HJ, Hyoung KK, Abd-EI BP, et al. Plasma proteomic analysis of patients with squamous cell carcinoma of the uterine cervix. Gynecol Oncol. 2008;19(3):173–80.
Paradkar PH, Joshi JV, Mertia PN, et al. Role of cytokines in genesis, progression and prognosis of cervical cancer. Asian Pac J Cancer Prev. 2014;15(9):3851–64.
Medina-Martinez I, Barrón V, Roman-Bassaure E, et al. Impact of gene dosage on gene expression, biological processes and survival in cervical cancer: a genome-wide follow-up study. PLoS One. 2014;9(5):e97842.
Zhao Y, Wang H, Gustafsson M, et al. Combined multivariate and pathway analyses show that allergen-induced gene expression changes in CD4+ T cells are reversed by glucocorticoids. PLoS One. 2012;7(6):e39016.
Lamba JK, Crews KR, Pounds SB, et al. Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes. Pharmacogenomics. 2011;12(3):327–39.
Wang HY, Tian YF, Chien CC, et al. Differential proteomic characterization between normal peritoneal fluid and diabetic peritoneal dialysate. Nephrol Dial Transplant. 2010;25(6):1955–63.
Bencharif K, Hoareau L, Murumalla RK, et al. Effect of apoA-I on cholesterol release and apoE secretion in human mature adipocytes. Lipids Health Dis. 2010;20(9):75.
Cine N, Baykal AT, Sunnetci D, et al. Identification of ApoA1, HPX and POTEE genes by omic analysis in breast cancer. Oncol Rep. 2014;32(3):1078–86.
His M, Zelek L, Deschasaux M, et al. Prospective associations between serum biomarkers of lipid metabolism and overall, breast and prostate cancer risk. Eur J Epidemiol. 2014;29(2):119–32.
Zamanian-Daryoush M, Lindner D, Tallant TC, et al. The cardioprotective protein apolipoprotein A1 promotes potent anti-tumorigenic effects. J Biol Chem. 2013;288(29):21237–52.
Van Hemelrijck M, Walldius G, Jungner I, et al. Low levels of apolipoprotein A-I and HDL are associated with risk of prostate cancer in the Swedish AMORIS study. Cancer Causes Control. 2011;22(7):1011–9.
Muntoni S, Atzori L, Mereu R, et al. Serum lipoproteins and cancer. Nutr Metab Cardiovasc Dis. 2009;19(3):218–25.
Moore RJ, Chamberlain RM, Khuri FR. Apolipoprotein E and the risk of breast cancer in African-American and non-Hispanic white women. Oncology. 2004;66(2):79–93.
Anand R, Prakash SS, Veeramanikandan R, et al. Association between apolipoprotein E genotype and cancer susceptibility: a meta-analysis. J Cancer Res Clin Oncol. 2014;140(7):1075–85.
Su WP, Chen YT, Lai WW, et al. Apolipoprotein E expression promotes lung adenocarcinoma proliferation and migration and as a potential survival marker in lung cancer. Lung Cancer. 2011;71(1):28–33.
Koltai T. Clusterin: a key player in cancer chemoresistance and its inhibition. Onco Targets Ther. 2014;20(7):447–56.
Lee S, Hong SW, Min BH, et al. Essential role of clusterin in pancreas regeneration. Dev Dyn. 2011;240(3):605–15.
Zoubeidi A, Ettinger S, Beraldi E, et al. Clusterin facilitates COMMD1 and I-kappaB degradation to enhance NF-kappaB activity in prostate cancer cells. Mol Cancer Res. 2010;8(1):119–30.
Conflicts of interest
This study was supported by Natural Science Foundation of China (81060171, 81260380 and 81360321). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Xia Guo and Yi Hao contributed equally to this work.
About this article
Cite this article
Guo, X., Hao, Y., Kamilijiang, M. et al. Potential predictive plasma biomarkers for cervical cancer by 2D-DIGE proteomics and Ingenuity Pathway Analysis. Tumor Biol. 36, 1711–1720 (2015). https://doi.org/10.1007/s13277-014-2772-5
- Plasma proteome
- Plasma biomarkers
- Ingenuity Pathway Analysis