Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Journal of Ovarian Research
Published in: Journal of Ovarian Research 1/2018

Open Access 01-12-2018 | Research

Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis

Authors: Ke Zhang, Xiangjun Kong, Guangde Feng, Wei Xiang, Long Chen, Fang Yang, Chunyu Cao, Yifei Ding, Hang Chen, Mingxing Chu, Pingqing Wang, Baoyun Zhang

Published in: Journal of Ovarian Research | Issue 1/2018

Login to get access

Abstract

Background

Ovarian cancer is a leading cause of the death from gynecologic malignancies. Hypoxia is closely related to the malignant growth of cells. However, the molecular mechanism of hypoxia-regulated ovarian cancer cells remains unclear. Thus, this study was conducted to identify the key genes and pathways implicated in the regulation of hypoxia by bioinformatics analysis.

Methods

Using the datasets of GSE53012 downloaded from the Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were screened by comparing the RNA expression from cycling hypoxia group, chronic hypoxia group, and control group. Subsequently, cluster analysis was performed followed by the construction of the protein-protein interaction (PPI) network of the overlapping DEGs between the cycling hypoxia and chronic hypoxia using ClusterONE. In addition, gene ontology (GO) functional and pathway enrichment analyses of the DEGs in the most remarkable module were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) software. Ultimately, the signaling pathways associated with hypoxia were verified by RT-PCR, WB, and MTT assays.

Results

A total of 931 overlapping DEGs were identified. Nine hub genes and seven node genes were screened by analyzing the PPI and pathway integration networks, including ESR1, MMP2, ErbB2, MYC, VIM, CYBB, EDN1, SERPINE1, and PDK. Additionally, 11 key pathways closely associated with hypoxia were identified, including focal adhesion, ErbB signaling, and proteoglycans in cancer, among which the ErbB signaling pathway was verified by RT-PCR, WB, and MTT assays. Furthermore, functional enrichment analysis revealed that these genes were mainly involved in the proliferation of ovarian cancer cells, such as regulation of cell proliferation, cell adhesion, positive regulation of cell migration, focal adhesion, and extracellular matrix binding.

Conclusion

The results show that hypoxia can promote the proliferation of ovarian cancer cells by affecting the invasion and adhesion functions through the dysregulation of ErbB signaling, which may be governed by the HIF-1α-TGFA-EGFR-ErbB2-MYC axis. These findings will contribute to the identification of new targets for the diagnosis and treatment of ovarian cancer.
Appendix
Available only for authorised users
Literature
1.
2.
Shiner A, Burbos N. Ovarian cysts and ovarian cancer. Innovait. 2012;2:24–36.CrossRef
3.
Ai Z, Lu Y, Qiu S, Fan Z. Overcoming cisplatin resistance of ovarian cancer cells by targeting HIF-1-regulated cancer metabolism. Cancer Lett. 2016;373:36–44.CrossRefPubMedPubMedCentral
4.
Ebbesen P, Eckardt K-U, Ciampor F, Pettersen EO. Linking measured intercellular oxygen concentration to human cell functions. Acta Oncol. 2004;43:598–600.CrossRefPubMed
5.
6.
Cianfrocca R, Tocci P, Rosanò L, Caprara V, Sestito R, Castro VD, et al. Nuclear β-arrestin1 is a critical cofactor of hypoxia-inducible factor-1α signaling in endothelin-1-induced ovarian tumor progression. Oncotarget. 2016;7:17790–804.CrossRefPubMedPubMedCentral
7.
Cheng KW, Lahad JP, Kuo W, Lapuk A, Yamada K, Auersperg N, et al. The RAB25 small GTPase determines aggressiveness of ovarian and breast cancers. Nat Med. 2004;10:1251–6.CrossRefPubMed
8.
Natividad GR, Mohan SN, Fiona MG, Chalmers AJ, Jim C, Jane P. Hypoxia-inducible factor 1 alpha is required for the tumourigenic and aggressive phenotype associated with Rab25 expression in ovarian cancer. Oncotarget. 2016;7:22650–64.
9.
Lee CT, Mace T, Repasky EA. Hypoxia-driven immunosuppression: a new reason to use thermal therapy in the treatment of cancer? Int J Hyperth. 2010;26:232–46.CrossRef
10.
11.
12.
Francesco EMD, Lappano R, Santolla MF, Marsico S, Caruso A, Maggiolini M. HIF-1α/GPER signaling mediates the expression of VEGF induced by hypoxia in breast cancer associated fibroblasts (CAFs). Breast Cancer Res. 2013;15:R64.CrossRefPubMedPubMedCentral
13.
14.
Kizaka-Kondoh S, Inoue M, Harada H, Hiraoka M. Tumor hypoxia: a target for selective cancer therapy. Cancer Sci. 2003;94:1021–8.CrossRefPubMed
15.
Fu LJ, Wang B. RETRACTED ARTICLE: investigation of the hub genes and related mechanism in ovarian cancer via bioinformatics analysis. J Ovarian Res. 2013;6:218.CrossRef
16.
Mori H, Yao Y, Learman BS, Kurozumi K, Ishida J, Ramakrishnan SK, et al. Induction of WNT11 by hypoxia and hypoxia-inducible factor-1α regulates cell proliferation, migration and invasion. Sci Rep. 2016;6:21520.CrossRefPubMedPubMedCentral
17.
Xue J, Yang G, Ding H, Wang P, Wang C. Role of NSC319726 in ovarian cancer based on the bioinformatics analyses. Oncotargets Ther. 2015;8:3757.
18.
Olbryt M, Habryka A, Student S, Jarząb M, Tyszkiewicz T, Lisowska KM. Global gene expression profiling in three tumor cell lines subjected to experimental cycling and chronic hypoxia. PLoS One. 2014;9:e105104.CrossRefPubMedPubMedCentral
19.
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res. 2013;41:991–5.CrossRef
20.
Gautier L, Cope L, Bolstad BM, Irizarry RA. Affy--analysis of Affymetrix GeneChip data at the probe level. Bioinformatics. 2004;20:307–15.CrossRefPubMed
21.
Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4:249–64.CrossRefPubMed
22.
23.
Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 2013;41:D808.CrossRefPubMed
24.
Carter GW, Thorsson V, Galitski T. Integrated network modeling of molecular and genetic interactions. Sourcebook of Models for Biomedical Research. Humana Press; 2008;67–74.
25.
Maraziotis IA, Konstantina D, Anastasios B. An in silico method for detecting overlapping functional modules from composite biological networks. BMC Syst Biol. 2008;2:1–14.CrossRef
26.
Huang DW, Sherman BT, Tan Q, Collins JR, Alvord WG, Roayaei J, et al. The DAVID gene functional classification tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol. 2007;8:R183.CrossRefPubMedPubMedCentral
27.
28.
Michael MD, Kilgore MW, Morohashi K, Simpson ER. Ad4BP/SF-1 regulates cyclic AMP-induced transcription from the proximal promoter (PII) of the human aromatase P450 (CYP19) gene in the ovary. J Biol Chem. 1995;270:13561.CrossRefPubMed
29.
Masson N, Willam C, Maxwell PH, Pugh CW, Ratcliffe PJ. Independent function of two destruction domains in hypoxia-inducible factor-α chains activated by prolyl hydroxylation. EMBO J. 2001;20:5197.CrossRefPubMedPubMedCentral
30.
Hilscherova K, Jones PD, Gracia T, Newsted JL, Zhang X, Sanderson JT, et al. Assessment of the effects of chemicals on the expression of ten steroidogenic genes in the H295R cell line using real-time PCR. Toxicol Sci Off J Soc Toxicol. 2004;81:78.CrossRef
31.
Xiang W, Zhang B, Lv F, Ma Y, Chen H, Chen L, et al. The inhibitory effects of RFamide-related peptide 3 on luteinizing hormone release involves an estradiol-dependent manner in Prepubertal but not in adult female Mice1. Biol Reprod. 2015;93:30.CrossRefPubMed
32.
Jin B, Wang W, Du G, Huang GZ, Han LT, Tang ZY, et al. Identifying hub genes and dysregulated pathways in hepatocellular carcinoma. Eur Rev Med Pharmacol Sci. 2015;19:592.PubMed
33.
34.
Zhang Y, Lv J, Guo H, Wei X, Li W, Xu Z. Hypoxia-induced proliferation in mesenchymal stem cells and angiotensin II-mediated PI3K/AKT pathway. Cell Biochem Funct. 2015;33:51–8.CrossRefPubMed
35.
Wang L, Wu B, Zhang Y, Tian Z. Hypoxia promotes the proliferation of MC3T3-E1 cells via the hypoxia-inducible factor-1α signaling pathway. Mol Med Rep. 2015;12:5267–73.CrossRefPubMed
36.
Chen-Tian L, Jian-Xiu L, Bo Y, Rui L, Chao D, Song-Jian L. Notch signaling represses hypoxia-inducible factor-1α-induced activation of Wnt/β-catenin signaling in osteoblasts under cobalt-mimicked hypoxia: Mol. Med Rep. 2016;14:689–96.CrossRef
37.
Brader S, Eccles SA. Phosphoinositide 3-kinase signalling pathways in tumor progression, invasion and angiogenesis. Tumori. 2004;90:2–8.PubMed
38.
Lee SH, Lee YJ, Han HJ. Role of hypoxia-induced fibronectin-integrin β1 expression in embryonic stem cell proliferation and migration: involvement of PI3K/Akt and FAK. J Cell Physiol. 2011;226:484.CrossRefPubMed
39.
Yang SH, Hu MH, Lo WY, Sun YH, Wu CC, Yang KC. The influence of oxygen concentration on the extracellular matrix production of human nucleus pulposus cells during isolation-expansion process. J Biomed Mater Res A. 2017;105:1575.CrossRefPubMed
40.
Whelan KA, Schwab LP, Karakashev SV, Franchetti L, Johannes GJ, Seagroves TN, et al. The oncogene HER2/neu (ERBB2) requires the hypoxia-inducible factor HIF-1 for mammary tumor growth and Anoikis resistance. J Biol Chem. 2013;288:15865.CrossRefPubMedPubMedCentral
41.
Clarke-Pearson DL. Screening for ovarian cancer. BJOG Int J Obstet Gynaecol. 2000;107:170–7.CrossRef
42.
Laughner E, Taghavi P, Chiles K, Mahon PC, Semenza GL. HER2 (neu) signaling increases the rate of hypoxia-inducible factor 1 (HIF-1 ) synthesis: novel mechanism for HIF-1-mediated vascular endothelial growth factor expression. Mol Cell Biol. 2001;21:3995–4004.CrossRefPubMedPubMedCentral
43.
Karakashev SV, Reginato MJ. Hypoxia/HIF1α induces lapatinib resistance in ERBB2-positive breast cancer cells via regulation of DUSP2. Oncotarget. 2015;6:1967–80.CrossRefPubMedPubMedCentral
44.
Marano L, Roviello F. The distinctive nature of HER2-positive gastric cancers. Eur J Surg Oncol. 2015;41:271–3.CrossRefPubMed
45.
Mitri Z. The HER2 receptor in breast cancer: pathophysiology, clinical use, and new advances in therapy. Chemother Res Pract. 2012;2012:743193.PubMedPubMedCentral
46.
Turan G, Usta CS, Usta A, Kanter M, Tavli L, Karacan M, et al. The expression of HER-2/neu (c-erbB2), survivin and cycline D1 in serous ovarian neoplasms: their correlation with clinicopathological variables. J Mol Histol. 2014;45:679–87.CrossRefPubMed
47.
Akcay T, Yasar O, Kuseyri MA, Dincer Y, Aydinli K, Benian A, et al. Significance of serum c-erbB-2 oncoprotein, insulin-like growth factor-1 and vascular endothelial growth factor levels in ovarian cancer. Bratisl Lekárske Listy. 2016;117:156.
48.
Wang J, Li G, Wang Y, Tang S, Xin S, Feng X, et al. Suppression of tumor angiogenesis by metformin treatment via a mechanism linked to targeting of HER2/HIF-1α/VEGF secretion axis. Oncotarget. 2015;6:44579–92.PubMedPubMedCentral
49.
Galardi S, Savino M, Scagnoli F, Pellegatta S, Pisati F, Zambelli F, et al. Resetting cancer stem cell regulatory nodes upon MYC inhibition. EMBO Rep. 2016;17:1872–89.
50.
Reyesgonzález JM, Armaizpeña GN, Mangala LS, Valiyeva F, Ivan C, Pradeep S, et al. Targeting c-MYC in platinum-resistant ovarian cancer. Mol Cancer Ther. 2015;14:2260.CrossRef
51.
Chihiro T, Masashi K, Hironori I, Takumi A, Kenichi O. Expression of hypoxia-inducible factor-1α affects tumor proliferation and antiapoptosis in surgically resected lung cancer: Mol. Clin Oncol. 2016;5:295–300.
52.
Goss GD, Spaans JN. Epidermal growth factor receptor inhibition in the Management of Squamous Cell Carcinoma of the lung. Oncologist. 2016;21:205–13.CrossRefPubMedPubMedCentral
53.
54.
Wu TH, Hsiue EH, Lee JH, Lin CC, Yang JC. New data on clinical decisions in NSCLC patients with uncommon EGFR mutations. Expert Rev Respir Med. 2017;11:51–5.
55.
Du P, Xu B, Zhang D, Shao Y, Zheng X, Li X, et al. Hierarchical investigating the predictive value of p53, COX2, EGFR, nm23 in the post-operative patients with colorectal carcinoma. Oncotarget. 2017;8:954–66.
Metadata
Title
Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis
Authors
Ke Zhang
Xiangjun Kong
Guangde Feng
Wei Xiang
Long Chen
Fang Yang
Chunyu Cao
Yifei Ding
Hang Chen
Mingxing Chu
Pingqing Wang
Baoyun Zhang
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Journal of Ovarian Research / Issue 1/2018
Electronic ISSN: 1757-2215
DOI
https://doi.org/10.1186/s13048-018-0388-x

Other articles of this Issue 1/2018

Journal of Ovarian Research 1/2018 Go to the issue

Research

Adipokine RBP4 drives ovarian cancer cell migration

Review

DNA damage repair in ovarian cancer: unlocking the heterogeneity

Research

Protective role of Ficus deltoidea against BPA-induced impairments of the follicular development, estrous cycle, gonadotropin and sex steroid hormones level of prepubertal rats

Research

Diagnostic value of the gynecology imaging reporting and data system (GI-RADS) with the ovarian malignancy marker CA-125 in preoperative adnexal tumor assessment

Research

With low ovarian reserve, Highly Individualized Egg Retrieval (HIER) improves IVF results by avoiding premature luteinization

Research

Role of BMI1 in epithelial ovarian cancer: investigated via the CRISPR/Cas9 system and RNA sequencing