POPDC3 is a potential biomarker for prognosis and radioresistance in patients with head and neck squamous cell carcinoma

He,Xu; Xu,Hongfa; Zhao,Wei; Zhan,Meixiao; Li,Yong; Liu,Hongyi; Tan,Li; Lu,Ligong

doi:10.3892/ol.2019.10888

POPDC3 is a potential biomarker for prognosis and radioresistance in patients with head and neck squamous cell carcinoma

Authors:
- Xu He
- Hongfa Xu
- Wei Zhao
- Meixiao Zhan
- Yong Li
- Hongyi Liu
- Li Tan
- Ligong Lu
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Affiliations: Department of Interventional Oncology, Guangdong Provincial Cardiovascular Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, P.R. China, Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People's Hospital Affiliated with Jinan University, Zhuhai, Guangdong 519000, P.R. China, Center of Hematology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510230, P.R. China
Published online on: September 19, 2019 https://doi.org/10.3892/ol.2019.10888
Pages: 5468-5480
Copyright: © He et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Radiotherapy is the primary means of treatment for patients with head and neck squamous cell carcinoma (HNSCC); however, radioresistance‑induced recurrence is the primary cause of HNSCC treatment failure. Therefore, identifying specific predictive biomarkers of the response to radiotherapy may improve prognosis. In the present study, to identify the potential candidate genes associated with radioresistance in patients with HNSCC, the microarray datasets GSE9716, GSE61772 and GSE20549 were downloaded from the Gene Expression Omnibus database. The original CEL files were preprocessed using the Affymetrix package and quantile normalization and background correction were conducted using the Core package in Bioconductor. The GSE9716 dataset, consisting of 18 irradiated and 16 non‑irradiated samples, was divided into two groups according to their exposure to irradiation: i) Non‑irradiation group, which included 8 radioresistant samples and 8 radiosensitive samples; and ii) post‑irradiation group, which included 9 radioresistant samples and 9 radiosensitive samples. The two groups were treated as separate datasets and screened. A total of 86 differentially expressed genes (DEGs) were identified in the non‑irradiation group and 405 DEGs in the post‑irradiation group. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis detected several significant functions associated with the DEGs. In the co‑expression analysis, 76 hub genes in the light green module and 917 hub genes with a high connectivity were selected for further analysis. Finally, overlapping the DEGs and hub genes from the two groups yielded a map of 13 shared differentially expressed genes. The 13 genes showed significantly different expression in radioresistant samples compared with the radiosensitive samples before and after irradiation. Out of these genes, popeye domain‑containing protein 3 (POPDC3) was highly expressed in the post‑irradiation group compared with the non‑irradiation group. In survival analysis, high POPDC3 expression correlated with poor a prognosis for patients with HNSCC. The independent prognostic factors were identified using univariate and multivariate Cox analyses based on The Cancer Genome Atlas database. These were incorporated into a nomogram to predict 3‑ and 5‑year overall survival. Receiver operating characteristic curves were used to estimate the accuracy of the nomogram. Together these studies suggest that POPDC3 may serve as a potential predictive biomarker for prognosis and radioresistance of patients with HNSCC as well as clinical diagnosis and treatment of patients.

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1	Siegel RL, Miller KD and Jemal A: Cancer statistics, 2018. CA Cancer J Clin. 68:7–30. 2018. View Article : Google Scholar : PubMed/NCBI
2	Agostini LP, Stur E, Garcia FM, Ventorim DP, Dos Reis RS, Dettogni RS, Dos Santos EVW, Peterle GT, Maia LL, Mendes SO, et al: ATM, BCL2, and TGFβ gene polymorphisms as radiotherapy outcome biomarkers in head and neck squamous cell carcinoma patients. Genet Test Mol Biomarkers. 21:727–735. 2017. View Article : Google Scholar : PubMed/NCBI
3	Edgar R, Domrachev M and Lash AE: Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30:207–210. 2002. View Article : Google Scholar : PubMed/NCBI
4	Cheng J, Lu X, Wang J, Zhang H, Duan P and Li C: Interactome analysis of gene expression profiles of cervical cancer reveals dysregulated mitotic gene clusters. Am J Transl Res. 9:3048–3059. 2017.PubMed/NCBI
5	Zhu L, Shu Z and Sun X: Bioinformatic analysis of four miRNAs relevant to metastasis-regulated processes in endometrial carcinoma. Cancer Manag Res. 10:2337–2346. 2018. View Article : Google Scholar : PubMed/NCBI
6	Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC and Lempicki RA: DAVID: Database for annotation, visualization, and integrated discovery. Genome Biol. 4:P32003. View Article : Google Scholar : PubMed/NCBI
7	Yu G, Wang LG, Han Y and He QY: clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 16:284–287. 2012. View Article : Google Scholar : PubMed/NCBI
8	Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, Sabedot TS, Malta TM, Pagnotta SM, Castiglioni I, et al: TCGAbiolinks: An R/Bioconductor package for integrative analysis of TCGA data. Nucleic Acids Res. 44:e712016. View Article : Google Scholar : PubMed/NCBI
9	Langfelder P and Horvath S: WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics. 9:5592008. View Article : Google Scholar : PubMed/NCBI
10	Khodarev NN, Minn AJ, Efimova EV, Darga TE, Labay E, Beckett M, Mauceri HJ, Roizman B and Weichselbaum RR: Signal transducer and activator of transcription 1 regulates both cytotoxic and prosurvival functions in tumor cells. Cancer Res. 67:9214–9220. 2007. View Article : Google Scholar : PubMed/NCBI
11	Xiong W, Zhao J, Yu H, Li X, Sun S, Li Y, Xia Q, Zhang C, He Q, Gao X, et al: Elevated expression of AKR1C3 increases resistance of cancer cells to ionizing radiation via modulation of oxidative stress. PLoS One. 9:e1119112014. View Article : Google Scholar : PubMed/NCBI
12	Gautier L, Cope L, Bolstad BM and Irizarry RA: Affy-analysis of Affymetrix GeneChip data at the probe level. Bioinformatics. 20:307–315. 2004. View Article : Google Scholar : PubMed/NCBI
13	Bolstad BM, Irizarry RA, Astrand M and Speed TP: A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 19:185–193. 2003. View Article : Google Scholar : PubMed/NCBI
14	Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W and Smyth GK: limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43:e472015. View Article : Google Scholar : PubMed/NCBI
15	Horvath S and Dong J: Geometric interpretation of gene coexpression network analysis. PLoS Comput Biol. 4:e10001172008. View Article : Google Scholar : PubMed/NCBI
16	Albert R: Scale-free networks in cell biology. J Cell Sci. 118:4947–4957. 2005. View Article : Google Scholar : PubMed/NCBI
17	Seo CH, Kim JR, Kim MS and Cho KH: Hub genes with positive feedbacks function as master switches in developmental gene regulatory networks. Bioinformatics. 25:1898–1904. 2009. View Article : Google Scholar : PubMed/NCBI
18	Schmitz S, Ang KK, Vermorken J, Haddad R, Suarez C, Wolf GT, Hamoir M and Machiels JP: Targeted therapies for squamous cell carcinoma of the head and neck: Current knowledge and future directions. Cancer Treat Rev. 40:390–404. 2014. View Article : Google Scholar : PubMed/NCBI
19	Zibelman M and Mehra R: Overview of current treatment options and investigational targeted therapies for locally advanced squamous cell carcinoma of the head and neck. Am J Clin Oncol. 39:396–406. 2016. View Article : Google Scholar : PubMed/NCBI
20	Corvò R: Evidence-based radiation oncology in head and neck squamous cell carcinoma. Radiother Oncol. 85:156–170. 2007. View Article : Google Scholar : PubMed/NCBI
21	Brand T and Schindler R: New kids on the block: The Popeye domain containing (POPDC) protein family acting as a novel class of cAMP effector proteins in striated muscle. Cell Signal. 40:156–165. 2017. View Article : Google Scholar : PubMed/NCBI
22	Amunjela JN and Tucker SJ: POPDC proteins as potential novel therapeutic targets in cancer. Drug Discov Today. 21:1920–1927. 2016. View Article : Google Scholar : PubMed/NCBI
23	Andrée B, Hillemann T, Kessler-Icekson G, Schmitt-John T, Jockusch H, Arnold HH and Brand T: Isolation and characterization of the novel popeye gene family expressed in skeletal muscle and heart. Dev Biol. 223:371–382. 2000. View Article : Google Scholar : PubMed/NCBI
24	Plattner F, Hayashi K, Hernández A, Benavides DR, Tassin TC, Tan C, Day J, Fina MW, Yuen EY, Yan Z, et al: The role of ventral striatal cAMP signaling in stress-induced behaviors. Nat Neurosci. 18:1094–1100. 2015. View Article : Google Scholar : PubMed/NCBI
25	Kumar N, Prasad P, Jash E, Jayasundar S, Singh I, Alam N, Murmu N, Somashekhar SP, Goldman A and Sehrawat S: cAMP regulated EPAC1 supports microvascular density, angiogenic and metastatic properties in a model of triple negative breast cancer. Carcinogenesis. 39:1245–1253. 2018. View Article : Google Scholar : PubMed/NCBI
26	Williams CS, Zhang B, Smith JJ, Jayagopal A, Barrett CW, Pino C, Russ P, Presley SH, Peng D, Rosenblatt DO, et al: BVES regulates EMT in human corneal and colon cancer cells and is silenced via promoter methylation in human colorectal carcinoma. J Clin Invest. 121:4056–4069. 2011. View Article : Google Scholar : PubMed/NCBI
27	Amunjela JN and Tucker SJ: POPDC1 is suppressed in human breast cancer tissues and is negatively regulated by EGFR in breast cancer cell lines. Cancer Lett. 406:81–92. 2017. View Article : Google Scholar : PubMed/NCBI
28	Kim M, Jang HR, Haam K, Kang TW, Kim JH, Kim SY, Noh SM, Song KS, Cho JS, Jeong HY, et al: Frequent silencing of popeye domain-containing genes, BVES and POPDC3, is associated with promoter hypermethylation in gastric cancer. Carcinogenesis. 31:1685–1693. 2010. View Article : Google Scholar : PubMed/NCBI
29	Wang X, Gao P, Long M, Lin F, Wei JX, Ren JH, Yan L, He T, Han Y and Zhang HZ: Essential role of cell cycle regulatory genes p21 and p27 expression in inhibition of breast cancer cells by arsenic trioxide. Med Oncol. 28:1225–1254. 2011. View Article : Google Scholar : PubMed/NCBI
30	Spitzner M, Emons G, Kramer F, Gaedcke J, Rave-Fränk M, Scharf JG, Burfeind P, Becker H, Beissbarth T, Ghadimi BM, et al: A gene expression signature for chemoradiosensitivity of colorectal cancer cells. Int J Radiat Oncol Biol Phys. 78:1184–1192. 2010. View Article : Google Scholar : PubMed/NCBI
31	Luo D, Lu ML, Zhao GF, Huang H, Zheng MY, Chang J, Lv L and Luo JB: Reduced Popdc3 expression correlates with high risk and poor survival in patients with gastric cancer. World J Gastroenterol. 18:2423–2429. 2012. View Article : Google Scholar : PubMed/NCBI