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Radiation Oncology
Published in: Radiation Oncology 1/2016

Open Access 01-12-2016 | Research

Transcriptomic analyses of the radiation response in head and neck squamous cell carcinoma subclones with different radiation sensitivity: time-course gene expression profiles and gene association networks

Authors: Agata Michna, Ulrike Schötz, Martin Selmansberger, Horst Zitzelsberger, Kirsten Lauber, Kristian Unger, Julia Hess

Published in: Radiation Oncology | Issue 1/2016

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Abstract

Background

Acquired and inherent radioresistance of tumor cells is related to tumor relapse and poor prognosis – not only in head and neck squamous cell carcinoma (HNSCC). The underlying molecular mechanisms are largely unknown. Therefore, systemic in-depth analyses are needed to identify key regulators of radioresistance. In the present study, subclones of the CAL-33 HNSCC cell line with different radiosensitivity were analyzed to identify signaling pathways related to the different phenotypes.

Methods

Subclones with altered radiosensitivity were generated by fractionated irradiation of the parental CAL-33 cells. Differences in radiosensitivity were confirmed in colony formation assays. Selected subclones were characterized at the genomic and transcriptomic level by SKY, array CGH, and mRNA-microarray analyses. Time-course gene expression analyses upon irradiation using a natural cubic spline regression model identified temporally differentially expressed genes. Moreover, early and late responding genes were identified. Gene association networks were reconstructed using partial correlation. The Reactome pathway database was employed to conduct pathway enrichment analyses.

Results

The characterization of two subclones with enhanced radiation resistance (RP) and enhanced radiosensitivity (SP) revealed distinct genomic and transcriptomic changes compared to the parental cells. Differentially expressed genes after irradiation shared by both subclones pointed to important pathways of the early and late radiation response, including senescence, apoptosis, DNA repair, Wnt, PI3K/AKT, and Rho GTPase signaling. The analysis of the most important nodes of the gene association networks revealed pathways specific to the radiation response in different phenotypes of radiosensitivity. Exemplarily, for the RP subclone the senescence-associated secretory phenotype (SASP) together with GPCR ligand binding were considered as crucial. Also, the expression of endogenous retrovirus ERV3-1in response to irradiation has been observed, and the related gene association networks have been identified.

Conclusions

Our study presents comprehensive gene expression data of CAL-33 subclones with different radiation sensitivity. The resulting networks and pathways associated with the resistant phenotype are of special interest and include the SASP. The radiation-associated expression of ERV3-1 also appears highly attractive for further studies of the molecular mechanisms underlying acquired radioresistance. The identified pathways may represent key players of radioresistance, which could serve as potential targets for molecularly designed, therapeutical intervention.
Appendix
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Literature
1.
2.
Network NCC. NCCN Clinical Practice Guidelines in Oncology: head and neck cancers. Version 2. 2013.
3.
Hashibe M, Brennan P, Chuang SC, Boccia S, Castellsague X, Chen C, Curado MP, Dal Maso L, Daudt AW, Fabianova E, et al. Interaction between tobacco and alcohol use and the risk of head and neck cancer: pooled analysis in the International Head and Neck Cancer Epidemiology Consortium. Cancer Epidemiol Biomarkers Prev. 2009;8(2):541–50.CrossRef
4.
Guha N, Boffetta P, Wünsch Filho V, Eluf Neto J, Shangina O, Zaridze D, Curado MP, Koifman S, Matos E, Menezes A, et al. Oral health and risk of squamous cell carcinoma of the head and neck and esophagus: results of two multicentric case–control studies. Am J Epidemiol. 2007;66(10):1159–73.CrossRef
5.
Pannone G, Santoro A, Papagerakis S, Lo Muzio L, De Rosa G, Bufo P. The role of human papillomavirus in the pathogenesis of head & neck squamous cell carcinoma: an overview. Infect Agents Cancer. 2011;6:4.CrossRefPubMedPubMedCentral
6.
Seiwert TY, Salama JK, Vokes EE. The chemoradiation paradigm in head and neck cancer. Nat Clin Pract Oncol. 2007;4(3):156–71.CrossRefPubMed
7.
Bar-Ad V, Palmer J, Yang H, Cognetti D, Curry J, Luginbuhl A, Tuluc M, Campling B, Axelrod R. Current management of locally advanced head and neck cancer: the combination of chemotherapy with locoregional treatments. Semin Oncol. 2014;41(6):798–806.CrossRefPubMed
8.
Weichselbaum RR, Beckett MA, Schwartz JL, Dritschilo A. Radioresistant tumor cells are present in head and neck carcinomas that recur after radiotherapy. Int J Radiat Oncol Biol Phys. 1988;15(3):575–9.CrossRefPubMed
9.
Perri F, Pacelli R, Della Vittoria Scarpati G, Cella L, Giuliano M, Caponigro F, Pepe S: Radioresistance in head and neck squamous cell carcinoma: biological bases and therapeutic implications. Head Neck. 2015;37(5):763–70.CrossRefPubMed
10.
Gioanni J, Fischel JL, Lambert JC, Demard F, Mazeau C, Zanghellini E, Ettore F, Formento P, Chauvel P, Lalanne CM, et al. Two new human tumor cell lines derived from squamous cell carcinomas of the tongue: Establishment, characterization and response to cytotoxic treatment. Eur J Cancer Clin Oncol. 1988;24(9):1445–55.CrossRefPubMed
11.
Ernst A, Anders H, Kapfhammer H, Orth M, Hennel R, Seidl K, Winssinger N, Belka C, Unkel S, Lauber K. HSP90 inhibition as a means of radiosensitizing resistant, aggressive soft tissue sarcomas. Cancer Lett. 2015;365(2):211–22.CrossRefPubMed
12.
13.
Kinzel L, Ernst A, Orth M, Albrecht V, Hennel R, Brix N, Frey B, Gaipl US, Zuchtriegel G, Reichel CA, et al. A novel HSP90 inhibitor with reduced hepatotoxicity synergizes with radiotherapy to induce apoptosis, abrogate clonogenic survival, and improve tumor control in models of colorectal cancer. Oncotarget. 2016. doi:10.​18632/​oncotarget.​9774.PubMed
14.
Hieber L, Huber R, Bauer V, Schäffner Q, Braselmann H, Thomas G, Bogdanova T, Zitzelsberger H. Chromosomal rearrangements in post-Chernobyl papillary thyroid carcinomas: evaluation by spectral karyotyping and automated interphase FISH. J Biomed Biotechnol. 2011;2011:693691.CrossRefPubMedPubMedCentral
15.
Neuvial P, Hupe P. MANOR: CGH Micro-Array NORmalization. R package version 1.42.0.
16.
Neuvial P, Hupe P, Brito I, Liva S, Manie E, Brennetot C, Radvanyi F, Aurias A, Barillot E. Spatial normalization of array-CGH data. BMC Bioinformatics. 2006;7(264):1–20.
17.
van de Wiel MA, Brosens R, Eilers PHC, Kumps C, Meijer GA, Menten B, Sistermans E, Speleman F, Timmerman ME, Ylstra B. Smoothing waves in array CGH tumor profiles. Bioinformatics. 2009;25(9):1099–104.CrossRefPubMed
18.
Seshan VE, Olshen A. DNAcopy: DNA copy number data analysis. R package version 1.44.0.
19.
Olshen AB, Venkatraman ES, Lucito R, Wigler M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics. 2004;5(4):557–72.CrossRefPubMed
20.
van de Wiel MA, Kim KI, Vosse SJ, van Wieringen WN, Wilting SM, Ylstra B. CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics. 2007;23(7):892–4.CrossRefPubMed
21.
van de Wiel MA, van Wieringen WN. CGHregions: dimension reduction for array CGH data with minimal information loss. Cancer Informatics. 2007;3:55–63.PubMedPubMedCentral
22.
R Core Team: R: A language and environment for statistical computing 2013.
23.
Smyth GK. Limma: linear models for microarray data. In: Bioinformatics and Computational Biology Solutions Using {R} and Bioconductor. New York: Springer; 2005. p. 397–420.CrossRef
24.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5(10):R80.CrossRefPubMedPubMedCentral
25.
Lopez-Romero P: Agi4x44PreProcess: PreProcessing of Agilent 4x44 array data. R package version 1.16.0.
26.
Li Q, Birkbak NJ, Gyorffy B, Szallasi Z, Eklund AC. Jetset: selecting the optimal microarray probe set to represent a gene. BMC Bioinformatics. 2011;12:474.CrossRefPubMedPubMedCentral
27.
Michna A. splineTimeR: Time-course differential gene expression data analysis using spline regression models followed by gene association network reconstruction. R package version 0995 2015.
28.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Stat Soc. 1995;57:289–300.
29.
Opgen-Rhein R, Strimmer K. Using regularized dynamic correlation to infer gene dependency networks from time-series microarray data. The 4th International Workshop on Computational Systems Biology, WCSB 2006.
30.
Opgen-Rhein R, Strimmer K. From correlation to causation networks: a simple approximate learning algorithm and its application to high-dimensional plant gene expression data. BMC Syst Biol. 2007;1:37.CrossRefPubMedPubMedCentral
31.
Koschützki D, Schreiber F. Centrality analysis methods for biological networks and their application to gene regulatory networks. Gene Regulation Syst Biol. 2008;2:193–201.
32.
Abbasi A, Hossain L. Hybrid Centrality Measures for Binary and Weighted Networks. In: Menezes R, Evsukoff A, González MC, editors. Complex Networks. Volume 424, edn. Berlin: Springer; 2013. p. 1–7.
33.
Matthews L, Gopinath G, Gillespie M, Caudy M, Croft D, de Bono B, Garapati P, Hemish J, Hermjakob H, Jassal B, et al. Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res. 2009;37(Database issue):D619–22.CrossRefPubMed
34.
35.
Wang J, Hu L, Gupta N, Shamseldin T, Ozawa T, Klem J, Cardell M, Deen DF. Induction and characterization of human glioma clones with different radiosensitivities. Neoplasia. 1999;1(2):138–44.CrossRefPubMedPubMedCentral
36.
Bentzen SM, Atasoy BM, Daley FM, Dische S, Richman PI, Saunders MI, Trott KR, Wilson GD. Epidermal growth factor receptor expression in pretreatment biopsies from head and neck squamous cell carcinoma as a predictive factor for a benefit from accelerated radiation therapy in a randomized controlled trial. J Clin Oncol. 2005;23(24):5560.CrossRefPubMed
37.
Kalyankrishna S, Grandis JR. Epidermal growth factor receptor biology in head and neck cancer. J Clin Oncol. 2006;24(17):2666–72.CrossRefPubMed
38.
Stadler ME, Patel MR, Couch ME, Hayes DN. Molecular biology of head and neck cancer: risks and pathways. Hematol Oncol Clin North Am. 2008;22(6):1099–124.CrossRefPubMedPubMedCentral
39.
Yang H, Cai YC, Cao Y, Song M, An X, Xia Y, Wei J, Jiang WQ, Shi YX. The prognostic value of Tiam1 protein expression in head and neck squamous cell carcinoma: a retrospective study. Chin J Cancer. 2015;34(12):614–21.PubMed
40.
Lui VW, Hedberg ML, Li H, Vangara BS, Pendleton K, Zeng Y, Lu Y, Zhang Q, Du Y, Gilbert BR, et al. Frequent mutation of the PI3K pathway in head and neck cancer defines predictive biomarkers. Cancer Discov. 2013;3(7):761–9.CrossRefPubMedPubMedCentral
41.
Szczepanski MJ, Czystowska M, Szajnik M, Harasymczuk M, Boyiadzis M, Kruk-Zagajewska A, Szyfter W, Zeromski J, Whiteside TL. Triggering of Toll-like receptor 4 expressed on human head and neck squamous cell carcinoma promotes tumor development and protects the tumor from immune attack. Cancer Res. 2009;69(7):3105–13.CrossRefPubMedPubMedCentral
42.
Overgaard J. Hypoxic modification of radiotherapy in squamous cell carcinoma of the head and neck - a systematic review and meta-analysis. Radiother Oncol. 2011;100(1):22–32.CrossRefPubMed
43.
Li JZ, Gao W, Chan JY, Ho WK, Wong TS. Hypoxia in head and neck squamous cell carcinoma. ISRN Otolaryngol. 2012;2012:708974.PubMedPubMedCentral
44.
Meijer TW, Kaanders JH, Span PN, Bussink J. Targeting hypoxia, HIF-1, and tumor glucose metabolism to improve radiotherapy efficacy. Clin Cancer Res. 2012;18(20):5585–94.CrossRefPubMed
45.
Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin. 2005;55(2):74–108.CrossRefPubMed
46.
Vokes EE, Weichselbaum RR, Lippman SM, Hong WK. Head and neck cancer. N Engl J Med. 1993;328(3):184–94.CrossRefPubMed
47.
Sharafinski ME, Ferris RL, Ferrone S, Grandis JR. Epidermal growth factor receptor targeted therapy of squamous cell carcinoma of the head and neck. Head Neck. 2010;32(10):1412–21.CrossRefPubMedPubMedCentral
48.
Ang KK, Berkey BA, Tu X, Zhang HZ, Katz R, Hammond EH, Fu KK, Milas L. Impact of epidermal growth factor receptor expression on survival and pattern of relapse in patients with advanced head and neck carcinoma. Cancer Res. 2002;62(24):7350–6.PubMed
49.
Nijkamp MM, Span PN, Bussink J, Kaanders JH. Interaction of EGFR with the tumour microenvironment: implications for radiation treatment. Radiother Oncol. 2013;108(1):17–23.CrossRefPubMed
50.
Ibrahim SO, Vasstrand EN, Liavaag PG, Johannessen AC, Lillehaug JR. Expression of c-erbB proto-oncogene family members in squamous cell carcinoma of the head and neck. Anticancer Res. 1997;17(6D):4539–46.PubMed
51.
Xia W, Lau YK, Zhang HZ, Liu AR, Li L, Kiyokawa N, Clayman GL, Katz RL, Hung MC. Strong correlation between c-erbB-2 overexpression and overall survival of patients with oral squamous cell carcinoma. Clin Cancer Res. 1997;3(1):3–9.PubMed
52.
Shintani S, Funayama T, Yoshihama Y, Alcalde RE, Matsumura T. Prognostic significance of ERBB3 overexpression in oral squamous cell carcinoma. Cancer Lett. 1995;95(1–2):79–83.CrossRefPubMed
53.
Di Maggio FM, Minafra L, Forte GI, Cammarata FP, Lio D, Messa C, Gilardi MC, Bravatà V. Portrait of inflammatory response to ionizing radiation treatment. J Inflamm (Lond). 2015;12:14.CrossRef
54.
Roses RE, Xu M, Koski GK, Czerniecki BJ. Radiation therapy and Toll-like receptor signaling: implications for the treatment of cancer. Oncogene. 2008;27(2):200–7.CrossRefPubMed
55.
Koschützki D. Network Centralities. In: Junker BH, Schreiber F, editors. Analysis of Biological Networks. Hoboken: Wiley; 2007. p. 65–84.
56.
Acosta JC, O'Loghlen A, Banito A, Guijarro MV, Augert A, Raguz S, Fumagalli M, Da Costa M, Brown C, Popov N, et al. Chemokine signaling via the CXCR2 receptor reinforces senescence. Cell. 2008;133(6):1006–18.CrossRefPubMed
57.
Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, Devon K, Dewar K, Doyle M, FitzHugh W, et al. Initial sequencing and analysis of the human genome. Nature. 2001;409(6822):860–921.CrossRefPubMed
58.
Löwer R, Löwer J, Kurth R. The viruses in all of us: characteristics and biological significance of human endogenous retrovirus sequences. Proc Natl Acad Sci U S A. 1996;93(11):5177–84.CrossRefPubMedPubMedCentral
59.
60.
Hughes JF, Coffin JM. Evidence for genomic rearrangements mediated by human endogenous retroviruses during primate evolution. Nat Genet. 2001;29(4):487–9.CrossRefPubMed
61.
Whitelaw E, Martin DI. Retrotransposons as epigenetic mediators of phenotypic variation in mammals. Nat Genet. 2001;27(4):361–5.CrossRefPubMed
62.
Stoye JP. Studies of endogenous retroviruses reveal a continuing evolutionary saga. Nat Rev Microbiol. 2012;10(6):395–406.PubMed
63.
Wang-Johanning F, Rycaj K, Plummer JB, Li M, Yin B, Frerich K, Garza JG, Shen J, Lin K, Yan P, et al. Immunotherapeutic potential of anti-human endogenous retrovirus-K envelope protein antibodies in targeting breast tumors. J Natl Cancer Inst. 2012;104(3):189–210.CrossRefPubMedPubMedCentral
64.
Wang-Johanning F, Liu J, Rycaj K, Huang M, Tsai K, Rosen DG, Chen DT, Lu DW, Barnhart KF, Johanning GL. Expression of multiple human endogenous retrovirus surface envelope proteins in ovarian cancer. Int J Cancer. 2007;120(1):81–90.CrossRefPubMed
65.
Wang-Johanning F, Frost AR, Jian B, Azerou R, Lu DW, Chen DT, Johanning GL. Detecting the expression of human endogenous retrovirus E envelope transcripts in human prostate adenocarcinoma. Cancer. 2003;98(1):187–97.CrossRefPubMed
66.
Li Z, Sheng T, Wan X, Liu T, Wu H, Dong J. Expression of HERV-K correlates with status of MEK-ERK and p16INK4A-CDK4 pathways in melanoma cells. Cancer Invest. 2010;28(10):1031–7.CrossRefPubMed
67.
Lee JR, Jung YD, Kim YH, Park SJ, Huh JW, Kim HS. Effects of HERV-R env knockdown in combination with ionizing radiation on apoptosis-related gene expression in A549 lung cancer cells. Biochem Physiol. 2016;5:1.
Metadata
Title
Transcriptomic analyses of the radiation response in head and neck squamous cell carcinoma subclones with different radiation sensitivity: time-course gene expression profiles and gene association networks
Authors
Agata Michna
Ulrike Schötz
Martin Selmansberger
Horst Zitzelsberger
Kirsten Lauber
Kristian Unger
Julia Hess
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Radiation Oncology / Issue 1/2016
Electronic ISSN: 1748-717X
DOI
https://doi.org/10.1186/s13014-016-0672-0

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