Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-28T00:19:52.091Z Has data issue: false hasContentIssue false

A review of radiation genomics: integrating patient radiation response with genomics for personalised and targeted radiation therapy

Published online by Cambridge University Press:  26 October 2018

Lu Xu
Affiliation:
Department of Medical Sciences (IMS and Medical Biophysics), Western University, London, Ontario, Canada Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, Ontario, Canada
Beverley Osei
Affiliation:
Department of Health Sciences, McMaster University, Hamilton, Ontario, Canada Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, Ontario, Canada
Ernest Osei*
Affiliation:
Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, Ontario, Canada Department of Physics and Astronomy, University of Waterloo, Waterloo, Ontario, Canada Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, Ontario,Canada Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada
*
Author for correspondence: Ernest Osei, Grand River Regional Cancer Centre, 835 King Street West, Kitchener, Ontario N2G1G3, Canada. Tel: 519 749 4300. E-mail: [email protected]

Abstract

Background

The success of radiation therapy for cancer patients is dependent on the ability to deliver a total tumouricidal radiation dose capable of eradicating all cancer cells within the clinical target volume, however, the radiation dose tolerance of the surrounding healthy tissues becomes the main dose-limiting factor. The normal tissue adverse effects following radiotherapy are common and significantly impact the quality of life of patients. The likelihood of developing these adverse effects following radiotherapy cannot be predicted based only on the radiation treatment parameters. However, there is evidence to suggest that some common genetic variants are associated with radiotherapy response and the risk of developing adverse effects. Radiation genomics is a field that has evolved in recent years investigating the association between patient genomic data and the response to radiation therapy. This field aims to identify genetic markers that are linked to individual radiosensitivity with the potential to predict the risk of developing adverse effects due to radiotherapy using patient genomic information. It also aims to determine the relative radioresponse of patients using their genetic information for the potential prediction of patient radiation treatment response.

Methods and materials

This paper reports on a review of recent studies in the field of radiation genomics investigating the association between genomic data and patients response to radiation therapy, including the investigation of the role of genetic variants on an individual’s predisposition to enhanced radiotherapy radiosensitivity or radioresponse.

Conclusion

The potential for early prediction of treatment response and patient outcome is critical in cancer patients to make decisions regarding continuation, escalation, discontinuation, and/or change in treatment options to maximise patient survival while minimising adverse effects and maintaining patients’ quality of life.

Type
Literature Review
Copyright
© Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Cite this article: Xu L, Osei B, Osei E. (2019) A review of radiation genomics: integrating patient radiation response with genomics for personalised and targeted radiation therapy. Journal of Radiotherapy in Practice18: 198–209. doi: 10.1017/S1460396918000547

References

1. Guo, Z, Shu, Y, Zhou, H, Zhang, W, Wang, H. Radiogenomics helps to achieve personalized therapy by evaluating patient responses to radiation treatment. Carcinogenesis 2015; 36 (3): 307317.Google Scholar
2. Kerns, S L, West, C M, Andreassen, C N et al. Radiogenomics: the search for genetic predictors of radiotherapy response. Future Oncol 2014; 10 (15): 23912406.Google Scholar
3. Naqa, I E, Kerns, S L, Coates, J et al. Radiogenomics and radiotherapy response modeling. Phys Med Biol 2017; 62: R179R206.Google Scholar
4. West, C M, Barnett, G C. Genetics and genomics of radiotherapy toxicity: towards prediction. Genome Med 2001; 3 (8): 5267.Google Scholar
5. Kerns, S L, Ruysscher, D, Andreassen, C N et al. STROGAR – strengthening the reporting of genetic association studies in radiogenomics. Radiother Oncol 2014; 110 (1): 182188.Google Scholar
6. Fan, C, Tang, Y, Wang, J et al. Role of long noncoding RNAs in glucose metabolism in cancer. Mol Cancer 2017; 16: 130141.Google Scholar
7. Rattay, T, Talbot, C J. Finding the genetic determinants of adverse reactions to radiotherapy. Clin Oncol 2014; 26: 301308.Google Scholar
8. Kerns, S L, Kundu, S, Oh, J H et al. The prediction of radiotherapy toxicity using single nucleotide polymorphism (SNP)-based models: a step towards prevention. Semin Radiat Oncol 2015; 25 (4): 281291.Google Scholar
9. Bai, H X, Lee, A M, Yang, L et al. Imaging genomics in cancer research: limitations and promises. Br J Radiol 2016; 89 (1061): 20151030.Google Scholar
10. Wu, J, Tha, K K, Xing, L, Li, R. Radiomics and radiogenomics for precision radiotherapy. J Radiat Res 2018; 59 (suppl_1): i2531.Google Scholar
11. Incoronato, M, Aiello, M, Infante, T et al. Radiogenomic analysis of oncological data: a technical survey. Int J Mol Sci 2017; 18 (4): 805833.Google Scholar
12. Zinn, P O, Mahmood, Z, Elbanan, M G, Colen, R R. Imaging genomics in gliomas. Canc J 2015; 21 (3): 225234.Google Scholar
13. ElBanan, M G, Amer, A M, Zinn, P O, Colen, R R. Imaging genomics of Glioblastoma: state of the art bridge between genomics and neuroradiology. Neuroimag Clin 2015; 25 (1): 141153.Google Scholar
14. Mazurowski, M A. Radiogenomics: what it is and why it is important. J Am Coll Radiol 2015; 12 (8): 862866.10.1016/j.jacr.2015.04.019Google Scholar
15. Barnett, G C, Coles, C E, Elliot, R M et al. Independent validation of genes and polymorphisms reported to be associated with radiation toxicity: a prospective analysis study. Lancet Oncol 2012; 13 (1): 6577.Google Scholar
16. Rosenstein, B S, West, C M, Bentzen, S M, Alsner, J, Andreassen, C N, Azria, D. Radiogenomics: radiobiology enters the era of big data and team science. Int J Radiat Oncol Biol Phys 2014; 89 (4): 709713.Google Scholar
17. Lambin, P, Leikennaar, R T H, Deist, T M, Peerlings, J, de Jong, E E C, van Timmeren, J. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 2017; 14 (12): 749762.Google Scholar
18. Pawlik, T M, Keyomarsi, K. Role of cell cycle in mediating sensitivity to radiotherapy. Int J Radiat Oncol Biol Phys 2004; 59 (4): 928942.Google Scholar
19. Suit, H. The gray lecture 2001: coming technical advances in radiation oncology. Int J Radiat Oncol Biol Phys 2002; 15 (4): 798809.Google Scholar
20. Rosenstein, B S. Radiogenomics: identification of genomic predictors for radiation toxicity. Sem Radiat Oncol 2017; 27 (4): 300309.Google Scholar
21. Brenner, H. Long-term survival rates of cancer patients achieved by the end of the 20th century: a period analysis. Lancet 2002; 360 (9340): 11311135.Google Scholar
22. Emami, B, Lyman, J, Brown, A et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991; 21: 109122.Google Scholar
23. Azria, D, Lapierre, A, Gourgou, S et al. Data-based radiation oncology: design of clinical trials in the toxicity biomarkers era. Front Oncol 2017; 7: 8394.Google Scholar
24. Group, B D W. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001; 69 (3): 8995.Google Scholar
25. Andreassen, C N, Alsner, J, Overgaard, J. Does variability in normal tissue reactions after radiotherapy have a genetic basis – where and how to look for it? Radiother Oncol 2002; 64 (2): 131140.Google Scholar
26. Andreassen, C N, Schack, L M, Laursen, L V, Alsner, J. Radiogenomics–current status, challenges and future directions. Canc Lett 2016; 382 (1): 127136.Google Scholar
27. Vaisnav, M, Xing, C, Ku, H C et al. Genome-wide association analysis of radiation resistance in Drosophila melanogaster . PLoS ONE 2014; 9 (8): e104858.Google Scholar
28. Barnett, G C, Thompson, D, Fachal, L et al. A genome wide association study (GWAS) providing evidence of an association between common genetic variants and late radiotherapy toxicity. Radiother Oncol 2014; 111: 178185.Google Scholar
29. Scott, D. Chromosomal radiosensitivity and low penetrance predisposition to cancer. Cytogenet Genome Res 2004; 104: 365370.Google Scholar
30. Barnett, G C, Kerns, S L, Noble, D J, Dunning, A M, West, C M, Brunet, N G. Incorporating genetic biomarkers into predictive models of normal tissue toxicity. Clin Oncol 2015; 27 (10): 579587.Google Scholar
31. Kelsey, C R, Jackson, I L, Langdon, S et al. Analysis of single nucleotide polymorphisms and radiation sensitivity of the lung assessed with an objective radiologic endpoint. Clin Lung Cancer 2013; 14 (3): 267274.Google Scholar
32. Kerns, S L, Ostrer, H, Rosenstein, B S. Radiogenomics: using genetics to identify cancer patients at risk for development of adverse effects following radiotherapy. Cancer Discov 2014; 4 (2): 155165.Google Scholar
33. Andreassen, C N. The future has begun in radiogenomics!. Radiother Oncol 2014; 111 (2): 165167.Google Scholar
34. Talbot, C J, Tanteles, G A, Barnett, G C et al. A replicated association between polymorphisms near TNFalpha and risk for adverse reactions to radiotherapy. Br J Canc 2012; 107 (4): 748753.Google Scholar
35. Seibold, P, Behrens, S, Schmezer, P et al. XRCC1 polymorphism associated with late toxicity after radiation therapy in breast cancer patients. Int J Radiat Oncol Biol Phys 2015; 92 (5): 10841092.Google Scholar
36. Pratesi, N, Mangoni, M, Mancini, I et al. Association between single nucleotide polymorphisms in XRCC1 and RAD51 genes and clinical radiosensitivity in head and neck cancer. Radiother Oncol 2011; 99: 356361.Google Scholar
37. Nogueira, A, Catarino, R, Faustino, I et al. Role of RAD51 G172T polymorphism in the clinical outcome of cervical cancer patients under concomitant chemoradiotherapy. Gene 2012; 504: 279283.Google Scholar
38. Venkatesh, G H, Manjunath, V B, Mumbrekar, K D et al. Polymorphisms in radio-responsive genes and its association with acute toxicity among head and neck cancer patients. PLoS One 2014; 9 (3): e89079.Google Scholar
39. Yin, M, Liao, Z X, Huang, Y J et al. Polymorphisms of homologous recombination genes and clinical outcomes of non-small lung cancer patients treated with definitive radiotherapy. PLoS One 2011; 6: e20055.Google Scholar
40. Yang, M, Zhang, L, Bi, N et al. Association of P53 and ATM polymorphisms with risk of radiation-induced pneumonitis in lung cancer patients treated with radiotherapy. Int J Radiat Oncol Biol Phys 2011; 79 (5): 14021407.Google Scholar
41. Chang-Claude, J, Ambrosone, C B, Lilla, C et al. Genetic polymorphisms in DNA repair and damage response genes and late normal tissue complications of radiotherapy for breast cancer. Br J Canc 2009; 100: 16801686.Google Scholar
42. Xie, X, Wang, H, Jin, H et al. Expression of pAkt affects p53 codon 72 polymorphism-based prediction of response to radiotherapy in nasopharyngeal carcinoma. Radiat Oncol 2013; 8: 117127.Google Scholar
43. Cintra, H S, Pinezi, J C D, Machado, G D P et al. Investigation of genetic polymorphisms related to outcome of radiotherapy for prostate cancer patients. Dis Markers 2013; 35 (6): 701710.Google Scholar
44. Mangoni, M, Bisanzi, S, Carozzi, F et al. Association between genetic polymorphisms in the XRCC1, XRCC3, XPD, GSTM1, GSTT1, MSH2, MLH1, MSH3, and MGMT genes and radiosensitivity in breast cancer patients. Int J Radiat Oncol Biol Phys 2011; 81 (1): 5258.Google Scholar
45. Zyla, J, Finnon, P, Bulman, R, Bouffler, S, Badie, C, Polanska, J. Seeking genetic signature of radiosensitivity – a novel method for data analysis in case of small sample sizes. Theoret Biol Med Model 2014; 11 (Suppl 1): S2S18.Google Scholar
46. Martin, L M, Marples, B, Davies, A M et al. DNA mismatch repair protein MSH2 dictates cellular survival in response to low dose radiation in endometrial carcinoma cells. Canc Lett 2013; 335: 1925.Google Scholar
47. Bernier, J, Poortmans, P. Clinical relevance of normal and tumour cell radiosensitivity in BRCA1/BRCA2 mutation carriers: a review. Breast 2015; 24 (2): 100106.Google Scholar
48. Park, H, Choi, D H, Noh, J M et al. Acute skin toxicity in Korean breast cancer patients carrying BRCA mutations. Int J Radiat Biol 2014; 90 (1): 9094.Google Scholar
49. Baert, A, Depuydt, J, Van Maerken, T et al. Analysis of chromosomal radiosensitivity of healthy BRCA2 mutation carriers and non-carriers in BRCA families with the G2 micronucleus assay. Oncol Rep 2017; 37 (3): 13791386.Google Scholar
50. Ernestos, B, Nikolaos, P, Koulis, G et al. Increased chromosomal radiosensitivity in women carrying BRCA1/BRCA2 mutations assessed with the G2 assay. Int J Radiat Oncol Biol Phys 2010; 76 (4): 11991205.Google Scholar
51. Pierce, L J, Strawderman, M, Narod, S A et al. Effect of radiotherapy after breast-conserving treatment in women with breast cancer and germline BRCA1/2 mutations. J Clin Oncol 2000; 18 (19): 33603369.Google Scholar
52. Moding, E J, Lee, C L, Castle, K D et al. Atm deletion with dual recombinase technology preferentially radiosensitizes tumor endothelium. J Clin Investig 2014; 124 (8): 33253338.Google Scholar
53. Zhang, L, Yang, M, Bi, N et al. ATM polymorphisms are associated with risk of radiation-induced pneumonitis. Int J Radiat Oncol Biol Phys 2010; 77 (5): 13601368.Google Scholar
54. Raabe, A, Derda, K, Reuther, S et al. Association of single nucleotide polymorphisms in the genes ATM, GSTP1, SOD2, TGFB1, XPD and XRCC1 with risk of severe erythema after breast conserving radiotherapy. Radiat Oncol 2012; 7 (1): 65–54.Google Scholar
55. Cintra, H S, Pinezi, J C, Machado, G D et al. Investigation of genetic polymorphisms related to the outcome of radiotherapy for prostate cancer patients. Dis Markers 2013; 35 (6): 701710.Google Scholar
56. Thacker, J, Zdzienicka, M Z. The mammalian XRCC genes: their roles in DNA repair and genetic stability. DNA Rep 2003; 2 (6): 655672.Google Scholar
57. Yin, M, Liao, Z, Liu, Z et al. Functional polymorphisms of base excision repair genes XRCC1 and APEX1 predict risk of radiation pneumonitis in patients with non–small cell lung cancer treated with definitive radiation therapy. Int J Radiat Oncol Biol Phys 2011; 81 (3): e67e73.Google Scholar
58. Burri, R J, Stock, R G, Cesaretti, J A et al. Association of single nucleotide polymorphisms in SOD2, XRCC1 and XRCC3 with susceptibility for the development of adverse effects resulting from radiotherapy for prostate cancer. Radiat Res 2008; 170 (1): 4959.Google Scholar
59. Cheuk, I W, Yip, S P, Kwong, D L, Wu, V W. Association of XRCC1 and XRCC3 gene haplotypes with the development of radiation‑induced fibrosis in patients with nasopharyngeal carcinoma. Mol Clin Oncol 2014; 2 (4): 553558.Google Scholar
60. Andreassen, C N, Alsner, J. Genetic variants and normal tissue toxicity after radiotherapy: a systematic review. Radiother Oncol 2009; 92: 299309.Google Scholar
61. Andreassen, C N. Searching for genetic determinants of normal tissue radiosensitivity – are we on the right track? Radiother Oncol 2010; 97 (1): 18.Google Scholar
62. Andreassen, C N, Schack, L M, Laursen, L V, Alsner, J. Radiogenomics-current status, challenges, and future directions. Canc Lett 2016; 382 (1): 127136.Google Scholar
63. Sachidanandam, R, Weissman, D, Schmidt, S C et al. A map of human genome sequence variation containing 1·42 million single nucleotide polymorphisms. Nature 2001; 409 (6822): 928933.Google Scholar
64. Kerns, S L, Kundu, S, Oh, J H et al. The prediction of radiotherapy toxicity using single nucleotide polymorphism-based models: a step toward prevention. Semin Radiat Oncol 2015; 25: 281291.Google Scholar
65. Herskind, C, Talbot, C J, Kerns, S L, Veldwijk, M R, Rosenstein, B S, West, C M. Radiogenomics: a systems biology approach to understanding genetic risk factors for radiotherapy toxicity? Canc Lett 2016; 382 (1): 95109.Google Scholar
66. West, C, Rosenstein, B S. Establishment of a radiogenomics consortium. Radiother Oncol 2010; 94: 117124.Google Scholar
67. Barnett, G C, West, C M, Dunning, A M et al. Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype. Nat Rev Canc 2009; 9: 134142.Google Scholar
68. Edwards, S L, Beesley, J, French, J D, Dunning, A M. Beyond GWASs: illuminating the dark road from association to function. Am J Hum Genet 2013; 93: 779797.Google Scholar
69. Zhang, F, Gu, W, Hurles, M E, Lupski, J R. Copy number variation in human health, disease, and evolution. Ann Rev Genom Human Genet 2009; 10: 451481.Google Scholar
70. Stranger, B E, Forrest, M S, Dunning, M et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science 2007; 315: 848853.Google Scholar
71. Eustace, A, Mani, N, Span, P N et al. A 26-gene hypoxia signature predicts benefit from hypoxia-modifying therapy in laryngeal cancer but not bladder cancer. Clin . Canc Res 2013; 19: 48794888.Google Scholar
72. Yang, L, Taylor, J, Eustace, A et al. A Gene signature for selecting benefit from hypoxia modification of radiotherapy for high risk bladder cancer patients. Clin Canc Res 2017; 23 (16): 47614768.Google Scholar
73. Yard, B D, Adams, D J, Chie, E K et al. A genetic basis for the variation in the vulnerability of cancer to DNA damage. Nat Commun 2016; 7: 11428.Google Scholar
74. Dickey, J S, Zemp, F J, Martin, O A, Kovalchuk, O. The role of miRNA in the direct and indirect effects of ionizing radiation. Radiat Environ Biophys 2011; 50: 491499.Google Scholar
75. Kovalchuk, O, Zemp, F J, Filkowski, J N et al. microRNAome changes in bystander three-dimensional human tissue models suggest priming of apoptotic pathways. Carcinogenesis 2010; 31: 18821888.Google Scholar
76. Dickey, J S, Zemp, F J, Altamirano, A, Sedelnikova, O A, Bonner, W M, Kovalchuk, O. H2AX phosphorylation in response to DNA double-strand break formation during bystander signalling: effect of microRNA knockdown. Radiat Prot Dosimetry 2011; 143: 264269.Google Scholar
77. Wang, W, Luo, Y-P. MicroRNAs in breast cancer: oncogene and tumor suppressors with clinical potential. J Zhejiang Univ 2015; 16: 1831.Google Scholar
78. O’Leary, V B, Ovsepian, S V, Carrascosa, L G et al. PARTICLE, a triplex-forming long ncRNA, regulates locus-specific methylation in response to low-dose irradiation. Cell Rep 2015; 11: 474485.Google Scholar
79. Zhang, Y, He, Q, Hu, Z et al. Long noncoding RNA LINP1 regulates repair of DNA double-strand breaks in triple-negative breast cancer. Nat Struct Mol Biol 2016; 23: 522530.Google Scholar
80. Wang, J, Xu, J, Fu, J et al. MiR-29a regulates radiosensitivity in human intestinal cells by targeting PTEN gene. Radiat Res 2016; 186 (3): 292301.Google Scholar
81. Weigel, C, Veldwijk, M R, Oakes, C C et al. Epigenetic regulation of diacylglycerol kinase alpha promotes radiation-induced fibrosis. Nat Commun 2016; 7: 10893.Google Scholar
82. Weigel, C, Schmezer, P, Plass, C, Popanda, O. Epigenetics in radiation-induced fibrosis. Oncogene 2015; 34: 21452155.Google Scholar
83. Merrifield, M, Kovalchuk, O. Epigenetics in radiation biology: a new research frontier. Front Genet 2013; 4: 4056.Google Scholar
84. Ilnytskyy, Y, Kovalchuk, O. Non-targeted radiation effects-an epigenetic connection. Mutat Res 2011; 714: 113125.Google Scholar
85. Ilnytskyy, Y, Koturbash, I, Kovalchuk, O. Radiation-induced bystander effects in vivo are epigenetically regulated in a tissue-specific manner. Environ Mol Mutagen 2009; 50: 105113.Google Scholar
86. Imadome, K, Iwakawa, M, Nakawatari, M et al. Subtypes of cervical adenosquamous carcinomas classified by EpCAM expression related to radiosensitivity. Canc Biol Ther 2010; 10: 10191026.Google Scholar
87. Tang, L, Wei, F, Wu, Y et al. Role of metabolism in cancer cell radioresistance and radiosensitization methods. J Exp Clin Canc Res 2018; 37: 87102.Google Scholar
88. Tang, Y, Wang, J, Lian, Y et al. Linking long noncoding RNAs and SWI/SNF complexes to chromatin remodeling in cancer. Mol Canc 2017; 16: 42.Google Scholar
89. Hanahan, D, Weinberg, R A. Hallmarks of cancer: the next generation. Cell 2011; 144: 646674.Google Scholar
90. Yoshida, G J. Metabolic reprogramming: the emerging concept and associated therapeutic strategies. J Exp Clin Cancer Res 2015; 34: 111121.Google Scholar
91. Fang, J, Zhou, S H, Fan, J, Yan, S X. Roles of glucose transporter-1 and the phosphatidylinositol 3kinase/protein kinase B pathway in cancer radioresistance (review). Mol Med Rep 2015; 11: 15731581.Google Scholar
92. Kunkel, M, Moergel, M, Stockinger, M et al. Overexpression of GLUT-1 is associated with resistance to radiotherapy and adverse prognosis in squamous cell carcinoma of the oral cavity. Oral Oncol 2007; 43: 796803.Google Scholar
93. De Schutter, H, Landuyt, W, Verbeken, E, Goethals, L, Hermans, R, Nuyts, S. The prognostic value of the hypoxia markers CA IX and GLUT 1 and the cytokines VEGF and IL 6 in head and neck squamous cell carcinoma treated by radiotherapy +/− chemotherapy. BMC Canc 2005; 5: 4253.Google Scholar
94. Vander Heiden, M G, Cantley, L C, Thompson, C B. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 2009; 324: 10291033.Google Scholar
95. Li, Z, Zhang, H. Reprogramming of glucose, fatty acid and amino acid metabolism for cancer progression. Cell Mol Life Sci 2016; 73: 377392.Google Scholar
96. Li, L, Li, W. Epithelial-mesenchymal transition in human cancer: comprehensive reprogramming of metabolism, epigenetics, and differentiation. Pharmacol Ther 2015; 150: 3346.Google Scholar
97. Bhatt, A N, Chauhan, A, Khanna, S et al. Transient elevation of glycolysis confers radio-resistance by facilitating DNA repair in cells. BMC Canc 2015; 15: 335347.Google Scholar
98. Shimura, T, Noma, N, Sano, Y et al. AKT-mediated enhanced aerobic glycolysis causes acquired radioresistance by human tumor cells. Radiother Oncol 2014; 112: 302307.Google Scholar
99. Fischer, K, Hoffmann, P, Voelkl, S et al. Inhibitory effect of tumor cell-derived lactic acid on human T cells. Blood 2007; 109: 38123819.Google Scholar
100. Feng, J, Yang, H, Zhang, Y et al. Tumor cell-derived lactate induces TAZ-dependent upregulation of PD-L1 through GPR81 in human lung cancer cells. Oncogene 2017; 36 (42): 58295839.Google Scholar
101. Hirschhaeuser, F, Sattler, U G, Mueller-Klieser, W. Lactate: a metabolic key player in cancer. Canc Res 2011; 71: 69216925.Google Scholar
102. Halestrap, A P. The monocarboxylate transporter family–structure and functional characterization. IUBMB Life 2012; 64: 19.Google Scholar
103. Fujiwara, S, Wada, N, Kawano, Y et al. Lactate, a putative survival factor for myeloma cells, is incorporated by myeloma cells through monocarboxylate transporters 1. Exp Hematol Oncol 2015; 4: 1220.Google Scholar
104. Bala, M, Goel, H C. Modification of low dose radiation induced radioresistance by 2-deoxy-D-glucose in Saccharomyces cerevisiae: mechanistic aspects. J Radiat Res 2007; 48: 335346.Google Scholar
105. Dwarkanath, B S, Zolzer, F, Chandana, S et al. Heterogeneity in 2-deoxy-D-glucose-induced modifications in energetics and radiation responses of human tumor cell lines. Int J Radiat Oncol Biol Phys 2001; 50: 10511061.Google Scholar
106. Toulany, M, Schickfluss, T A, Eicheler, W, Kehlbach, R. Schittek B., Rodemann H. P. Impact of oncogenic K-RAS on YB-1 phosphorylation induced by ionizing radiation. Breast Canc Res 2011; 13: R28.Google Scholar
107. Bur, H, Haapasaari, K M, Turpeenniemi-Hujanen, T et al. Low Rap1-interacting factor 1 and sirtuin 6 expression predict poor outcome in radiotherapy-treated Hodgkin lymphoma patients. Leuk Lymphoma 2018; 59: 679689.Google Scholar
108. Chen, Y, Li, Z, Dong, Z et al. 14-3-3sigma contributes to Radioresistance by regulating DNA repair and cell cycle via PARP1 and CHK2. Mol Cancer Res 2017; 15: 418428.Google Scholar
109. Wei, F, Tang, L, He, Y et al. BPIFB1 (LPLUNC1) inhibits radioresistance in nasopharyngeal carcinoma by inhibiting VTN expression. Cell Death Dis 2018; 9: 432.Google Scholar
110. Wei, F, Wu, Y, Tang, L et al. BPIFB1 (LPLUNC1) inhibits migration and invasion of nasopharyngeal carcinoma by interacting with VTN and VIM. Br J Cancer 2018; 118: 233247.Google Scholar
111. Zhou, R, Wu, Y, Wang, W et al. Circular RNAs (circRNAs) in cancer. Cancer Lett 2018; 425: 134142.Google Scholar
112. Zhang, X, Li, Y, Wang, D, Wei, X. miR-22 suppresses tumorigenesis and improves radiosensitivity of breast cancer cells by targeting Sirt1. Biol Res 2017; 50: 27.Google Scholar
113. Goffart, N, Lombard, A, Lallemand, F et al. CXCL12 mediates glioblastoma resistance to radiotherapy in the subventricular zone. Neuro-Oncology 2017; 19: 6677.Google Scholar
114. Zhang, Y, Xia, M, Jin, K et al. Function of the c-Met receptor tyrosine kinase in carcinogenesis and associated therapeutic opportunities. Mol Cancer 2018; 17: 45.Google Scholar
115. Zhang, H, Luo, H, Jiang, Z et al. Fractionated irradiation-induced EMT-like phenotype conferred radioresistance in esophageal squamous cell carcinoma. J Radiat Res 2016; 57: 370380.Google Scholar
116. Xie, G, Liu, Y, Yao, Q et al. Hypoxia-induced angiotensin II by the lactate-chymase-dependent mechanism mediates radioresistance of hypoxic tumor cells. Sci Rep 2017; 7: 42396.Google Scholar
117. Yang, L, Tang, Y, Xiong, F et al. LncRNAs regulate cancer metastasis via binding to functional proteins. Oncotarget 2017; 9 (1): 14261443.Google Scholar
118. Yoshida, G J, Saya, H. Therapeutic strategies targeting cancer stem cells. Cancer Sci 2016; 107: 511.Google Scholar
119. Osuka, S, Sampetrean, O, Shimizu, T et al. IGF1 receptor signaling regulates adaptive radioprotection in glioma stem cells. Stem cells 2013; 31: 627640.Google Scholar
120. Appukuttan, A, Flacke, J P, Flacke, H, Posadowsky, A, Reusch, H P, Ladilov, Y. Inhibition of soluble adenylyl cyclase increases the radiosensitivity of prostate cancer cells. Biochim Biophys Acta 1842; 2014: 26562663.Google Scholar
121. Hao, J, Graham, P, Chang, L et al. Proteomic identification of the lactate dehydrogenase a in a radioresistant prostate cancer xenograft mouse model for improving radiotherapy. Oncotarget 2016; 7: 7426974285.Google Scholar
122. He, R, Liu, P, Xie, X et al. circGFRA1 and GFRA1 act as ceRNAs in triple negative breast cancer by regulating miR-34a. J Exp Clin Cancer Res 2017; 36: 145157.Google Scholar
123. Li, X, Lu, P, Li, B et al. Sensitization of hepatocellular carcinoma cells to irradiation by miR34a through targeting lactate dehydrogenase A. Mol Med Rep 2016; 13: 36613667.Google Scholar
124. Liu, G, Li, Y I, Gao, X. Overexpression of microRNA-133b sensitizes non-small cell lung cancer cells to irradiation through the inhibition of glycolysis. Oncol Lett 2016; 11: 29032908.Google Scholar
125. Shen, H, Hau, E, Joshi, S, Dilda, P J, McDonald, K L. Sensitization of glioblastoma cells to irradiation by modulating the glucose metabolism. Mol Cancer Ther 2015; 14: 17941804.Google Scholar
126. Lynam-Lennon, N, Maher, S G, Maguire, A et al. Altered mitochondrial function and energy metabolism is associated with a radioresistant phenotype in oesophageal adenocarcinoma. PLoS One 2014; 9: e100738.Google Scholar
127. Fisher, C J, Goswami, P C. Mitochondria-targeted antioxidant enzyme activity regulates radioresistance in human pancreatic cancer cells. Cancer Biol Ther 2008; 7: 12711279.Google Scholar
128. Maus, F, Sakry, D, Biname, F et al. The NG2 proteoglycan protects oligodendrocyte precursor cells against oxidative stress via interaction with OMI/HtrA2. PLoS One 2015; 10: e0137311.Google Scholar
129. Chiou, J-F, Tai, C-J, Wang, Y-H, Liu, T-Z, Jen, Y-M, Shiau, C-Y. Sorafenib induces preferential apoptotic killing of a drug- and radio-resistant help G2 cells through a mitochondria-dependent oxidative stress mechanism. Cancer Biol Ther 2014; 8: 19041913.Google Scholar
130. Alphonse, G, Bionda, C, Aloy, M T, Ardail, D, Rousson, R, Rodriguez-Lafrasse, C. Overcoming resistance to gamma-rays in squamous carcinoma cells by poly-drug elevation of ceramide levels. Oncogene 2004; 23: 27032715.Google Scholar
131. Dong, G, Chen, Q, Jiang, F et al. Diisopropylamine dichloroacetate enhances radiosensitization in esophageal squamous cell carcinoma by increasing mitochondria-derived reactive oxygen species levels. Oncotarget 2016; 7: 6817068178.Google Scholar
132. You, W C, Chiou, S H, Huang, C Y et al. Mitochondrial protein ATPase family, AAA domain containing 3A correlates with radioresistance in glioblastoma. Neuro-Oncology 2013; 15: 13421352.Google Scholar
133. Liu, R, Fan, M, Candas, D et al. CDK1-mediated SIRT3 activation enhances mitochondrial function and tumor radioresistance. Mol Cancer Ther 2015; 14: 20902102.Google Scholar
134. Candas, D, Lu, C L, Fan, M et al. Mitochondrial MKP1 is a target for therapy-resistant HER2-positive breast cancer cells. Cancer Res 2014; 74: 74987509.Google Scholar
135. Li, Y L, Chang, J T, Lee, L Y et al. GDF15 contributes to radioresistance and cancer stemness of head and neck cancer by regulating cellular reactive oxygen species via a SMAD-associated signaling pathway. Oncotarget 2017; 8: 15081528.Google Scholar
136. Shonai, T, Adachi, M, Sakata, K et al. MEK/ERK pathway protects ionizing radiation-induced loss of mitochondrial membrane potential and cell death in lymphocytic leukemia cells. Cell Differ 2002; 9: 963971.Google Scholar
137. Huang, L, Li, B, Tang, S et al. Mitochondrial KATP channels control glioma radioresistance by regulating ROS-induced ERK activation. Mol Neurobiol 2015; 52: 626637.Google Scholar
138. Dong, Q, Sharma, S, Liu, H et al. HDAC inhibitors reverse acquired radio resistance of KYSE-150R esophageal carcinoma cells by modulating Bmi-1 expression. Toxicol Lett 2014; 224: 121129.Google Scholar
139. Kuwahara, Y, Roudkenar, M H, Suzuki, M et al. The involvement of mitochondrial membrane potential in cross-resistance between radiation and docetaxel. Int J Radiat Oncol Biol Phys 2016; 96: 556565.Google Scholar
140. Scaife, J E, Barnett, G C, Noble, D J et al. Exploiting biological and physical determinants of radiotherapy toxicity to individualize treatment. Br J Radiol 2015; 88 (1051): 20150172.Google Scholar
141. Seal, S, Thompson, D, Renwick, A et al. Truncating mutations in the Fanconi anemia J gene VRIP1 are low-penetrance breast cancer susceptibility alleles. Nat Genet 2006; 38 (11): 12391241.Google Scholar
142. Levitus, M, Waisfisz, Q, Godthelp, B C et al. The DNA helicase BRIP1 is defective in Fanconi anemia complementation group. J Nat Genet 2005; 37 (9): 934935.Google Scholar
143. Karppinen, S M, Barkardottir, R B, Backenhorn, K et al. Nordic collaborative study of the BARD1 Cys557Ser allele in 3956 patients with cancer: enrichment in familial BRCA1/BRCA2 mutation-negative breast cancer but not in other malignancies. J Med Genet 2006; 43: 856862.Google Scholar
144. Rudolf de Beer, H, Llobet, S G, van Vugt, M. Controlling the response to DNA damage by APC/C-Cdh1. Cell Mol Life Sci 2016; 73: 949960.Google Scholar
145. Wang, C, Su, Z, Hou, H et al. Inhibition of anaphase-promoting complex by silence APC/C-Cdh1 to enhance radiosensitivity of nasopharyngeal carcinoma cells. J Cell Biochem 2017; 118: 31503157.Google Scholar
146. Bayens, A, Claes, K, Willems, P, De Ruyck, K, Thierens, H, Vral, A. Chromosomal radiosensitivity of breast cancer with a CHEK2 mutation. Canc Genet Cytogenet 2005; 163: 106112.Google Scholar
147. Zhang, Q, Si, S, Schoen, S, Jin, X B, Chen, J, Wu, G. Folliculin deficient renal cancer cells show higher radiosensitivity through autophagic cell death. J Urol 2014; 191: 18801888.Google Scholar
148. Ni, J, Cozzi, P, Hao, J et al. Epithelial cell adhesion molecule (EpCAM) is associated with prostate cancer metastasis and chemo/radioresistance via the PI3K/Akt/mTOR signalling pathway. Int J Biochem Cell Biol 2013; 45: 27362748.Google Scholar
149. Yan, T, Seo, Y, Kinsella, T J. Differential cellular responses to prolonged LDR-IR in MLH1-proficient and MLH1-deficient colorectal cancer HCT116 cells. Clin Canc Res 2009; 15 (22): 69126920.Google Scholar
150. Wang, Q, Xiao, Z, Lin, Z et al. Autophagy influences the low-dose hyper-radiosensitivity of human lung adenocarcinoma cells by regulating MLH1. Int J Radiation Biol 2017; 93 (6): 600606.Google Scholar
151. Yin, J, Lu, C, Gu, J et al. Common genetic variants in cell cycle pathway are associated with survival in stage III-IV non-small-cell lung cancer. Carcinogenesis 2011; 32 (12): 18671871.Google Scholar
152. Yang, M, Zhang, L, Bi, N et al. Association of P53 and ATM polymorphisms with risk or radiation-induced pneumonitis in lung cancer patients treated with radiotherapy. Int J Radiat Oncol Biol Phys 2011; 79 (5): 14021407.Google Scholar
153. Jung, I L, Kang, H J, Kim, K C, Kim, I G. PTEN/pAkt/p53 signaling pathway correlates with radioresponse of non-small cell lung cancer. Int J Mol Med 2010; 25: 517523.Google Scholar
154. He, X C, Yin, T, Grindley, J C et al. PTEN-deficient intestinal stem cells initiate intestinal polyposis. Nat Genet 2007; 39: 189198.Google Scholar
155. Bentzen, S M, Heeren, G, Cottier, B et al. Towards evidence-based guidelines for radiotherapy infrastructure and staffing needs in Europe: the ESTRO QUARTS project. Radiother Oncol 2005; 75 (3): 355365.Google Scholar
156. Baumann, M, Petersen, C. TCP and NTCP: a basic introduction. Rays 2005; 30 (2): 99104.Google Scholar
157. Hsu, P D, Lander, E S, Zhang, F. Development and applications of CRISPR-Cas9 for genome engineering. Cell 2014; 157 (6): 12621278.Google Scholar
158. Yap, M L, Zubizarreta, E, Bray, F, Ferlay, J, Barton, M. Global access to radiotherapy services: have we made progress during the past decade? J Glob Oncol 2016; 2 (4): 207–215.Google Scholar