Radiotherapy and Oncology xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Radiotherapy and Oncology journal homepage: www.thegreenjournal.com
Editorial
The future has begun in radiogenomics! Christian Nicolaj Andreassen Department of Experimental Clinical Oncology, Aarhus University Hospital, Denmark
In the last decade, more than 100 published studies have addressed possible associations between genetic germline variants and risk of normal tissue toxicity after radiotherapy. With few exceptions, these were made up by relatively small studies using a candidate gene approach [1]. The results have generally been difficult to interpret and few if any associations have been convincingly replicated [2]. Consequently, most of the recent papers published on this topic have ended up concluding that large genome-wide association studies (GWASs) will be needed in the future in order to substantially advance this scientific field [3]. In the present issue of Radiotherapy & Oncology, the results from a multi-center two phase GWAS are published [4]. With more than 3500 patients, it is far bigger than the four GWASs previously conducted in normal tissue radiobiology [5–8]. In fact, it is bigger than all four previous studies taken together. Knowing how difficult it is to establish large cohorts of patients that are well-characterized concerning treatment details and normal tissue outcome, this collaborative research effort certainly represents a milestone in its field. Thus, it seems reasonable to state that the future has now begun in radiogenomics! The first contours are emerging The study by Barnett et al. does indeed provide a number of important observations. First of all, the Q–Q plots from phase 1 showed a higher than expected number of p values in the range between 5 10 5 and 5 10 8. This strongly supports the assumption that the risk of radiation-induced toxicity is in fact influenced by common low-penetrance genetic variants (i.e. SNPs). Nevertheless, in the combined analysis of data from phase 1 and phase 2 the p-values generally increased and none of the associations from phase 1 could be independently confirmed in phase 2 at a nominal significance level of 0.05. Only for the KCND3 SNP the result of the combined analysis reached the usual genomewide significance level of 5 10 8 with regard to rectal incontinence. As underlined by the authors, only one patient in the validation set experienced rectal incontinence and this finding should therefore be interpreted cautiously. Thus, it is probably fair to say that the primary asset of the present study is that it offers the first somewhat blurred contours of the genetics underlying normal tissue radiosensitivity rather than providing rock hard data for individual SNP associations. E-mail address: [email protected]
It has been a long standing discussion in radiogenomics whether we should expect genetic factors to have a general impact on radiosensitivity across different endpoints or if the impact would be endpoint specific [9]. Even though the study by Barnett had substantially more power to detect associations for overall toxicity, the strongest associations were in fact shown for individual endpoints. This observation may seem at odds with the fact that most of the rare radiosensitive syndromes with Mendelian inheritance seem to inflict a general enhancement of clinical radioresponsiveness [10]. Nevertheless, the observation is consistent with clinical data indicating that no strong association exists between the risks of developing different types of normal tissue toxicity [11–13]. Thus, the results of Barnett’s study underline the importance of not only looking for associations with regard to overall toxicity but also to address separate toxicity endpoints. Associations showing up all the unexpected (but somewhat plausible) places The study by Barnett as well as some of the previously published GWASs in normal tissue radiobiology has provided a number of SNP associations that reached or approached the genome wide significance level of 5 10 8 [3]. These associations of course need independent validation. Nevertheless, an interesting pattern seems to appear. The first GWAS in normal tissue radiobiology demonstrated an association between risk of erectile dysfunction after radiotherapy for prostate cancer and a SNP in the follicular stimulating hormone (FSH) receptor gene [5]. Another GWAS addressing the same endpoint showed putative associations for SNPs in the vicinity of the 17-beta-hydroxysteroid dehydrogenase II gene (HSD17B2) that catalyzes the oxidative metabolism of androgens and estrogens [6]. The SNP shown to affect rectal incontinence in Barnett’s study is located in the KCND3 gene that encodes a voltage gated ion channel involved in the electro-chemical processes underlying smooth muscle contraction [4]. Finally, this study also demonstrated possible associations with overall toxicity in the breast for SNPs with a putative impact on body mass index/breast size [4]. Thus, none of these SNPs were located in genes involved in radiobiology in a narrow sense and they were certainly not located in any of the ‘usual suspects’ investigated as part of candidate gene studies [1]. Instead, they were involved in physiological phenomena that may interact with various types of normal tissue toxicity. This experience brings reminiscences about the first GWASs addressing lung cancer susceptibility in which a
http://dx.doi.org/10.1016/j.radonc.2014.04.006 0167-8140/Ó 2014 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Andreassen CN. The future has begun in radiogenomics!. Radiother Oncol (2014), http://dx.doi.org/10.1016/ j.radonc.2014.04.006
2
Editorial
SNP in the nicotine receptor (presumably related to tobacco addiction) came out among the top hits [14]. This appetent pattern may have important implications. First of all, it severely questions the value of the candidate gene approach. Secondly, it demonstrates the exploratory nature of genome wide approaches and underlines that GWASs are likely to broaden our understanding of the mechanisms underlying radiation induced normal tissue complications. We are still at the foot of the mountain. . . Even though the study by Barnett provides several interesting insights, it does at the same time display a number of challenges related to genome-wide approaches. The associations detected in the first phase of a GWAS are selected from a very broad base. Consequently, associations not reaching the usual genome wide-significance level of 5 10 8 are hampered by a substantial risk of being false positives by chance. Due to the so-called winner’s course phenomenon, the effect size of the detected associations is furthermore likely to be overestimated. Thus, rigorous re-testing in an independent validation set is of utmost importance. In that regard, the limited size of the replication cohorts in Barnett’s study (particularly for the breast endpoints) represents a weakness. It has been a general experience in GWASs addressing various bio-medical phenotypes that the typical impact of SNPs is relatively small corresponding to genotype relative risks around or below 1.5 [15]. As demonstrated by the post hoc power calculations in Barnett’s paper, the study was at best only marginally powered to detect such associations. Thus, substantially larger studies will almost certainly be needed to lower the detection bar down to where the bulk of associations is likely to be located. Another fundamental challenge in GWASs is that the SNPs shown to be associated with the phenotype at interest are not necessarily the causal variants [16]. Thus, fine mapping and functional characterization will usually be required in order to get the full picture in detail. Furthermore, many of the identified SNPs are likely to be located in non coding regions [16]. Such regions have previously been referred to as ‘junk’ but have more recently been demonstrated to harbor very important regulatory functions. Consequently, the exploration of ‘intronic’ genetics and biology is likely to represent a new exciting chapter on its own [16]. It therefore seems obvious that the GWASs published so far in normal tissue radiobiology only represent the first tiny steps in a longer endeavor. In that sense, the future has merely just begun in radiogenomics. ...but we have found the path ahead The field of radiogenomics has evolved substantially over the past few years [18]. Even though controversies still exist concerning the exact allelic structure underlying non-Mendelian phenotypes [17], we have achieved a reasonable understanding of complex trait genetics [16]. Genome-wide SNP genotyping has become increasingly reachable. Furthermore, strong international cooperative research networks have been established [19–22]. Thus, for the first time ever we have the tools at hand to address the topic in a meaningful way [18]. The International Radiogenomics Consortium (RGC) was established in 2009 in order to foster large scale collaborative research projects [22]. It has 174 members from 90 institutions in 20 countries [23]. Several pivotal studies have been conducted by members of or within the framework of the RGC [4–8,24–26]. A set of reporting guidelines for radiogenomics studies have been published [27].The RGC recently obtained an EU grant of 6,000,000 Euros for the so-called REQUITE project that will prospectively collect outcome data and biological material from 5300 patients with the intention to establish and validate predictive tests for normal tissue radiosensitivity [28]. The RGC
has a close cooperation with the GAME-ON oncoarray initiative that has purchased 400,000 GWAS microarrays in order to address susceptibility to common cancers [29]. As part of this cooperation large breast cancer cohorts can be genotyped for only approximately 50 UK Pounds per patient. Thus, complete genome-wide SNP genotyping has almost become cheaper than doing a proper ‘phenotyping’. These developments herald that further progress is likely to be made in radiogenomics in the years to come [18]. So, have your patient cohorts ready to serve as validation cohorts for SNP associations detected in GWASs. Do GWASs that can be fed into large multi-center meta-analyses [3]. Whenever a patient is entered into a radiotherapy trial, bank a blood sample. Be prepared to take part in the future of radiogenomics!
References [1] Andreassen CN. Searching for genetic determinants of normal tissue radiosensitivity–are we on the right track? Radiother Oncol 2010;97:1–8. [2] Andreassen CN, Dikomey E, Parliament M, West CM. Will SNPs be useful predictors of normal tissue radiosensitivity in the future? Radiother Oncol 2012;105:283–8. [3] Kerns SL, Ostrer H, Rosenstein BS. Radiogenomics: using genetics to identify cancer patients at risk for development of adverse effects following radiotherapy. Cancer Discov 2014;4:155–65. [4] Barnett GC, Thompson D, Fachal L, Kerns S, et al. A Genome Wide Association Study (GWAS) providing evidence of an association between common genetic common variants and late toxicity. Radiother Oncol, in this issue. [5] Kerns SL, Ostrer H, Stock R, et al. Genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with the development of erectile dysfunction in African-American men after radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2010;78:1292–300. [6] Kerns SL, Stock R, Stone N, et al. A 2-stage genome-wide association study to identify single nucleotide polymorphisms associated with development of erectile dysfunction following radiation therapy for prostate cancer. Int J Radiat Oncol Biol Phys 2013;85:e21–8. [7] Kerns SL, Stone NN, Stock RG, Rath L, Ostrer H, Rosenstein BS. A 2-stage genome-wide association study to identify single nucleotide polymorphisms associated with development of urinary symptoms after radiotherapy for prostate cancer. J Urol 2013;190:102–8. [8] Kerns SL, Stock RG, Stone NN, et al. Genome-wide association study identifies a region on chromosome 11q14.3 associated with late rectal bleeding following radiation therapy for prostate cancer. Radiother Oncol 2013;107:372–6. [9] Andreassen CN, Barnett GC, Langendijk JA, et al. Conducting radiogenomic research–do not forget careful consideration of the clinical data. Radiother Oncol 2012;105:337–40. [10] Pollard JM, Gatti RA. Clinical radiation sensitivity with DNA repair disorders: an overview. Int J Radiat Oncol Biol Phys 2009;74:1323–31. [11] Bentzen SM, Overgaard M. Relationship between early and late normal-tissue injury after postmastectomy radiotherapy. Radiother Oncol 1991;20:159–65. [12] Bentzen SM, Overgaard M, Overgaard J. Clinical correlations between late normal tissue endpoints after radiotherapy: implications for predictive assays of radiosensitivity. Eur J Cancer 1993;29A:1373–6. [13] Barnett GC, Wilkinson JS, Moody AM, et al. The Cambridge Breast Intensitymodulated Radiotherapy Trial: patient- and treatment-related factors that influence late toxicity. Clin Oncol (R Coll Radiol) 2011;23:662–73. [14] Thorgeirsson TE, Geller F, Sulem P, et al. A variant associated with nicotine dependence, lung cancer and peripheral arterial disease. Nature 2008;452:638–42. [15] Manolio TA. Bringing genome-wide association findings into clinical use. Nat Rev Genet 2013;14:549–58. [16] Edwards SL, Beesley J, French JD, Dunning AM. Beyond GWASs: illuminating the dark road from association to function. Am J Hum Genet 2013;93:779–97. [17] Gibson G. Rare and common variants: twenty arguments. Nat Rev Genet 2012;13:135–45. [18] Rosenstein BS, West CM, Alsner J, et al. Radiogenomics: radiobiology enters the era of big data and team science. Int J Radiat Oncol Biol Phys, in press. [19] Burnet NG, Barnett GC, Elliott RM, et al. RAPPER: the radiogenomics of radiation toxicity. Clin Oncol (R Coll Radiol) 2013;25:431–4. [20] Ho AY, Atencio DP, Peters S, et al. Genetic predictors of adverse radiotherapy effects: the Gene-PARE project. Int J Radiat Oncol Biol Phys 2006;65:646–55. [21] Baumann M, Hölscher T, Begg AC. Towards genetic prediction of radiation responses: ESTRO’s GENEPI project. Radiother Oncol 2003;69:121–5. [22] West C, Rosenstein BS, Alsner J, et al. Establishment of a Radiogenomics Consortium. Int J Radiat Oncol Biol Phys 2010;76:1295–6. [23] Radiogenomics Consortium (RGC). Epidemiology and genomics research in NCI’s division of cancer control and population sciences. Available from: http://epi.grants.cancer.gov/radiogenomics. [24] Barnett GC, Elliott RM, Alsner J, et al. Individual patient data meta-analysis shows no association between the SNP rs1800469 in TGFB and late radiotherapy toxicity. Radiother Oncol 2012;105:289–95.
Please cite this article in press as: Andreassen CN. The future has begun in radiogenomics!. Radiother Oncol (2014), http://dx.doi.org/10.1016/ j.radonc.2014.04.006
C.N. Andreassen / Radiotherapy and Oncology xxx (2014) xxx–xxx [25] Talbot CJ, Tanteles GA, Barnett GC, et al. A replicated association between polymorphisms near TNFa and risk for adverse reactions to radiotherapy. Br J Cancer 2012;107:748–53. [26] Barnett GC, Coles CE, Elliott RM, et al. Independent validation of genes and polymorphisms reported to be associated with radiation toxicity: a prospective analysis study. Lancet Oncol 2012;13:65–77. [27] Kerns SL, de Ruysscher D, Andreassen CN, et al. STROGAR – STrengthening the Reporting Of Genetic Association studies in Radiogenomics. Radiother Oncol 2014;110:182–8.
3
[28] REQUITE. Validating predictive models of radiotherapy toxicity to improve quality-of-life and reduce side-effects in cancer survivors. Available from: http://ec.europa.eu/research/health/medical-research/cancer/fp7-projects/ requite_en.html. [29] Genetic Associations and Mechanisms in Oncology (GAME-ON). A network of consortia for post-Genome Wide Association (Post-GWA) research. Available from: http://epi.grants.cancer.gov/gameon/.
Please cite this article in press as: Andreassen CN. The future has begun in radiogenomics!. Radiother Oncol (2014), http://dx.doi.org/10.1016/ j.radonc.2014.04.006
Contents lists available at ScienceDirect
Radiotherapy and Oncology journal homepage: www.thegreenjournal.com
Editorial
The future has begun in radiogenomics! Christian Nicolaj Andreassen Department of Experimental Clinical Oncology, Aarhus University Hospital, Denmark
In the last decade, more than 100 published studies have addressed possible associations between genetic germline variants and risk of normal tissue toxicity after radiotherapy. With few exceptions, these were made up by relatively small studies using a candidate gene approach [1]. The results have generally been difficult to interpret and few if any associations have been convincingly replicated [2]. Consequently, most of the recent papers published on this topic have ended up concluding that large genome-wide association studies (GWASs) will be needed in the future in order to substantially advance this scientific field [3]. In the present issue of Radiotherapy & Oncology, the results from a multi-center two phase GWAS are published [4]. With more than 3500 patients, it is far bigger than the four GWASs previously conducted in normal tissue radiobiology [5–8]. In fact, it is bigger than all four previous studies taken together. Knowing how difficult it is to establish large cohorts of patients that are well-characterized concerning treatment details and normal tissue outcome, this collaborative research effort certainly represents a milestone in its field. Thus, it seems reasonable to state that the future has now begun in radiogenomics! The first contours are emerging The study by Barnett et al. does indeed provide a number of important observations. First of all, the Q–Q plots from phase 1 showed a higher than expected number of p values in the range between 5 10 5 and 5 10 8. This strongly supports the assumption that the risk of radiation-induced toxicity is in fact influenced by common low-penetrance genetic variants (i.e. SNPs). Nevertheless, in the combined analysis of data from phase 1 and phase 2 the p-values generally increased and none of the associations from phase 1 could be independently confirmed in phase 2 at a nominal significance level of 0.05. Only for the KCND3 SNP the result of the combined analysis reached the usual genomewide significance level of 5 10 8 with regard to rectal incontinence. As underlined by the authors, only one patient in the validation set experienced rectal incontinence and this finding should therefore be interpreted cautiously. Thus, it is probably fair to say that the primary asset of the present study is that it offers the first somewhat blurred contours of the genetics underlying normal tissue radiosensitivity rather than providing rock hard data for individual SNP associations. E-mail address: [email protected]
It has been a long standing discussion in radiogenomics whether we should expect genetic factors to have a general impact on radiosensitivity across different endpoints or if the impact would be endpoint specific [9]. Even though the study by Barnett had substantially more power to detect associations for overall toxicity, the strongest associations were in fact shown for individual endpoints. This observation may seem at odds with the fact that most of the rare radiosensitive syndromes with Mendelian inheritance seem to inflict a general enhancement of clinical radioresponsiveness [10]. Nevertheless, the observation is consistent with clinical data indicating that no strong association exists between the risks of developing different types of normal tissue toxicity [11–13]. Thus, the results of Barnett’s study underline the importance of not only looking for associations with regard to overall toxicity but also to address separate toxicity endpoints. Associations showing up all the unexpected (but somewhat plausible) places The study by Barnett as well as some of the previously published GWASs in normal tissue radiobiology has provided a number of SNP associations that reached or approached the genome wide significance level of 5 10 8 [3]. These associations of course need independent validation. Nevertheless, an interesting pattern seems to appear. The first GWAS in normal tissue radiobiology demonstrated an association between risk of erectile dysfunction after radiotherapy for prostate cancer and a SNP in the follicular stimulating hormone (FSH) receptor gene [5]. Another GWAS addressing the same endpoint showed putative associations for SNPs in the vicinity of the 17-beta-hydroxysteroid dehydrogenase II gene (HSD17B2) that catalyzes the oxidative metabolism of androgens and estrogens [6]. The SNP shown to affect rectal incontinence in Barnett’s study is located in the KCND3 gene that encodes a voltage gated ion channel involved in the electro-chemical processes underlying smooth muscle contraction [4]. Finally, this study also demonstrated possible associations with overall toxicity in the breast for SNPs with a putative impact on body mass index/breast size [4]. Thus, none of these SNPs were located in genes involved in radiobiology in a narrow sense and they were certainly not located in any of the ‘usual suspects’ investigated as part of candidate gene studies [1]. Instead, they were involved in physiological phenomena that may interact with various types of normal tissue toxicity. This experience brings reminiscences about the first GWASs addressing lung cancer susceptibility in which a
http://dx.doi.org/10.1016/j.radonc.2014.04.006 0167-8140/Ó 2014 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Andreassen CN. The future has begun in radiogenomics!. Radiother Oncol (2014), http://dx.doi.org/10.1016/ j.radonc.2014.04.006
2
Editorial
SNP in the nicotine receptor (presumably related to tobacco addiction) came out among the top hits [14]. This appetent pattern may have important implications. First of all, it severely questions the value of the candidate gene approach. Secondly, it demonstrates the exploratory nature of genome wide approaches and underlines that GWASs are likely to broaden our understanding of the mechanisms underlying radiation induced normal tissue complications. We are still at the foot of the mountain. . . Even though the study by Barnett provides several interesting insights, it does at the same time display a number of challenges related to genome-wide approaches. The associations detected in the first phase of a GWAS are selected from a very broad base. Consequently, associations not reaching the usual genome wide-significance level of 5 10 8 are hampered by a substantial risk of being false positives by chance. Due to the so-called winner’s course phenomenon, the effect size of the detected associations is furthermore likely to be overestimated. Thus, rigorous re-testing in an independent validation set is of utmost importance. In that regard, the limited size of the replication cohorts in Barnett’s study (particularly for the breast endpoints) represents a weakness. It has been a general experience in GWASs addressing various bio-medical phenotypes that the typical impact of SNPs is relatively small corresponding to genotype relative risks around or below 1.5 [15]. As demonstrated by the post hoc power calculations in Barnett’s paper, the study was at best only marginally powered to detect such associations. Thus, substantially larger studies will almost certainly be needed to lower the detection bar down to where the bulk of associations is likely to be located. Another fundamental challenge in GWASs is that the SNPs shown to be associated with the phenotype at interest are not necessarily the causal variants [16]. Thus, fine mapping and functional characterization will usually be required in order to get the full picture in detail. Furthermore, many of the identified SNPs are likely to be located in non coding regions [16]. Such regions have previously been referred to as ‘junk’ but have more recently been demonstrated to harbor very important regulatory functions. Consequently, the exploration of ‘intronic’ genetics and biology is likely to represent a new exciting chapter on its own [16]. It therefore seems obvious that the GWASs published so far in normal tissue radiobiology only represent the first tiny steps in a longer endeavor. In that sense, the future has merely just begun in radiogenomics. ...but we have found the path ahead The field of radiogenomics has evolved substantially over the past few years [18]. Even though controversies still exist concerning the exact allelic structure underlying non-Mendelian phenotypes [17], we have achieved a reasonable understanding of complex trait genetics [16]. Genome-wide SNP genotyping has become increasingly reachable. Furthermore, strong international cooperative research networks have been established [19–22]. Thus, for the first time ever we have the tools at hand to address the topic in a meaningful way [18]. The International Radiogenomics Consortium (RGC) was established in 2009 in order to foster large scale collaborative research projects [22]. It has 174 members from 90 institutions in 20 countries [23]. Several pivotal studies have been conducted by members of or within the framework of the RGC [4–8,24–26]. A set of reporting guidelines for radiogenomics studies have been published [27].The RGC recently obtained an EU grant of 6,000,000 Euros for the so-called REQUITE project that will prospectively collect outcome data and biological material from 5300 patients with the intention to establish and validate predictive tests for normal tissue radiosensitivity [28]. The RGC
has a close cooperation with the GAME-ON oncoarray initiative that has purchased 400,000 GWAS microarrays in order to address susceptibility to common cancers [29]. As part of this cooperation large breast cancer cohorts can be genotyped for only approximately 50 UK Pounds per patient. Thus, complete genome-wide SNP genotyping has almost become cheaper than doing a proper ‘phenotyping’. These developments herald that further progress is likely to be made in radiogenomics in the years to come [18]. So, have your patient cohorts ready to serve as validation cohorts for SNP associations detected in GWASs. Do GWASs that can be fed into large multi-center meta-analyses [3]. Whenever a patient is entered into a radiotherapy trial, bank a blood sample. Be prepared to take part in the future of radiogenomics!
References [1] Andreassen CN. Searching for genetic determinants of normal tissue radiosensitivity–are we on the right track? Radiother Oncol 2010;97:1–8. [2] Andreassen CN, Dikomey E, Parliament M, West CM. Will SNPs be useful predictors of normal tissue radiosensitivity in the future? Radiother Oncol 2012;105:283–8. [3] Kerns SL, Ostrer H, Rosenstein BS. Radiogenomics: using genetics to identify cancer patients at risk for development of adverse effects following radiotherapy. Cancer Discov 2014;4:155–65. [4] Barnett GC, Thompson D, Fachal L, Kerns S, et al. A Genome Wide Association Study (GWAS) providing evidence of an association between common genetic common variants and late toxicity. Radiother Oncol, in this issue. [5] Kerns SL, Ostrer H, Stock R, et al. Genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with the development of erectile dysfunction in African-American men after radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2010;78:1292–300. [6] Kerns SL, Stock R, Stone N, et al. A 2-stage genome-wide association study to identify single nucleotide polymorphisms associated with development of erectile dysfunction following radiation therapy for prostate cancer. Int J Radiat Oncol Biol Phys 2013;85:e21–8. [7] Kerns SL, Stone NN, Stock RG, Rath L, Ostrer H, Rosenstein BS. A 2-stage genome-wide association study to identify single nucleotide polymorphisms associated with development of urinary symptoms after radiotherapy for prostate cancer. J Urol 2013;190:102–8. [8] Kerns SL, Stock RG, Stone NN, et al. Genome-wide association study identifies a region on chromosome 11q14.3 associated with late rectal bleeding following radiation therapy for prostate cancer. Radiother Oncol 2013;107:372–6. [9] Andreassen CN, Barnett GC, Langendijk JA, et al. Conducting radiogenomic research–do not forget careful consideration of the clinical data. Radiother Oncol 2012;105:337–40. [10] Pollard JM, Gatti RA. Clinical radiation sensitivity with DNA repair disorders: an overview. Int J Radiat Oncol Biol Phys 2009;74:1323–31. [11] Bentzen SM, Overgaard M. Relationship between early and late normal-tissue injury after postmastectomy radiotherapy. Radiother Oncol 1991;20:159–65. [12] Bentzen SM, Overgaard M, Overgaard J. Clinical correlations between late normal tissue endpoints after radiotherapy: implications for predictive assays of radiosensitivity. Eur J Cancer 1993;29A:1373–6. [13] Barnett GC, Wilkinson JS, Moody AM, et al. The Cambridge Breast Intensitymodulated Radiotherapy Trial: patient- and treatment-related factors that influence late toxicity. Clin Oncol (R Coll Radiol) 2011;23:662–73. [14] Thorgeirsson TE, Geller F, Sulem P, et al. A variant associated with nicotine dependence, lung cancer and peripheral arterial disease. Nature 2008;452:638–42. [15] Manolio TA. Bringing genome-wide association findings into clinical use. Nat Rev Genet 2013;14:549–58. [16] Edwards SL, Beesley J, French JD, Dunning AM. Beyond GWASs: illuminating the dark road from association to function. Am J Hum Genet 2013;93:779–97. [17] Gibson G. Rare and common variants: twenty arguments. Nat Rev Genet 2012;13:135–45. [18] Rosenstein BS, West CM, Alsner J, et al. Radiogenomics: radiobiology enters the era of big data and team science. Int J Radiat Oncol Biol Phys, in press. [19] Burnet NG, Barnett GC, Elliott RM, et al. RAPPER: the radiogenomics of radiation toxicity. Clin Oncol (R Coll Radiol) 2013;25:431–4. [20] Ho AY, Atencio DP, Peters S, et al. Genetic predictors of adverse radiotherapy effects: the Gene-PARE project. Int J Radiat Oncol Biol Phys 2006;65:646–55. [21] Baumann M, Hölscher T, Begg AC. Towards genetic prediction of radiation responses: ESTRO’s GENEPI project. Radiother Oncol 2003;69:121–5. [22] West C, Rosenstein BS, Alsner J, et al. Establishment of a Radiogenomics Consortium. Int J Radiat Oncol Biol Phys 2010;76:1295–6. [23] Radiogenomics Consortium (RGC). Epidemiology and genomics research in NCI’s division of cancer control and population sciences. Available from: http://epi.grants.cancer.gov/radiogenomics. [24] Barnett GC, Elliott RM, Alsner J, et al. Individual patient data meta-analysis shows no association between the SNP rs1800469 in TGFB and late radiotherapy toxicity. Radiother Oncol 2012;105:289–95.
Please cite this article in press as: Andreassen CN. The future has begun in radiogenomics!. Radiother Oncol (2014), http://dx.doi.org/10.1016/ j.radonc.2014.04.006
C.N. Andreassen / Radiotherapy and Oncology xxx (2014) xxx–xxx [25] Talbot CJ, Tanteles GA, Barnett GC, et al. A replicated association between polymorphisms near TNFa and risk for adverse reactions to radiotherapy. Br J Cancer 2012;107:748–53. [26] Barnett GC, Coles CE, Elliott RM, et al. Independent validation of genes and polymorphisms reported to be associated with radiation toxicity: a prospective analysis study. Lancet Oncol 2012;13:65–77. [27] Kerns SL, de Ruysscher D, Andreassen CN, et al. STROGAR – STrengthening the Reporting Of Genetic Association studies in Radiogenomics. Radiother Oncol 2014;110:182–8.
3
[28] REQUITE. Validating predictive models of radiotherapy toxicity to improve quality-of-life and reduce side-effects in cancer survivors. Available from: http://ec.europa.eu/research/health/medical-research/cancer/fp7-projects/ requite_en.html. [29] Genetic Associations and Mechanisms in Oncology (GAME-ON). A network of consortia for post-Genome Wide Association (Post-GWA) research. Available from: http://epi.grants.cancer.gov/gameon/.
Please cite this article in press as: Andreassen CN. The future has begun in radiogenomics!. Radiother Oncol (2014), http://dx.doi.org/10.1016/ j.radonc.2014.04.006
