host genome variants affect the complex biology involved in pharmacokinetics / pharmacodynamics and need to be addressed to identify the critical factors determining treatment outcomes .
childhood acute lymphoblastic leukemia ( all ) has for several reasons been a model disease for such research owing to its frequency , well - described epidemiology , clinical characteristics and biologic profiles within cytogenetically defined subsets . in general ,
childhood all is very chemosensitive , and patients are almost uniformly treated within collaborative groups that stratify treatment according to known molecular aberrations in the leukemic clone , clinical characteristics and treatment response .
however , even with risk group - adapted treatment there is a wide diversity in cure rates , partly explainable by both host and cancer genomes .
several candidate gene studies have associated inherited polymorphisms with treatment response and cure rates in childhood all .
still , the biologic relevance and interpretation of multiple single - nucleotide polymorphisms ( snps ) identified in recent genome - wide association studies ( gwas ) remain unclear , as the functions of several of the most significant genes are unknown , and effect sizes of single snp associations are in any case extremely limited . to address some of these limitations and complement the gwas approach , we applied a multiplexed targeted sequencing method allowing screening of 25  00034 
000 preselected snps within biologic domains potentially relevant to childhood all , allowing both single variants and multiple snps acting in the same pathways to be explored for association with relapse , and finally combining it with known clinical risk factors in a predictive profile .
danish patients were 115 years of age and diagnosed 19922008 with b - cell precursor all ( bcp - all ) or t - lineage all and treated according to the nordic society for pediatric hematology and oncology ( nopho ) all92 ( n=227 ) or nopho all2000 protocols ( n=268 ) ( figure 1 , supplementary online material and supplementary tables 1 ) .
these two treatment protocols are very similar and included a 4-week , 3-drug induction phase ( prednisolone , vincristine and doxorubicin ( with intrathecal methotrexate ) ) with no glucocorticosteroid prephase , a risk group - adapted consolidation phase and methotrexate/6-mercaptopurine maintenance therapy up until 2 to 2.5 years from diagnosis ( detailed in supplementary online material ) .
end of induction minimal residual disease ( mrd ) measurements were available for 73% of nopho all2000 patients , but not included in risk stratification . for cross - protocol validation of relapse - predictive host genomic variants , 500 german childhood all patients 118 years at diagnosis were included , all treated according to the bfm all2000 protocol .
the bfm all2000 protocol included a 1-week prednisolone prephase , a 4-week , 4-drug induction phase ( prednisolone or dexamethasone , vincristine , doxorubicin and l - asparaginase ( with intrathecal methotrexate ) ) , a risk group - adapted consolidation phase and methotrexate/6-mercaptopurine maintenance therapy until 2 years from diagnosis ( supplementary online material ) .
a total of 352 danish and 426 german patients were eligible for the final relapse - risk analysis ( figure 1 and supplementary tables s1 ) .
patients were enrolled between 1992 and 2008 with a median follow - up of 7.6 years ( 50% range : 5.39.2 years ) for patients in first remission . in this study ,
owing to the complexity of the bioinformatic analysis and the application of nonlinear machine learning , and as it is uncertain how to weight competing events ( induction failures , deaths in remission and second cancers ) , we chose , in this exploratory , hypothesis - generating study , to exclude patients with such events already at the time of diagnosis of all ( figure 1 ) .
the study was conducted in accordance with the declaration of helsinki principles of 1975 , and approved by the danish data protection agency , the committee on biomedical research ethics and by the ethics committee of the hannover medical school , hannover , germany .
snp selection and bait design have been previously described in detail ( wesolowska et al . and supplementary online material ) .
snps were selected to cover all known and putative clinically relevant genetic variation with regard to childhood all treatment ( 13 drugs ) , drug pharmacokinetics and pharmacodynamics , relapse risk and several toxicities ( supplementary figure s1 ) . in short , clinically important genes and snps for the 13 most commonly administered antileukemic drugs
were evaluated with regard to genes encoding proteins involved in metabolism , transport , target proteins , regulation of drug - target response and to some extent drug - related toxicity ( e.g. coagulation , immune function ) ( supplementary online material ) .
initially , this was carried out by literature curation , and then expanded to cover additional aspects of response to chemotherapy such as genes encoding proteins involved in apoptosis pathways and dna repair .
this also included consultations with experts within such areas and through various online resources ( supplementary online material ) . finally , known drug  protein associations and first - order protein 
protein interactions were evaluated and added ( supplementary online material and supplementary figure s1 ) .
the selected genes were then screened for known polymorphisms with putative functional consequence on their transcript ( supplementary table s3 ) .
baits for the sureselect target enrichment system ( protocol version 1.2 april 2009 ; agilent technologies , santa clara , ca , usa ) were designed for all identified snps .
the first design included baits targeting 25  086 clinically relevant snps in 1540 genes ( supplementary figure s2 ) .
as baits covered more genomic material than just the targeted snps , readouts on the targeted regions covered 116  646 known human variants ( supplementary table s4 ) .
this panel was subsequently updated after sequencing the first group of patients ( from nopho all2000 ) ( supplementary online material and supplementary tables s3 and s4 ) .
thus , the nopho all92 and bfm all2000 cohorts were screened using an expanded bait design , covering 33  683 snps in 2254 genes .
the patients were genotyped for either of the two snp panels by multiplex targeted sequencing as described previously .
briefly , the agilent sureselect target enrichment system protocol ( protocol version 1.2 april 2009 ; agilent technologies ) was modified , allowing nucleotide barcoding , and then pooling of samples before target enrichment and sequencing .
genomic dna from leukemia remission samples was sheared , purified , end - repaired and 3 adenylated .
custom - made adaptors containing unique four - base barcodes were ligated to the dna fragments before size selection and amplification .
the dna libraries were subsequently mixed in groups of up to eight samples , and the pooled libraries were hybridized to the custom - designed baits .
posthybridization amplification pcr was performed , and the pooled libraries were sequenced ( supplementary online material ) .
the sequencing reads were mapped to the reference human genome ( grch37 ) , and snp calling was performed ( supplementary figure s3 ) . the threshold set for snp calling was minimum 10  sequencing depth .
patient samples not clustering together with the hapmap central european ancestry samples in the principal component analysis ( supplementary figures s4 and s5 ) were removed . to make sure that the data did not contain any bias arising either from sequencing or data processing ,
the observed minor allele frequencies ( mafs ) of the genotyped snps were plotted against the hapmap ceu - reported mafs for the 5962 snps , where data were available ( supplementary figure s7 ) .
furthermore , snps for which < 50% of the patients could be genotyped at the minimum depth of 10  and snps with maf < 1% were excluded from the analyses . to validate readouts , genotyping from this experiment
was compared with genotype calls obtained from the illumina human 1m - duo snp chip performed on a subset of patients ( n=275 , overlap of 2394 snps on both platforms ) .
the mean genotyping concordance of those two methods was 98.2% ( supplementary online material ) .
single snps were explored for associations with risk of relapse using a fisher 's exact test separately for the nopho and bfm cohorts .
p - values obtained were corrected for multiple testing by adaptive permutation , and subsequently only snps with adjusted p - values below 0.05 in both cohorts were considered significant . besides investigating such contribution of individual variations , the combined effects of multiple snps acting in the same biologic pathways were investigated using nonlinear machine learning . all pathways from the reactome database and 12-drug metabolism pathways from the pharmgkb database ( ref .
27 in supplementary online material ) , with up to 193 snps in a pathway , were interrogated .
briefly , ann models including all combinations of up to three snps together with white blood cell counts ( wbc ) and age at diagnosis were tested within each pathway and stepwise expanded with up to 15 snps in a pathway , if threefold cross - validated performance improved ( supplementary online material ) ( figure 2 ) . the best model for each pathway
was then chosen , and the most informative pathway models were combined with clinical information in classification and regression tree ( cart ) analysis assigning for each pathway a score from 1 to 10 for every patient based on the relapse prediction from the neural network . as induction therapy differed between the danish and german cohorts , each of these was dichotomously subdivided based on the approximate median end of induction mrd levels in each cohort being 10 and 10 in nopho and bfm cohorts , respectively ( supplementary online material ) .
single snps were explored for associations with risk of relapse using a fisher 's exact test separately for the nopho and bfm cohorts .
p - values obtained were corrected for multiple testing by adaptive permutation , and subsequently only snps with adjusted p - values below 0.05 in both cohorts were considered significant . besides investigating such contribution of individual variations , the combined effects of multiple snps acting in the same biologic pathways were investigated using nonlinear machine learning .
all pathways from the reactome database and 12-drug metabolism pathways from the pharmgkb database ( ref .
27 in supplementary online material ) , with up to 193 snps in a pathway , were interrogated .
briefly , ann models including all combinations of up to three snps together with white blood cell counts ( wbc ) and age at diagnosis were tested within each pathway and stepwise expanded with up to 15 snps in a pathway , if threefold cross - validated performance improved ( supplementary online material ) ( figure 2 ) . the best model for each pathway
was then chosen , and the most informative pathway models were combined with clinical information in classification and regression tree ( cart ) analysis assigning for each pathway a score from 1 to 10 for every patient based on the relapse prediction from the neural network . as induction therapy differed between the danish and german cohorts , each of these was dichotomously subdivided based on the approximate median end of induction mrd levels in each cohort being 10 and 10 in nopho and bfm cohorts , respectively ( supplementary online material ) .
of the genotyped patients ( n=869 ) , 808 fulfilled the quality control and the european ancestry criteria ( figure 1 ) , of which 778 patients could be included in the final relapse - risk analysis .
the majority of genotyped variants had very low heterogeneity ( maf < 1% ) between patients and thus did not contribute with sufficient power to the single snp analysis .
thus , a total of 4260 and 3865 snps in the nopho and the bfm cohorts were included in the relapse - risk analysis , respectively .
the qq plots showed good agreement with the null distribution and absence of genomic inflation ( supplementary figure s8 ) , and several loci were significantly associated with risk of relapse ( supplementary figure s9 ) .
a total of 188 and 152 snps were associated with relapse risk in the nopho and bfm cohorts , respectively ( supplementary tables s5 and s6 ) . as some of these will reflect chance findings , we included in the subsequent analyses only the 11 snps that were associated with relapse risk in both cohorts .
importantly , these 11 snps were related to risk of relapse independent of other known risk factors ( table 1 , supplementary table s7 and supplementary online material ) . as further support of their biologic significance , kaplan  meier analyses for these snps showed a general tendency of gene dose effects ( 0 versus 1 versus 2 alleles associated with increased risk of relapse ) with log - rank trend p - values ranging from 4.8  10 for rs3216144 ( matrix metalloproteinase 7 , mmp7 ) to 0.03 for rs35721373 ( dysferlin , dysf ) , respectively ( supplementary figure s9 ) .
next , functional snps were grouped by biologic pathways , and the relevance of the pathways to risk of relapse was assessed by training anns on different combinations of snps from each pathway , allowing nonlinear correlations between snps .
the top - associated reactome pathway ranked by matthew 's correlation coefficient ( mcc , ranging from 0 to 1 ) was  atp - binding cassette ( abc ) family protein - mediated transport ' ( mcc=0.33 , area under the receiver - operator curve ( auc)=0.69 ) ( supplementary table s8 ) .
similarly , 12-drug metabolism pathways from the pharmgkb database relevant for the administered drugs were investigated , and the top pathways were  vinka alkaloid pathway , pharmacokinetics ' ( mcc=0.321 , auc=0.72 ) ,  glucocorticoid pathway ( peripheral tissue ) , pharmacodynamics ' ( mcc=0.320 , auc=0.75 ) and  methotrexate pathway ( brain cell ) , pharmacokinetics ' ( mcc=0.320 , auc=0.70 ) ( supplementary table s9 ) . to explore and illustrate the combined significance of clinical data and host genomic findings ,
cart analysis was applied to subclassify sequentially patients in a multivariate model , including the 426 patients from both cohorts with complete information on sex , age , immunophenotype , wbc , leukemia karyotype , end of induction mrd , risk group and genotypes of the 11 cross - cohort - associated snps ( figure 3a ) .
end of induction mrd levels divided the patients into two major groups : one group with high mrd levels ( i.e. above median for that cohort ) and a high risk of relapse , which could be further stratified by snps in the myeloperoxidase ( mpo ) , estrogen receptor 1 ( esr1 ) , lamin b1 ( lmnb1 ) and mmp7 genes , and another large group with low mrd levels and low cumulative relapse risk .
as the latter group , because of its size , accounts for 25% of all relapses , a subsequent cart analysis with pathway profiles for the top 10 reactome and the pharmgkb pathways was added ( all having aucs of approximately 0.70 ) , which indicated a role of abc transporters and glucocorticosteroid transcription regulation pathways ( figure 3b ) . finally , based on mrd , wbc , the aforementioned host genomic data and the resulting observed incidence of relapse ( figures 3a and b ) , we could define three large subsets of patients with significant differences in the risk of relapse ( p<0.001 ) . with 92% of projected relapses by kaplan 
meier analysis having been observed in the total cohort , the two extreme subgroups of patients had 6-year cumulative risks of relapse of 4% ( 95% confidence interval : 1.66.3% ) for the best outcome group ( 71.5% of all patients ) and 76% ( 95% confidence interval : 4190% ) for the worst outcome group ( 5% of all patients ) ( figure 3c and table 2 ) , leaving age , immunophenotype ( bcp versus t - all ) , cytogenetics ( table 2 ; high risk , that is , t(9;22 ) , hypodiploid , t(4;11 ) ; low risk , that is , high hyperdiploid , t(12;21 ) ; other ) and risk group nonsignificant with this approach .
as mrd was not available for all patients , an additional cart analysis was performed not including mrd ( supplementary figure s10 ) .
survival analysis taking into account the time to event was also performed ( supplementary figure s11 ) , with results largely agreeing with the model in figure 3 .
multivariate regression analysis to predict risk of relapse found all the features selected by cart analysis to be statistically significant , with mrd being the most significant clinical factor ( p=7.9  10 ) , mpo rs28730837 being the most significant snp region ( p=0.002 ) and glucocorticosteroid pathway ( transcription regulation , pharmacodynamics ) ( p=2.0  10 ) being the most significant pathway .
today , many high - risk patients do not respond to intensified treatment , but most relapses occur among non - high - risk patients . the present study
, using genomic candidate gene genotyping and front - line bioinformatics analyses , provides a novel biology / pharmacology - driven approach for outcome prediction and goes beyond conventional genome - wide association studies ( gwas ) approaches , while still being more cost - effective than whole - genome sequencing ( for cost details see supplementary online material ) .
the rapidly growing understanding of the complex human genome and its derived functional biology allows selection of candidate snps based on the current knowledge of pharmacogenomics , disease mechanisms , signaling pathways and protein interactions .
large - scale , genomic candidate gene setup facilitates not only single snp investigations but also associations of multiple variations grouped by their putative function .
further associations of combinations of snps grouped by biologic pathways tested with neural network models enable detection of meaningful nonlinear snp interactions .
the results obtained through these strategies can provide conclusions at new levels of genomic complexity , collectively emphasizing the importance of specific biologic mechanisms for the phenotype .
the 11 cross - cohort relapse - associated snps resided in genes previously suggested as markers for leukemia aggressiveness , involved in steroid response , implicated in resistance mechanisms or toxicities of certain drugs ( supplementary online material ) .
the pathway analysis strongly indicated an importance of the abc family protein - mediated transport , activation of matrix metalloproteinases , toll - like receptor cascade signaling and various signal - transduction pathways , as well as involvement of the cell cycle . the top - associated pathway 
abc family protein - mediated transport ' confirms the role of pharmacogenomics in drug response by pointing to the importance of drug transport .
the atp - dependent drug efflux pumps have broad substrate specificities ; they influence drug accumulation and are associated with the development of resistance to anticancer drugs .
matrix metalloproteinases are involved in tumor progression , whereas the toll - like receptor cascades and nucleotide - binding oligomerization domain - containing protein 1 and 2 signaling pathways support a role for the innate immune system function for proper drug response or all biology .
it is noteworthy that the three top drug metabolism pathways for relapse risk corresponded to pharmacodynamics of glucocorticosteroids and pharmacokinetics of vinka alkaloids and methotrexate .
this emphasizes the clinical significance of glucocorticosteroid therapy and cell cycle - arresting agents such as vincristine and methotrexate , and also highlights the potential profound consequence of adverse drug disposition on the effect of these agents . as risk factors linked to host genomics , leukemia biology , treatment response markers and drug pharmacokinetics accumulate , cart analysis facilitates integration of the different layers of molecular complexity with patients ' clinical characteristics to identify groups of patients with distinct treatment outcomes , and accordingly candidates for such treatment adaption .
thus , combining patients ' genotypes with their clinical features is likely to explain treatment outcome better than single snps .
even though the binary recursive partitioning of the cart methodology offers an approach to patient classifications that is easier to perceive from a biologic point of view and to apply in the clinical setting , cart does not necessarily outperform conventional , stepwise , multivariate regression analyses .
interactions between variables ( and combinations hereof ) may be missed , and the downstream decision branching may be unstable if one variable is removed .
although the cart analysis presented here classified patients into highly different prognostic subsets , and conventional regression analysis confirmed the most significant clinical feature , snp and pathway , larger independent data sets will be needed to determine which of these two biostatistical approaches is superior for relapse prediction . in future trials
, the small group of patients who have the highest risk of relapse can be offered intensified treatments , or be candidates for phase 2 trials , whereas treatment reduction to avoid specific toxicities may be relevant for the large subset of patients who have a projected risk of relapse of < 5% . in this context , the least relapse - predictive drug metabolism pathways may point to which drug doses potentially could be safely reduced in complex combination chemotherapy , and/or to which patients a specific drug is important owing to the patient 's genomic variants .
although further verification is needed to strengthen the findings , the present approach has , when compared with other large - scale studies , the clear advantage of specifically targeting potential causative variants , which reduces the need to investigate genomic patterns of linkage disequilibrium , or conducting follow - up fine - mapping studies .
functional prioritization of the potential snps to be genotyped eliminates the difficulties linked to gwas when mapping significant variants to genes and genotypes , and can be more directly combined in functional analyses . as an example , only one of the 134 snps associated to relapse risk in the recent childhood all gwas study of yang et al .
was also genotyped in the present study , as the remaining snps resided in noncoding or functionally unannotated regions , and it was not found significant . moreover , as the associated snps in most cases were difficult to map to the gene on which they exert their effects , it is difficult to evaluate the involved biologic mechanisms .
the present study combines large - scale genetic investigations of a gwas approach with the targeted focus of a candidate gene approach .
thus , the major strength of our approach is that a wide panel of functional snps was selected with various prior assumptions of their potential relevance for childhood all treatment outcome .
owing to annotation to specific pathways , the results obtained are easier to interpret , and eventually to implement in the clinic based on existing knowledge of all disease mechanisms and pharmacokinetics and pharmacodynamics of administered drugs .
thus , the snp / pathway - based approach can also be applied for prediction of specific side effects of antileukemic therapy .
host genome profiles may then indicate drugs with little importance for cure but associated with a high risk for side effects for specific patients , and this information could be applied for tailored therapy .
accordingly , the strategies and findings of this paper will be validated in the ongoing nordic / baltic nopho all2008 protocol addressing risk grouping , occurrence of toxicities ( including infections ) and risk of relapse before they are included into future treatment allocation .
we acknowledge that not covering the whole genome will certainly miss unknown , important genetic components of treatment response , which may benefit from alternative genome - wide screening approaches such as gwas or whole - exome / transcriptome / genome sequencing , although the latter is still burdened by high costs owing to required patient numbers for statistical significance , and requires extensive follow - up for unannotated variants to be credibly accepted . in conclusion , this large - scale integration of the knowledge of disease mechanisms and drug pharmacokinetics / pharmacodynamics in host genome studies in childhood all can offer both significant improvements to the current relapse prediction algorithms , and , importantly , indicate specific directions for leukemia response and toxicity risk - based treatments adaptation for the individual patient .
 childhood acute lymphoblastic leukemia survival approaches 90% . 
 new strategies are needed to identify the 1015% who evade cure . 
 we applied targeted , sequencing - based genotyping of 25  000 to 34  000 preselected potentially clinically relevant single - nucleotide polymorphisms ( snps ) to identify host genome profiles associated with relapse risk in 352 patients from the nordic all92/2000 protocols and 426 patients from the german berlin  frankfurt  munster ( bfm ) all2000 protocol . 
 patients were enrolled between 1992 and 2008 ( median follow - up : 7.6 years ) . 
 eleven cross - validated snps were significantly associated with risk of relapse across protocols . 
 snp and biologic pathway level analyses associated relapse risk with leukemia aggressiveness , glucocorticosteroid pharmacology / response and drug transport / metabolism pathways . classification and regression tree analysis identified three distinct risk groups defined by end of induction residual leukemia , white blood cell count and variants in myeloperoxidase ( mpo ) , estrogen receptor 1 ( esr1 ) , lamin b1 ( lmnb1 ) and matrix metalloproteinase-7 ( mmp7 ) genes , atp - binding cassette transporters and glucocorticosteroid transcription regulation pathways . 
 relapse rates ranged from 4% ( 95% confidence interval ( ci ) : 1.66.3% ) for the best group ( 72% of patients ) to 76% ( 95% ci : 4190% ) for the worst group ( 5% of patients , p<0.001 ) 
 . validation of these findings and similar approaches to identify snps associated with toxicities may allow future individualized relapse and toxicity risk - based treatments adaptation . 
Introduction
Materials and methods
SNP associations
Results
Discussion
Supplementary Material