SPECIFIC AIMS Dihidrofolate reductase (DHFR) activity is needed to convert synthetic folic acid from fortified foods and supplements into biological folate. We have previously demonstrated that women homozygous for the rs70991108 polymorphism,(DHFR19bpdel) are at increased risk for having a child with retinoblastoma (OR 3.78; 95%CI:1.89,7.55) [1] This risk appears specific to women consuming folic acid supplements during the first trimester of pregnancy. Therefore our finding suggests that tumor formation may begin in utero. Women homozygous for DHFR19bpdel (17-19% of populations studied in the US)[2] [3] have impaired ability to incorporate folic acid into biologically useable folate. Exposure to high levels of folic acid that cannot be fully metabolized might influence both tumor specific methylation and mutagenesis during retinal formation. Pilot data in our case series of Mexican children with retinoblastoma suggest that tumors in children of women homozygous for DHFR19bpdel are more likely to have methylation induced changes affecting RB1( “meCpG-RB1”) when compared with tumors of children whose mothers are not homozygous for DHFR19bpdel (OR 2.4; 95%CI: 0.7-7.9; N=58). These RB1 changes include deamination at 11 specific methylated cytosines leading to C-to-T transversions with resulting stop codons and truncated (non–functional) retinoblastoma protein (pRb), or involve RB1 promoter methylation leading to absent pRb and are present in 55% of tumors in children in our pilot study. Our data suggest that mothers homozygous for DHFR19bpdel have children with meCpG-RB1 defects in tumor, conditional on folic acid intake, with higher methylation defects in RB1 with higher intake. We hypothesize that methylation changes detectable in the tumor may reflect susceptibility and exposures present during tumor development.We now propose to examine methylation changes in RB1 in tumor in order to understand the role that DHFR and folic acid may play in retinoblastoma tumor formation.

AIM 1We hypothesize that in retinal development, RB1 is particularly susceptible to genetically regulated variations in natural folate and synthetic folic acid metabolism, and that in tumor DNA, methylation in RB1 and other genes may vary with DHFR genotype and intake suggesting a possible pathway for folic acid associated carcinogenesis.

We propose to examine meCpG-RB1 defects in tumor DNA , DHFR19bpdel genotype (maternal and child) in genomic DNA, and dietary intake data from 225 participants in our case-series

AIM 1a: To examine whether presence of methylation defects in RB1 (meCpGRB1) in a child’s retinoblastoma tumor is predicted by maternal DHFR19bpdel genotype.

AIM1b: To examine whether the relationship between meCpGRB1 in a child’s retinoblastoma tumor and maternal DHFR19bpdel genotype is dependent on maternal folate and folic acid intake.

AIM 2: Illumina 450k methylation array data on pre-treatment tumor DNA from 24 retinoblastoma cases suggest that methylation on RB1 differs depending on maternal genotype for DHFR19bpdel. Tumors of children whose mothers are homozygous for DHFR19bpdel appear to have higher methylation in RB1 than tumors from children of mothers not homozygous for DHFR19bpdel. Our data suggests that this effect varies with maternal prenatal folic acid intake.

In DNA from the 225 retinoblastoma tumors analyzed for Aim 1, using methylation array data we propose to examine the effects of DHFR19bpdel and folic acid intake on retinoblastoma tumor development, using RB1 as a candidate gene.

AIM 2a: To examine whether RB1 is differentially methylated in retinoblastoma tumors differ depending on presence of homozygosity for maternal DHFR19bpdel i

AIM 2b: To examine whether differential methylation of RB1 in retinoblastoma tumors associated with maternal DHFR19bpdel is dependent on maternal folic acid intake

AIM 3 (exploratory): Our pilot data suggest that retinoblastoma tumors may have differential methylation in non-RB1 genes depending on a mother’s DHFR genotype, with potential impact during tumor formation. Delineation of additional differentially methylated cancer associated genes can inform our understanding of tumor development and progression.

AIM 3: Using methylation array data from 225 tumors we propose to examine whether retinoblastoma tumors have differential methylation in additional key cancer regulatory genes depending on maternal genotype for DHFR 19bpdel

a) analylising data from 125 tumors for discovery, and then

b) analysing data from an additional 100 tumors for validation of our initial findings

SIGNIFICANCE

Retinoblastoma is a rare but model disease whose study has led to critical insights into our understanding of carcinogenesis[4]. Incidence of unilateral retinoblastoma varies geographically[5]. In the US, incidence is highest among latino children[6]. Little is known regarding its etiology. Median age for diagnosis of its unilateral form is 23 months, and 11 months for its bilateral form suggesting that tumor genesis begins during fetal development or infancy. In both forms, the disease results from lack of functional retinoblastoma protein pRb due to defects in RB1. Approximately 45% of defective RB1 leading to development of retinoblastoma may be ascribed to aberrant methylation. Constitutive DNA methylation of exonic CpGs in the RB1 gene is potentially a major contributor of point mutations leading to retinoblastoma, with approximately 32% of mutations occurring in CpG sites that spontaneous deamination of 5-methyl cytosine, causes a C toT transition[7] resulting in a nonsense mutation leading to a stop codon[8] An additional 12-16% of retinoblastoma tumors appear to originate from RB1 promoter hypermethylation[9-11]. RB1 is a critical cell cycle regulating gene, and defective RB1 is also implicated in multiple common adult cancers[12-16].

We previously reported that decreased intake of vegetable-derived (natural) folate during pregnancy is associated with higher risk for having a child with retinoblastoma [17]. Recently, we reported that maternal homozygozity for a 19 base pair (bp) deletion in intron-1a of the DHFR gene (DHFR19bpdel) is associated with increased risk for having a child with unilateral retinoblastoma (OR 2.81; 95% CI: 1.32,5.99, accounting for the child’s genotype), and this risk appears specific for mothers consuming prenatal supplements of folic acid [1]. Another study found that a child’s genotype for methionine synthase (MTRA2756G) is associated with increased retinoblastoma risk, though without accounting for maternal genes or diet [18].

DHFR is critical for reducing folic acid and converting it into tetrahydrofolate. Physiologic folate is naturally occurring in some vegetables and other foods, while folic acid is the synthetic form found in fortified foods and vitamin supplements. Homozygosity for the DHFR19bpdel is present in 17-19% of US populations studied and impairs ability to metabolize synthetic folic acid present in fortified foods and vitamin supplements.[3][2] Persons homozygous for DHFR19bpdel[2] were more likely to have high plasma concentrations of unmetabolized folic acid when folic acid intake was more than 500 micrograms(mcg).[2, 19] Folic acid intake of 500 mcg is in the range of the Daily Recommended Intake (DRI)for women of childbearing age and is well below the tolerable Upper Limit(UL) of 1000 mcg.[20] suggesting that women homozygous for DHFR19bpdel may have impaired ability to metabolize even with intake at the DRI. Increased risk for breast cancer was reported in US women homozygous for DHFR19bpdel taking multivitamins[3]. Smaller studies in China and Japan documented DHFR19bpdel homozygosity in 40%[21, 22], suggesting that potential carcinogenic contribution of this polymorphism may be globally important particularly where folic acid intake is higher.

This project proposes to examine the potential contribution of DHFR19bpdel and folic acid intake to the development of methylation related mutations and promoter methylation in RB1 in retinoblastoma.

Synthetic folic acid: Folic acid intake has been rising in the US. In humans, prospective studies have shown that ingestion of folic acid at the UL may contribute to tumor progression in colonic adenomas[23], prostate[24], and lung[25] cancer. In rodent models, folic acid contributes to tumor development when pre-neoplastic colonic lesions are present [26-28], while deficiency inhibits mammary tumor development[29].and prenatal and postweaning folic acid supplementation result in increased mammary tumor development and global hypomethylation [30]. While a recent meta-analysis did not find increased cancer risk (at 5 years) in adult supplementation trials[31] there remain concerns about carcinogenic effect [32]. Fortification is mandatory in approximately 42 countries worldwide, though levels of fortification vary. In the US, since 1998, wheat and corn flour is fortified with 1.4 mg of folic acid /kg, while in Mexico, since 2001, wheat and some corn flour is fortified at a level of 2 mg/kg [33, 34]. Fortification has been controversial, with some arguing for higher levels in the US, while many European countries have decided not to fortify [35, 36] and most Latin American countries fortify flour at the same level as Mexico [37]. After fortification, mean daily food and total folate intake levels are estimated to have increased by 200 mcg/day in the general US population[19, 38-41]. We propose the current study to help understand the contribution of higher intake of folic acid to carcinogenic development.

INNOVATION:

Our series of cases in Mexico is uniquely informative as they are well characterized, arise in a country where exposure levels are high because of common usage of prenatal vitamins and elevated fortification of wheat and corn flour, and in which tumor samples have been collected prospectively prior to administration of chemotherapy.That we are aware, this is the first documentation of a trans-generational effect of maternal genotype on tumor methylation and mutation in a pediatric malignancy.

Although several groups have examined the role of genotype variations in MTHFR and Methionine Synthase [42] in global methylation, that we know of, no other groups have examined the role of DHFR19bpdel in tumor genome methylation. Although one study examined DHFR and promoter methylation of13 breast cancer specific genes [43] it did not examine the homozygous form of DHFR19bpdel and did not examine the relationship with dietary intake. That we know of, no groups have examined DHFR and methylation during organogenesis. Periconception and early pregnancy may be key time points for development of methylation-related changes [44, 45]. The period of retinogenesis may be particularly critical for RB1 in retinoblastoma. Our data suggests that RB1 may be especially sensitive to fluctuations in dietary methyl donors and genetic regulation of their metabolism, and that in circumstances of folic acid fortification and supplementation, RB1 may be susceptible to methylation related changes. Differential methylation of RB1 and other genes in retinoblastoma may yield insight into the role of folic acid in tumor development and progression.

Significance and Translational Impact Understanding the contribution from modifiable risk factors such as folic acid intake is key for informing prevention efforts. If the results of this proposed study demonstrate that RB1 inactivating methylation is predicted by the (rs70991108) DHFR polymorphism as well as folic acid intake, these results may impact policies and recommendations for supplementation including consideration of folic acid alternatives [35, 36, 46] thus significantly affecting both health policy and our understanding of carcinogenesis.

Most epidemiologic studies have not adequately examined the role of maternal genetics combined with prenatal period-specific measurement of synthetic folic acid intake. That we know, our study is the first to document a trans-generational effect on a specific tumor causing methylation change. This multi-pronged approach combining largely existing samples and data with the investigative team’s collective expertise in these measures and their interpretation, contributes to an innovative, timely and efficiently informative study.

The EpiRbMx study (Estudio Epidemologico de Biomarcadores de Factores de Riesgo para el Retinoblastoma Esporadico en Mexico) based at the Hospital Infantil de Mexico Federico Gomez (HIM) and the Hospital de Pediatria of the Centro Medico Nacional Siglo XXI, of the Instituto Mexicano de Seguro Social (IMSS) in Mexico City was founded by Drs Orjuela, Cabrera, and Ponce in 2001 and is a uniquely well characterized population of Mexican children with retinoblastoma which permits examination of prenatal dietary intake with parental and child biomarkers and tumor markers and provides an ideal setting for examining our study hypothesis. Assessment of our aims will help us identify key pathways and/or mechanisms relevant to RB1 and folic acid associated carcinogenesis.. As samples and data are largely readily available, this study will greatly contribute to the literature-to-date in a cost- and time-efficient manner.

Multidisciplinary team: Innovative strengths of this proposed study include that a) analyses will be performed on samples and data that have largely (84%)already been collected as part of a comprehensive prospective study with a well characterized population; b) existing measurements on key covariates such as dietary intake, plasma nutrients, genotype and demographic characteristics; and c) a multidisciplinary team of established investigators with complementary skills and expertise in molecular and nutrition epidemiology, statistical genetics, bioinformatics, molecular biology, methylation, and nutrition science.

Specifically, the PI has critical insight into the biology of folate metabolism and carcinogenesis, and the model proposed here. In addition to the PI, our multidisclipinary team includes experts in basic nutrition science experienced in measurement of folate and folic acid metabolism (Drs Selhub and Paul), experts in maternal/ child nutritional epidemiology in Mexico (Drs Mejia and Villalpando), an internationally renowned expert in retinoblastoma biology and genetics (Dr Gallie) and experts in methylation. Dr Houseman is a recognized expert in novel methods for analysing methylation arrays in cancer outcome population studies and has been a long term collaborator with Dr Kelsey in similar studies. Dr Kelsey is a molecular epidemiologist with expertise in methylation and has been a long time mentor to the PI. Dr Tycko is an expert in methylation in experimental cancer models, while Dr Kung is an expert in epigenetics in cancer therapeutic models. Dr Ponce, a molecular biologist, and Dr Cabrera a pathology expert in retinoblastoma, and Dr Medina a pediatric oncologist specializing in treatment of retinoblastoma have worked together with Dr Orjuela from the beginning of the EpiRbMx study [17, 47, 48]. Dr Liu has been the statistician for EpiRbMx since its beginning.. F Mejia validated the diet instruments used in the study.[49, 50] Drs Paul and Selhub are long standing collaborators with the study. Drs Orjuela, Ponce, Liu, Cabrera, Medina, Paul, Selhub, Mejia, Villalpando, Houseman and Gallie have collaborated to generate the pilot data for this proposal, while Drs Kelsey, Kung, and Tycko have advised in its preparation. The collective expertise of this interdisciplinary team, the uniqueness of the resource with which we will work and the extensive institutional resources available make us ideally poised to carry out the proposed research.

APPROACH

Data available for addressing Aims

Uni

Bi

total

Total cases to be included in the study

155

70

225

Mother-child pairs enrolled,completed FFQ & sample collection (as of Mar 2014)

130

58

188

DHFR Genotype

 

Mother

Available or Under analysis N=105

71

34

188

To send Yr1 for Genotyping N=83

59

24

Child

Available or Under analysis N=99

70

29

188

for Genotyping in Yr 1 N=89

60

29

RB1 Analysis

 

Tumor

Results available N=53

39

14

188

For analysisYr 1 (Toronto) N=135

91

44

Dietary Intake Nutrient Analysis

 

Mother

FFQ already collected

130

58

188

Nutrient intake data will reflect fortification before Yr1 (N=97)

97

0

188

Nutrient intake to be recalculated to reflect fortification, Yr1 (N=91)

33

58

Child

FFQ collected, recalculation nutrients to reflect fortification,Yr1

130

58

188

Plasma Nutrient Level

 

Mother

Available or under analysis N=100

67

33

188

For analysis in Yr 1 to Tufts N=88

63

25

Child

Available or under analysis N=78

51

27

188

For analysis in Yr1 to Tufts N=110

80

30

Additional Cases to be recruited

for DHFR, FFQ,plasma,RB1 measurements

25

13

38

2014, prior to Yr1

12

6

18

inYr1

13

7

20

Tumor DNA for methylation arrays Yr3

155

70

225

Total cases included in the study

155

70

225

Overall Study Design: We will use an efficient case-series design to examine whether genetic variation in metabolism of folic acid is associated with methylation associated RB1 defects in retinoblastoma tumors. Specifically, we will measure maternal DHFR19bpdel and prenatal folic acid intake in development of RB1-specific methylation changes. Our overarching goal is to examine the association between dietary intake of folic acid, homozygosity for the 19bp deletion in DHFR, and methylation changes in RB1 and other key regulatory genes in retinoblastoma. In secondary analyses, we will examine whether associations of RB1 methylation, DHFR and folic acid intake might vary by disease laterality. We will study. tumor and maternal and child blood samples collected at diagnosis, prenatal dietary intake of folic acid in fortified foods and supplements, and the DHFR19bpdel (rs70991108) genotype in 225 participants in our longstanding epidemiologic study in Mexico

Study population: We will use samples and questionnaire data from 225 mother–child pairs participating in our case series study RbEpiMx (Orjuela,PI) in Mexico City. Already collected (in February 2014) are 188 and 18 more will be collected prior to this the beginning of this proposed study. Twenty more will be collected in year 1 of the proposal. Maternal and child blood samples and prenatal and infant diet data were obtained at the time of child’s diagnosis; fresh frozen tumor tissue was obtained at enucleation prior to chemo or radiotherapy. Inclusion criteria Children with histopathologically diagnosis of retinoblastoma, available tumor stored frozen child and mother blood or saliva samples (for genomic DNA), and mother and dietary Food Frequency Questionnaire (FFQ). Exclusion criteria: Children lacking tumor or tumor DNA genomic DNA of mother and child, or FFQ data for mother and child. . For all mothers and children meeting inclusion criteria, we will analyze diet and supplement intake data, and document DHFR 19bpdel genotype and RB1 methylation-associated changes in tumor.

AIM 1a, To examine whether presence of methylation defects in RB1 (meCpG-RB1) in a child’s retinoblastoma tumor is predicted by maternal DHFR 19bpdel genotype.

AIM1 b To examine whether the association between meCpG-RB1 in a child’s retinoblastoma tumor and maternal DHFR19bpdel genotype depends on maternal prenatal folic acid intake

Rationale: DNA methylation appears a major contributor to defects in RB1 that result in retinoblastoma, either through methylation of exonic CpGs in RB1 resulting in disease causing point mutations or through promoter methylation. We have reported that maternal homozygosity for DHFR19bpdel predicts risk of retinoblastoma and hypothesize that this may be associated with development of methylation associated changes in RB1.

Pilot data supporting AIM 1:

Our pilot study examined whether the maternal DHFR 19bpdel genotype is associated with methylation associated changes in the child’s tumor, resulting in either RB1 mutation or promoter methylation causing impaired or absent pRb. We studied 53 tumors in Dr. Gallie’s laboratory in Toronto (Impact Genetics, see below and attached letter). Of these samples 51 (37 unilateral and 14 bilateral disease) currently have data available on DHFR genotypes and nutrient intake and are reported here. Using ASPCR, assayed 11 mutations sites that account for 90% of meCpG mutations in RB1(see methods)[8] These mutations are all recurrent nonsense mutations resulting in arginine to stop codon (CGA>TGA). The hypermutability of CpG sites, is attributed to spontaneous deamination of 5-methyl cytosine, causing a C to T transition.[7] Results of ASPCR mutation analysis in these 51 samples is shown in Table X ASPCR detected meCpG site mutations in both alleles of RB1 in 16 samples (11 unilateral, 5 bilateral), and in one RB1 allele in 7 samples (5 unilateral, 2 bilateral (43.4%) (23/51).. Analyses of >1000 tumors had shown recurrent (CGA>TGA) nonsense mutations in RB1 in 24.6% of bilateral cases and in at least one RB1 allele in 37% of non-hereditary, unilateral tumors.

Table X: meCpGRB1 pilot

Mutation

Sites RB1*

1 allele (+/-)

2 allele

(+/+)

**R251X

1

1

R255X

2

1

**R320X

2

1

**R358X

2

2

R445X

1

2

R455X

0

2

**R467X

3

1

**R552X

2

1

R556X

1

1

**R579X

2

2

R787X

0

0

Promoter^

3

4

*51 tested; **3 tumors had mutations in 2 RxxxX sites

(1 per allele) ; ^35 tested

Additional RB-inactivating methylation related changes occur via methylation of the RB1 promoter. The RB1 gene contains a normally unmethylated CpG-rich island within its 5’ promoter region. Methylation inactivates the RB1 promoter, reducing gene activity [9, 10]. RBF-1 and ATF factors do not bind when their recognition sequences are methylated, resulting in reduced RB1 promoter activity and retinoblastoma in 12% tumors. Promoter hypermethylation can occur on one or both RB1 alleles. Proposed etiologies for this hypermethylation include a mutation far upstream of the gene, a methylation imprint, or an error in methyltransferase .

We tested Promoter methylation (CpG106) [51] in all 35 tumors (26 unilateral, 9 bilateral).that did not have bi-allelic RB1 mutations using methylation-specific PCR:. Promoter methylation was present in 7 unilateral tumors (19%), homozygous and 3 heterozygous (table X). Combining ASPCR and Promoter results, methylation related RB1 changes (meCpG-RB1) inactivated at least one allele of 30/ 51 (58.8%). tumors informative for maternal (and child) DHFR genotype and prenatal supplement intake. Of 33 children whose mothers are not homozygous for DHFR19bpdel, 17 have meCpG-RB1, 13 of 18 children with homozygous DHFR19bpdel mothers had meCpG-RB1.

Table X : Maternal DHFR 19bpdel genotype as predictor for meCpG-RB1

DHFR 19bpdel genotype

Sig.

OR (95%CI)

Maternal 19bpdel homozygous N=51

0.16

2.45 (0.71, 8.43)

Maternal 19bpdel homozygous* N=51

0.11

2.98 (0.78,11.36)

Maternal 19bpdel homozygous Unilateral (N=37)

0.10

3.25 (0.78 ,13.48)

Maternal 19bpdel homozygous Bilateral (N=14)

0.85

1.29 (0.09, 17.95)

*After adjusting for child’s genotype.

Maternal homozygosity for DHFR19bpdel appears strongly predictive that the child’s tumor will have an meCpG-RB1 change irrespective of the child’s genotype. The effect appears stronger in tumors of children with Unilateral disease, though our pilot data includes only 14 children with bilateral disease since prior and current funding has been specifically for unilateral disease The child’s DHFR genotype does not appear to predict presence of one of these an RB1 methylation associated change (in either disease laterality). These 51 tumors described above also have available data on maternal dietary supplement intake during the first trimester of pregnancy, and maternal plasma folate level measured at the time of the child’s diagnosis. Prenatal and infancy FFQ data is available for these children but dietary intake of folic acid from fortified foods is still being calculated and not presently available. We therefore compared the reported first trimester intake of Folic acid supplements for mothers whose children had tumors with and without meCpGRB1 mutations and further examined this comparison separately by maternal DHFR 19bpdel genotype. Mothers whose children have meCpG_RB1mutations appear to have consumed different amounts of folic acid from the mothers of children whose tumors do not have these meCpG-RB1 changes. However, the direction of this differed intake depends on DHFR genotype. Among mothers homozygous for DHFR19bpdel, folic acid supplement intake is higher among those whose children’s tumors have meCpG-RB1 changes, while for mothers not homozygous for DHFR19bpdel, the pattern is inverted with lower folic acid intake among those with meCpG-RB1 changes. We examined maternal plasma levels of folate obtained at the time of diagnosis as a proxy for plasma levels during pregnancy, assuming that levels at diagnosis reflect variations in metabolism, and because first trimester folic acid supplement intake in our population is significantly correlated with maternal plasma level at time of diagnosis (r=0.112, p<0.05). Maternal plasma concentrations (measured by microbial LC assay in the laboratory of Drs Selhub and Paul) are shown in Table X. A similar pattern is observed to that observed with prenatal first trimester folic acid supplement intake.

Table x: Comparison of Maternal folic acid supplement intake and Maternal plasma folate levels (at diagnosis) between children with & without meCpGRB1

Maternal DHFR 19bpdel

Number meCpG-RB1

Alleles

1st trimester Folic acid^ µg/day

Mean (SD)

Maternal folate ng/µl

Mean (SD)

Not homo-zygous 19bpdel

none (N=17)

426.67 (689)

*12.15 (8.61)

1 or 2 ( N=16)

93.33(241)

*7.46(5.59)

Total N=33

260.00 (XX)

9.88 (7.57)

Homo-zygous

19bpdel

none (N=5)

45.33 (101)

*6.05 (5.77)

1 or 2 (N=12)

164.40 (229)

*12.31(10.15)

Total N=17

131.32

10.47 (9.37)

*difference p<0.05 by Mann-Whitney; ^ folic acid from supplements

Among mothers homozygous for DHFR19bpdel, plasma folate concentrations are significantly higher in mothers whose children’s tumors have meCpG-RB1changes, while among mothers who are not homozygous for DHFR19bpdel, the inverse is true, with significantly lower plasma folate concentration in mothers whose child’s tumor has meCpG-RB1 changes).

U-shaped model: A recent study of pancreatic cancer in the European EPIC cohort suggests that cancer risk associated with folate is actually characterized by a U-shaped curve with increased risk when plasma folate concentrations are below 5 or >20nmol/L.[52] Other work in colon cancer has suggested a similar phenomenon where both scarcity and excess may predict increased risk [53, 54]. A similar U-shaped model involving the DHFR polymorphism might be relevant for retinoblastoma and methylation associated changes in RB1.

METHODS for addressing AIM1: To address AIM1a, we propose to utilize data from 225 participants in our EpiRbMx case-series in order to examine meCpGRB1 in tumor DNA using ASPCR and promoter methylation, examining DHFR19bpdel genotype (maternal and child) in genomic DNA. To address AIM1b, we will use the same markers as in AIM1a, but will also calculate prenatal folic acid intake using dietary intake data in order to examine the effect of maternal DHFR19bpdel by folic acid intake, and will examine the effect of the child’s intake.in infancy with the child’s DHFR19bpdel.

Laboratory analyses for addressing AIM 1: Initial sample separation and storage occur in the laboratory of Dr. Ponce at the IMSS in Mexico City where there is a dedicated -70C Revco for this study. Plasma and DNA aliquots are prepared and inventoried and then transported to Dr Orjuela’s laboratory (Columbia) where they are inventoried, aliquoted, diluted (DNA), and prepared for shipment to Tufts, and Impact Genetics for analysis, in the same manner done to generate the pilot data. All plasma samples are maintained at -80C throughout their transportation. .All laboratory personnel are blinded to sample identifiers.

Measurement of LC folate: Total folate from plasma will be determined using a microbiological assay with Lactobacillus casei [55, 56] in the laboratory of Jacob Selhub and Ligi Paul at the USDA laboratory for Human Nutrition Research at Tufts University. Every batch will contain quality control standards of known concentrations of folate in duplicates.

DHFR genotype for rs70991108 is already available on a large proportion of samples (Table X). for the remainder of mother and child pairs, genotyping will be conducted in the Selhub laboratory using methods previously established in this laboratory for assessing rs70991108 [2], with 10% of samples randomly chosen to test for reproducibility and analyzed as blind duplicates.[2] We are focusing our analyses on SNPs that have been shown to modify disease risk based on folate status [1] and hence will not be looking at other one carbon pathway SNP’s. In our secondary analyses we will also account for maternal and child presence of MTHFR C677T which can affect global methylation, given known high prevalence in Mexico (23% homozygous TT) [57]. We have MTHFR genotyping already on most of our cases and mothers [1].. We will perform genotyping for MTHFR C677T on the remainder of our study population using Taqman allelic discrimination assay with primers and probes designed for the polymorphic region available from Life Technologies (CA) using 7300 real time PCR equipment. For quality control the PCR products of 5 randomly selected samples will be sequenced at Tufts DNA sequencing core facility to confirm genotype results.

Tumor samples fitting our inclusion criteria are already available from 188 children participating in EpiRbMx who underwent enucleation of an affected eye as part of their clinical management. Criteria for enucleation usually include loss of useful vision in the affected eye or recurring tumor. About 90% of cases are enucleated at the HIM. Dr Cabrera ensures that the enucleated eye is processed appropriately to permit preservation of tissue not needed for diagnostic purposes. Tumor is frozen at -70° C at the HIM and then stored in the laboratory of Dr. Ponce. Tumor is unavailable for a few children enucleated before coming to HIM, or who did not have an enucleation for other clinical criteria. Those children are excluded from this study.

Analyses for RB1 will be carried out by Impact Genetics (formerly Retinoblastoma Solutions),founded in 1999 and a world leader in retinoblastoma genetic testing (see letter of support and detailed quote) directed by Brenda Gallie, genetic scientist and clinical ophthalmologist and co-Investigator on this proposal. Their RB test sensitivity is presently 96%. The following four methods constitute the screening methodology for RB1 mutation detection in retinoblastoma tumors at Impact Genetics that will be utilized on our samples. [58].

Allele-specific PCR (AS-PCR) is used to detect eleven recurrent nonsense (CGA→TGA) mutations in the RB1 gene: p.Arg251X, p.Arg255X, p.Arg320X, p.Arg358X, p.Arg445X, p.Arg455X, p.Arg467X, p.Arg552X, p.Arg556X, p.Arg579X, and p.Arg787X[8]. AS-PCR is done near the beginning of analysis, and identifies the above nonsense mutations in over 22% of tumors, eliminating the need for intensive sequencing in these tumors. The AS-PCR screen consist of four multiplex reactions; each reaction uses a Qiagen multiplex hot-start reagent, specific mutant primer sets and highly optimized conditions that allow amplification only when one of the mutations in the multiplex group is present. For each recurrent mutation assessed by AS-PCR, either the 5’ primer, or the 3’ primer, has the mutated base (T instead of C) at the final 3’ primer position; the opposite primer has normal RB1 sequence. Amplification only occurs when the mutation is present, and is detected by agarose gel electrophoresis; the identity of the mutation is determined by the size of the product. Each reaction is run in conjunction with an internal PCR control to demonstrate amplifiable DNA and includes a diluted positive control for each mutation in the multiplex, as well as normal samples as specificity controls, yielding no PCR band. All positive results are confirmed by sequencing the exon of interest, which also establishes whether the mutation is homozygous, heterozygous , or hemizygous in the tumor DNA.

Methylation of the RB1 Promoter: The RB1 gene contains a normally unmethylated CpG-rich island within its 5’ promoter region. Methylation of the RB1 promoter is an epigenetic change that inactivates the promoter and reduces gene activity [9, 10]. Promoter hypermethylation can occur on one or both RB1 alleles. Impact Genetics uses a PCR-based non-radioactive method to identify hypermethylation of the RB1 promoter in CpG region 106 [51, 59]. Small quantities of denatured genomic tumor DNA are treated with bisulfite to convert all unmethylated cytosines to uracils, leaving only abnormally methylated cytosines in CpG dinucleotides unaltered. After bisulfite conversion, a methylated RB1 allele differs from an unmethylated allele in nucleotide sequence in a number of CpG positions. The 5’ RBmet primer has been designed to bind only to the DNA first round strand derived from the methylated allele, and yields a 201- bp product. Primer Rbunmet is designed to bind further downstream from Rbmet, and will only bind to the DNA first-round strand generated from the unmethylated RB1 allele, resulting in a 154 bp product. The downstream 3’ primer (Rbcom) is designed to bind to the bisulfite treated DNA regardless of methylation status. Binding of Rbcom to a methylated or unmethylated allele, respectively, results in different size PCR products. Methylated and unmethylated RB1 alleles are determined by size on agarose gel. Unmodified genomic DNA is not amplified under test conditions. Each run includes homozygous and heterozygous methylated controls, as well as normal controls, and untreated controls. Comment by manuela: BRENDA, Is this perhaps pRb activity?

Tumors not found to have either promoter methylation or ASPCR mutations will be analysed further using either Quantitative multiplex PCR or Sequence analysis or Next Gen sequencing in order to determine the types of RB1 changes present, using methods previously established at Impact Genetics.

Quantitative multiplex PCR (QM-PCR): detects large, single-exon or multi-exon RB1 gene deletions or duplications, which lead to retinoblastoma in over 15 % of unilateral retinoblastomas[60] , and which are not detected by sequence analysis. As well, QM-PCR can detect small deletions and insertions in about 18% of retinoblastomas, visible as changes in PCR product size; these small indels are subsequently confirmed by sequencing. QM-PCR can eliminate the need for intensive sequencing in approximately 30% of samples. All 27 RB1 exons and core promoter region are amplified in three to five multiplex groupings under conditions that allow quantitative amplification (19 amplification cycles), so that size and copy number of each exon can be determined. Each exon is amplified using one unlabelled primer and one Cy5.5 labelled primer. The Qiagen Multiplex. Amplified products are mixed with loading dye, and run on polyacrylamide gel on Long-Read Tower sequencers (Siemens). Calculation of peak areas is performed by GeneObjects software (Siemens/VGI). Ratios of RB1–derived peaks to the internal control peaks are used to calculate gene copy number in relation to a known 2-copy RB1 calibration control. QM-PCR test measures MYCN genomic copy number in any tumor sample without an RB1 mutation [58].Comment by manuela: BRENDA , I need to shorten this, is there a reference I can list and just summarize in one brief sentence?

Sequence analysis: Impact Genetics sequences the core promoter, exons 1 through 25 and nearby flanking intronic regions (from -16 to +7), to detect point mutations, splice mutaitons and small insertions and deletions. Duplex PCR reactions amplify pairs of RB1 exons using the AmpliTaq DNA polymerase kit (Applied Biosystems) or the Invitrogen Platinum High-FidelityTM kit. Each exon is then sequenced using a Cy 5.0 labelled sequencing primer, with unlabeled terminators and ThermoSequenaseTM (USB)DNA polymerase, containing pyrophosphatase to prevent pyrophosphorolysis, thus allowing even peak heights. Termination mixes are prepared with dNTP : ddNTP concentration ratios (300:1). Sequencing products are then run on Long-Read Tower (Siemens) sequencers and are compared to wild type RB1 (Genbank accession #L11910.1) for sequence alterations, using OpenGene and GeneLibrarian software (Siemens)8. Sequences are also visually inspected to ensure good quality sequence over the whole exonic area. Our lab uses literature searches, amino acid conservation analysis, splice score analysis and our extensive experience and knowledge of RB1 mutations in determining the significance of any variant identified.Comment by manuela: BRENDA, Similarly, can you advise how to shorten this since we are not focusing onthis and could mention with less detail?

Next Generation Sequencing The RB1 gene is screened for the presence of small indels (less than 10bp) and point mutations by next generation sequencing. The target sequence, RB1 coding exons plus 25 bp of flanking intronic sequence, is enriched using molecular inversion probes and run on Illumina’s MiSeq, using the v2 2x150bp kit. We use SeqMan NGen and SeqMan Pro software (DNAStar) for alignment and variant calling.

Questionnaire Data. Upon enrollment, parents of participating children were interviewed using a detailed questionnaire collecting information on non-dietary factors including parental age at conception and pregnancy, education levels, occupations, self-reported income and alcohol intake during pregnancy (reported in <5%).

Dietary intake for assessing folic acid intake has been collected using FFQ designed and validated specifically for this study population [50, 61]. Existing nutrient content tables in Mexico do not fully account for folic acid from fortified wheat and corn flour. As part of an ongoing study (R21CA167833), we are in the process of updating the nutrient content tables to more accurately reflect fortification such that folic acid intake can be calculated for our study population accounting for the synthetic folic acid content of industrialized and non-industrialized foods consumed. For most mothers of children with unilateral disease, nutrient content for their dietary intake during pregnancy and lactation will already be updated to reflect these new values before this proposed study begins. However we will need to recalculate nutrient intake using the updated food composition tables for mothers not included in currently funded study (see table X) such as mothers of bilateral cases as well as more recently diagnosed unilateral cases. Nutrient content from intake during the first 2 years of life will also need to be recalculated for all 225 children whose tumors are included in this proposal.

We will calculate nutrient intake for study mothers, for each trimester, and for the current diet, and for children for the first 2 years of life in order to estimate intake of naturally occurring folate and synthetic folic acid, for each period. The measurement of folate will be quantified into the following forms: Total folate Dietary Folate equivalents (DFE) (combination of synthetic folic acid and natural folate using the equation: [mcg of food folate + 1.7 x mcg folic acid] as folic acid is more bioavailable) [20]. Dietary Folic acid (includes only the portion of folic acid from enriched/fortified foods; sources post 2001). Dietary Natural Folate (includes only non-synthetic forms of folate, e.g., fruits, vegetables). Intake of each of the 3 forms of dietary folate from a given food will be calculated by multiplying the portion size, the daily frequency of intake, number of servings/day and the nutrient content per serving. Supplement intake noted by brand, dose and frequency will be calculated using the INSP compendium of Mexican supplements.[62] Total (supplemental and dietary) folic acid intake will be calculated by summing contributions from fortified foods and supplements. The daily nutrient intake for each study subject and time period will then be calculated by summing across all food items. Energy-adjusted intakes will be calculated for each nutrient using residual methods[63].

FFQ: The semi-quantitative FFQs used for our study were designed by INSP experts in maternal -infant diet for use as an interview for mothers of limited literacy. The FFQ are designed for retrospective collection of prenatal diet and diet in the first 2 years of life at up to 6 years post partum. Both FFQs capturing Supplement intake querying on brand, dose, frequency and duration of intake for each time period. The validation study of these FFQ was performed in participants from a large prospective study of diet during pregnancy which was carried out prior to fortification[50, 61, 64, 65] . The 73-item prenatal FFQ is divided into 3 sections: 1) FFQ-month, queries women regarding diet intake during the last month (“current” diet)[64]; 2) FFQ-pregnancy, examines differences between current dietary intake and intake during each trimester using the current diet as reference. 3) FFQ-supplement queries on supplement intake during each trimester and in the 3 months pre-pregnancy. Food items were selected based on energy and micronutrient contribution from 24hr recalls from 18,311 women of childbearing age participating in the Mexican National health and Nutrition survey.[66] In our study, all FFQs are administered in person by highly trained interviewers using visual props to facilitate quantifying portions.[61] Median values of dietary, supplemental and total folate equivalents per trimester in mothers in our study were 268.5 mcg/d, 89.4 mcg/d and 456.4 mcg/d in the 1st trimester; 261.9 mcg/d, 453.3 mcg/d and 773.2 mcg/d in the 2nd trimester; 254.4 mcg/d, 97.1 mcg/d and 567.4 mcg/d in the 3rd trimester. However, these values do not account for fortification. In the current diet <7% mothers took vitamins, thus median total and dietary food folate were equal at 238.9 mcg/d. In our validation[61], Pearson correlation coefficients for estimates measured with 24hr recalls and the FFQ-pregnancy were 0.26 (p<0.05) for energy adjusted dietary folate, and 0.50 (1st trimester), and 0.73 (3rd trimester) for energy adjusted total folate (diet and supplements).

FFQ Child is composed of 3 parts and administered to mothers (see appendix). FFQ-Yr1 queries mothers on the child’s diet during infancy (from 0-11 months of age), FFQ-Yr2 queries on diet during 12-24 months of age, and FFQ-Supp queries on supplement intake in both years . Mothers are asked how many times per day their child ate each food item and whether the item was industrialized.. FFQ-Yr1 includes questions designed to estimate complimentary feeding practices to infer the timing of the introduction of foods in infancy, as well as to adjust for the starting month of food consumption for each type of food, when calculating energy and nutrient estimates. Mothers are queried regarding the child’s diet until diagnosis. If a child is less than 13 months old at diagnosis FFQ-Yr2 is not administered. Median daily intake for total folate (not including synthetic folic acid from fortified foods) was 66.2 mcg (IQR 32.4, 132.4) in year 1, and 240.3 mcg (IQR 150.1, 413.2) in year 2

Diet Exposure variables: The FFQs will be used to construct variables for the intake of synthetic folic acid as the primary predictor. We will also calculate intake for naturally occurring folate, as well as the other methyl donors (betaine, choline, methionine), and methylation pathway cofactors B6 and B12 for both children and mothers. The main predictor of infant nutrient intake will be derived from the infants own intake(FFQ-Yr1), after taking into account maternal nutrient intake during lactation, the number of months the child was reported with exclusive breast feeding, and the number of months during which the child received breast milk in addition to foods [partial breast feeding = months total duration of breast feeding – months of exclusive breast feeding]. We did not attempt to quantify breast milk intake. Based on our prior studies, we assume that the production of breast milk will not be affected by maternal nutritional status and will estimate folate content in breast milk based on prior measures [67]. For the second year, intake will be derived from the FFQ-Yr2.

Data Management We will utilize an existing adaptable secure relational database structure created for the EpiRbMx parent study which is linked to an inventory database.

Statistical analysis for AIM 1: We propose to examine meCpGRB1 defects in tumor DNA, DHFR19bpdel genotype (maternal and child) in genomic DNA, and dietary intake data from 225 participants in our case-series to test whether in AIM1a) children with meCpG_RB1 mutations in their retinoblastoma tumors are more likely to have mothers who are DHFR19bpdel homozygous; and in AIM 1b, whether presence of meCpGRB1 in a child’s retinoblastoma tumor will be associated with maternal DHFR genotype depending on mother’s folic acid intake during the first trimester. We expect that meCpG_RB1 will be present either when total folate intake (from natural and synthetic) is very low and DHFR is not homozygous delete, or when synthetic folic acid intake is high and DHFR is homozygous delete.

Analysis will begin with examining the distribution of all variables. To examine bivariate association between variables, scatter plot and Spearman correlation coefficient will be used for quantitative variables; cross-tables and Chi-square test for categorical variables; box-plot and Kruscal-Wallis test for difference between categories of a categorical variable. Proper transformation will be applied to factors with skewed distribution to reduce the impact of extreme values in hypothesis-specific regression analysis.

For AIM 1a, logistic regression models will be used for binary outcome of presence of methylation related mutations affecting RB1 in child’s tumor with main predictor for maternal DHFR19bpdel genotype, with and without controlling for child’s DHFR19bpdel genotype. For AIM 1b, we will first examine the distribution and calculate summary statistics for the two variables of prenatal folate and folic acid intakes levels (total intake and fortified FA) by RB1 mutation and maternal DHFR19bpdel genotype (presence vs. absence), then examine the differences in prenatal folate and synthetic folic acid intake levels between children with and without RB1 mutation using T-test or Wilcoxon rank sum test for those with maternal DHFR19bpdel and those without separately. Linear regression model will be applied to the continuous measure of prenatal folate and folic acid intake (Y, transformed as appropriate) with main predictor X indicating groups for RB1 mutation status by DHFR19bpdel genotype. Particularly, X=1 for absence of meCpGRB1 and.maternal DHFR not homozygous delete, X=2 for presence of meCpGRB1 and.maternal DHFR homozygous delete, X=3 for absence of meCpGRB1 and.maternal DHFR homozygous delete, X=4 for presence of meCpGRB1 and.maternal DHFR not homozygous delete as a reference group. To detect specific group differences we will examine the model, E(Y) = β0 + β1I(X=1) + β2I(X=2) + β3I(X=3), where I() is the indicator function taking values 0 or 1, and parameter βk indicates mean difference between group k and the reference group. We will also fit the model E(Y) = β0 + β1I(X=1) + β2I(X=2), with groups X=3 and X=4 combined to be a reference category. Then the parameters of interest are β1 and β2. To examine the pattern in the odds of meCpGRB1 presence we will apply the logistic model log [P(D=1)/P(D=0)] = (β0 + β1 Z) I(G=1) + (β2 + β3 Z) I(G=0), where variables D=1 is for meCpGRB1 presence, 0 else; G=1 for maternal DHFR homozygous delete, 0 else; and Z is for a continuous measure of maternal folic acid intake. Parameters of interest are β1 and β2 for effect of folic acid intake among mothers with and without DHFR19bpdel genotype. As a secondary analysis, we will repeat the analysis using child’s folic acid and folate intake and DHFR19bpdel genotype to replace the variable for maternal folate and folic acid intake during pregnancy. We will also examine the correlations between maternal current plasma level, current folic acid intake and folic acid/ foate intake during pregnancy. If they are correlated, we will explore the pattern in DHFR genotype specific association between measures for current folic acid intake, as a surrogate for long term folic acid and folate exposure, and presence of meCpGRB1 by repeating the analysis with the variable for folic acid intake during pregnancy being replaced by the surrogate variable for long term folate exposure.

Statistical Power: For AIM1a, assuming that 35.29% of mothers are homozygous for DHFR19bpdel, and that as seen in the pilot data, among tumors from children whose mothers are homozgous DHFR19bpdel, 72.22% had meCpG_RB1 while among tumors from children whose mothers are not homozygous for DHFR19bdel, 50% tumors had meCp_GRB1, a sample size of 225 will enable a two-sided test with power of 80% to detect an OR of 2.27 at a significance level of α The minimum detectable effect size is smaller than the observed OR=2.45 in pilot data from 51 mothers. A sample size of 155 unilateral cases may have 80% power and α to detect an OR=2.70, smaller than OR=3.25 estimated with data from 37 mothers of unilateral cases. This suggests a sufficient power to detect the effect. For AIM1b, we will test for difference between specified groups of DHFR19bpdel genotype and meCpG_RB1 in folate and folic acid intake variables in linear models. With a sample size of 225, one-way ANOVA for a folic acid variable may have power of 80% to detect minimum variation in group means of 0.222 within group standard deviation (SD) for four specified groups, and 0.208 SD for three specified groups. Both are smaller than observed 0.423SD and 0.437SD in pilot data of maternal folic acid intake during pregnancy (with variance stabilized transformation) from 51 mother-child pairs, indicating that we have sufficient power.

Disease laterality: In addition to the primary analyses where we will combine all cases, we will also repeat the above analyses to explore laterality specific (unilateral , bilateral ) effect of DHFR on meCpG_RB1..

AIM 2: To assess whether maternal DHFR genotype predicts differential methylation on arrays using RB1 as a candidate gene, and to assess whether the association varies with reported prenatal folic acid intake

Rationale We hypothesized that maternal genotype for DHFR19bpdel would predict differential methylation in RB1 on tumor methylation arrays, and that this differential methylation would be dependent on

Array Pilot Characteristics

(n/N)

RB1 RxxxX (byASPCR)

None

11/24

1 Allele

4/24

2 Alleles

9/24

RB1 Promoter Methylation*

one allele

2/15

Both alleles

2/15

DHFR 19bpdel

Mother Homozygous 19bpdel

9/24

Child Homozygous 19bpdel

7/24

Trimester 1 Folic Acid intake by Maternal DHFR19bpdel

Mother Homozygote, High intake

4/9

Mother not Homozygote High intake

6/15

*only tested in samples that did not have RxxxX mutation in both alleles1 N = 24, 9 Males; 15 Females

first trimester folic acid intake. We hypothesize that methylation changes in the tumor may reflect the prenatal environment in which the tumor developed.

Pilot data supporting AIM2 We hypothesized that maternal genotype for DHFR19bpdel would predict differential methylation in RB1 on tumor methylation arrays, and that this differential methylation would be dependent on first trimester folic acid intake. DNA from 24 tumors that had been analysed for meCpGRB1 (Gallie lab) was assayed with the Illumina 450K methylation array (at Roswell Park). Data was analysed to examine whether RB1 is differentially methylated depending on maternal genotype and prenatal folic acid intake. Tumor DNA were compared by Maternal genotype for DHFR 19bpdel, comparing homozygous 19bpdel with non-homozygous 19bpdel. Prenatal folic acid intake in the first trimester was classified as “high” if mothers took folic acid containing supplements in the first trimester and reported eating multiple daily servings of foods made with fortified flour including bread, tortillas, and cereal, or “low” if they did not. Since the nutrient content is not yet available this classification was approximated based on number of servings of fortified foods reported consumed.

Figure 3. Shows a heat map showing CpG sites in RB1 and array results for the 24 tumor samples in our pilot RB1 CpG’s are listed progressing from promoter to body with color coded region annotation. Blue or dark shows relative hypermethylation. Hypermethylation in the RB1 promoter regions (TSS200,1500)is evident in 4 tumors (see circle in cluster) corresponding to 4 children with mothers with DHFR 19bpdel homozygous with first trimester folic acid intake classified as high, when compared to the other tumors corresponding to children with mothers homozygous for DHFR19bpdel who consumed low folic acid in the first trimester, or were not homozygous for DHFR19bpdel. These cases correspond to children with unilateral disease with promoter methylation detected on the PCR based assay. Figure 4 shows the volcano plot for differential methylation in RB1CpGs comparing tumors of children with mothers homozygous for 19bpdel with high folic acid to tumors of children with mothers not DHFR19bpdel homozygous. The p value is for permutation across the 52 CpGs in RB1. The 4 children with differentially hypermethylated CpG’s in the RB1 promoter are also themselves homozygous for DHFR19bpdel, though others who are homozygous do not appear differentially hypermethylated but we are unable to estimate child intake infancy at present without updated nutrient content, because of the complexities of infant intake.

Figure 3CpG sites in RB1 by Maternal DHFR19bpdel

Figure 4 RB1 CpGs by DHFR-M &intake

Impact and Significance

Our pilot suggests that CpG sites throughout the promoter region in RB1 are differentially hypermethylated in tumors of children whose mothers are homozygous for DHFR19bpdel and consumed high folic acid compared with tumors of those whose mothers are not homozygous.

Further exploration of this finding may help better characterize the window of susceptibility, but suggests that prenatal exposure is relevant to tumor formation. Our pilot data further suggest that the RB1 promoter may be preferentially hypermethylated in tumors when maternal DHFR is homozygous delete particularly in the presence of high folic acid. The RB1 promoter is known to be diffusely hypermethylated in retinoblastoma tumors demonstrating promoter hypermethylation [11] Our model may be of additional relevance for other tumors in which RB1 is mutated or in which the RB1 promoter may be hypermethylated, (including small cell lung cancer, bladder cancer, and osteosarcoma). Of these lung cancer is notable because of the finding of increased risk associated with taking folic acid supplements [25]. Our findings may be especially relevant for other populations in which wheat and corn flour are fortified at levels similar or even higher than legislated in Mexico including many Central and South American countries, or where supplement use is widespread. Although our findings above are most striking for the differentiaI methylation of RB1 in association with maternal diet and DHFR19bpdel, if we find differential methylation in tumors of children with bilateral disease by the child’s genotype, this may have implications for better understanding the development of subsequent tumors and secondary malignancies in these children who are at lifelong risk of subsequent malignancies.

AIM 3 To explore whether maternal DHFR genotype predicts methylation in other key cancer regulatory genes and whether this association varies with reported prenatal folic acid intake .

Rationale We hypothesize that homozygosity for DHFR 19bpdel may lead to differential hypermethylation in the promoters of other genes involved in tumor progression and that such differential methylation may have implications for tumor development and response to therapy. In addition, although maternal DHFR19bpdel may be associated with differential methylation of RB1, and other genes relevant in early tumor formation, it is also relevant to explore the possible role of the child’s genotype and dietary intake when evaluating the role DHFR19bpdel may have in tumor progression and response.

Preliminary data for Aim 3 We examined our pilot data of 24 arrays (described above) to compare whether there is differential methylation of the promoter region of other key cancer regulatory genes, restricting to those with the largest differential coefficient. The data were examined similarly to Aim 2, in which the reference group

Table X: Cancer related Genes with differentially methylated CpGs by mother’s DHFR19bpdel

Gene

cgsite

Group

coef

pval

NAME

RB1**

22766818

TSS200/1500

4.811

0.000

Retinoblastoma

SEPT10

21563597

TSS200

2.53

0.042

septin 10

NAPRT1^

08508337

TSS200

2.38

0.065

nicotinate phosphor-ribosyltransferase

PTEN

16687447

5’UTR; TSS200

1.87

0.081

phosphatase and tensin homolog

EI24

13607511

TSS200

1.81

0.055

etoposide induced 2.4

DBNDD2

18500556

TSS200;5’UTR

1.64

0.033

dystrobrevin binding protein1DC 2

TLE3

09732150

TSS200

1.62

0.186

transducin-like enhancer of split 3

**RB1 appears 16 times; coefficient range 4.81-2.56,2.03, 1.61, ^ appears twice

were tumors of children whose mothers were not DHFR19bpdel homozygous Table X shows those cancer related genes with the highest coefficient for hypermethylation of CpGs in the promoter region in tumors of children with mothers homozygous DHFR19bpdel. Although consistent with our findings shown above, CpG sites in RB1 appear to be the most differentially hypermethylated (17 of those with largest coeffficients are in RB1). CpG sites in promoter regions of other genes potentially relevant in cancer progression or therapeutic response appear differentially hypermethylated. These genes include the tumor suppressor PTEN [68, 69].and the putative tumor suppressor El24, an immediate early induction target of p53-mediated apoptosis[70]. Two other genes potentially involved in inhibiting apoptosis have differentially methylated CpG’s: DBNDD2, [71]. and NAPRT1 [74, 75]). a coenzyme in cellular redox reactions and stress responses. TLE3 which encodes a transcriptional co-repressor protein, acting in the Notch signaling pathway [76] , and SEPT10 encoding a septin family of cytoskeletal proteins with GTPase activity predicts increased sensitivity to paclitaxel[77]).

Notably absent was SYK recently described to have promoter histone modification in retinoblastoma tumors [78] . We also hypothesize that cancer specific genes may have differentially methylated CpGdepending on a child’s DHFR19bpdel. Several cancer genes that appear differentially methylated when examined by mother’s genotype also appear differentially methylated by the child’s DHFR19bpdel. If we find differential methylation in tumors of children with bilateral disease, our result may have therapeutic implications given their risk for development of subsequent tumors and secondary malignancies.

AIM 3 Using data from methylation arrays from 225 tumors we will explore whether tumors in children who mothers have DHFR 19bp deletion have differential methylation in promoters of additional key cancer regulatory genes analysing 125 tumors for discovery, and then analysing data from 100 tumors for validation of our initial findings.

The two data sets will have the same proportion of uni and bi-lateral tumors.

Methods for Aims 2 and 3

Methylation Arrays In the same manner done to obtain our pilot data, we will prepare and send 1ug of high quality DNA (via picogreen quantitation), from 225 samples to Roswell Park (see letter) on carefully distributed 12 sample batches for analysis of DNA methylation using the HumanMethylation450 BeadChip and Infinium assay. Each array contains >450K highly informative CpG sites covering 99% of RefSeq genes including promoters, 5'UTR, first exons, gene body and 3'UTRs. 96% of all known CpG islands are covered, along with CpG sites outside of CpG islands, Non-CpG methylated sites, FANTOM 4 promoters, miRNA promoters and DNase hypersensitive sites combining Bisulfite conversion of genomic DNA and whole-genome amplification sample preparation with direct, array-based capture and enzymatic scoring of the CpG loci. Samples are processed for array analysis using the Infinium methylation assay, as per Illumina's protocol. Following bisulfite treatment of 500ng genomic DNA using the EZ DNA Methylation kit (Zymo, Inc.), the bisulfite-converted DNA samples are chemically denatured and neutralized, enzymatically fragmented then loaded onto the HumanMethylation450 BeadChips and hybridized, washed, labeled, stained, and scanned with the Illumina iScan Reader. The image data is processed with Illumina GenomeStudio, with validation of assay controls and report generation. The level of methylation for the interrogated locus is determined by calculating the ratio of the fluorescent signals from the methylated vs unmethylated sites.

Data analysis for Aims 2 and 3 will be carried out by the biostatistics post-doctoral researcher at Columbia under the direction of Dr Houseman utilizing the High Performance Computing facility at Columbia. We will perform standard normalization and QA/QC procedures on the 450K array data, using the R package minfi. We will omit CpGs on the sex chromosomes (chromosome X = 11,232 and chromosome Y = 416) as well as CpGs that contain an annotated SNP in the CpG site (N=16,756), at the single base extension site (N=7,880) or in the probe itself (N=88,680). Quantile normalization will be performed on the M and U channels separately. All statistical analysis will be performed on the logit (M-value) scale, log2(M/U), although results will be visualized on Illumina's beta scale, M/(U+M). Arrays will subsequently be adjusted for BeadChip batch effects using the ComBAT algorithm [79] if necessary. Principal components reflecting residual confounders will also be removed (e.g. [80]). The limma procedure [81] will be used to fit linear models on the logit (M-value) scale.

For Aim 2, we will restrict analysis to the 52 CpGs mapped to the RB1 gene (and satisfying the above criteria) and inference will be achieved by permutation test (i.e. permuting the phenotypes relative to the array data as well as surrogate variables and non-genetic confounders). Models for mother’s genotype will include mother’s genotype coded as homozygous null (0) vs. other (1). Effect modification by dietary folic acid will be addressed by adding a term for folic acid consumption (in the original units or else categorized as above or below the RDI[20] and its corresponding interaction with genotype. Models for the child’s genotype will be handled similarly. Additionally, we will attempt to stratify by disease laterality (uni-/bi-lateral) by conducting separate analyses for each disease type.

For Aim 3 we will conduct analyses similar to Aim 2 but using nearly half (55%) of the arrays (n=125) and all 377,785 autosomal CpGs lacking nearby SNPs. Resulting p-values will be transformed to q-values via the R package qvalue. We will use the remaining n=100 to confirm the findings from the initial genome-wide scan, selecting those CpGs with q < 0.05 or else (if there are a large number of such CpGs) the maximum number of CpGs that can be tested (at 80% power and 5% Type I error) with n=100 subjects, assuming Holm/ Bonferroni adjustment. Note that we are extremely well-powered to achieve Aim 2, as the pilot data already show p < 0.0001. Even averaging the data over all 52 CpGs (which diminishes the overall effect size by contaminating the strong promoter effect shown in Figure 3 with null exon-effects) results in a t-test p-value of p = 2.0 x 10-9, translating to power = 1 for n=225. Even at effect sizes 20 times lower it would still be possible to test ~3000 features with n=100 at 90% power with Bonferroni adjusted Type I error = 0.05. Thus we anticipate being able to find and validate all effects at other loci that have effects on the same order as RB1.

For those cancer specific genes confirmed to have differential hypermethylation in the validation set, future plans include using bisulfite Nextgen sequence validation in an independent group of informative samples utilizing the infrastructure created through the global collaborations in place through Impact Genetics.

Summary

Our preliminary data suggest that DHFR and folic acid intake may influence development of methylation associated mutations in RB1 and may impact tumor methylation overall. If confirmed in a larger sample size, this could suggest alternative strategies for targeted prevention and therapy in these tumors and has implications for our understanding of folic acid as a tumor promoter or co-carcinogen. This work includes examination of other gene-specific methylation changes associated with impaired metabolism of folic acid and has the potential for improving our understanding of mechanisms through which carcinogenesis may be increased or facilitated by folic acid. Our disease model may be relevant for other tumors in which RB1 is mutated. Our preliminary data suggest that documentation of gene-specific and tumor epigenome wide methylation combined with documentation of this common variant of DHFR, and dietary intake will be informative for delineating the role of folic acid and folate intake as a contributor to RB1 associated carcinogenesis . We propose this cost efficient project using largely existing samples and data. Figure x shows our proposed 5 year timeline. The EpiRbMx represents an ideal population for elucidating the complex relationship between folic acid intake and RB1 mutagenesis. Our well characterized population which includes genomic DNA as well as plasma and tumor samples renders the EpiRbMx uniquely informative for addressing this critical unknown in understanding both retinoblastoma etiology and the potential role of folic acid in carcinogenesis and for informing future strategies for prevention.

Figure XX Proposed TImeline

Yr1

Yr2

Yr3

Yr4

Yr5

DNA extraction, Tumor (IMSS) & genomic (Columbia)

X

x

Additional Case & Tumor collection HIM, IMSS

X

Maternal & child DNA genotyping (Tufts)

X

X

Plasma nutrients (Tufts)

X

X

Tumor DNA preparation for send out for mutation & arrays (Columbia)

X

X

RB1 mutation(Impact Genetics)

x

X

Tumor DNA methylation array(Roswell Park)

X

Array analysis (Columbia and Oregon State)

X

X

X

Dietary intake, data entry (IMSS) nutrient intake calculations (INSP)

X

X

Analysis ( year 2, 3, 4, 5) manuscripts (year 3, 4 and 5)

x

Aim1

Aim 2

Aim 3

Strengths: A critical strength of this proposed study is that analyses will be performed on samples and data that are largely already collected (R01CA98180, R21CA167833) and are part of a comprehensive study with a) a well characterized population, b) an existing relational database c) existing measurements on key covariates such as dietary intake and genotype and d) a team of investigators with a demonstrated ability to collaborate Thiis study is thus cost-effective and makes efficient use of a unique resource.

Limitations: although we are limited to patients w tumor tissue, we have information on all patients who joined our EpiRbMx sudy. Refusal rates are low (3%) [1, 48] and diet and plasma are available on all participants. Study measures can thus be compared to those without tumors. Although we recognize that it would be ideal to measure intake and plasma prospectively during pregnancy. Since retinoblastoma is a rare disease; this is not possible. However, our finding that maternal levels of plasma folate at time of the child’s diagnosis (age 11-23 months) are associated with RB1 methylation suggests that mothers with DHFR19bpdel may have a chronic dysregulation of folate metabolism

Geographic Distance. The core of the study group has worked together productively for several years and generating the unique EpiRbMx resource, despite geographic distance using skype for regular meetings. Drs Orjuela, Ponce and Villalpando also meet as a benefit of the Mexican Studies Center at Columbia (see letter) and support from CoNaCyt. Although Dr Houseman is in Oregon, he is experienced in directing analyses and training post-doctoral researchers at distant collaborating institutions. Drs Gallie and Houseman will also meet with co-investigators in Mexico during the analysis phase of the study.

IN CONCLUSION

IMPACT AND FUTURE DIRECTIONS This proposed study is uniquely poised to help elucidate the relation between a common polymorphism regulating metabolism of folic acid, folic acid intake during a key period of development, and tumor- specific hypermethylation in RB1 in retinoblastoma. Data generated through this model will be relevant for adult tumors involving RB1 mutations and hypermethylation such as lung, prostate, and bladder cancer. Increased risk for both prostate and lung [25] cancer have been associated with folic acid supplementation [31] thus our results are of potentially high cancer and public health relevance. The use of largely pre-existing data and samples will permit cost-effective and timely assembly of data to permit valid statistical analysis. This study presents a unique collaboration which joins research efforts of a multinational and multidisciplinary team involving clinicians, nutrition scientists, molecular biologists, experts in methylation and analysis of complex methylation data, and molecular epidemiologists, building on an existing infrastructure. Our study population offers unique opportunities to study exposures that may affect the characteristic genetic and epigenetic changes present in this disease. This proposed project permits a translational approach to examining etiology of this disease, which though rare, has been informative for modeling early events in oncogenesis.. Our novel pilot data demonstrates that our expanded team will be able to effectively build on our existing infrastructure in order to address our aims and inform understanding of the role that folic acid and genetic variation in its metabolism may have in RB1 associated carcinogenesis..

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