Chantal Richer

Role of NQO1, MPO and CYP2E1 genetic polymorphisms in the susceptibility to childhood acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer. The genetic factors underlying the susceptibility to this disease remain elusive. The enzymes CYP2E1, MPO and NQO1 are involved in the biotransformation of a variety of xenobiotics present in organic solvents, tobacco smoke, drugs, plastic derivatives and pesticides. They also control the level of the oxidative stress by catalyzing the formation of free radicals or by protecting cells from their deleterious effect. DNA variants in the corresponding genes have been associated with an increased susceptibility to different adult cancers, including hematologic malignancies. To investigate whether they represent risk‐modifying factors in childhood ALL, we conducted a case‐control study involving 174 patients and 337 controls, both of French‐Canadian origin. We found that carriers of the CYP2E1*5 variant were at 2.8‐fold higher risk of ALL (95%CI, 1.2–6.4) and that NQO1 alleles *2 and *3 contributed to the risk of ALL as well (OR = 1.7, 95%CI, 1.2–2.4). No such association was found with MPO alone. However, when the wild‐type MPO allele was considered together with the CYP2E1 and NQO1 risk‐elevating genotypes, the risk of ALL was increased further (OR = 5.4, 95%CI, 1.2–23.4) suggesting a combined effect. We also found a gene‐gene interaction between the GSTM1 null genotype and NQO1 mutant alleles. It is therefore plausible that exposure to xenobiotics metabolized by these enzymes play a role in the etiology of childhood ALL.

Genetic susceptibility to breast cancer in French-Canadians: Role of carcinogen-metabolizing enzymes and gene–environment interactions

Breast cancer is the most frequent malignancy among women. Since genetic factors such as BRCA1 and BRCA2 as well as reproductive history constitute only 30% of the cause, environmental exposure may play a significant role in the development of breast cancer. Likewise, the relevant enzymes involved in the biotransformation of xenobiotics (from tobacco smoke, diet or other environmental sources) might play a role in breast carcinogenesis. Since individuals with modified ability to metabolize these carcinogens could have a different risk for breast cancer, we investigated the role of cytochromes P‐450 (CYP1A1, CYP2D6), glutathione‐S‐transferases (GSTM1, GSTT1, GSTP1) and N‐acetyltransferases (NAT1, NAT2) gene variants in breast carcinogenesis. A case‐control study was conducted on 149 women with breast carcinoma and 207 healthy controls, both of French‐Canadian origin. The CYP1A1*4 allele was found to be a significant risk determinant of breast carcinoma (OR = 3.3, 95% CI 1.1–9.7), particularly among post‐menopausal women (OR = 4.0, 95% CI 1.2–13.8). The frequency of NAT2 rapid acetylators was increased among smokers (OR = 2.6, 95% CI 0.8–8.2), while the NAT1*10 allele conferred a 4‐fold increase in risk among women who consumed well‐done meat (OR = 4.4, 95% CI 1.0–18.9). These data suggest that CYP1A1*4, NAT1 and NAT2 variants are involved in the susceptibility to breast carcinoma by modifying the impact of exogenous and/or endogenous exposures.

Evolution of mouse B1 repeats: 7SL RNA folding pattern conserved

SummaryIn a recent report mouse B1 genomic repeats were divided into six families representing different waves of fixation of B1 variants, consistent with the retroposition model of human Alu elements. These data are used to examine the distribution of nucleotide substitutions in individual genomic repeats with respect to family consensus sequences and to compare the minimal energy structures of the corresponding B1 RNAs. By an enzymatic approach the predicted structure of B1 RNAs is experimentally confirmed using as a model sequence an RNA of a young B1 family member transcribed in vitro by T7 RNA polymerase. B1 RNA preserves folding domains of the Alu fragment of 7SL RNA, its progenitor molecule. Our results reveal similarities among 7SL-like retroposons, human Alu, and rodent B1 repeats, and relate the evolutionary conservation of B1 family consensus sequences to selection at the RNA level.

Replication analysis confirms the association of ARID5B with childhood B-cell acute lymphoblastic leukemia

Although childhood acute lymphoblastic leukemia is the most common pediatric cancer, its etiology remains poorly understood. In an attempt to replicate the findings of 2 recent genome-wide association studies in a French-Canadian cohort, we confirmed the association of 5 SNPs [rs7073837 (P=4.2 × 10−4), rs10994982 (P=3.8 × 10−4), rs10740055 (P=1.6 × 10−5), rs10821936 (P=1.7 × 10−7) and rs7089424 (P=3.6 × 10−7)] in the ARID5B gene with childhood acute lymphoblastic leukemia. We also confirmed a selective effect for B-cell acute lymphoblastic leukemia with hyperdiploidy and report a putative gender-specific effect of ARID5B SNPs on acute lymphoblastic leukemia risk in males. This study provides a strong rationale for more detailed analysis to identify the causal variants at this locus and to better understand the overall functional contribution of ARID5B to childhood acute lymphoblastic leukemia susceptibility.

Analyses of bulky DNA adduct levels in human breast tissue and genetic polymorphisms of cytochromes P450 (CYPs), myeloperoxidase (MPO), quinone oxidoreductase (NQO1), and glutathione S-transferases (GSTs).

Environmental carcinogens are converted into DNA-reactive metabolites by phase I and phase II enzymes that are involved in the activation and detoxification of xenobiotics. Several of these enzymes display genetic polymorphisms that alter their activity leading to individual variation in DNA damage levels and thus cancer susceptibility. We investigated the relationship between DNA adduct levels and genetic polymorphisms in key enzymes of chemical carcinogenesis: CYP1A1, CYP1A2, GSTT1, GSTM1, GSTP1, NQO1 and MPO. Levels of DNA adducts were determined in human breast tissue using the 32P-postlabeling method. A significantly higher adduct level was observed for individuals with the A-463 variant in the MPO gene (P=0.008), providing the first observation of an association between a predicted reduced MPO gene transcription and a higher level of DNA adducts. Furthermore, levels of DNA adducts were about 45% higher in individuals with either GSTP1*B or GSTP1*C variants compared to those homozygous for the wild-type allele. When the MPO and GSTP1 were examined together, individuals with these combined variant genotypes had significantly higher adduct levels than all other genotype combinations (P=0.003).

Integration of High-Resolution Methylome and Transcriptome Analyses to Dissect Epigenomic Changes in Childhood Acute Lymphoblastic Leukemia

B-cell precursor acute lymphoblastic leukemia (pre-B ALL) is the most common pediatric cancer. Although the genetic determinants underlying disease onset remain unclear, epigenetic modifications including DNA methylation are suggested to contribute significantly to leukemogenesis. Using the Illumina 450K array, we assessed DNA methylation in matched tumor-normal samples of 46 childhood patients with pre-B ALL, extending single CpG-site resolution analysis of the pre-B ALL methylome beyond CpG-islands (CGI). Unsupervised hierarchical clustering of CpG-site neighborhood, gene, or microRNA (miRNA) gene-associated methylation levels separated the tumor cohort according to major pre-B ALL subtypes, and methylation in CGIs, CGI shores, and in regions around the transcription start site was found to significantly correlate with transcript expression. Focusing on samples carrying the t(12;21) ETV6-RUNX1 fusion, we identified 119 subtype-specific high-confidence marker CpG-loci. Pathway analyses linked the CpG-loci-associated genes with hematopoiesis and cancer. Further integration with whole-transcriptome data showed the effects of methylation on expression of 17 potential drivers of leukemogenesis. Independent validation of array methylation and sequencing-derived transcript expression with Sequenom Epityper technology and real-time quantitative reverse transcriptase PCR, respectively, indicates more than 80% empirical accuracy of our genome-wide findings. In summary, genome-wide DNA methylation profiling enabled us to separate pre-B ALL according to major subtypes, to map epigenetic biomarkers specific for the t(12;21) subtype, and through a combined methylome and transcriptome approach to identify downstream effects on candidate drivers of leukemogenesis.

Genomic loci susceptible to replication errors in cancer cells

Microsatellite instability due to a deficiency in DNA mismatch repair is characteristic of a replication error (RER) phenotype. This widespread genomic instability is well documented in hereditary non-polyposis colon cancer (HNPCC) as well as subsets of sporadic carcinomas. Features of the RER phenotype such as the early appearance in tumour development and better prognosis of RER+ colorectal tumours render its examination important for cancer patients. Recently, we identified four loci that were shown to be highly susceptible to RER in cancer cells. Here, we used these loci to detect the RER phenotype in sporadic carcinomas of colon, breast, lung, endometrium and ovary. Replication errors revealed by these four markers followed the same tumour specificity as observed in HNPCC patients. In particular, 24% (6/25) of colorectal, 33% (4/12) of endometrial and 17% (2/12) of ovarian cancers displayed the RER phenotype characterized by an increased allelic mobility, whereas none of the breast (n = 22) and the lung (n = 27) carcinomas were found to be unstable. Assaying RERs sensitive loci provides us with a useful diagnostic tool for HNPCC-like sporadic tumours.

SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing

BackgroundNext-generation sequencing (NGS) allows unbiased, in-depth interrogation of cancer genomes. Many somatic variant callers have been developed yet accurate ascertainment of somatic variants remains a considerable challenge as evidenced by the varying mutation call rates and low concordance among callers. Statistical model-based algorithms that are currently available perform well under ideal scenarios, such as high sequencing depth, homogeneous tumor samples, high somatic variant allele frequency (VAF), but show limited performance with sub-optimal data such as low-pass whole-exome/genome sequencing data. While the goal of any cancer sequencing project is to identify a relevant, and limited, set of somatic variants for further sequence/functional validation, the inherently complex nature of cancer genomes combined with technical issues directly related to sequencing and alignment can affect either the specificity and/or sensitivity of most callers.ResultsFor these reasons, we developed SNooPer, a versatile machine learning approach that uses Random Forest classification models to accurately call somatic variants in low-depth sequencing data. SNooPer uses a subset of variant positions from the sequencing output for which the class, true variation or sequencing error, is known to train the data-specific model. Here, using a real dataset of 40 childhood acute lymphoblastic leukemia patients, we show how the SNooPer algorithm is not affected by low coverage or low VAFs, and can be used to reduce overall sequencing costs while maintaining high specificity and sensitivity to somatic variant calling. When compared to three benchmarked somatic callers, SNooPer demonstrated the best overall performance.ConclusionsWhile the goal of any cancer sequencing project is to identify a relevant, and limited, set of somatic variants for further sequence/functional validation, the inherently complex nature of cancer genomes combined with technical issues directly related to sequencing and alignment can affect either the specificity and/or sensitivity of most callers. The flexibility of SNooPer’s random forest protects against technical bias and systematic errors, and is appealing in that it does not rely on user-defined parameters. The code and user guide can be downloaded at https://sourceforge.net/projects/snooper/.

Single-strand conformational polymorphisms (SSCP) : detection of useful polymorphisms at the dystrophin locus

SummaryWe searched for DNA polymorphisms in seven amplified fragments of the dystrophin gene. Three fragments exhibited variable mobilities during nondenaturing strand-separating gel electrophoresis (SSGE). These variants were due to single base changes (three transversions and one transition). Three were intronic (upstream from exons 17, 15, and 48) and one was in exon 48. The frequencies of these sequence variants were determined in a sample of 54 normal X chromosomes of Caucasian origin. One of these DNA polymorphisms was observed in every 650 bp tested and the average heterozygosity was 0.05% per base pair (0.08% if exons were excluded). Such a detection density and the fact that single-strand conformational polymorphisms do not depend on the presence of any specific sequence makes them especially valuable as genetic markers. In the dystrophin locus this approach could allow simultaneous detection of frequent deletions.

Whole-exome sequencing of a rare case of familial childhood acute lymphoblastic leukemia reveals putative predisposing mutations in Fanconi anemia genes

BackgroundAcute lymphoblastic leukemia (ALL) is the most common pediatric cancer. While the multi-step model of pediatric leukemogenesis suggests interplay between constitutional and somatic genomes, the role of inherited genetic variability remains largely undescribed. Nonsyndromic familial ALL, although extremely rare, provides the ideal setting to study inherited contributions to ALL. Toward this goal, we sequenced the exomes of a childhood ALL family consisting of mother, father and two non-twinned siblings diagnosed with concordant pre-B hyperdiploid ALL and previously shown to have inherited a rare form of PRDM9, a histone H3 methyltransferase involved in crossing-over at recombination hotspots and Holliday junctions. We postulated that inheritance of additional rare disadvantaging variants in predisposing cancer genes could affect genomic stability and lead to increased risk of hyperdiploid ALL within this family.MethodsWhole exomes were captured using Agilent’s SureSelect kit and sequenced on the Life Technologies SOLiD System. We applied a data reduction strategy to identify candidate variants shared by both affected siblings. Under a recessive disease model, we focused on rare non-synonymous or frame-shift variants in leukemia predisposing pathways.ResultsThough the family was nonsyndromic, we identified a combination of rare variants in Fanconi anemia (FA) genes FANCP/SLX4 (compound heterozygote - rs137976282/rs79842542) and FANCA (rs61753269) and a rare homozygous variant in the Holliday junction resolvase GEN1 (rs16981869). These variants, predicted to affect protein function, were previously identified in familial breast cancer cases. Based on our in-house database of 369 childhood ALL exomes, the sibs were the only patients to carry this particularly rare combination and only a single hyperdiploid patient was heterozygote at both FANCP/SLX4 positions, while no FANCA variant allele carriers were identified. FANCA is the most commonly mutated gene in FA and is essential for resolving DNA interstrand cross-links during replication. FANCP/SLX4 and GEN1 are involved in the cleavage of Holliday junctions and their mutated forms, in combination with the rare allele of PRDM9, could alter Holliday junction resolution leading to nondisjunction of chromosomes and segregation defects.ConclusionTaken together, these results suggest that concomitant inheritance of rare variants in FANCA, FANCP/SLX4 and GEN1 on the specific genetic background of this familial case, could lead to increased genomic instability, hematopoietic dysfunction, and higher risk of childhood leukemia.