Identification of IGF2 as Genomic Driver and Actionable Therapeutic Target in Hepatoblastoma.

Management of hepatoblastoma (HB), the most frequent pediatric liver cancer, is based on surgical resection and perioperative chemotherapy regimens. In this study, we aimed to identify actionable targets in HB and assess the efficacy of molecular therapies in preclinical models of HB. Paired tumor and adjacent tissues from 31 HBs and a validation set of 50 HBs were analyzed using RNA-seq, SNP, and methylation arrays. IGF2 overexpression was identified as the top targetable HB driver, present in 71% of HBs (22/31). IGF2high tumors displayed progenitor cell features and shorter recurrence-free survival. IGF2 overexpression was associated in 91% of cases with fetal promoter hypomethylation, ICR1 deregulation, 11p15.5 loss of heterozygosity or miR483-5p overexpression. The antitumor effect of xentuzumab (a monoclonal antibody targeting IGF1/2) alone or in combination with the conventional therapeutic agent cisplatin was assessed in HB cell lines, in PDX-derived HB organoids and in a xenograft HB murine model. The combination of xentuzumab with cisplatin showed strong synergistic antitumor effects in organoids and in IGF2high cell lines. In mice (n = 55), the combination induced a significant decrease in tumor volume and improved survival compared with cisplatin alone. These results suggest that IGF2 is an HB actionable driver and that, in preclinical models of HB, the combination of IGF1/2 inhibition with cisplatin induces superior antitumor effects than cisplatin monotherapy. Overall, our study provides a rationale for testing IGF2 inhibitors in combination with cisplatin in HB patients with IGF2 overexpression.

Analytical evaluation of the clonoSEQ Assay for establishing measurable (minimal) residual disease in acute lymphoblastic leukemia, chronic lymphocytic leukemia, and multiple myeloma.

BACKGROUND: The clonoSEQ® Assay (Adaptive Biotechnologies Corporation, Seattle, USA) identifies and tracks unique disease-associated immunoglobulin (Ig) sequences by next-generation sequencing of IgH, IgK, and IgL rearrangements and IgH-BCL1/2 translocations in malignant B cells. Here, we describe studies to validate the analytical performance of the assay using patient samples and cell lines. METHODS: Sensitivity and specificity were established by defining the limit of detection (LoD), limit of quantitation (LoQ) and limit of blank (LoB) in genomic DNA (gDNA) from 66 patients with multiple myeloma (MM), acute lymphoblastic leukemia (ALL), or chronic lymphocytic leukemia (CLL), and three cell lines. Healthy donor gDNA was used as a diluent to contrive samples with specific DNA masses and malignant-cell frequencies. Precision was validated using a range of samples contrived from patient gDNA, healthy donor gDNA, and 9 cell lines to generate measurable residual disease (MRD) frequencies spanning clinically relevant thresholds. Linearity was determined using samples contrived from cell line gDNA spiked into healthy gDNA to generate 11 MRD frequencies for each DNA input, then confirmed using clinical samples. Quantitation accuracy was assessed by (1) comparing clonoSEQ and multiparametric flow cytometry (mpFC) measurements of ALL and MM cell lines diluted in healthy mononuclear cells, and (2) analyzing precision study data for bias between clonoSEQ MRD results in diluted gDNA and those expected from mpFC based on original, undiluted samples. Repeatability of nucleotide base calls was assessed via the assay's ability to recover malignant clonotype sequences across several replicates, process features, and MRD levels. RESULTS: LoD and LoQ were estimated at 1.903 cells and 2.390 malignant cells, respectively. LoB was zero in healthy donor gDNA. Precision ranged from 18% CV (coefficient of variation) at higher DNA inputs to 68% CV near the LoD. Variance component analysis showed MRD results were robust, with expected laboratory process variations contributing ≤3% CV. Linearity and accuracy were demonstrated for each disease across orders of magnitude of clonal frequencies. Nucleotide sequence error rates were extremely low. CONCLUSIONS: These studies validate the analytical performance of the clonoSEQ Assay and demonstrate its potential as a highly sensitive diagnostic tool for selected lymphoid malignancies.

Correction to: Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits.

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Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits.

BACKGROUND: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. RESULTS: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. CONCLUSION: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.

STAR Chimeric Post for rapid detection of circular RNA and fusion transcripts.

Motivation: The biological relevance of chimeric RNA alignments is now well established. Chimera arising as chromosomal fusions are often drivers of cancer and recently discovered circular RNA (circRNA) are only now being characterized. While software already exists for fusion discovery and quantitation, high false positive rates and high run-times hamper scalable fusion discovery on large datasets. Furthermore, software available for circRNA detection and quantification is limited. Results: Here, we present STAR Chimeric Post (STARChip), a novel software package that processes chimeric alignments from the STAR aligner and produces annotated circRNA and high precision fusions in a rapid, efficient and scalable manner that is appropriate for high dimensional medical omics datasets. Availability and implementation: STARChip is available at https://github.com/LosicLab/STARChip. Supplementary information: Supplementary data are available at Bioinformatics online.

Associations between arsenic (+3 oxidation state) methyltransferase (AS3MT) and N-6 adenine-specific DNA methyltransferase 1 (N6AMT1) polymorphisms, arsenic metabolism, and cancer risk in a chilean population.

Inter-individual differences in arsenic metabolism have been linked to arsenic-related disease risks. Arsenic (+3) methyltransferase (AS3MT) is the primary enzyme involved in arsenic metabolism, and we previously demonstrated in vitro that N-6 adenine-specific DNA methyltransferase 1 (N6AMT1) also methylates the toxic inorganic arsenic (iAs) metabolite, monomethylarsonous acid (MMA), to the less toxic dimethylarsonic acid (DMA). Here, we evaluated whether AS3MT and N6AMT1 gene polymorphisms alter arsenic methylation and impact iAs-related cancer risks. We assessed AS3MT and N6AMT1 polymorphisms and urinary arsenic metabolites (%iAs, %MMA, %DMA) in 722 subjects from an arsenic-cancer case-control study in a uniquely exposed area in northern Chile. Polymorphisms were genotyped using a custom designed multiplex, ligation-dependent probe amplification (MLPA) assay for 6 AS3MT SNPs and 14 tag SNPs in the N6AMT1 gene. We found several AS3MT polymorphisms associated with both urinary arsenic metabolite profiles and cancer risk. For example, compared to wildtypes, individuals carrying minor alleles in AS3MT rs3740393 had lower %MMA (mean difference = -1.9%, 95% CI: -3.3, -0.4), higher %DMA (mean difference = 4.0%, 95% CI: 1.5, 6.5), and lower odds ratios for bladder (OR = 0.3; 95% CI: 0.1-0.6) and lung cancer (OR = 0.6; 95% CI: 0.2-1.1). Evidence of interaction was also observed for both lung and bladder cancer between these polymorphisms and elevated historical arsenic exposures. Clear associations were not seen for N6AMT1. These results are the first to demonstrate a direct association between AS3MT polymorphisms and arsenic-related internal cancer risk. This research could help identify subpopulations that are particularly vulnerable to arsenic-related disease. Environ. Mol. Mutagen. 58:411-422, 2017. © 2017 Wiley Periodicals, Inc.

Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases.

Genome-wide association studies (GWAS) have identified hundreds of cardiometabolic disease (CMD) risk loci. However, they contribute little to genetic variance, and most downstream gene-regulatory mechanisms are unknown. We genotyped and RNA-sequenced vascular and metabolic tissues from 600 coronary artery disease patients in the Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task study (STARNET). Gene expression traits associated with CMD risk single-nucleotide polymorphism (SNPs) identified by GWAS were more extensively found in STARNET than in tissue- and disease-unspecific gene-tissue expression studies, indicating sharing of downstream cis-/trans-gene regulation across tissues and CMDs. In contrast, the regulatory effects of other GWAS risk SNPs were tissue-specific; abdominal fat emerged as an important gene-regulatory site for blood lipids, such as for the low-density lipoprotein cholesterol and coronary artery disease risk gene PCSK9 STARNET provides insights into gene-regulatory mechanisms for CMD risk loci, facilitating their translation into opportunities for diagnosis, therapy, and prevention.

Coding variants at hexa-allelic amino acid 13 of HLA-DRB1 explain independent SNP associations with follicular lymphoma risk.

Non-Hodgkin lymphoma represents a diverse group of blood malignancies, of which follicular lymphoma (FL) is a common subtype. Previous genome-wide association studies (GWASs) have identified in the human leukocyte antigen (HLA) class II region multiple independent SNPs that are significantly associated with FL risk. To dissect these signals and determine whether coding variants in HLA genes are responsible for the associations, we conducted imputation, HLA typing, and sequencing in three independent populations for a total of 689 cases and 2,446 controls. We identified a hexa-allelic amino acid polymorphism at position 13 of the HLA-DR beta chain that showed the strongest association with FL within the major histocompatibility complex (MHC) region (multiallelic p = 2.3 × 10⁻¹5). Out of six possible amino acids that occurred at that position within the population, we classified two as high risk (Tyr and Phe), two as low risk (Ser and Arg), and two as moderate risk (His and Gly). There was a 4.2-fold difference in risk (95% confidence interval = 2.9-6.1) between subjects carrying two alleles encoding high-risk amino acids and those carrying two alleles encoding low-risk amino acids (p = 1.01 × 10⁻¹4). This coding variant might explain the complex SNP associations identified by GWASs and suggests a common HLA-DR antigen-driven mechanism for the pathogenesis of FL and rheumatoid arthritis.

Common variants within 6p21.31 locus are associated with chronic lymphocytic leukaemia and, potentially, other non-Hodgkin lymphoma subtypes.

A recent meta-analysis of three genome-wide association studies of chronic lymphocytic leukaemia (CLL) identified two common variants at the 6p21.31 locus that are associated with CLL risk. To verify and further explore the association of these variants with other non-Hodgkin lymphoma (NHL) subtypes, we genotyped 1196 CLL cases, 1699 NHL cases, and 2410 controls. We found significant associations between the 6p21.31 variants and CLL risk (rs210134: P = 0·01; rs210142: P = 6·8 × 10(-3)). These variants also showed a trend towards association with some of the other NHL subtypes. Our results validate the prior work and support specific genetic pathways for risk among NHL subtypes.

Association of HLA-DQB1 alleles with risk of follicular lymphoma.

In a recent genome-wide association study of follicular lymphoma (FL), we identified novel risk alleles on chromosome 6p21.33 that appeared to be part of an extended haplotype including HLA-DRB1*0101, DQA1*0101, and DQB1*0501. To follow up on these findings, we obtained 2-4 digit HLA-DQB1 allelotypes on a subset of 265 cases of FL and 757 controls using a novel assay that applies multiplexed ligation-dependent probe amplification (MLPA). We confirmed a positive association between FL and the HLA-DQB1*05 allele group (OR = 1.70, 95% CI 1.28-2.27; adjusted p-value = 0.013) and also identified an allele group inversely associated with FL risk, HLA-DQB1*06 (OR = 0.51, 95% CI 0.38-0.69; adjusted p-value = 4.46 × 10(-5)). Although these findings require verification, the role of HLA class II proteins in B-cell survival and proliferation makes this a biologically plausible association.

Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32.

To identify susceptibility loci for non-Hodgkin lymphoma subtypes, we conducted a three-stage genome-wide association study. We identified two variants associated with follicular lymphoma at 6p21.32 (rs10484561, combined P = 1.12 x 10(-29) and rs7755224, combined P = 2.00 x 10(-19); r(2) = 1.0), supporting the idea that major histocompatibility complex genetic variation influences follicular lymphoma susceptibility. We also found confirmatory evidence of a previously reported association between chronic lymphocytic leukemia/small lymphocytic lymphoma and rs735665 (combined P = 4.24 x 10(-9)).