Wu, Gang

Abstract Although sequencing costs have steadily decreased with advances in technology, they remain high for large scale studies. The design of traditional individual-disease sequencing studies is either case only or cases with relatively few controls, resulting in potential loss of statistical power for discovery of disease associated genes. Here we show that for a given number of sequenced cases, a large control sample size is critical to maximize power for rare variant burden analysis. Furthermore, we have developed an end-to-end workflow based tool (CoCoRV-nf) to facilitate the use of external biobank sequence resources as controls. The modules include consistent variant QC, variant annotation, ancestry population prediction, and gene based burden analysis using summary genotype information, and combined analysis from multiple independent results. The tool supports exomes and genomes from gnomAD and All of Us as controls with preprocessed datasets. We apply the tool in two rare neurological diseases: amyotrophic lateral sclerosis and neuroblastoma. For each disease, two case cohorts are paired with gnomAD and All of Us data, respectively, followed by a combined analysis. Not only did we recapture known genes, but also, we identified new candidate genes for both diseases. By leveraging multiple large external biobank sequence data, we demonstrate the feasibility of using our tool to maximize statistical power to identify new disease predisposition genes.

PURPOSE Recent studies reveal that 5%-18% of children with cancer harbor pathogenic variants in known cancer-predisposing genes. However, DNA damage repair (DDR) genes, which are frequently somatically altered in pediatric tumors, have not been systematically examined as a source of novel cancer-predisposing signals. METHODS To address this gap, we interrogated 189 DDR genes for presence of germline predisposing variants (PV) among 5,993 childhood cancer cases and 14,477 adult noncancer controls (discovery cohort). PV were determined using a tiered approach incorporating ClinVar annotations, InterVar classification, and in silico tools (REVEL, CADD, and MetaSVM). Using logistic and firth regression, we identified genes with PV statistically enriched in the germline of children with tumors and replicated findings among 1,497 additional childhood cancer cases across three independent cohorts. RESULTS Analysis across all cases with cancer revealed enrichment of TP53 PV. Cancer-specific analyses confirmed known associations including germline TP53 PV in adrenocortical carcinoma, high-grade glioma (HGG), and medulloblastoma (MB), PMS2 in HGG and non-Hodgkin lymphoma (NHL), MLH1 in HGG, BRCA2 in NHL, and BARD1 in neuroblastoma. In addition, four novel associations were uncovered, including BRCA1 in ependymoma, SPIDR in HGG, SMC5 in MB, and SMARCAL1 in osteosarcoma (OS). Importantly, the SMARCAL1 :OS association was significant in the discovery (6/230, 2.6%, false discovery rate [FDR] logistic = 0.0189) as well as all three replication cohorts (Childhood Cancer Survivor Study: 8/275, 2.9%; P Fisher < .0001; Cancer Predisposition Syndrome-German Childhood Cancer Registry: 4/135, 3%, P Fisher = .002; Individualized Therapy for Relapsed Malignancies in Childhood: 4/217, 1.8%, P Fisher = .012). The remaining wild-type SMARCAL1 allele was deleted in three of four OS tumors with available data. CONCLUSION Our study confirms the relevance DDR genetic variation in pediatric cancer risk and establishes SMARCAL1 as a novel OS predisposing gene, providing insights into tumor biology and creating opportunities to optimize care for patients with this challenging tumor.

PURPOSE Although cure rates for childhood acute lymphoblastic leukemia (ALL) exceed 90%, ALL remains a leading cause of cancer death in children. Half of relapses arise in children initially classified with standard-risk (SR) disease. MATERIALS AND METHODS To identify genomic determinants of relapse in children with SR ALL, we performed genome and transcriptome sequencing of diagnostic and remission samples of children with SR (n = 1,381) or high-risk B-ALL with favorable cytogenetic features (n = 115) enrolled on Children's Oncology Group trials. We used a case-control study design analyzing 439 patients who relapsed and 1,057 who remained in complete remission for at least 5 years. RESULTS Genomic subtype was associated with relapse, which occurred in approximately 50% of cases of PAX5 -altered ALL (odds ratio [OR], 3.31 [95% CI, 2.17 to 5.03]; P = 3.18 × 10 –8 ). Within high-hyperdiploid ALL, gain of chromosome 10 with disomy of chromosome 7 was associated with favorable outcome (OR, 0.27 [95% CI, 0.17 to 0.42]; P = 8.02 × 10 –10 ; St Jude Children's Research Hospital validation cohort: OR, 0.22 [95% CI, 0.05 to 0.80]; P = .009), and disomy of chromosomes 10 and 17 with gain of chromosome 6 was associated with relapse (OR, 7.16 [95% CI, 2.63 to 21.51]; P = 2.19 × 10 –5 ; validation cohort: OR, 21.32 [95% CI, 3.62 to 119.30]; P = .0004). Genomic alterations were associated with relapse in a subtype-dependent manner, including alterations of INO80 in ETV6::RUNX1 ALL, IKZF1 , and CREBBP in high-hyperdiploid ALL and FHIT in BCR::ABL1 -like ALL. Genomic alterations were also associated with the presence of minimal residual disease, including NRAS and CREBBP in high-hyperdiploid ALL. CONCLUSION Genetic subtype, patterns of aneuploidy, and secondary genomic alterations determine risk of relapse in childhood ALL. Comprehensive genomic analysis is required for optimal risk stratification.

Abstract Given the frequent and largely incurable occurrence of multiple myeloma, identification of germline genetic mutations that predispose cells to multiple myeloma may provide insight into disease etiology and the developmental mechanisms of its cell of origin, the plasma cell (PC). Here, we identified familial and early-onset multiple myeloma kindreds with truncating mutations in lysine-specific demethylase 1 (LSD1/KDM1A), an epigenetic transcriptional repressor that primarily demethylates histone H3 on lysine 4 and regulates hematopoietic stem cell self-renewal. In addition, we found higher rates of germline truncating and predicted deleterious missense KDM1A mutations in patients with multiple myeloma unselected for family history compared with controls. Both monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma cells have significantly lower KDM1A transcript levels compared with normal PCs. Transcriptome analysis of multiple myeloma cells from KDM1A mutation carriers shows enrichment of pathways and MYC target genes previously associated with myeloma pathogenesis. In mice, antigen challenge followed by pharmacologic inhibition of KDM1A promoted PC expansion, enhanced secondary immune response, elicited appearance of serum paraprotein, and mediated upregulation of MYC transcriptional targets. These changes are consistent with the development of MGUS. Collectively, our findings show that KDM1A is the first autosomal-dominant multiple myeloma germline predisposition gene providing new insights into its mechanistic roles as a tumor suppressor during post-germinal center B-cell differentiation. Significance: KDM1A is the first germline autosomal dominant predisposition gene identified in multiple myeloma and provides new insights into multiple myeloma etiology and the mechanistic role of KDM1A as a tumor suppressor during post-germinal center B-cell differentiation. Cancer Res; 78(10); 2747–59. ©2018 AACR.