Unique Copy Number Variations Research Articles

Multilevel gene expression changes in lineages containing adaptive copy number variants.

Copy-number variants (CNVs) are an important class of genetic variation that can mediate rapid adaptive evolution. Whereas CNVs can increase the relative fitness of the organism, they can also incur a cost due to the associated increased gene expression and repetitive DNA. We previously evolved populations of Saccharomyces cerevisiae over hundreds of generations in glutamine-limited (Gln-) chemostats and observed the recurrent evolution of CNVs at the GAP1 locus. To understand the role that gene expression plays in adaptation, both in relation to the adaptation of the organism to the selective condition and as a consequence of the CNV, we measured the transcriptome, translatome, and proteome of 4 strains of evolved yeast, each with a unique CNV, and their ancestor in Gln- conditions. We find CNV-amplified genes correlate with higher mRNA abundance; however, this effect is reduced at the level of the proteome, consistent with post-transcriptional dosage compensation. By normalizing each level of gene expression by the abundance of the preceding step we were able to identify widespread differences in the efficiency of each level of gene expression. Genes with significantly different translational efficiency were enriched for potential regulatory mechanisms including either upstream open reading frames (uORFs), RNA binding sites for Ssd1, or both. Genes with lower protein expression efficiency were enriched for genes encoding proteins in protein complexes. Taken together, our study reveals widespread changes in gene expression at multiple regulatory levels in lineages containing adaptive CNVs highlighting the diverse ways in which genome evolution shapes gene expression.

Multilevel gene expression changes in lineages containing adaptive copy number variants.

Copy-number variants (CNVs) are an important class of recurrent variants that mediate adaptive evolution. While CNVs can increase the relative fitness of the organism, they can also incur a cost. We previously evolved populations of Saccharomyces cerevisiae over hundreds of generations in glutamine-limited (Gln-) chemostats and observed the recurrent evolution of CNVs at the GAP1 locus. To understand the role that expression plays in adaptation, both in relation to the adaptation of the organism to the selective condition, and as a consequence of the CNV, we measured the transcriptome, translatome, and proteome of 4 strains of evolved yeast, each with a unique CNV, and their ancestor in Gln- conditions. We find CNV-amplified genes correlate with higher RNA abundance; however, this effect is reduced at the level of the proteome, consistent with post-transcriptional dosage compensation. By normalizing each level of expression by the abundance of the preceding step we were able to identify widespread divergence in the efficiency of each step in the gene in the efficiency of each step in gene expression. Genes with significantly different translational efficiency were enriched for potential regulatory mechanisms including either upstream open reading frames, RNA binding sites for SSD1, or both. Genes with lower protein expression efficiency were enriched for genes encoding proteins in protein complexes. Taken together, our study reveals widespread changes in gene expression at multiple regulatory levels in lineages containing adaptive CNVs highlighting the diverse ways in which adaptive evolution shapes gene expression.

Genome integrity as a potential index of longevity in Ashkenazi Centenarian’s families

The aging process, or senescence, is characterized by age-specific decline in physical and physiological function, and increased frailty and genomic changes, including mutation accumulation. However, the mechanisms through which changes in genomic architecture influence human longevity have remained obscure. Copy number variants (CNVs), an abundant class of genomic variants, offer unique opportunities for understanding age-related genomic changes. Here we report the spectrum of CNVs in a cohort of 670 Ashkenazi Jewish centenarians, their progeny, and unrelated controls. The average ages of these groups were 97.4 ± 2.8, 69.2 ± 9.2, and 66.5 ± 7.0 respectively. For the first time, we compared different size classes of CNVs, from 1 kB to 100 MB in size. Using a high-resolution custom Affymetrix array, targeting 44,639 genomic regions, we identified a total of 12,166, 22,188, and 10,285 CNVs in centenarians, their progeny, and control groups, respectively. Interestingly, the offspring group showed the highest number of unique CNVs, followed by control and centenarians. While both gains and losses were found in all three groups, centenarians showed a significantly higher average number of both total gains and losses relative to their controls (p < 0.0327, 0.0182, respectively). Moreover, centenarians showed a lower total length of genomic material lost, suggesting that they may maintain superior genomic integrity over time. We also observe a significance fold increase of CNVs among the offspring, implying greater genomic integrity and a putative mechanism for longevity preservation. Genomic regions that experienced loss or gains appear to be distributed across many sites in the genome and contain genes involved in DNA transcription, cellular transport, developmental pathways, and metabolic functions. Our findings suggest that the exceptional longevity observed in centenarians may be attributed to the prolonged maintenance of functionally important genes. These genes are intrinsic to specific genomic regions as well as to the overall integrity of the genomic architecture. Additionally, a strong association between longer CNVs and differential gene expression observed in this study supports the notion that genomic integrity could positively influence longevity.

Abstract B032: Use of patient-derived organoids to model tumor evolution in response to chemotherapy

Abstract Serous endometrial and ovarian cancers represent significant morbidity and mortality for gynecologic cancers due to the high rate of resistance to chemotherapy and recurrence after treatment. Among the many reasons for poor outcomes is a lack of preclinical models that reflect the complex heterogeneity across patients. Our objective was to create patient-derived organoid (PDO) models of serous endometrial and ovarian cancer and examine how genomic profiles evolve in response to standard therapy. This study was performed in four PDO models of serous gynecologic cancer, including serous endometrial, high grade and low grade serous ovarian, and high grade serous fallopian tube. We first compared genomic alterations in the primary tumors and PDOs using a 484-gene NGS panel (NovoPM 2.0, Novogene). A large overlap in single nucleotide variants (SNVs), copy number variations (CNVs) and indels was observed between primary tumor tissue and the corresponding PDO model. For example, there was an average of 175 shared SNVs between each primary tumor and PDO model and &amp;lt;20 unique variants in the PDO that were not present in primary tumor specimen. For the patient with serous fallopian tube cancer, we were further able to generate PDO models from tumor tissue acquired from three different sites: ovary, omentum, and ascites fluid. We found that 217 SNVs were shared among the PDOs from the three sites, with only 2-11 variants unique to each location. Interestingly, eight unique CNVs were detected in the ovary and ascites PDOs but not in the metastatic (omentum) PDO. We next exposed each PDO to a short 3-day pulse of carboplatin+paclitaxel to create chemoexposed models. The rationale for this duration of exposure is that clinical response in patients has been shown to correlate with drug response at 72 hrs in PDO models of ovarian cancer. As expected, all chemoexposed PDOs were more resistant to chemotherapy as compared to treatment-naïve counterparts. Genomic analysis of the treatment-naïve vs. chemoexposed PDOs revealed acquisition of new variants, such as a p53 mutation in the serous endometrial model after the pulse of chemotherapy. Finally, we compared drug sensitivity of the treatment-naïve vs. chemoexposed PDOs to agents used in the adjuvant and recurrent settings. The chemoexposed models yielded different drug profiles, with some showing increased sensitivity and others increased resistance. Taken together, these data substantiate that PDO models retain tumor heterogeneity, exhibited by the different genomic profiles and varying chemosensitivity. In addition, PDO models can be used to model the genomic and drug response profiles that arise in response to chemotherapy. Citation Format: Andreea Newtson, Emily Symons, Paige Malmrose, Eric Devor, Samantha Parks, Craig Rush, Jessica Andrew-Udoh, Haley Losh, Jay Gertz, Kristina Thiel, Kimberly Leslie. Use of patient-derived organoids to model tumor evolution in response to chemotherapy [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr B032.

Detection and characterization of copy number variation in three differentially-selected Nellore cattle populations.

Introduction: Nellore cattle (Bos taurus indicus) is the main beef cattle breed raised in Brazil. This breed is well adapted to tropical conditions and, more recently, has experienced intensive genetic selection for multiple performance traits. Over the past 43years, an experimental breeding program has been developed in the Institute of Animal Science (IZ, Sertaozinho, SP, Brazil), which resulted in three differentially-selected lines known as Nellore Control (NeC), Nellore Selection (NeS), and Nellore Traditional (NeT). The primary goal of this selection experiment was to determine the response to selection for yearling weight (YW) and residual feed intake (RFI) on Nellore cattle. The main objectives of this study were to: 1) identify copy number variation (CNVs) in Nellore cattle from three selection lines; 2) identify and characterize CNV regions (CNVR) on these three lines; and 3) perform functional enrichment analyses of the CNVR identified. Results: A total of 14,914 unique CNVs and 1,884 CNVRs were identified when considering all lines as a single population. The CNVRs were non-uniformly distributed across the chromosomes of the three selection lines included in the study. The NeT line had the highest number of CNVRs (n = 1,493), followed by the NeS (n = 823) and NeC (n = 482) lines. The CNVRs covered 23,449,890 bp (0.94%), 40,175,556 bp (1.61%), and 63,212,273 bp (2.54%) of the genome of the NeC, NeS, and NeT lines, respectively. Two CNVRs were commonly identified between the three lines, and six, two, and four exclusive regions were identified for NeC, NeS, and NeT, respectively. All the exclusive regions overlap with important genes, such as SMARCD3, SLC15A1, and MAPK1. Key biological processes associated with the candidate genes were identified, including pathways related to growth and metabolism. Conclusion: This study revealed large variability in CNVs and CNVRs across three Nellore lines differentially selected for YW and RFI. Gene annotation and gene ontology analyses of the exclusive CNVRs to each line revealed specific genes and biological processes involved in the expression of growth and feed efficiency traits. These findings contribute to the understanding of the genetic mechanisms underlying the phenotypic differences among the three Nellore selection lines.

Characterization of copy-number variants in a large cohort of patients with von Willebrand disease reveals a relationship between disrupted regions and disease type

BackgroundGenetic analysis for von Willebrand disease (VWD) commonly utilizes DNA sequencing to identify variants in the von Willebrand factor (VWF) gene; however, this technique cannot always detect copy-number variants (CNVs). Additional mapping of CNVs in patients with VWD is needed. ObjectivesThis study aimed to characterize CNVs in a large sample of VWF mutation-negative VWD patients. MethodsTo determine the role of CNVs in VWD, a VWF high-resolution comparative genomic hybridization array was custom-designed to avoid multiple sequence variations, repeated sequences, and the VWF pseudogene. This was performed on 204 mutation-negative subjects for whom clinical variables were also available. ResultsAmong the 204 patients, 7 unique CNVs were found, with a total of 24 CNVs (12%). Of the 7 unique CNVs, 1 was novel, 1 was found in a VWF database, and 5 were previously reported. All patients with type 1C VWD and a CNV had the same exon 33 and 34 in-frame deletion. Certain clinical variables were also significantly different between those with and without CNVs. ConclusionThe in-frame deletion in patients with type 1C VWD exactly matches the D4N module of the D4 domain, a region where mutations and deletions are known to affect clearance. We observed significantly higher VWF–to–ristocetin cofactor levels in patients with type 1C VWD and a CNV than in patients without a CNV, suggesting a relationship between CNVs and the increased clearance observed in patients with type 1C VWD. Glycoprotein IbM activity was significantly lower in patients with type 1 VWD and a CNV than in patients without a CNV, suggesting that platelet binding is more affected by CNVs than single base pair mutations. This work elucidates some of the underlying genetic mechanisms of CNVs in these patients.

Implementation of Nanopore sequencing as a pragmatic workflow for copy number variant confirmation in the clinic

BackgroundDiagnosis of rare genetic diseases can be a long, expensive and complex process, involving an array of tests in the hope of obtaining an actionable result. Long-read sequencing platforms offer the opportunity to make definitive molecular diagnoses using a single assay capable of detecting variants, characterizing methylation patterns, resolving complex rearrangements, and assigning findings to long-range haplotypes. Here, we demonstrate the clinical utility of Nanopore long-read sequencing by validating a confirmatory test for copy number variants (CNVs) in neurodevelopmental disorders and illustrate the broader applications of this platform to assess genomic features with significant clinical implications.MethodsWe used adaptive sampling on the Oxford Nanopore platform to sequence 25 genomic DNA samples and 5 blood samples collected from patients with known or false-positive copy number changes originally detected using short-read sequencing. Across the 30 samples (a total of 50 with replicates), we assayed 35 known unique CNVs (a total of 55 with replicates) and one false-positive CNV, ranging in size from 40 kb to 155 Mb, and assessed the presence or absence of suspected CNVs using normalized read depth.ResultsAcross 50 samples (including replicates) sequenced on individual MinION flow cells, we achieved an average on-target mean depth of 9.5X and an average on-target read length of 4805 bp. Using a custom read depth-based analysis, we successfully confirmed the presence of all 55 known CNVs (including replicates) and the absence of one false-positive CNV. Using the same CNV-targeted data, we compared genotypes of single nucleotide variant loci to verify that no sample mix-ups occurred between assays. For one case, we also used methylation detection and phasing to investigate the parental origin of a 15q11.2-q13 duplication with implications for clinical prognosis.ConclusionsWe present an assay that efficiently targets genomic regions to confirm clinically relevant CNVs with a concordance rate of 100%. Furthermore, we demonstrate how integration of genotype, methylation, and phasing data from the Nanopore sequencing platform can potentially simplify and shorten the diagnostic odyssey.

Abstract 6064: Patient-partnered research enables germline characterization of angiosarcoma predisposition genes

Abstract Background: Angiosarcoma (ASC) represents 1-2% of soft tissue sarcomas. Due to its rarity, to date, no large-scale studies have been done to systematically identify ASC-predisposition genes and the broader landscape of pathogenic germline variants in patients with ASC remains unclear. Methods: Through the Angiosarcoma Project, an ongoing patient-partnered research approach that allows patients living anywhere in the U.S. or Canada with angiosarcoma to participate through a website, blood and saliva samples were collected from more than 300 patients and whole-exome-sequencing was performed. Machine-learning frameworks were used to identify germline short variants (SNPs, indels) and rare germline copy number variants (CNVs). The pathogenicity of variants in 107 curated cancer-predisposition and sarcoma-related genes were evaluated according to the ACMG guidelines. A short-variant-based gene-burden analysis was then performed using 223 unrelated ASC patients and 4557 ancestry-matched unrelated cancer-free controls. Results: In total, 38 patients (17.04%) carried at least one pathogenic short variant, including 37 carrying germline heterozygous pathogenic variants in POT1 (9, 4.04%), BRCA2 (3, 1.35%), CHEK2 (3, 1.35%), MUTYH (3, 1.35%), BRCA1 (2, 0.90%), PRF1 (2, 0.90%), ERCC3 (1, 0.45%), TP53 (2, 0.90%), ATM (1, 0.45%), TSHR (1, 0.45%), TSC2 (1, 0.45%), SDHA (1, 0.45%), SBDS (1, 0.45%), MSH6 (1, 0.45%), MITF (1, 0.45%), MET (1, 0.45%), LZTR1 (1, 0.45%), FH (1, 0.45%), ERCC2 (1, 0.45%), XPC (1, 0.45%). In addition, one patient harbored pathogenic short variants in both BRCA1 and ERCC3. In the 8 unique CNVs detected in 10 (4.55%) patients, 6 were classified as pathogenic including 3 heterozygous duplications overlapping MSH2, LZTR1, SMARCB1, and 3 heterozygous deletions overlapping NF1, MSH2, and WRN. Two unique heterozygous duplications met VUS criteria including one overlapping ERCC2 and one overlapping SMARCB1. In a comparison between ASC patients and cancer-free controls of predominantly European ancestry, we found ASC patients tobe 40 times more likely to carry a pathogenic variant in POT1 (OR: 42.91, CI: [15.40-174.08], q &amp;lt; 0.001, p &amp;lt; 0.001), while TP53 was nominally significant (OR: 7.37, CI: [1.19 - 41.13], p = 0.037). Conclusion: We confirmed prior observations of POT1 being responsible for ASC and called for attention to investigate the effect of germline CNVs in ASC. Overall, the elucidation of various germline elements associated with ASC risk highlighted the value and importance of patient-partnered research, particularly for rare cancers, and the analysis support using germline testing of patients for more precise clinical management. Citation Format: Hoyin Chu, Marissa Hollyer, Seunghun Han, Sabrina Y. Camp, Riaz Gillani, Eliezer Van Allen, Nikhil Wagle, Corrie A. Painter, Saud H. AlDubayan. Patient-partnered research enables germline characterization of angiosarcoma predisposition genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6064.

Decoding the Impact of Genetic Variants in Gastric Cancer Patients Based on High-Dimensional Copy Number Variation Data Using Next-Generation Knowledge Discovery Methods

Objectives: Despite a reduction in the incidence and mortality rates of gastric cancer (GC), it remains the fifth most frequently diagnosed malignancy globally. A better understanding of the regulatory mechanisms involved in the progression and development of GC is important for developing novel targeted approaches for treatment. We aimed to identify a set of differentially regulated pathways and cellular, molecular, and physiological system development and functions in GC patients infected with H. pylori infection based on copy number variation (CNV) data using next-generation knowledge discovery (NGKD) methods. Methods: In this study, we used our previous CNV data derived from tissue samples from GC patients (n = 33) and normal gastric samples (n = 15) by the comparative genome hybridization (CGH) method using Illumina HumanOmni1-Quad v.1.0 BeadChip (Zenodo Accession No: 1346283). The variant effects analysis of genetic gain or loss of function in GC was conducted using Ingenuity Pathway Analysis (IPA) software. In addition, in silico validation was performed with iPathwayGuide software using high-throughput RNA sequencing (RNAseq) data (GSE83088) from GC patients. Results: We observed 213 unique CNVs in the control group, 420 unique CNVs in the GC group, and 225 common variants. We found that cancer, gastrointestinal diseases, and organismal injury and abnormalities were the three diseases or disorders that were most affected in the GC group. We also identified that the programmed cell death ligand 1 (PD-L1) cancer immunotherapy pathway, T-cell apoptosis, T-cell exhaustion, and Type 1 regulatory T-cell (Tr1 cells) specialization were dysregulated in GC patients. RNAseq data from GC patients showed that the PD-1/PD-L1 pathway was significantly upregulated in GC samples compared with controls. Conclusions: In conclusion, in the present study, we decoded differentially impacted GC-specific diseases and biological functions and pathways based on CNV data using NGKD methods that can be adopted to design personalized therapeutic approaches for patients with GC in a typical clinical milieu.

Somatic single nucleotide variations and copy number variation can be used to distinguish high grade serous ovarian cancer from benign fallopian tubes with high accuracy (219)

Somatic single nucleotide variations and copy number variation can be used to distinguish high grade serous ovarian cancer from benign fallopian tubes with high accuracy (219)

Abstract 760: Concordance of DNA copy number profiles between primary and metastatic colorectal carcinoma

Abstract The most common form of genomic instability in sporadic colorectal cancer (CRC) is chromosomal instability, a phenotype characterized by a high frequency of DNA copy number gain (CNG) and loss (CNL). Given the fundamental role of chromosomal instability in the pathogenesis of CRC, this study aimed to investigate the concordance of DNA copy number variants (CNV) between primary and metastatic CRC to better understand how the genomic structure differs during tumor evolution. In this study, the SurePrint G3 Human Genome CGH+SNP 2x400K Microarray (Agilent, SC, California, USA) was used for genome-wide screening of CNV in 9 pairs of primary tumors and metachronous liver metastases obtained during surgical resection from patients diagnosed with advanced CRC. Data from the Microarray-based Comparative Genomic Hybridization was analyzed by COSMIC Cancer Gene Census (CGC) and an independent non-CGC panel to map hotspot regions harboring genes causally implicated in cancer in the course of the metastatic cascade. Also, unique CNV in metastases were further investigated to identify loci advantageous for tumor progression and those presumably associated with therapy resistance. Overall, CNG observed in primary tumors were highly concordant with those in liver metastases. The CNG hotspot regions for both tissues represented chr7 (p22.3-p13), chr8 (q21.13-q24.3), chr13 (q12.11-q13.3), chr20 (q11.1-q13.33) and chrX (q11.1-q28) loci, while the most frequent CNL was at chr8 (p21.3-p12) locus. All identified loci underwent CNV events with a higher frequency in metastases (67-100%) than in primary tumors (55%). The identified genomic loci with CNG encode DNA repair genes (such as PMS2, NBN, BRCA2, RAD54B, RAD21, RPA3,4, and TREX2), homeobox genes (HOXA9,11,13), genes encoding centrosome-associated proteins (CETN2, MPLKIP), proto-oncogenes (MYC), and also tumor suppressor (ATRX, ASXL1). Additionally, an analysis of unique CNV within distinct tissues revealed CNG at Chr6 (p25.1-p22.3) in 89% of metastatic samples and absent in all the primary tumor lesions. This particular genomic region contains proto-oncogene DEK. Although the analysis is still underway, we have identified several shared and unique regions of altered copy number in both, primary tumors and metastases. We conclude that despite the high inter- and intra-tumoral genomic heterogeneity, metachronous metastases “inherit” a similar profile of DNA CNV from their respective primary tumor tissues. We intend to further extend our studied group of patients and perform integrative analyses of CNV with gene expression. This study was supported by the Charles University (UNCE/MED/006) and the Grant Agency of the Czech Republic (21-04607X, 21-27902S) Citation Format: Michal Kroupa, Kristyna Tomasova, Katerina Saskova, Jana Drabova, Josef Horak, Ludmila Vodickova, Jachym Rosendorf, Vaclav Liska, Pavel Vodicka. Concordance of DNA copy number profiles between primary and metastatic colorectal carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 760.

Dynamic monitoring of cerebrospinal fluid circulating tumor DNA to identify unique genetic profiles of brain metastatic tumors and to better predict intracranial tumor response in patients with non–small cell lung cancer with brain metastases: A prospective cohort study.

2023 Background: Cerebrospinal fluid (CSF) can be used as a type of liquid biopsy to detect brain tumors. We aimed to explore the genetic profiles of CSF-derived circulating tumor DNA (ctDNA) to predict intracranial tumor response and monitor mutational evolution during systemic treatment in non-small cell lung cancer (NSCLC) patients with brain metastases. Methods: We conducted aprospective study of 92 newly diagnosed NSCLC patients with brain metastases. Paired CSF and plasma samples were collected at baseline, 8 weeks after treatment initiation, and at disease progression. Primary extracranial tumor samples were available for 58 patients and all samples underwent targeted next generation sequencing of 425 cancer-related genes. Results: At baseline, the positive detection rates of ctDNA in CSF, plasma, and extracranial tumors were 63.7% (58/91), 91.1% (82/90), and 100% (58/58), respectively. A high level of heterogeneity was observed between paired CSF and plasma samples, while concordance in driver mutations was also observed. A higher number of unique copy number variations (CNVs) were detected in CSF ctDNA than in plasma. CtDNA-positivity in baseline CSF samples was associated with poor outcomes (HR = 2.565, P = 0.003). Moreover, patients with increased concentrations of ctDNA in CSF after 8 weeks of treatment had significantly shorter intracranial progression-free survivals (PFS) than patients with decreased concentrations of CSF ctDNA (6.13 months vs 13.27 months, HR = 3.92, P = 0.007). Increased concentrations of plasma ctDNA were associated with shorter extracranial PFS (6.13 months vs 11.57 months, HR = 2.626, P = 0.032). From clonal evolution analyses, the accumulation of subclonal mutations in CSF ctDNA was observed after 8 weeks of systemic treatment. The clonal mutations remained more than 80% in CSF after 8-weeks of treatment also predicted a shorter intracranial PFS (HR = 3.785, P = 0.039). Conclusions: CSF ctDNA revealed unique genetic profiles of brain metastases, and dynamic changes in CSF ctDNA could better predict intracranial tumor response and track clonal evolution during treatment in NSCLC patients with brain metastases.

Integrated genomic and DNA methylation analysis of patients with advanced non-small cell lung cancer with brain metastases

BackgroundBrain metastasis is a common and lethal complication of non-small cell lung cancer (NSCLC). It is mostly diagnosed only after symptoms develop, at which point very few treatment options are available. Therefore, patients who have an increased risk of developing brain metastasis need to be identified early. Our study aimed to identify genomic and epigenomic biomarkers for predicting brain metastasis risk in NSCLC patients.MethodsPaired primary lung tumor tissues and either brain metastatic tissues or cerebrospinal fluid (CSF) samples were collected from 29 patients with treatment-naïve advanced NSCLC with central nervous system (CNS) metastases. A control group comprising 31 patients with advanced NSCLC who died without ever developing CNS metastasis was also included. Somatic mutations and DNA methylation levels were examined through capture-based targeted sequencing with a 520-gene panel and targeted bisulfite sequencing with an 80,672 CpG panel.ResultsCompared to primary lung lesions, brain metastatic tissues harbored numerous unique copy number variations. The tumor mutational burden was comparable between brain metastatic tissue (P = 0.168)/CSF (P = 0.445) and their paired primary lung tumor samples. Kelch-like ECH-associated protein (KEAP1) mutations were detected in primary lung tumor and brain metastatic tissue samples of patients with brain metastasis. KEAP1 mutation rate was significantly higher in patients with brain metastasis than those without (P = 0.031). DNA methylation analysis revealed 15 differentially methylated blocks between primary lung tumors of patients with and without CNS metastasis. A brain metastasis risk prediction model based on these 15 differentially methylated blocks had an area under the curve of 0.94, with 87.1% sensitivity and 82.8% specificity.ConclusionsOur analyses revealed 15 differentially methylated blocks in primary lung tumor tissues, which can differentiate patients with and without CNS metastasis. These differentially methylated blocks may serve as predictive biomarkers for the risk of developing CNS metastasis in NSCLC. Additional larger studies are needed to validate the predictive value of these markers.

Genome-Wide Detection of Copy Number Variations and Their Association With Distinct Phenotypes in the World's Sheep.

Copy number variations (CNVs) are a major source of structural variation in mammalian genomes. Here, we characterized the genome-wide CNV in 2059 sheep from 67 populations all over the world using the Ovine Infinium HD (600K) SNP BeadChip. We tested their associations with distinct phenotypic traits by conducting multiple independent genome-wide tests. In total, we detected 7547 unique CNVs and 18,152 CNV events in 1217 non-redundant CNV regions (CNVRs), covering 245 Mb (∼10%) of the whole sheep genome. We identified seven CNVRs with frequencies correlating to geographical origins and 107 CNVRs overlapping 53 known quantitative trait loci (QTLs). Gene ontology and pathway enrichment analyses of CNV-overlapping genes revealed their common involvement in energy metabolism, endocrine regulation, nervous system development, cell proliferation, immune, and reproduction. For the phenotypic traits, we detected significantly associated (adjusted P < 0.05) CNVRs harboring functional candidate genes, such as SBNO2 for polycerate; PPP1R11 and GABBR1 for tail weight; AKT1 for supernumerary nipple; CSRP1, WNT7B, HMX1, and FGFR3 for ear size; and NOS3 and FILIP1 in Wadi sheep; SNRPD3, KHDRBS2, and SDCCAG3 in Hu sheep; NOS3, BMP1, and SLC19A1 in Icelandic; CDK2 in Finnsheep; MICA in Romanov; and REEP4 in Texel sheep for litter size. These CNVs and associated genes are important markers for molecular breeding of sheep and other livestock species.

16. Copy number variants at Chr16p11.2 and relevant clinical presentations

Recurrent microdeletions and microduplications on chromosome 16p11.2 (MIM: 611913 and 614671) confer susceptibility to autism spectrum disorder (ASD) in ∼1% of individuals with ASD, in addition to other clinical features. To further analyze copy number variants (CNVs) in this region, we studied 41 individuals with 16p11.2 duplications and 53 individuals with 16p11.2 deletions at Greenwood Genetic Center. They share common clinical features including: developmental delay, intellectual disability, autism spectrum disorder, seizures, and some features that are unique to either deletions or duplications. We summarize unique CNVs in individuals with either deletion (n=41) or duplication (n=35) of these regions. By overlapping the del/dup regions, we identify six subtypes of CNVs and classify them by potential relevant breakpoints based on size and location. Types 1, 2 and 3 are more common with both deletions and duplications found in these regions, and they overlap with BP1-BP3, BP1-BP2 and BP4-BP5 regions, respectively, in the literature. Types 4, 5 and 6 are less frequent, locating at 31.5-32.5 Mb, 29.6-47.5 Mb and 28.48-28.49 Mb regions on chromosome 16. Type 5 is found only in individuals with duplications and type 6 only in individuals with deletions. Type 4 variants are more frequently observed in individuals of African American decent, yet no clear association could be determined due to small sample size in this study. Genotype-phenotype correlation analysis was also performed to narrow down the potentially causative genes for specific clinical features. It is also worth noting that de novo CNVs are observed with much higher frequency in individuals with 16p11.2 deletions (68.2%, n=22) compared to those with duplications (28.6%, n=14). In conclusion, our analysis explores 16p11.2 CNVs in more detail for rarely observed regions, and could broaden the understanding of the clinical significance of genes and non-coding regions in this chromosomal region.

Estimating the effects of copy-number variants on intelligence using hierarchical Bayesian models.

It is challenging to estimate the phenotypic impact of the structural genome changes known as copy-number variations (CNVs), since there are many unique CNVs which are nonrecurrent, and most are too rare to be studied individually. In recent work, we found that CNV-aggregated genomic annotations, that is, specifically the intolerance to mutation as measured by the pLI score (probability of being loss-of-function intolerant), can be strong predictors of intellectual quotient (IQ) loss. However, this aggregation method only estimates the individual CNV effects indirectly. Here, we propose the use of hierarchical Bayesian models to directly estimate individual effects of rare CNVs on measures of intelligence. Annotation information on the impact of major mutations in genomic regions is extracted from genomic databases and used to define prior information for the approach we call HBIQ. We applied HBIQ to the analysis of CNV deletions and duplications from three datasets and identified several genomic regions containing CNVs demonstrating significant deleterious effects on IQ, some of which validate previously known associations. We also show that several CNVs were identified as deleterious by HBIQ even if they have a zero pLI score, and the converse is also true. Furthermore, we show that our new model yields higher out-of-sample concordance (78%) for predicting the consequences of carrying known recurrent CNVs compared with our previous approach.

Six years\u2019 experience with LipidSeq: clinical and research learnings from a hybrid, targeted sequencing panel for dyslipidemias

BackgroundIn 2013, our laboratory designed a targeted sequencing panel, “LipidSeq”, to study the genetic determinants of dyslipidemia and metabolic disorders. Over the last 6 years, we have analyzed 3262 patient samples obtained from our own Lipid Genetics Clinic and international colleagues. Here, we highlight our findings and discuss research benefits and clinical implications of our panel.MethodsLipidSeq targets 69 genes and 185 single-nucleotide polymorphisms (SNPs) either causally related or associated with dyslipidemia and metabolic disorders. This design allows us to simultaneously evaluate monogenic—caused by rare single-nucleotide variants (SNVs) or copy-number variants (CNVs)—and polygenic forms of dyslipidemia. Polygenic determinants were assessed using three polygenic scores, one each for low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol.ResultsAmong 3262 patient samples evaluated, the majority had hypertriglyceridemia (40.1%) and familial hypercholesterolemia (28.3%). Across all samples, we identified 24,931 unique SNVs, including 2205 rare variants predicted disruptive to protein function, and 77 unique CNVs. Considering our own 1466 clinic patients, LipidSeq results have helped in diagnosis and improving treatment options.ConclusionsOur LipidSeq design based on ontology of lipid disorders has enabled robust detection of variants underlying monogenic and polygenic dyslipidemias. In more than 50 publications related to LipidSeq, we have described novel variants, the polygenic nature of many dyslipidemias—some previously thought to be primarily monogenic—and have uncovered novel mechanisms of disease. We further demonstrate several tangible clinical benefits of its use.

1479O - Integrated genomic and DNA methylation analyses of non-small cell lung cancer patients with brain metastases

BackgroundBrain metastases (BM), with a dismal prognosis, are a common and lethal complication of non-small cell lung cancer. Recognition of its genomic and epigenomic landscape is very necessary. MethodsCapture-based targeted sequencing for somatic mutation profiling was performed on 27 treatment-naïve advanced NSCLC patients with paired lung primary and BM lesions using a pane consisting of 520 cancer related genes. DNA methylation analyses was performed on same samples using a DNA methylation panel consisting of 100,000 CpG sites. ResultsCollectively, we identified 370 (291 SNVs+Indels, 78 CNVs and 1 rearrangement) and 574 (245 SNVs+Indels, 327 CNVs and 2 rearrangements) mutations from lung primary lesions and BM, respectively. Among them, 242 mutations were shared; 128 were lung primary-specific and 332 were BM-specific. Among the BM specific mutations, a majority of them (82%, 272/332) were copy number variations (CNVs). Only 16% of CNVs were shared by lung lesions and BM. The concordance for SNVs and indels were much higher-54% between the two sources of tissues. Furthermore, we observed a much higher concordance rate (79%) in TP53 and classic lung cancer driver genes than other genes (p<0.001), indicating that they might be stem mutations. Next, we performed pathway analysis of genes that were only mutated in BM and revealed an enrichment of genes participating in PI3K-AKT and focal adhesion pathways. Our DNA methylation analysis revealed distinct methylation patterns with 268 blocks that are significantly differentially methylated between primary lung lesions and BM. Among them, 211 blocks were hypermethylated in BM and the remaining 57 blocks were hypermethylated in lung lesions. These blocks were enrichment in genes participating in cell adhesion, Rap1 signaling and calcium signaling pathways. ConclusionsWe revealed diverse somatic mutation and DNA methylation profiles between lung primary lesions and BM. BM had significantly more unique CNVs. A great concordance was observed for classic lung cancer driver genes and TP53. Our study provided a comprehensive view of genomic and DNA methylation profiling for lung primary lesions and BM, paving the avenue for the development of targeted therapies for treating BM. Legal entity responsible for the studyThe authors. FundingHas not received any funding. DisclosureAll authors have declared no conflicts of interest.

Characterization of Copy Number Variations in Oral Cavity Squamous Cell Carcinoma Reveals a Novel Role for MLLT3 in Cell Invasiveness.

DNA copy number variations (CNVs) are a hallmark of cancer, and the current study aimed to demonstrate the profile of the CNVs for oral cavity squamous cell carcinoma (OSCC) and elucidate the clinicopathological associations and molecular mechanisms of a potential marker derived from CNVs, mixed-lineage leukemia translocated to chromosome 3 protein (MLLT3), in OSCC carcinogenesis. CNVs in 37 OSCC tissue specimens were analyzed using a high-resolution microarray, the OncoScan array. Gene expression was analyzed by real-time polymerase chain reaction in 127 OSCC and normal tissue samples. Cell function assays included cell cycle, migration, invasion and chromatin immunoprecipitation assays. We found a novel copy number amplified region, chromosome 9p, encompassing MLLT3 via the comparison of our data set with six other OSCC genome-wide CNV data sets. MLLT3 overexpression was associated with poorer overall survival in patients with OSCC (p = .048). MLLT3 knockdown reduced cell migration and invasion. The reduced invasion ability in MLLT3-knockdown cells was rescued with double knockdown of MLLT3 and CBP/p300-interacting transactivator with ED rich carboxy-terminal domain 4 (CITED4; 21.0% vs. 61.5%). Knockdown of MLLT3 impaired disruptor of telomeric silencing-1-like (Dot1L)-associated hypermethylation in the promoter of the tumor suppressor, CITED4 (p < .001), and hence dysregulated HIF-1α-mediated genes (TWIST, MMP1, MMP2, VIM, and CDH1) in OSCC cells. We identified unique CNVs in tumors of Taiwanese patients with OSCC. Notably, MLLT3 overexpression is related to the poorer prognosis of patients with OSCC and is required for Dot1L-mediated transcriptional repression of CITED4, leading to dysregulation of HIF-1α-mediated genes. This article reports unique copy number variations in oral cavity squamous cell carcinoma (OSCC) tumors of Taiwanese patients. Notably, MLLT3 overexpression is related to the poorer prognosis of patients with OSCC and is required for Dot1L-mediated transcriptional repression of CITED4, leading to dysregulation of HIF-1α-mediated genes.

886: Detection of copy-number variants in expanded carrier screening maximizes identification of cystic fibrosis carriers

Cystic fibrosis is one of the most common autosomal recessive conditions. Medical-society guidelines recommend routine carrier screening for cystic fibrosis via targeted genotyping of 23 frequent single-nucleotide variants (SNVs) and short insertions or deletions (indels) in the CFTR gene. Screening for copy-number variants (CNVs) is recommended only when a reproductive partner is a known carrier. Here we assess the performance and clinical impact of routinely screening for SNVs, indels, and CNVs in a next-generation sequencing (NGS)-based expanded carrier screen (ECS). Pathogenic variants in CFTR from 103,718 patients were discovered via a validated NGS-based ECS. A custom algorithm identified CNVs via relative deviations in NGS read depth. Approximate CNV breakpoints were inferred from the NGS-depth profile. Positive CNVs were orthogonally assessed via multiplex ligation-dependent probe amplification (MLPA). CFTR CNV sensitivity was explored across a range of length scales via in silico simulations. Among carriers of cystic fibrosis, 98.7% had pathogenic SNVs or indels in the CFTR gene (79% had one of the 23 common variants), and the remaining 1.3% harbored a pathogenic CNV spanning at least one exon. In total, we observed 25 unique CNVs with a diversity of breakpoints, suggesting that algorithms must be configured to detect novel CNVs. Further, single-exon deletions were observed for seven different CFTR exons; analysis of confidence scores for these empirical deletions—coupled with extensive simulations—demonstrated that the bioinformatics pipeline was both accurate and robust, even for short CNVs. All CNVs identified via NGS were confirmed via MLPA. CNV detection maximizes identification of cystic fibrosis carriers and can be applied to all patients undergoing an NGS-based ECS test validated to detect these complicated variants. Clinical guidelines recommending screening of only the 23 most frequent variants miss critical identification of carriers and should be revisited.