Small Indels Research Articles

Molecular characteristics of early-onset versus average-onset gastroesophageal adenocarcinoma.

496 Background: Incidence of early-onset gastroesophageal adenocarcinoma (eoGEA, ages <50 years) has been increasing in the United States since the 1990s, the etiology of which is still unclear, and limited data exists on molecular drivers. This study evaluates somatic and germline profiles in eoGEA compared to average-onset GEA (aoGEA, ages≥ 50 years). Methods: This is a retrospective, cross-sectional study utilizing data from de-identified records of GEA (esophageal, gastroesophageal junction and gastric adenocarcinomas) patients who underwent somatic NGS testing via the Tempus xT assay (595-648 gene DNA panel) from 12/2017 to 07/2024. This assay assesses somatic tumor mutations (including SNVs, Indels, CNVs, and select SVs), MSI, TMB, and incidentally detected germline SNVs and small indels in matched normal tissue. Clinical characteristics and immunotherapy markers were compared between eoGEA and aoGEA by Wilcoxon Rank Sum or Chi-squared test. Somatic and germline mutations were compared between two age groups with false discovery rate adjustments. Results: We compared the demographic, clinical, and molecular features of a total of 5863 patients with eoGEA (n=785, median age 43) and aoGEA (n=5078, median age 68). Over 80% of patients were diagnosed with stage IV disease. The eoGEA group had a higher proportion of females, non-white, and Hispanic or Latino patients compared to the aoGEA group (p<0.001). Prevalence of MSI-H/ dMMR, and TMB-H was lower in eoGEA vs aoGEA (p<0.001), while PD-L1 expression was similar. Prevalence of somatic CDH1 , CDKN2A , and TP53 SNVs, and FGFR2 and KRAS CNAs were higher in eoGEA vs aoGEA (q<0.001). In a subset of 3286 patients with tumor/normal match testing (eoGEA=464 and aoGEA=2822), eoGEA also had a higher prevalence of germline CDH1 mutations (q<0.001). Conclusions: eoGEA has a unique somatic and germline mutation profile compared to aoGEA; further study evaluating the molecular landscape including epigenetic changes could shed light on underlying mechanisms responsible for the rising incidence of eoGEA. eoGEA (n=785) aoGEA (n=5078) p-value/q-value* Baseline characteristics Median age at diagnosis (IQR) 43 (38, 47) 68 (61,74) <0.001 Gender: male 509 (65%) 3798 (75%) <0.001 Race (white) 280 (69%) 2347 (80%) <0.001 Ethnicity (not hispanic or latino) 206 (60%) 1768 (86% <0.001 Stage IV 495 (85%) 2883 (81%) 0.073 Immunologic markers TMB ≥ 10 25 (3.2%) 519(10%) <0.001 MSI-H 13 (1.7%) 261 (5.1%) <0.001 dMMR 7 (2.2%) 120 (5.9%) 0.007 Somatic mutations profiles * CDH1 126 (16%) 334 (6.6%) <0.001 TP53 515 (66%) 3764 (74%) <0.001 CDKN2A 101 (13%) 1011 (20%) <0.001 KRAS 92 (12%) 931 (18%) <0.001 NOTCH1 12 (1.5%) 228 (4.5%) 0.002 Germline mutation profiles * eoGEA (N=464) aoGEA (N= 2,822) Overall prevalence 46 (9.9%) 207 (7.3%) CDH1 10 (2.2%) 8 (0.3%) 0.001 TP53 3 (0.6%) 0 (0%) 0.039 BRCA2 2 (0.4%) 38 (1.3%) 0.6 BRIP1 4 (0.9%) 10 (0.4%) 0.6

Multiplex generation and single-cell analysis of structural variants in mammalian genomes.

Studying the functional consequences of structural variants (SVs) in mammalian genomes is challenging because (i) SVs arise much less commonly than single-nucleotide variants or small indels and (ii) methods to generate, map, and characterize SVs in model systems are underdeveloped. To address these challenges, we developed Genome-Shuffle-seq, a method that enables the multiplex generation and mapping of thousands of SVs (deletions, inversions, translocations, and extrachromosomal circles) throughout mammalian genomes. We also demonstrate the co-capture of SV identity with single-cell transcriptomes, facilitating the measurement of SV impact on gene expression. We anticipate that Genome-Shuffle-seq will be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, the chromatin landscape, and three-dimensional nuclear architecture, while also initiating a path toward a minimal mammalian genome.

Mitochondrial DNA variant detection in over 6,500 rare disease families by the systematic analysis of exome and genome sequencing data resolves undiagnosed cases.

Variants in the mitochondrial genome (mtDNA) cause a diverse collection of mitochondrial diseases and have extensive phenotypic overlap with Mendelian diseases encoded on the nuclear genome. The mtDNA is often not specifically evaluated in patients with suspected Mendelian disease, resulting in overlooked diagnostic variants. Using dedicated pipelines to address the technical challenges posed by the mtDNA - circular genome, variant heteroplasmy, and nuclear misalignment - single nucleotide variants, small indels, and large mtDNA deletions were called from exome and genome sequencing data, in addition to RNA-sequencing when available. A cohort of 6,660 rare disease families were analyzed (5,625 genetically undiagnosed, 84%) from the Genomics Research to Elucidate the Genetics of Rare diseases (GREGoR) Consortium as well as other rare disease cohorts. Diagnostic mtDNA variants were identified in 10 previously genetically undiagnosed families (one large deletion, eight reported pathogenic variants, one novel pathogenic variant). In one additional undiagnosed proband, the detection of >900 heteroplasmic variants provided functional evidence of pathogenicity to a novel de novo variant in the nuclear gene POLG (DNA polymerase gamma), responsible for mtDNA replication and repair. mtDNA variant calling from data generated by exome and genome sequencing for nuclear variant analysis resulted in a genetic diagnosis or detection of a candidate variant for 0.4% of undiagnosed families affected by a broad range of rare diseases.

The synthesis of the novel Escherichia coli toxin-colibactin and its mechanisms of tumorigenesis of colorectal cancer.

Escherichia coli is part of the normal flora of the human gut and performs vital functions; however, certain strains can cause disease in the host, impairing gut function and adversely affecting overall health. The pks gene cluster in the E. coli B2 serogroup encodes colibactin, a secondary metabolite and a potential gut toxin. However, the mechanism underlying colibactin production in E. coli is complex, and the function of the pks gene cluster is not fully understood. This review explores the complex mechanisms and processes by which the pks island in E. coli produces colibactin, clarifying the specific role played by the clbA-S genes within it. It also reveals the toxic effects of colibactin on the host cell's DNA and elaborates the mechanisms that may be important in inducing the development of colorectal cancer, such as single-base substitution (SBS), small insertion/deletion (small indel) features (ID-pks), inter-chromosomal linkages (ICLs), and DNA double-strand breaks (DSBs). The elucidation of these mechanisms is of great significance for the further exploration and development of related drugs.

Unveiling non-coding DMD variants: synergising RNA sequencing and DNA sequencing for enhanced molecular diagnosis

BackgroundPathogenic variants in the DMD gene are associated with dystrophinopathy including Duchenne and Becker muscular dystrophy (DMD/BMD). Targeted DMD gene, gene panels, exomes and genome sequencing have advanced genetic diagnostics,...

Experimental Evolution of Poxviruses.

Experimental evolution is the process of exposing virus populations to defined selective pressures in a laboratory setting to identify adaptive changes. Coupled with deep sequencing, this experimental approach allows for nucleotide-level resolution of poxvirus adaptive strategies over time. Here, we present a general method of poxvirus experimental evolution, Illumina-based deep sequencing, and bioinformatic analyses to identify structural changes (e.g., gene duplication) as well as local adaptive changes (e.g., small indels and single nucleotide polymorphisms).

SurVIndel2: improving copy number variant calling from next-generation sequencing using hidden split reads

Deletions and tandem duplications (commonly called CNVs) represent the majority of structural variations in a human genome. They can be identified using short reads, but because they frequently occur in repetitive regions, existing methods fail to detect most of them. This is because CNVs in repetitive regions often do not produce the evidence needed by existing short reads-based callers (split reads, discordant pairs or read depth change). Here, we introduce a new CNV short reads-based caller named SurVIndel2. SurVindel2 builds on statistical techniques we previously developed, but also employs a novel type of evidence, hidden split reads, that can uncover many CNVs missed by existing algorithms. We use public benchmarks to show that SurVIndel2 outperforms other popular callers, both on human and non-human datasets. Then, we demonstrate the practical utility of the method by generating a catalogue of CNVs for the 1000 Genomes Project that contains hundreds of thousands of CNVs missing from the most recent public catalogue. We also show that SurVIndel2 is able to complement small indels predicted by Google DeepVariant, and the two software used in tandem produce a remarkably complete catalogue of variants in an individual. Finally, we characterise how the limitations of current sequencing technologies contribute significantly to the missing CNVs.

Fitness consequences of structural variation inferred from a House Finch pangenome

Genomic structural variants (SVs) play a crucial role in adaptive evolution, yet their average fitness effects and characterization with pangenome tools are understudied in wild animal populations. We constructed a pangenome for House Finches (Haemorhous mexicanus), a model for studies of host-pathogen coevolution, using long-read sequence data on 16 individuals (32 de novo-assembled haplotypes) and one outgroup. We identified 887,118 SVs larger than 50 base pairs, mostly (60%) involving repetitive elements, with reduced SV diversity in the eastern US as a result of its introduction by humans. The distribution of fitness effects of genome-wide SVs was estimated using maximum likelihood approaches and revealed that SVs in both coding and noncoding regions were on average more deleterious than smaller indels or single nucleotide polymorphisms. The reference-free pangenome facilitated identification of a > 10-My-old, 11-megabase-long pericentric inversion on chromosome 1. We found that the genotype frequencies of the inversion, estimated from 135 birds widely sampled temporally and geographically, increased steadily over the 25 y since House Finches were first exposed to the bacterial pathogen Mycoplasma gallisepticum and showed signatures of balancing selection, capturing genes related to immunity and telomerase activity. We also observed shorter telomeres in populations with a greater number of years exposure to Mycoplasma. Our study illustrates the utility of long-read sequencing and pangenome methods for understanding wild animal populations, estimating fitness effects of genome-wide SVs, and advancing our understanding of adaptive evolution through structural variation.

Benchmarking nanopore sequencing and rapid genomics feasibility: validation at a quaternary hospital in New Zealand

Approximately 200 critically ill infants and children in New Zealand are in high-dependency care, many suspected of having genetic conditions, requiring scalable genomic testing. We adopted an acute care genomics protocol from an accredited laboratory and established a clinical pipeline using Oxford Nanopore Technologies PromethION 2 solo system and Fabric GEM™ software. Benchmarking of the pipeline was performed using Global Alliance for Genomics and Health benchmarking tools and Genome in a Bottle samples (HG002-HG007). Evaluation of single nucleotide variants resulted in a precision and recall of 0.997 and 0.992, respectively. Small indel identification approached a precision of 0.922 and recall of 0.838. Large genomic variations from Coriell Copy Number Variation Reference Panel 1 were reliably detected with ~2 M long reads. Finally, we present results obtained from fourteen trio samples, ten of which were processed in parallel with a clinically accredited short-read rapid genomic testing pipeline (Newborn Genomics Programme; NCT06081075; 2023-10-12).

Mutation profiling through whole genome sequencing of electron beam-induced black gram (Vigna mungo L. Hepper) mutant

Purpose Black gram (Vigna mungo [L.] Hepper) is an important annual legume with great economic, nutritional and ecological significance. Novel variations through induced mutagenesis can accelerate narrow genetic base-impeded black gram improvement. This is a first study on characterization of genome-wide mutation spectrum induced by electron beam (EB). Materials and methods Black gram genotype ‘Pant U-31’ was irradiated with 400 Gy EB generated in a 10 MeV LINAC. A stable mutant PM-32 (M6) was re-sequenced by combining Illumina (BIOO Scientific, Inc., Austin, TX) and Nanopore Technologies (Oxford, UK). Variants were predicted in reference to the available whole genome scaffold level draft assembly of parent ‘Pant U-31’. Results Genome analysis predicted a total of 76,893 genes of which 58,517 were annotated. The identified variants totaling 728,161, largely comprised (91.56%) of single base substitutions (SBSs) with a transition (Ti) to transversion (Tv) ratio of 1.95. Of the indels constituting 8.44% of total induced variants, insertions accounted for 4.29%, with preponderance of multiple bases (53.63%) and 2–5 bp insertions as the major class (33.71%). Multiple-base deletions (2–5 bases) formed the bulk (31.14%) of the total deletions. The genic variants (2438) with estimated high and moderate effects were located within 1271 predicted genes. A higher number of mutations were observed on chromosomes Vm1 (588) and Vm3 (428) with the highest frequency on chromosome Vm3 (every 0.07 Mb). Conclusions Our study reiterated the mutagenic utility of EB for inducing SBSs and small indels genome-wide. The knowledge gained from SNP-level profiling of EB-induced mutations can expedite comparative mutation breeding studies in legumes.

Reproductive and germ-cell mutagenic effects of poly-and perfluoroalkyl substances (PFAS) to Caenorhabditis elegans after multigenerational exposure

Per- and polyfluoroalkyl substances (PFAS) are a class of globally ubiquitous persistent organic pollutants (POPs). The developmental and reproductive toxicity of PFAS have attracted considerable attention. However, the influence of PFAS exposure on genomic stability of germ cells remains unexplored. In this study, we evaluated long-term reproductive toxicity of environmentally relevant levels of four long-chain PFAS compounds: perfluorooctanoic acid (PFOA, C8), perfluorononanoic acid (PFNA, C9), perfluorodecanoic acid (PFDA, C10), and perfluorooctanesulfonic acid (PFOS, C8), and examined their germ-cell mutagenicity in Caenorhabditis elegans. Our findings reveal that multigenerational exposure to PFAS exhibited minor impacts on development and reproduction of worms. Among all tested PFAS, PFNA significantly increased mutation frequencies of progeny by preferentially inducing T:A → C:G substitutions and small indels within repetitive regions. Further analysis of mutation spectra uncovered elevated frequencies of microhomology-mediated deletions and large deletions in PFOA-treated worms, indicating its potential activity in eliciting DNA double-strand breaks. This study provides the first comparative analysis of the genome-wide mutational profile of PFAS compounds, underscoring the importance of assessing germ-cell mutagenic actions of long-chain PFAS.

Genome sequencing reveals novel causative structural and single nucleotide variants in Pakistani families with congenital hypogonadotropic hypogonadism

Background/ObjectivesThis study aims to elucidate the genetic causes of congenital hypogonadotropic hypogonadism (CHH), a rare genetic disorder resulting in GnRH deficiency, in six families from Pakistan.MethodsEighteen DNA samples from six families underwent genome sequencing followed by standard evaluation for pathogenic single nucleotide variants (SNVs) and small indels. All families were subsequently analyzed for pathogenic copy number variants (CNVs) using CoverageMaster.ResultsNovel pathogenic homozygous SNVs in known CHH genes were identified in four families: two families with variants in GNRHR, and two others harboring KISS1R variants. Subsequent investigation of CNVs in the remaining two families identified novel unique large deletions in ANOS1.ConclusionA combined, systematic analysis of single nucleotide and CNVs helps to improve the diagnostic yield for variants in patients with CHH.

Genomic insights into prenatal diagnosis of congenital heart defects: value of CNV-seq and WES in clinical practice.

This study aimed to assess the efficiency of CNV-seq and WES in detecting genetic cause of congenital heart disease (CHDs) in prenatal diagnoses and to compare CNV detection rate between isolated and non-isolated CHD cases. We conducted a retrospective study of 118 Chinese fetuses diagnosed with CHD by prenatal ultrasound. Participants underwent CNV-seq and, if necessary, WES to detect chromosomal and single nucleotide variations. The overall detection rate for pathogenic or likely pathogenic chromosomal abnormalities was 16.9%, including 7.6% aneuploidies and 9.3% pathogenic/likely pathogenic copy number variations (CNVs), predominantly 22q11.2 deletion syndrome (54.4%). The sensitivity and specificity of CNV-Seq for detecting P/Lp CNVs were 95% and 100%, respectively. CNV-Seq offered a 6.7% improvement in detecting chromosomal abnormalities over karyotyping. WES further identified significant single nucleotide and small indel variations contributing to CHD in genes such as TMEM67, PLD1, ANKRD11, and PNKP, enhancing diagnostic yield by 14.8% in cases negative for CNVs. Non-isolated CHD cases exhibited higher rates of detectable chromosomal abnormalities compared to isolated cases (32.4% vs. 9.9%, p = 0.005), underlining the genetic complexity of these conditions. The combined use of CNV-seq and WES provides a comprehensive approach to prenatal genetic testing for CHDs, unveiling significant genetic cause that could impact clinical management and parental decision-making. This study supports the integration of these advanced genomic technologies in routine prenatal diagnostics to increase detection diagnostic yields of causal genetic variants associated with CHDs.

VolcanoSV enables accurate and robust structural variant calling in diploid genomes from single-molecule long read sequencing

Structural variants (SVs) significantly contribute to human genome diversity and play a crucial role in precision medicine. Although advancements in single-molecule long-read sequencing offer a groundbreaking resource for SV detection, identifying SV breakpoints and sequences accurately and robustly remains challenging. We introduce VolcanoSV, an innovative hybrid SV detection pipeline that utilizes both a reference genome and local de novo assembly to generate a phased diploid assembly. VolcanoSV uses phased SNPs and unique k-mer similarity analysis, enabling precise haplotype-resolved SV discovery. VolcanoSV is adept at constructing comprehensive genetic maps encompassing SNPs, small indels, and all types of SVs, making it well-suited for human genomics studies. Our extensive experiments demonstrate that VolcanoSV surpasses state-of-the-art assembly-based tools in the detection of insertion and deletion SVs, exhibiting superior recall, precision, F1 scores, and genotype accuracy across a diverse range of datasets, including low-coverage (10x) datasets. VolcanoSV outperforms assembly-based tools in the identification of complex SVs, including translocations, duplications, and inversions, in both simulated and real cancer data. Moreover, VolcanoSV is robust to various evaluation parameters and accurately identifies breakpoints and SV sequences.

Genotyping SNPs and Indels: A method to improve the scope and sensitivity of High-Resolution melt (HRM) analysis based applications

High-resolution melt (HRM) analysis is a closed-tube technique for detecting single nucleotide polymorphisms (SNPs). However, it has limited use in high-resolution melting devices, even those with high thermal accuracy (HTA). In addition to the cost of switching to these specialized devices, the presence of nearest neighbour neutral changes (class III, IV SNPs and small indels) made HRM-based assays a challenging task due to reduced sensitivity. This study aimed to design a common modified competitive amplification of differently melting amplicons (CADMA)-based assay to address these challenges by generating allele-specific qPCR products that are detectable on most qPCR platforms.For this study, SNPs were selected from all four classes of SNPs (class I: C/T or G/A mutation; class II: C/A or G/T mutation; class III: G/C mutation; class IV: A/T mutation). A single base pair and 19 bp indels were also chosen to simulate how CADMA primers could be designed for indels of varying lengths. The melting temperatures (Tm) were determined using IDT oligoAnalyzer. qPCR and melt data acquisition were performed on the CFX96 qPCR platform, and the melt curve data were analyzed using Precision Melt software (Bio-Rad, USA). The clusters for different genotypes were successfully identified with the aid of the control samples, and Tm predictions were carried out using the uMelt batch and Tm online tools for comparison.Using HRM-qPCR assays based on the modified CADMA method, genotyping of various SNPs was successfully carried out. For some SNPs, similarly shaped melt curves were observed for homozygotes and heterozygotes, making shape-based genotype prediction difficult. The Tm values calculated via the Blake and Delcourts (1998) method were the closest to the experimental Tm values after adjusting for the salt concentration.Since HRM assays usually depend on the ΔTm caused by mutations, they are prone to a high error rate due to nearest neighbour neutral changes. The technique developed in this study significantly reduces the failure rates in HRM-based genotyping and could be applied to any SNP or indel in any platform. It is crucial to have a deep understanding of the melt instrument, its accuracy and the nature of the target (SNP class or indel length and GC content of the flanking region). Furthermore, the availability of controls is essential for a high success rate.

High-depth whole-genome sequencing identifies structure variants, copy number variants and short tandem repeats associated with Parkinson’s disease

While numerous single nucleotide variants and small indels have been identified in Parkinson’s disease (PD), the contribution of structural variants (SVs), copy number variants (CNVs), and short tandem repeats (STRs) remains poorly understood. Here we investigated the association using the high-depth whole-genome sequencing data from 466 Chinese PD patients and 513 controls. Totally, we identified 29,561 SVs, 32,153 CNVs, and 174,905 STRs, and found that CNV deletions were significantly enriched in the end-proportion of autosomal chromosomes in PD. After genome-wide association analysis and replication in an external cohort of 352 cases and 547 controls, we validated that the 1.6 kb-deletion neighboring MUC19, 12.4kb-deletion near RXFP1 and GGGAAA repeats in SLC2A13 were significantly associated with PD. Moreover, the MUC19 deletion and the SLC2A13 5-copy repeat reduced the penetrance of the LRRK2 G2385R variant. Moreover, genes with these variants were dosage-sensitive. These data provided novel insights into the genetic architecture of PD.

Paired comparison of the analytical performance between the Oncomine™ Comprehensive Assay v3 and whole-exome sequencing of ovarian cancer tissue

BackgroundNext-generation sequencing (NGS) has been implemented in clinical oncology as a personalized medicine tool to identify targetable genetic alterations and to guide treatment decisions. However, the optimal NGS test strategy and target genes for clinical use are still being discussed. The aim was to compare the performance of the Oncomine™ Comprehensive Assay v3 (OCAv3) (targeted gene panel) and whole-exome sequencing (WES) to investigate somatic single and multiple nucleotide variants and small indels in ovarian cancer patients.Methods and resultsGenomic DNA was isolated from fresh frozen samples of five high-grade serous (HGSC) and three clear cell ovarian (oCCC) cancer patients. Exome sequencing libraries were prepared by using the Ion AmpliSeq Exome RDY kit, whereas libraries for OCAv3 were prepared using by Ion AmpliSeq™ Library Kit Plus. Sequencing was performed using the Ion S5XL System (Thermo Fisher Scientific). When including only variants classified as pathogenic, likely pathogenic or unknown significance based on ClinVar database verdicts and comparing overlapping regions covered both by the OCAv3 assay and WES, 23 variants were detected by both assays. However, OCAv3 detected additionally two variants: ARID1A: p.Gln563Ter and TP53: p.Ser261ValfsTer84 that have not passed WES filtering criteria due to low coverage.ConclusionsWith the present treatment possibilities, OCAv3 panel testing provided higher diagnostic yield due to better coverage. Our study emphasizes that WES, although offering the potential to identify novel findings in genes not covered by OCAv3, might overlook variants in genes relevant for OC.

Phenotypic and mutational spectrum of 17 Chinese patients with Menkes Disease.

Menkes Disease (MD) is a fatal X-linked recessive disorder caused by mutations in the ATP7A gene. Severe cases typically die before the age of three. Mild MD and occipital horn syndrome are variants of MD characterized by a less severe phenotype and longer survival. This case series aims to validate previous findings, expand the clinical phenotype, identify novel ATP7A mutations of MD patients. Observational data with follow-up were collected from 17 genetically diagnosed Chinese MD patients. All 17 patients exhibited neurological symptoms, including delayed motor milestones (100%) and seizures (58.8%). Unspecific pregnancy or delivery complications occurred in 9 patients (52.9%). The most prevalent connective tissue problems were abnormal hair (76.5%), followed by skeletal and dental abnormalities (52.9%), skin problems (41.2%) and hernia (35.3%). Sensorineural hearing loss (17.6%) was previously unreported. Coronary artery aneurysm and patent foramen ovale (5.9%) were infrequent. One 16-year-old boy carries pathological exon 3-4 deletion, presents novel mild phenotype including short stature and cerebellar ataxia. Out of 13 patients with follow-up (median: 24 months), 7 patients (53.8%) died with median survival of 40 months (range: 21-48 months), 3 patients (23.1%) show severe motor development delay and 2 (15.4%) have refractory epilepsy, only the mild MD patient shows improved cerebellar ataxia. Sixteen ATP7A mutations were identified including 6 small indels (37.5%), 5 nonsense mutations (31.2%), 2 missense mutations (12.5%), 2 exon deletions (12.5%), and 1 splice site mutation (6.25%). Fourteen mutations were novel. Our study further broadens the phenotypic and genotypic spectrums of Menkes disease.

METB-14. INTEGRATED GERMLINE AND SOMATIC PROFILING OF PEDIATRIC BRAIN TUMORS REVEALS INCIDENTAL FINDINGS AND NOVEL TUMOR BIOLOGY

Abstract BACKGROUND The contribution of rare pathogenic germline variation to central nervous system (CNS) tumor formation in pediatric patients without a family history of cancer remains unclear. METHODS We characterized the prevalence of pathogenic germline variants in 214 cancer predisposition genes (CPGs) in 837 patients profiled in the Pediatric Brain Tumor Atlas by whole genome or exome sequencing (n=820 and n=17, respectively). Rare SNVs and small INDELs were annotated as pathogenic (P) or likely pathogenic (LP) consistent with American College of Medical Genetics criteria using AutoGVP, our open-source automated pathogenicity assessment tool. We classified pathogenicity of germline structural variants (SVs) using ClassifyCNV and AnnotSV. Somatic alterations and mutational signatures from matched tumor sequencing were integrated to identify functional consequences associated with germline pathogenic variation. RESULTS We observed 206 germline P/LP SNVs/small INDELs and 18 SVs (16 deletions, 2 duplications) within 78 unique CPGs in 195 patients (23.3%). We detected syndrome-associated P/LP variants in 45/58 patients with a clinically-reported cancer predisposition syndrome and incidentally in 41 patients. Ninety-five (42%) germline P/LP variants co-occurred with at least one somatic alteration in the same gene in matched tumors: n=6 oncogenic SNVs, n=28 CNVs, n=54 loss of heterozygosity (LOH), n=26 differential gene or protein expression, and n=18 alternative splicing. NF1, TSC1, and TSC2 germline P/LP carriers exhibited significantly higher tumor LOH scores and lower gene expression in tumors relative to non-P/LP carriers. Patients with germline splice region P/LP variants exhibited significantly increased skipping of most the proximal exon in matched tumor relative to patients with non-splice region P/LP variants (W=401, p=1.1E-04). CONCLUSION We have identified rare germline P/LP variants associated with cancer predisposition syndromes and diverse functional consequences in pediatric CNS tumor patients. Efforts are underway to extend this work to include 1,801 additional probands and 1,105 parents to further characterize the prevalence and heritability of germline pathogenic variation in children diagnosed with CNS tumors.

Abstract IA020: Functional studies of genetic variation using precision genome editing

Abstract Tumor genomes often harbor a complex spectrum of single nucleotide mutations, small indels, and large chromosome rearrangements that can perturb coding and non-coding regions of the genome in ways that remain poorly understood. The mutational processes responsible for the genesis of these events are also not static; instead, they continue to operate throughout disease evolution and further diversify the genetic and phenotypic landscape of cancer cells. Mounting evidence suggests that tumor genotype can be an important determinant of disease progression and therapy response, such as by modulating the sensitivity or resistance of cancer cells to mutant-specific drugs. These types of observations have motivated efforts to treat cancers with genome-informed therapies, highlighting the need to understand how different genetic variants precisely affect gene function and overall tumor phenotypes. Variant-function maps that provide a mechanistic understanding of the biology driven by cancer-associated mutations are needed to design these types of treatment strategies. Precision genome editing technologies like base and prime editing are uniquely suited to tackle this problem. Nevertheless, deploying these methods for systematic variant-function studies and disease modeling in vivo has not been straightforward due to lack of robust and scalable platforms capable of assessing editing efficiency and precision, particularly at endogenous loci. With this goal in mind, we previously developed and applied high-throughput base editing ‘sensor’ approaches that link endogenous genome editing outcomes with synthetic DNA-based readouts and cellular fitness measurements. Using these approaches, we showed that several uncharacterized mutant p53 alleles drive cancer cell proliferation and in vivo tumor development. Building upon this work, we recently developed new prime editing guide RNA design tools and sensor-based approaches that similarly couple quantitative editing outcomes to cellular fitness, allowing us to significantly expand the breadth of cancer-associated mutations that can be interrogated using these precision genome editing technologies. In this talk, I will describe ongoing work using base and prime editing sensor libraries to probe the biological impact of thousands of functionally-distinct genetic variants in diverse types of protein-coding genes and families to learn how these influence various cancer phenotypes. I will also discuss how the implementation of these modular technologies will allow researchers to functionally disentangle the impact of endogenous and exogenous mutational processes on functional selection and tumor evolution with close to single base pair resolution. This generalizable precision genome editing framework will facilitate the functional interrogation of genetic variants across diverse biological contexts, providing much needed insight into cancer variant-function relationships that could be leveraged to develop more precise cancer treatment paradigms, including synthetic lethal therapies that exploit tumor genotype. Citation Format: Francisco J. Sánchez-Rivera, Samuel I. Gould, Alexandra N. Wuest, Kexin Dong, Grace A. Johnson, Alvin Hsu, Varun K. Narendra, Ondine Atwa, Stuart S. Levine, David R. Liu. Functional studies of genetic variation using precision genome editing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA020.