Tumor Antigens beyond the Human Exome.

With the advent of immunotherapeutics, a new era in the combat against cancer has begun. Particularly promising are neo-epitope-targeted therapies as the expression of neo-antigens is tumor-specific. In turn, this allows the selective targeting and killing of cancer cells whilst healthy cells remain largely unaffected. So far, many advances have been made in the development of treatment options which are tailored to the individual neo-epitope repertoire. The next big step is the achievement of efficacious "off-the-shelf" immunotherapies. For this, shared neo-epitopes propose an optimal target. Given the tremendous potential, a thorough understanding of the underlying mechanisms which lead to the formation of neo-antigens is of fundamental importance. Here, we review the various processes which result in the formation of neo-epitopes. Broadly, the origin of neo-epitopes can be categorized into three groups: canonical, noncanonical, and viral neo-epitopes. For the canonical neo-antigens that arise in direct consequence of somatic mutations, we summarize past and recent findings. Beyond that, our main focus is put on the discussion of noncanonical and viral neo-epitopes as we believe that targeting those provides an encouraging perspective to shape the future of cancer immunotherapeutics.

Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension.

Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.

Whole-exome-based single nucleotide variants and copy number analysis for prenatal diagnosis of compound heterozygosity of SMPD4.

BACKGROUND: Biallelic loss-of-function variants in SMPD4 cause a rare and severe neurodevelopmental disorder. These variants have been identified in a group of children with neurodevelopmental disorders with microcephaly, arthrogryposis, and structural brain anomalies. SMPD4 encodes a sphingomyelinase that hydrolyzes sphingomyelin into ceramide at neutral pH and can thereby affect membrane lipid homeostasis. SMPD4 localizes to the membranes of the endoplasmic reticulum and nuclear envelope and interacts with nuclear pore complexes. MATERIALS AND METHODS: For the efficient prenatal diagnosis of rare and undiagnosed diseases, the parallel detection of copy number variants (CNVs) and single nucleotide variants using whole-exome analysis is required. A physical examination of the parents was performed. Karyotype and whole-exome analysis were performed for the fetus and the parents. RESULTS: A fetus with microcephaly and arthrogryposis; biallelic null variants (c.387-1G>A; Chr2[GRCh38]: g.130142742_130202459del) were detected by whole-exome sequencing (WES). We have reported for the first time the biallelic loss-of-function mutations in SMPD4 in patients born to unrelated parents in China. CONCLUSION: WES could replace chromosomal microarray analysis and copy number variation sequencing as a more cost-effective genetic test for detecting CNVs and diagnosing highly heterogeneous conditions.

Exome-wide analysis implicates rare protein-altering variants in human handedness.

Handedness is a manifestation of brain hemispheric specialization. Left-handedness occurs at increased rates in neurodevelopmental disorders. Genome-wide association studies have identified common genetic effects on handedness or brain asymmetry, which mostly involve variants outside protein-coding regions and may affect gene expression. Implicated genes include several that encode tubulins (microtubule components) or microtubule-associated proteins. Here we examine whether left-handedness is also influenced by rare coding variants (frequencies ≤ 1%), using exome data from 38,043 left-handed and 313,271 right-handed individuals from the UK Biobank. The beta-tubulin gene TUBB4B shows exome-wide significant association, with a rate of rare coding variants 2.7 times higher in left-handers than right-handers. The TUBB4B variants are mostly heterozygous missense changes, but include two frameshifts found only in left-handers. Other TUBB4B variants have been linked to sensorineural and/or ciliopathic disorders, but not the variants found here. Among genes previously implicated in autism or schizophrenia by exome screening, DSCAM and FOXP1 show evidence for rare coding variant association with left-handedness. The exome-wide heritability of left-handedness due to rare coding variants was 0.91%. This study reveals a role for rare, protein-altering variants in left-handedness, providing further evidence for the involvement of microtubules and disorder-relevant genes.

Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease.

Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and, with new innovative methods, can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the Genomics Research to Elucidate the Genetics of Rare Diseases consortium and analyzed using the seqr platform. The addition of CNV detection to exome analysis identified causal CNVs for 171 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb. The causal CNVs consisted of 140 deletions, 15 duplications, 3 suspected complex structural variants (SVs), 3 insertions, and 10 complex SVs, the latter two groups being identified by orthogonal confirmation methods. To classify CNV variant pathogenicity, we used the 2020 American College of Medical Genetics and Genomics/ClinGen CNV interpretation standards and developed additional criteria to evaluate allelic and functional data as well as variants on the X chromosome to further advance the framework. We interpreted 151 CNVs as likely pathogenic/pathogenic and 20 CNVs as high-interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher-resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.

Genome and RNA sequencing boost neuromuscular diagnoses to 62% from 34% with exome sequencing alone.

OBJECTIVE: Most families with heritable neuromuscular disorders do not receive a molecular diagnosis. Here we evaluate diagnostic utility of exome, genome, RNA sequencing, and protein studies and provide evidence-based recommendations for their integration into practice. METHODS: In total, 247 families with suspected monogenic neuromuscular disorders who remained without a genetic diagnosis after standard diagnostic investigations underwent research-led massively parallel sequencing: neuromuscular disorder gene panel, exome, genome, and/or RNA sequencing to identify causal variants. Protein and RNA studies were also deployed when required. RESULTS: Integration of exome sequencing and auxiliary genome, RNA and/or protein studies identified causal or likely causal variants in 62% (152 out of 247) of families. Exome sequencing alone informed 55% (83 out of 152) of diagnoses, with remaining diagnoses (45%; 69 out of 152) requiring genome sequencing, RNA and/or protein studies to identify variants and/or support pathogenicity. Arrestingly, novel disease genes accounted for <4% (6 out of 152) of diagnoses while 36.2% of solved families (55 out of 152) harbored at least one splice-altering or structural variant in a known neuromuscular disorder gene. We posit that contemporary neuromuscular disorder gene-panel sequencing could likely provide 66% (100 out of 152) of our diagnoses today. INTERPRETATION: Our results emphasize thorough clinical phenotyping to enable deep scrutiny of all rare genetic variation in phenotypically consistent genes. Post-exome auxiliary investigations extended our diagnostic yield by 81% overall (34-62%). We present a diagnostic algorithm that details deployment of genomic and auxiliary investigations to obtain these diagnoses today most effectively. We hope this provides a practical guide for clinicians as they gain greater access to clinical genome and transcriptome sequencing.

Exome-Based Amino Acid Optimization: A Dietary Strategy to Satisfy Human Nutritional Demands and Enhance Muscle Strength in Breast Tumor Mice Undergoing Chemotherapy.

Breast cancer patients undergoing chemotherapy often experience muscle wasting and weakness, which impact their quality of life. A potential solution lies in customizing amino acid compositions based on exome-derived formulations (ExAAs). The study hypothesized that tailoring dietary amino acids using ExAAs could enhance muscle health. Theoretical amino acid requirements were calculated from the genome's exome region, and a breast cancer mouse model undergoing paclitaxel treatment was established. The mice were supplemented with a cancer-specific nutritional formula (QJS), and the effects of QJS and amino acid-adjusted QJS (adjQJS) were compared. Both formulations improved the nutritional status without compromising tumor growth. Notably, adjQJS significantly enhanced muscle strength compared to QJS (1.51 ± 0.25 vs. 1.30 ± 0.08 fold change, p < 0.05). Transcriptome analysis revealed alterations in complement and coagulation cascades, with an observed upregulation of C3 gene expression in adjQJS. Immune regulation also changed, showing a decrease in B cells and an increase in monocytes in skeletal muscle with adjQJS. Importantly, adjQJS resulted in a notable increase in Alistipes abundance compared to QJS (10.19 ± 0.04% vs. 5.03 ± 1.75%). This study highlights the potential of ExAAs as valuable guide for optimizing amino acid composition in diets for breast cancer patients undergoing chemotherapy.

Implementation of whole-exome sequencing for pharmacogenomics profiling and exploring its potential clinical utilities.

Whole-exome sequencing (WES) is widely used in clinical settings; however, the exploration of its use in pharmacogenomic analysis remains limited. Our study compared the variant callings for 28 core absorption, distribution, metabolism and elimination genes by WES and array-based technology using clinical trials samples. The results revealed that WES had a positive predictive value of 0.71-0.92 and a sensitivity of single-nucleotide variants between 0.68 and 0.95, compared with array-based technology, for the variants in the commonly targeted regions of the WES and PhamacoScan™ assay. Besides the common variants detected by both assays, WES identified 200-300 exclusive variants per sample, totalling 55 annotated exclusive variants, including important modulators of metabolism such as rs2032582 (ABCB1) and rs72547527 (SULT1A1). This study highlights the potential clinical advantages of using WES to identify a wider range of genetic variations and enabling precision medicine.

Investigation of Recessive Effects of Coding Variants on Common Clinical Phenotypes in Exome-Sequenced UK Biobank Participants.

INTRODUCTION: Previous studies have demonstrated effects of rare coding variants on common, clinically relevant phenotypes although the additive burden of these variants makes only a small contribution to overall trait variance. Although recessive effects of individual homozygous variants have been studied, little work has been done to elucidate the impact of rare coding variants occurring together as compound heterozygotes. METHODS: In this study, attempts were made to identify pairs of variants likely to be occurring as compound heterozygotes using 200,000 exome-sequenced subjects from the UK Biobank. Pairs of variants, which were seen together in the same subject more often than would be expected by chance, were excluded as it was assumed that these might be present in the same haplotype. Attention was restricted to variants with minor allele frequency ≤0.05 and to those predicted to alter amino acid sequence or prevent normal gene expression. For each gene, compound heterozygotes were assigned scores based on the rarity and predicted functional consequences of the constituent variants and the scores were used in a logistic regression analysis to test for association with hypertension, hyperlipidaemia, and type 2 diabetes. RESULTS: No statistically significant associations were observed and the results conformed to the distribution, which would be expected under the null hypothesis. The average number of apparently compound heterozygous subjects for each gene was only 282.2. CONCLUSION: It seems difficult to detect an effect of compound heterozygotes on the risk of these phenotypes. Even if recessive effects from compound heterozygotes do occur, they would only affect a small number of people and overall would not make a substantial contribution to phenotypic variance. This research has been conducted using the UK Biobank Resource.

Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas: next-generation sequencing and machine learning for full tumor exome analysis.

About 7% of all cancer deaths are caused by pancreatic cancer (PCa). PCa is known for its lowest survival rates among all oncological diseases and heterogenic molecular profile. Enormous amount of genetic changes, including somatic mutations, exceeds the limits of routine clinical genetic laboratory tests and further stagnates the development of personalized treatments. We aimed to build a mutational landscape of PCa in the Russian population based on full exome next-generation sequencing (NGS) of the limited group of patients. Applying a machine learning model on full exome individual data we received personalized recommendations for targeted treatment options for each clinical case and summarized them in the unique therapeutic landscape.

A Rare Inherited Bone Marrow Failure Syndrome Disclosed by Reanalysis of the Exome Data of a Patient Evaluated for Cytopenia and Dysmorphic Features.

BACKGROUND: Multisystemic findings of inherited bone marrow failure syndromes may cause difficulty in diagnosis. Exome sequencing (ES) helps to define the etiology of rare diseases and reanalysis offers a valuable new diagnostic approach. Herein, we present the clinical and molecular characteristics of a girl who was referred for cytopenia and frequent infections. CASE REPORT: A 5-year-old girl with cytopenia, dysmorphism, short stature, developmental delay, and myopia was referred for genetic counseling. Reanalysis of the ES data revealed a homozygous splice-site variant in the DNAJC21 (NM_001012339.3:c.983+1G>A), causing Shwachman-Diamond Syndrome (SDS). It was shown by the RNA sequencing that exon 7 was skipped, causing an 88-nucleotide deletion. CONCLUSIONS: Precise genetic diagnosis enables genetic counseling and improves patient management by avoiding inappropriate treatment and unnecessary testing. This report would contribute to the clinical and molecular understanding of this rare type of SDS caused by DNAJC21 variants and expand the phenotypic features of this condition.

Rapid exome sequencing for children with severe acute encephalopathy - A case series.

Increasingly, next-generation sequencing (NGS) is becoming an invaluable tool in the diagnosis of unexplained acute neurological disorders, such as acute encephalopathy/encephalitis. Here, we describe a brief series of pediatric patients who presented at the pediatric intensive care unit with severe acute encephalopathy, initially suspected as infectious or inflammatory but subsequently diagnosed with a monogenic disorder. Rapid exome sequencing was performed during the initial hospitalization of three unrelated patients, and results were delivered within 7-21 days. All patients were previously healthy, 1.5-3 years old, of Muslim Arab descent, with consanguineous parents. One patient presenting with acute necrotizing encephalopathy (ANEC). Her sister presented with ANEC one year prior. Exome sequencing was diagnostic in all three patients. All were homozygous for pathogenic and likely-pathogenic variants associated with recessive disorders; MOCS2, NDUFS8 and DBR1. Surprisingly, the initial workup was not suggestive of the final diagnosis. This case series demonstrates that the use of rapid exome sequencing is shifting the paradigm of diagnostics even in critical care situations and should be considered early on in children with acute encephalopathy. A timely diagnosis can direct initial treatment as well as inform decisions regarding long-term care.

[The foetal exome revealed]. / L'ADN fœtal révélé.

New developments in the analysis of maternal cell-free DNA now allow complete analysis of the foetal exome. This makes possible an important extension of the breadth of prenatal diagnostics but raises significant ethical questions.

Identification of Synonymous Pathogenic Variants in Monogenic Disorders by Integrating Exome with Transcriptome Sequencing.

Exome sequencing is becoming a first-tier clinical diagnostic test for Mendelian diseases, drastically reducing the time and cost of diagnostic odyssey and improving the diagnosis rate. Despite its success, exome sequencing faces practical challenges in assessing the pathogenicity of numerous intronic and synonymous variants, leaving a significant proportion of patients undiagnosed. In this study, a whole-blood transcriptome database was constructed that showed the expression profile of 2981 Online Mendelian Inheritance in Man disease genes in blood samples. Meanwhile, a workflow integrating exome sequencing, blood transcriptome sequencing, and in silico prediction tools to identify and validate splicing-altering intronic or synonymous variants was proposed. Following this pipeline, seven synonymous variants in eight patients were discovered. Of these, the functional evidence of c.981G>A (PIGN), c.1161A>G (ALPL), c.858G>A (ATP6AP2), and c.1011G>T (MTHFR) have not been reported previously. RNA sequencing validation confirmed that these variants induced aberrant splicing, expanding the disease-causing variant spectrum of these genes. Overall, this study shows the feasibility of combining multi-omics data to identify splicing-altering variants, especially the power of RNA sequencing. It also reveals that synonymous variants, which often are overlooked in standard diagnostic approaches, comprise an important portion of unresolved genetic diseases.

Protocol for detecting rare and common genetic associations in whole-exome sequencing studies using MAGICpipeline.

Whole-exome sequencing (WES) is a major approach to uncovering gene-disease associations and pinpointing effector genes. Here, we present a protocol for estimating genetic associations of rare and common variants in large-scale case-control WES studies using MAGICpipeline, an open-access analysis pipeline. We describe steps for assessing gene-based rare-variant association analyses by incorporating multiple variant pathogenic annotations and statistical techniques. We then detail procedures for identifying disease-related modules and hub genes using weighted correlation network analysis, a systems biology approach. For complete details on the use and execution of this protocol, please refer to Su et al. (2023).1.

Exome-Wide Sequencing Study Identified Genetic Variants Associated With Sarcopenic Obesity.

Sarcopenic obesity (SO) is an age-related disease characterized by the coexistence of excessive adiposity and low muscle mass or function. Although obesity and sarcopenia are heritable conditions, the genetic determinants of SO have not been fully understood. We conducted a large-scale exome-wide association analysis of SO in a sequenced sample of 2 887 cases and 113 284 controls and an imputed sample of 4 003 cases and 161 990 controls in the UK Biobank cohort. Single-variant association analysis identified one locus 1q41 (lead SNP rs1417066, LYPLAL1-AS1, odds ratio [OR] = 1.15, 95% confidence interval [CI] = [1.11-1.19], p = 1.75 × 10-14) that was significantly associated with SO at the exome-wide significance level (p < 1 × 10-8). Colocalization analysis in the Genotype-Tissue Expression expression quantitative trait locus database showed that LYPLAL1-AS1 was colocalized with SO in multiple musculoskeletal-related tissues. Gene-based burden test of rare loss-of-function variants identified 5 genes at the gene-wise significance level (p < 4.3 × 10-6): PDE3B (OR = 2.48, p = 1.10 × 10-6), MYOZ3 (OR = 25.49, p = 1.41 × 10-7), SLC15A3 (OR = 4.75, p = 6.82 × 10-7), RNF130 (OR = 25.83, p = 4.07 × 10-6), and TNK2 (OR = 4.25, p = 8.75 × 10-8). Overall, our study uncovered the genetic effects of both common and rare variants on SO susceptibility, expanded existing knowledge of the genetic architecture of SO, and improved understanding of the genetic mechanisms underlying SO.

STIGMA: Single-cell tissue-specific gene prioritization using machine learning.

Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.

The cost of proband and trio exome and genome analysis in rare disease: A micro-costing study.

PURPOSE: Rare disease genomic testing is a complex process involving various resources. Accurate resource estimation is required for informed prioritization and reimbursement decisions. This study aims to analyze the costs and cost drivers of clinical genomic testing. METHODS: Based on genomic sequencing workflows we microcosted limited virtual panel analysis on exome sequencing backbone, proband and trio exome, and genome testing for proband and trio analysis in 2023 Australian Dollars ($). Deterministic and probabilistic sensitivity analyses were undertaken. RESULTS: Panel testing costs AUD $2373 ($733-$6166), and exome sequencing costs $2823 ($802-$7206) and $5670 ($2006-$11,539) for proband and trio analysis, respectively. Genome sequencing costs $4840 ($2153-$9890) and $11,589 ($5842-$16,562) for proband and trio analysis. The most expensive cost component of genomic testing was sequencing (36.9%-69.4% of total cost), with labor accounting for 27.1%-63.2% of total cost. CONCLUSION: We provide a comprehensive analysis of rare disease genomic testing costs, for a range of clinical testing types and contexts. This information will accurately inform economic evaluations of rare disease genomic testing and decision making on policy settings that assist with implementation, such as genomic testing reimbursement.

Narrowing the diagnostic gap: Genomes, episignatures, long-read sequencing, and health economic analyses in an exome-negative intellectual disability cohort.

PURPOSE: Genome sequencing (GS)-specific diagnostic rates in prospective tightly ascertained exome sequencing (ES)-negative intellectual disability (ID) cohorts have not been reported extensively. METHODS: ES, GS, epigenetic signatures, and long-read sequencing diagnoses were assessed in 74 trios with at least moderate ID. RESULTS: The ES diagnostic yield was 42 of 74 (57%). GS diagnoses were made in 9 of 32 (28%) ES-unresolved families. Repeated ES with a contemporary pipeline on the GS-diagnosed families identified 8 of 9 single-nucleotide variations/copy-number variations undetected in older ES, confirming a GS-unique diagnostic rate of 1 in 32 (3%). Episignatures contributed diagnostic information in 9% with GS corroboration in 1 of 32 (3%) and diagnostic clues in 2 of 32 (6%). A genetic etiology for ID was detected in 51 of 74 (69%) families. Twelve candidate disease genes were identified. Contemporary ES followed by GS cost US$4976 (95% CI: $3704; $6969) per diagnosis and first-line GS at a cost of $7062 (95% CI: $6210; $8475) per diagnosis. CONCLUSION: Performing GS only in ID trios would be cost equivalent to ES if GS were available at $2435, about a 60% reduction from current prices. This study demonstrates that first-line GS achieves higher diagnostic rate than contemporary ES but at a higher cost.