The use of technical replication for detection of low-level somatic mutations in next-generation sequencing

Threshold of somatic mosaicism leading to brain dysfunction with focal epilepsy

Somatic mosaicism in a fraction of brain cells causes neurodevelopmental disorders, including childhood intractable epilepsy. However, the threshold for somatic mosaicism leading to brain dysfunction is unknown. In this study, we induced various mosaic burdens in focal cortical dysplasia type II (FCD II) mice, featuring mTOR somatic mosaicism and spontaneous behavioural seizures. The mosaic burdens ranged from approximately 1000 to 40 000 neurons expressing the mTOR mutant in the somatosensory or medial prefrontal cortex. Surprisingly, approximately 8000-9000 neurons expressing the MTOR mutant, extrapolated to constitute 0.08%-0.09% of total cells or roughly 0.04% of variant allele frequency in the mouse hemicortex, were sufficient to trigger epileptic seizures. The mutational burden was correlated with seizure frequency and onset, with a higher tendency for electrographic inter-ictal spikes and beta- and gamma-frequency oscillations in FCD II mice exceeding the threshold. Moreover, mutation-negative FCD II patients in deep sequencing of their bulky brain tissues revealed somatic mosaicism of the mTOR pathway genes as low as 0.07% in resected brain tissues through ultra-deep targeted sequencing (up to 20 million reads). Thus, our study suggests that extremely low levels of somatic mosaicism can contribute to brain dysfunction.

Low-level brain somatic mutations in exonic regions are collectively implicated in autism with germline mutations in autism risk genes

Low-level somatic mutations in the human brain are implicated in various neurological disorders. The contribution of low-level brain somatic mutations to autism spectrum disorder (ASD), however, remains poorly understood. Here, we performed high-depth exome sequencing with an average read depth of 559.3x in 181 cortical, cerebellar, and peripheral tissue samples to identify brain somatic single nucleotide variants (SNVs) in 24 ASD subjects and 31 controls. We detected ~2.4 brain somatic SNVs per exome per single brain region, with a variant allele frequency (VAF) as low as 0.3%. The mutational profiles, including the number, signature, and type, were not significantly different between the ASD patients and controls. Intriguingly, when considering genes with low-level brain somatic SNVs and ASD risk genes with damaging germline SNVs together, the merged set of genes carrying either somatic or germline SNVs in ASD patients was significantly involved in ASD-associated pathophysiology, including dendrite spine morphogenesis (p = 0.025), mental retardation (p = 0.012), and intrauterine growth retardation (p = 0.012). Additionally, the merged gene set showed ASD-associated spatiotemporal expression in the early and mid-fetal cortex, striatum, and thalamus (all p < 0.05). Patients with damaging mutations in the merged gene set had a greater ASD risk than did controls (odds ratio = 3.92, p = 0.025, 95% confidence interval = 1.12-14.79). The findings of this study suggest that brain somatic SNVs and germline SNVs may collectively contribute to ASD-associated pathophysiology.

MTFP1 controls mitochondrial fusion to regulate inner membrane quality control and maintain mtDNA levels

Mitochondrial dynamics play a critical role in cell fate decisions and in controlling mtDNA levels and distribution. However, the molecular mechanisms linking mitochondrial membrane remodeling and quality control to mtDNA copy number (CN) regulation remain elusive. Here, we demonstrate that the inner mitochondrial membrane (IMM) protein mitochondrial fission process 1 (MTFP1) negatively regulates IMM fusion. Moreover, manipulation of mitochondrial fusion through the regulation of MTFP1 levels results in mtDNA CN modulation. Mechanistically, we found that MTFP1 inhibits mitochondrial fusion to isolate and exclude damaged IMM subdomains from the rest of the network. Subsequently, peripheral fission ensures their segregation into small MTFP1-enriched mitochondria (SMEM) that are targeted for degradation in an autophagic-dependent manner. Remarkably, MTFP1-dependent IMM quality control is essential for basal nucleoid recycling and therefore to maintain adequate mtDNA levels within the cell.

Extended Enrichment for Ultrasensitive Detection of Low-Frequency Mutations by Long Blocker Displacement Amplification

Detecting low-frequency DNA mutations hotspots cluster is critical for cancer diagnosis but remains challenging. Quantitative PCR (qPCR) is constrained by sensitivity, and allele-specific PCR is restricted by throughput. Here we develop a long blocker displacement amplification (LBDA) coupled with qPCR for ultrasensitive and multiplexed variants detection. By designing long blocker oligos to perfectly match wildtype sequences while mispairing with mutants, long blockers enable 14-44 nt enrichment regions which is 2-fold longer than normal BDA in the experiments. For wild template with a specific nucleotide, LBDA can detect different mutation types down to 0.5 % variant allele frequency (VAF) in one reaction, with median enrichment fold of 1,000 on 21 mutant DNA templates compared to the wild type. We applied LBDA-qPCR to detect KRAS and NRAS mutation hotspots, utilizing a single plex assay capable of covering 81 mutations and tested in synthetic templates and colorectal cancer tissue samples. Moreover, the mutation types were verified through Sanger sequencing, demonstrating concordance with results obtained from next generation sequencing. Overall, LBDA-qPCR provides a simple yet ultrasensitive approach for multiplexed detection of low VAF mutations hotspots, presenting a powerful tool for cancer diagnosis and monitoring.

Recent advances in enzyme-free and enzyme-mediated single-nucleotide variation assay in vitro

Single-nucleotide variants (SNVs) are the most common type variation of sequence alterations at a specific location in the genome, thus involving significant clinical and biological information. The assay of SNVs has engaged great awareness, because many genome-wide association studies demonstrated that SNVs are highly associated with serious human diseases. Moreover, the investigation of SNV expression levels in single cells are capable of visualizing genetic information and revealing the complexity and heterogeneity of single-nucleotide mutation-related diseases. Thus, developing SNV assay approaches in vitro, particularly in single cells, is becoming increasingly in demand. In this review, we summarized recent progress in the enzyme-free and enzyme-mediated strategies enabling SNV assay transition from sensing interface to the test tube and single cells, which will potentially delve deeper into the knowledge of SNV functions and disease associations, as well as discovering new pathways to diagnose and treat diseases based on individual genetic profiles. The leap of SNV assay achievements will motivate observation and measurement genetic variations in single cells, even within living organisms, delve into the knowledge of SNV functions and disease associations, as well as open up entirely new avenues in the diagnosis and treatment of diseases based on individual genetic profiles.

Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Reveals Widespread Degeneration from Focal Mutations

Although mutations in dozens of genes have been implicated in familial forms of amyotrophic lateral sclerosis (fALS) and frontotemporal degeneration (fFTD), most cases of these conditions are sporadic (sALS and sFTD), with no family history, and their etiology remains obscure. We tested the hypothesis that somatic mosaic mutations, present in some but not all cells, might contribute in these cases, by performing ultra-deep, targeted sequencing of 88 genes associated with neurodegenerative diseases in postmortem brain and spinal cord samples from 404 individuals with sALS or sFTD and 144 controls. Known pathogenic germline mutations were found in 20.6% of ALS, and 26.5% of FTD cases. Predicted pathogenic somatic mutations in ALS/FTD genes were observed in 2.7% of sALS and sFTD cases that did not carry known pathogenic or novel germline mutations. Somatic mutations showed low variant allele fraction (typically <2%) and were often restricted to the region of initial discovery, preventing detection through genetic screening in peripheral tissues. Damaging somatic mutations were preferentially enriched in primary motor cortex of sALS and prefrontal cortex of sFTD, mirroring regions most severely affected in each disease. Somatic mutation analysis of bulk RNA-seq data from brain and spinal cord from an additional 143 sALS cases and 23 controls confirmed an overall enrichment of somatic mutations in sALS. Two adult sALS cases were identified bearing pathogenic somatic mutations in DYNC1H1 and LMNA, two genes associated with pediatric motor neuron degeneration. Our study suggests that somatic mutations in fALS/fFTD genes, and in genes associated with more severe diseases in the germline state, contribute to sALS and sFTD, and that mosaic mutations in a small fraction of cells in focal regions of the nervous system can ultimately result in widespread degeneration.

A critical spotlight on the paradigms of FFPE-DNA sequencing

In the late 19th century, formalin fixation with paraffin-embedding (FFPE) of tissues was developed as a fixation and conservation method and is still used to this day in routine clinical and pathological practice. The implementation of state-of-the-art nucleic acid sequencing technologies has sparked much interest for using historical FFPE samples stored in biobanks as they hold promise in extracting new information from these valuable samples. However, formalin fixation chemically modifies DNA, which potentially leads to incorrect sequences or misinterpretations in downstream processing and data analysis. Many publications have concentrated on one type of DNA damage, but few have addressed the complete spectrum of FFPE-DNA damage. Here, we review mitigation strategies in (I) pre-analytical sample quality control, (II) DNA repair treatments, (III) analytical sample preparation and (IV) bioinformatic analysis of FFPE-DNA. We then provide recommendations that are tested and illustrated with DNA from 13-year-old liver specimens, one FFPE preserved and one fresh frozen, applying target-enriched sequencing. Thus, we show how DNA damage can be compensated, even when using low quantities (50 ng) of fragmented FFPE-DNA (DNA integrity number 2.0) that cannot be amplified well (Q129 bp/Q41 bp = 5%). Finally, we provide a checklist called 'ERROR-FFPE-DNA' that summarises recommendations for the minimal information in publications required for assessing fitness-for-purpose and inter-study comparison when using FFPE samples.

High-Depth PRNP Sequencing in Brains With Sporadic Creutzfeldt-Jakob Disease

Background and Objectives

Sporadic Creutzfeldt-Jakob disease (sCJD) has established genetic risk factors, but, in contrast to genetic and acquired CJD, the initial trigger for misfolded prion aggregation and spread is not known. In this study, we tested the hypotheses that pathologic somatic variants in the prion gene PRNP are increased in sCJD, potentially leading to the seeding of misfolded prion protein.

Methods

High-depth amplicon-based short read sequencing of the PRNP coding region was performed on postmortem brain tissue from patients with a clinical and neuropathologic diagnosis of sCJD (n = 142), Alzheimer disease (AD) (n = 51) and controls with no clinical or neuropathologic diagnosis of a neurodegenerative disease (n = 71). Each DNA sample was sequenced twice, including independent PCR amplification, library preparation, and sequencing. We used RePlow to call somatic variants with high sensitivity and specificity and optimal sequence kernel association test to compare variant burden between groups.

Results

Two sCJD cases had somatic (variant allele frequency 0.5-1%) PRNP variants not previously identified, but with high in silico predicated pathogenicity. However, the pathogenicity of these variants is uncertain, as both located in the octapeptide repeat region where no point variations have previously been associated with sCJD. There was no overall difference in burden somatic PRNP in sCJD compared with controls and a lower burden compared with Alzheimer disease.

Discussion

Somatic variants in PRNP are unlikely to play a major role in sCJD but may contribute to the disease mechanism in a minority of cases.

Inferring parameters of cancer evolution in chronic lymphocytic leukemia

As a cancer develops, its cells accrue new mutations, resulting in a heterogeneous, complex genomic profile. We make use of this heterogeneity to derive simple, analytic estimates of parameters driving carcinogenesis and reconstruct the timeline of selective events following initiation of an individual cancer, where two longitudinal samples are available for sequencing. Using stochastic computer simulations of cancer growth, we show that we can accurately estimate mutation rate, time before and after a driver event occurred, and growth rates of both initiated cancer cells and subsequently appearing subclones. We demonstrate that in order to obtain accurate estimates of mutation rate and timing of events, observed mutation counts should be corrected to account for clonal mutations that occurred after the founding of the tumor, as well as sequencing coverage. Chronic lymphocytic leukemia (CLL), which often does not require treatment for years after diagnosis, presents an optimal system to study the untreated, natural evolution of cancer cell populations. When we apply our methodology to reconstruct the individual evolutionary histories of CLL patients, we find that the parental leukemic clone typically appears within the first fifteen years of life.

Analysis of low-level somatic mosaicism reveals stage and tissue-specific mutational features in human development

Most somatic mutations that arise during normal development are present at low levels in single or multiple tissues depending on the developmental stage and affected organs. However, the effect of human developmental stages or mutations of different organs on the features of somatic mutations is still unclear. Here, we performed a systemic and comprehensive analysis of low-level somatic mutations using deep whole-exome sequencing (average read depth ~500×) of 498 multiple organ tissues with matched controls from 190 individuals. Our results showed that early clone-forming mutations shared between multiple organs were lower in number but showed higher allele frequencies than late clone-forming mutations [0.54 vs. 5.83 variants per individual; 6.17% vs. 1.5% variant allele frequency (VAF)] along with less nonsynonymous mutations and lower functional impacts. Additionally, early and late clone-forming mutations had unique mutational signatures that were distinct from mutations that originated from tumors. Compared with early clone-forming mutations that showed a clock-like signature across all organs or tissues studied, late clone-forming mutations showed organ, tissue, and cell-type specificity in the mutation counts, VAFs, and mutational signatures. In particular, analysis of brain somatic mutations showed a bimodal occurrence and temporal-lobe-specific signature. These findings provide new insights into the features of somatic mosaicism that are dependent on developmental stage and brain regions.

Most somatic mutations that arise during normal development are present at low levels in single or multiple tissues, and often show a degree of clonality depending on the time and origin of the mutation. Recent studies have identified the characteristics of postzygotic variants of somatic mutations at the single-cell or mono-clonal levels. However, the results may not be fully representative of the mutational processes involved. Here, we describe a comprehensive analysis of low-level somatic mutations identified after deep whole-exome sequencing in peripheral and brain tissues. We found that clone-forming mutations are uniquely defined by early and late-stage aspects in the mutational profiles. Thus, we identified reliable spatiotemporal characteristics of mosaic variants. Additionally, we found low-level clone-forming mosaic variants across multiple stages and tissues, and identified their intrinsic features.

Clinical implementation of genetic testing in adults for hereditary hematologic malignancy syndromes

PURPOSE

As research on hereditary hematologic malignancy syndromes (HHMS) are accumulating, cancer genetics clinics are identifying more adult hematology patients with an inherited component to their disease. However, investigations for HHMS are complex, and there is no formal consensus on genetic testing criteria.

METHODS

We developed genetic testing criteria for adult hematology patients through a comprehensive literature review and our experience at the Princess Margaret Cancer Centre. We validated our criteria by applying them retrospectively to patients referred to our clinic for HHMS assessment.

RESULTS

Our genetic testing criteria are comprehensive of myeloid malignancies, lymphoid malignancies, and bone marrow failure, including age at diagnosis, family history, and genetic test results in blood and bone marrow. Of the 104 patients who met the criteria, 26% had at least 1 actionable variant in any gene associated with an increased risk of cancer and 13% had an actionable variant resulting in an HHMS diagnosis. A total of 15 patients had incidental findings, including 11 patients with a pathogenic variant associated with carrier status for an autosomal recessive disorder and 4 patients with a mosaic result.

CONCLUSION

Our high gene positivity rate shows the utility of a broad approach to germline testing in an adult hematology population.

Identification of Somatic Mutations From Bulk and Single-Cell Sequencing Data

Somatic mutations are DNA variants that occur after the fertilization of zygotes and accumulate during the developmental and aging processes in the human lifespan. Somatic mutations have long been known to cause cancer, and more recently have been implicated in a variety of non-cancer diseases. The patterns of somatic mutations, or mutational signatures, also shed light on the underlying mechanisms of the mutational process. Advances in next-generation sequencing over the decades have enabled genome-wide profiling of DNA variants in a high-throughput manner; however, unlike germline mutations, somatic mutations are carried only by a subset of the cell population. Thus, sensitive bioinformatic methods are required to distinguish mutant alleles from sequencing and base calling errors in bulk tissue samples. An alternative way to study somatic mutations, especially those present in an extremely small number of cells or even in a single cell, is to sequence single-cell genomes after whole-genome amplification (WGA); however, it is critical and technically challenging to exclude numerous technical artifacts arising during error-prone and uneven genome amplification in current WGA methods. To address these challenges, multiple bioinformatic tools have been developed. In this review, we summarize the latest progress in methods for identification of somatic mutations and the challenges that remain to be addressed in the future.

Lineage tracing in human tissues

The dynamical process of cell division that underpins homeostasis in the human body cannot be directly observed in vivo, but instead is measurable from the pattern of somatic genetic or epigenetic mutations that accrue in tissues over an individual's lifetime. Because somatic mutations are heritable, they serve as natural lineage tracing markers that delineate clonal expansions. Mathematical analysis of the distribution of somatic clone sizes gives a quantitative readout of the rates of cell birth, death, and replacement. In this review we explore the broad range of somatic mutation types that have been used for lineage tracing in human tissues, introduce the mathematical concepts used to infer dynamical information from these clone size data, and discuss the insights of this lineage tracing approach for our understanding of homeostasis and cancer development. We use the human colon as a particularly instructive exemplar tissue. There is a rich history of human somatic cell dynamics surreptitiously written into the cell genomes that is being uncovered by advances in sequencing and careful mathematical analysis lineage of tracing data. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Heteroplasmic mitochondrial DNA mutations in frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD) is a common cause of young onset dementia and is characterised by focal neuropathology. The reasons for the regional neuronal vulnerability are not known. Mitochondrial mechanisms have been implicated in the pathogenesis of FTLD, raising the possibility that frontotemporal regional mutations of mitochondrial DNA (mtDNA) are contributory causes. Here we applied dual sequencing of the entire mtDNA at high depth to identify high-fidelity single nucleotide variants (mtSNVs) and mtDNA rearrangements in post mortem brain tissue of people affected by FTLD and age-matched controls. Both mtSNVs and mtDNA rearrangements were elevated in the temporal lobe, with the greatest burden seen in FTLD. mtSNVs found in multiple brain regions also reached a higher heteroplasmy levels in the temporal lobe. The temporal lobe of people with FTLD had a higher burden of ribosomal gene variants predicted to affect intra-mitochondrial protein synthesis, and a higher proportion of missense variants in genes coding for respiratory chain subunits. In conclusion, heteroplasmic mtDNA variants predicted to affect oxidative phosphorylation are enriched in FTLD temporal lobe, and thus may contribute to the regional vulnerability in pathogenesis.

Somatic Mutations Detected in Parkinson Disease Could Affect Genes With a Role in Synaptic and Neuronal Processes

The role of somatic mutations in complex diseases, including neurodevelopmental and neurodegenerative disorders, is becoming increasingly clear. However, to date, no study has shown their relation to Parkinson disease’s phenotype. To explore the relevance of embryonic somatic mutations in sporadic Parkinson disease, we performed whole-exome sequencing in blood and four brain regions of ten patients. We identified 59 candidate somatic single nucleotide variants (sSNVs) through sensitive calling and a careful filtering strategy (COSMOS). We validated 27 of them with amplicon-based ultra-deep sequencing, with a 70% validation rate for the highest-confidence variants. The identified sSNVs are in genes with synaptic functions that are co-expressed with genes previously associated with Parkinson disease. Most of the sSNVs were only called in blood but were also found in the brain tissues with ultra-deep amplicon sequencing, demonstrating the strength of multi-tissue sampling designs.

Direct comparison of the next-generation sequencing and iTERT PCR methods for the diagnosis of TERT hotspot mutations in advanced solid cancers

Background

Mutations in the telomerase reverse transcriptase (TERT) promoter region have been proposed as novel mechanisms for the transcriptional activation of telomerase. Two recurrent mutations in the TERT promoter, C228T and C250T, are prognostic biomarkers. Herein, we directly compared the commercially available iTERT PCR kit with NGS-based deep sequencing to validate the NGS results and determine the analytical sensitivity of the PCR kit.

Methods

Of the 2032 advanced solid tumors diagnosed using the TruSight Oncology 500 NGS test, mutations in the TERT promoter region were detected in 103 cases, with 79 cases of C228T, 22 cases of C250T, and 2 cases of C228A hotspot mutations. TERT promoter mutations were detected from 31 urinary bladder, 19 pancreato-biliary, 22 hepatic, 12 malignant melanoma, and 12 other tumor samples.

Results

In all 103 TERT-mutated cases detected using NGS, the same DNA samples were also tested with the iTERT PCR/Sanger sequencing. PCR successfully verified the presence of the same mutations in all cases with 100% agreement. The average read depth of the TERT promoter region was 320.4, which was significantly lower than that of the other genes (mean, 743.5). Interestingly, NGS read depth was significantly higher at C250 compared to C228 (p < 0.001).

Conclusions

The NGS test results were validated by a PCR test and iTERT PCR/Sanger sequencing is sensitive for the identification of the TERT promoter mutations.

Establishment of reference standards for multifaceted mosaic variant analysis

Detection of somatic mosaicism in non-proliferative cells is a new challenge in genome research, however, the accuracy of current detection strategies remains uncertain due to the lack of a ground truth. Herein, we sought to present a set of ultra-deep sequenced WES data based on reference standards generated by cell line mixtures, providing a total of 386,613 mosaic single-nucleotide variants (SNVs) and insertion-deletion mutations (INDELs) with variant allele frequencies (VAFs) ranging from 0.5% to 56%, as well as 35,113,417 non-variant and 19,936 germline variant sites as a negative control. The whole reference standard set mimics the cumulative aspect of mosaic variant acquisition such as in the early developmental stage owing to the progressive mixing of cell lines with established genotypes, ultimately unveiling 741 possible inter-sample relationships with respect to variant sharing and asymmetry in VAFs. We expect that our reference data will be essential for optimizing the current use of mosaic variant detection strategies and for developing algorithms to enable future improvements.

Measurement(s)	genotype
Technology Type(s)	DNA sequencing
Factor Type(s)	genotyping
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	cell line

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16970041

Defining and quantifying the core microbiome: Challenges and prospects

The term "core microbiome" has become widely used in microbial ecology over the last decade. Broadly, the core microbiome refers to any set of microbial taxa, or the genomic and functional attributes associated with those taxa, that are characteristic of a host or environment of interest. Most commonly, core microbiomes are measured as the microbial taxa shared among two or more samples from a particular host or environment. Despite the popularity of this term and its growing use, there is little consensus about how a core microbiome should be quantified in practice. Here, we present a brief history of the core microbiome concept and use a representative sample of the literature to review the different metrics commonly used for quantifying the core. Empirical analyses have used a wide range of metrics for quantifying the core microbiome, including arbitrary occurrence and abundance cutoff values, with the focal taxonomic level of the core ranging from phyla to amplicon sequence variants. However, many of these metrics are susceptible to sampling and other biases. Developing a standardized set of metrics for quantifying the core that accounts for such biases is necessary for testing specific hypotheses about the functional and ecological roles of core microbiomes.

FDA-led consortium studies advance quality control of targeted next generation sequencing assays for precision oncology

Cancer is the second leading cause of mortality worldwide despite tremendous advances in treatment. The promise of precision oncology depends on accurate characterization of tumor mutations and subsequent therapy selection. The lack of tumor reference samples along with the associated next generation sequencing (NGS) technical assessments has hindered the development of NGS assays and the realization of benefits for precision oncology. The summarized results and recommendations of several seminal SEQC2 studies along with a vision of the changing landscape of precision oncology and anticipated next steps by the SEQC2 consortium are reported. Importantly, these studies utilized a new robust reference sample material which was developed and constructed to support multiple DNA and RNA-based NGS assay studies. These studies focused on a wide variety of precision oncology assay scenarios and provided guidelines for standardized analyses and best practice recommendations. The evolving landscape of precision oncology requires insights into critical factors supporting the sensitivity and reproducibility of clinical NGS assays for continued improvement in patient outcomes. Persistent development of robust reference materials, quantitative performance metrics, and actionable data analysis recommendations are needed. This series of SEQC2 studies serve to advance NGS-based assays for precision oncology and support regulatory science endeavors.

STIC: Predicting Single Nucleotide Variants and Tumor Purity in Cancer Genome

Single nucleotide variant (SNV) plays an important role in cellular proliferation and tumorigenesis in various types of human cancer. Next-generation sequencing (NGS) has provided high-throughput data at an unprecedented resolution to predict SNVs. Currently, there exist many computational methods for either germline or somatic SNV discovery from NGS data, but very few of them are versatile enough to adapt to any situations. In the absence of matched normal samples, the prediction of somatic SNVs from single-tumor samples becomes considerably challenging, especially when the tumor purity is unknown. Here, we propose a new approach, STIC, to predict somatic SNVs and estimate tumor purity from NGS data without matched normal samples. The main features of STIC include: (1) extracting a set of SNV-relevant features on each site and training the BP neural network algorithm on the features to predict SNVs; (2) creating an iterative process to distinguish somatic SNVs from germline ones by disturbing allele frequency; and (3) establishing a reasonable relationship between tumor purity and allele frequencies of somatic SNVs to accurately estimate the purity. We quantitatively evaluate the performance of STIC on both simulation and real sequencing datasets, the results of which indicate that STIC outperforms competing methods.

Advances in the genetic classification of amyotrophic lateral sclerosis

PURPOSE OF REVIEW

Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease wherein disease risk and severity are, for the majority of patients, the product of interaction between multiple genetic and environmental factors. We are in a period of unprecedented discovery with new large-scale genome-wide association study (GWAS) and accelerating discovery of risk genes. However, much of the observed heritability of ALS is undiscovered and we are not yet approaching elucidation of the total genetic architecture, which will be necessary for comprehensive disease subclassification.

RECENT FINDINGS

We summarize recent developments and discuss the future. New machine learning models will help to address nonlinear genetic interactions. Statistical power for genetic discovery may be boosted by reducing the search-space using cell-specific epigenetic profiles and expanding our scope to include genetically correlated phenotypes. Structural variation, somatic heterogeneity and consideration of environmental modifiers represent significant challenges which will require integration of multiple technologies and a multidisciplinary approach, including clinicians, geneticists and pathologists.

SUMMARY

The move away from fully penetrant Mendelian risk genes necessitates new experimental designs and new standards for validation. The challenges are significant, but the potential reward for successful disease subclassification is large-scale and effective personalized medicine.

Characterization of DNA lesions associated with cell-free DNA by targeted deep sequencing

BACKGROUND

Recently, a next-generation sequencing (NGS)-based method has been used for the successful detection of circulating tumor DNA (ctDNA) in various cancer types. Thus, the use of NGS on liquid biopsies will improve cancer diagnosis and prognosis. However, the low-allelic fraction of ctDNA poses a challenge for the sensitive and specific detection of tumor variants in cell-free DNA (cfDNA). To distinguish true variants from false positives, the characteristics of errors that occur during sample preparation and sequencing need to be elucidated.

METHODS

We generated capture-based targeted deep sequencing data from plasma cfDNA and peripheral blood leucocyte (PBL) gDNA to profile background errors. To reveal cfDNA-associated DNA lesions, background error profiles from two sample types were compared in each nucleotide substitution class.

RESULTS

In this study, we determined the prevalence of single nucleotide substitutions in cfDNA sequencing data to identify DNA damage preferentially associated with cfDNA. On comparing sequencing errors between cfDNA and cellular genomic DNA (gDNA), we observed that the total substitution error rates in cfDNA were significantly higher than those in gDNA. When the substitution errors were divided into 12 substitution error classes, C:G>T:A substitution errors constituted the largest difference between cfDNA and gDNA samples. When the substitution error rates were estimated based on the location of DNA-fragment substitutions, the differences in error rates of most substitution classes between cfDNA and gDNA samples were observed only at the ends of the DNA fragments. In contrast, C:G>T:A substitution errors in the cfDNA samples were not particularly associated with DNA-fragment ends. All observations were verified in an independent dataset.

CONCLUSIONS

Our data suggested that cytosine deamination increased in cfDNA compared to that in cellular gDNA. Such an observation might be due to the attenuation of DNA damage repair before the release of cfDNA and/or the accumulation of cytosine deamination after it. These findings can contribute to a better understanding of cfDNA-associated DNA damage, which will enable the accurate analysis of somatic variants present in cfDNA at an extremely low frequency.

Genomic Mosaicism Formed by Somatic Variation in the Aging and Diseased Brain

Over the past 20 years, analyses of single brain cell genomes have revealed that the brain is composed of cells with myriad distinct genomes: the brain is a genomic mosaic, generated by a host of DNA sequence-altering processes that occur somatically and do not affect the germline. As such, these sequence changes are not heritable. Some processes appear to occur during neurogenesis, when cells are mitotic, whereas others may also function in post-mitotic cells. Here, we review multiple forms of DNA sequence alterations that have now been documented: aneuploidies and aneusomies, smaller copy number variations (CNVs), somatic repeat expansions, retrotransposons, genomic cDNAs (gencDNAs) associated with somatic gene recombination (SGR), and single nucleotide variations (SNVs). A catch-all term of DNA content variation (DCV) has also been used to describe the overall phenomenon, which can include multiple forms within a single cell's genome. A requisite step in the analyses of genomic mosaicism is ongoing technology development, which is also discussed. Genomic mosaicism alters one of the most stable biological molecules, DNA, which may have many repercussions, ranging from normal functions including effects of aging, to creating dysfunction that occurs in neurodegenerative and other brain diseases, most of which show sporadic presentation, unlinked to causal, heritable genes.

Low-Level Brain Somatic Mutations Are Implicated in Schizophrenia

BACKGROUND

Somatic mutations arising from the brain have recently emerged as significant contributors to neurodevelopmental disorders, including childhood intractable epilepsy and cortical malformations. However, whether brain somatic mutations are implicated in schizophrenia (SCZ) is not well established.

METHODS

We performed deep whole exome sequencing (average read depth > 550×) of matched dorsolateral prefrontal cortex and peripheral tissues from 27 patients with SCZ and 31 age-matched control individuals, followed by comprehensive and strict analysis of somatic mutations, including mutagenesis signature, substitution patterns, and involved pathways. In particular, we explored the impact of deleterious mutations in GRIN2B through primary neural culture.

RESULTS

We identified an average of 4.9 and 5.6 somatic mutations per exome per brain in patients with SCZ and control individuals, respectively. These mutations presented with average variant allele frequencies of 8.0% in patients with SCZ and 7.6% in control individuals. Although mutational profiles, such as the number and type of mutations, showed no significant difference between patients with SCZ and control individuals, somatic mutations in SCZ brains were significantly enriched for SCZ-related pathways, including dopamine receptor, glutamate receptor, and long-term potentiation pathways. Furthermore, we showed that brain somatic mutations in GRIN2B (encoding glutamate ionotropic NMDA receptor subunit 2B), which were found in two patients with SCZ, disrupted the location of GRIN2B across the surface of dendrites among primary cultured neurons.

CONCLUSIONS

Taken together, this study shows that brain somatic mutations are associated with the pathogenesis of SCZ.

Toward a better definition of focal cortical dysplasia: An iterative histopathological and genetic agreement trial

OBJECTIVE

Focal cortical dysplasia (FCD) is a major cause of difficult-to-treat epilepsy in children and young adults, and the diagnosis is currently based on microscopic review of surgical brain tissue using the International League Against Epilepsy classification scheme of 2011. We developed an iterative histopathological agreement trial with genetic testing to identify areas of diagnostic challenges in this widely used classification scheme.

METHODS

Four web-based digital pathology trials were completed by 20 neuropathologists from 15 countries using a consecutive series of 196 surgical tissue blocks obtained from 22 epilepsy patients at a single center. Five independent genetic laboratories performed screening or validation sequencing of FCD-relevant genes in paired brain and blood samples from the same 22 epilepsy patients.

RESULTS

Histopathology agreement based solely on hematoxylin and eosin stainings was low in Round 1, and gradually increased by adding a panel of immunostainings in Round 2 and the Delphi consensus method in Round 3. Interobserver agreement was good in Round 4 (kappa = .65), when the results of genetic tests were disclosed, namely, MTOR, AKT3, and SLC35A2 brain somatic mutations in five cases and germline mutations in DEPDC5 and NPRL3 in two cases.

SIGNIFICANCE

The diagnoses of FCD 1 and 3 subtypes remained most challenging and were often difficult to differentiate from a normal homotypic or heterotypic cortical architecture. Immunohistochemistry was helpful, however, to confirm the diagnosis of FCD or no lesion. We observed a genotype-phenotype association for brain somatic mutations in SLC35A2 in two cases with mild malformation of cortical development with oligodendroglial hyperplasia in epilepsy. Our results suggest that the current FCD classification should recognize a panel of immunohistochemical stainings for a better histopathological workup and definition of FCD subtypes. We also propose adding the level of genetic findings to obtain a comprehensive, reliable, and integrative genotype-phenotype diagnosis in the near future.

A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency

BACKGROUND

Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance.

RESULTS

In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5-100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels.

CONCLUSION

These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

DEEPGENTM-A Novel Variant Calling Assay for Low Frequency Variants

Detection of genetic variants in clinically relevant genomic hot-spot regions has become a promising application of next-generation sequencing technology in precision oncology. Effective personalized diagnostics requires the detection of variants with often very low frequencies. This can be achieved by targeted, short-read sequencing that provides high sequencing depths. However, rare genetic variants can contain crucial information for early cancer detection and subsequent treatment success, an inevitable level of background noise usually limits the accuracy of low frequency variant calling assays. To address this challenge, we developed DEEPGEN^TM, a variant calling assay intended for the detection of low frequency variants within liquid biopsy samples. We processed reference samples with validated mutations of known frequencies (0%-0.5%) to determine DEEPGEN^TM's performance and minimal input requirements. Our findings confirm DEEPGEN^TM's effectiveness in discriminating between signal and noise down to 0.09% variant allele frequency and an LOD(90) at 0.18%. A superior sensitivity was also confirmed by orthogonal comparison to a commercially available liquid biopsy-based assay for cancer detection.

Detection of BRAF V600E Mutation in Ganglioglioma and Pilocytic Astrocytoma by Immunohistochemistry and Real-Time PCR-Based Idylla Test

The BRAF V600E mutation is an important oncological target in certain central nervous system (CNS) tumors, for which a possible application of BRAF-targeted therapy grows continuously. In the present study, we aim to determine the prevalence of BRAF V600E mutations in a series of ganglioglioma (GG) and pilocytic astrocytoma (PA) cases. Simultaneously, we decided to verify whether the combination of fully automated tests—BRAF-VE1 immunohistochemistry (IHC) and Idylla BRAF mutation assay—may be useful to accurately predict it in the case of specified CNS tumors. The study included 49 formalin-fixed, paraffin-embedded tissues, of which 15 were GG and 34 PA. Immunohistochemistry with anti-BRAF V600E (VE1) antibody was performed on tissue sections using the VentanaBenchMark ULTRA platform. All positive or equivocal cases on IHC and selected negative ones were further assessed using the Idylla BRAF mutation assay coupled with the Idylla platform. The BRAF-VE1 IHC was positive in 6 (6/49; 12.3%) and negative in 39 samples (39/49; 79.6%). The interpretation of immunostaining results was complicated in 4 cases, of which 1 tested positive for the Idylla BRAF mutation assay. Therefore, the overall positivity rate was 14.3%. This included 2 cases of GG and 5 cases of PA. Our study found that BRAF V600E mutations are moderately frequent in PA and GG and that for these tumor entities, IHC VE1 is suitable for screening purposes, but all negative, equivocal, and weak positive cases should be further tested with molecular biology techniques, of which the Idylla system seems to be a promising tool.

Detailed analysis of phenotypes and genotypes in megalencephaly-capillary malformation-polymicrogyria syndrome caused by somatic mosaicism of PIK3CA mutations

Background

Megalencephaly-capillary malformation-polymicrogyria syndrome (MCAP) belongs to a group of conditions called the PIK3CA-related overgrowth spectrum (PROS). The varying phenotypes and low frequencies of each somatic mosaic variant make confirmative diagnosis difficult. We present 12 patients who were diagnosed clinically and genetically with MCAP. Genomic DNA was extracted mainly from the skin of affected lesions, also from peripheral blood leukocytes and buccal epithelial cells, and target panel sequencing using high-depth next-generation sequencing technology was performed.

Results

Macrocephaly was present in 11/12 patients (92%). All patients had normal body asymmetry. Cutaneous vascular malformation was found in 10/12 patients (83%). Megalencephaly or hemimegalencephaly was noted in all 11 patients who underwent brain magnetic resonance imaging. Arnold–Chiari type I malformation was also seen in 10 patients. Every patient was identified as having pathogenic or likely pathogenic variants of the PIK3CA gene. The variant allele frequency (VAF) ranged from 6.3 to 35.3%, however, there was no direct correlation between VAF and the severity of associated anomalies. c.2740G > A (p.Gly914Arg) was most commonly found, in four patients (33%). No malignancies developed during follow-up periods.

Conclusions

This is the first and largest cohort of molecularly diagnosed patients with MCAP in Korea. Targeted therapy with a PI3K-specific inhibitor, alpelisib, has shown successful outcomes in patients with PROS in a pilot clinical study, so early diagnosis for genetic counseling and timely introduction of emerging treatments might be achieved in the future through optimal genetic testing.

Next-Generation Sequencing in High-Sensitive Detection of Mutations in Tumors: Challenges, Advances, and Applications

Next-generation sequencing (NGS) technologies have come of age as preferred technologies for screening of genomic variants of pathologic and therapeutic potential. Because of their capability for high-throughput and massively parallel sequencing, they can screen for a variety of genomic changes in multiple samples simultaneously. This has made them platforms of choice for clinical testing of solid tumors and hematological malignancies. Consequently, they are increasingly replacing conventional technologies, such as Sanger sequencing and pyrosequencing, expression arrays, real-time PCR, and fluorescence in situ hybridization methods, for routine molecular testing of tumors. However, one limitation of routinely used NGS technologies is the inability to detect low-level genomic variants with high accuracy. This can be attributed to the frequent occurrence of low-level sequencing errors and artifacts in NGS workflow that need specialized approaches to be identified and eliminated. This review focuses on the origins and nature of these artifacts and recent improvements in the NGS technologies to overcome them to facilitate accurate high-sensitive detection of low-level mutations. Potential applications of high-sensitive NGS in oncology and comparisons with non-NGS technologies of similar capabilities are also summarized.

Development of tumour peptide vaccines: From universalization to personalization

In recent years, relying on the human immune system to kill tumour cells has become an effective means of cancer treatment. The development of peptide vaccines, which not only break the immune tolerance of a tumour but also attack malignant cells via specific antitumour immunity, has received increased attention in tumour immunization therapy due to their safety and easy preparation. The use of large-scale sequencing technology enables the continuous discovery of new tumour antigens. With improved accuracy of epitope prediction by computer simulation and the usage of a tetramer assay, cytotoxic lymphocyte epitopes can be screened and identified more easily. Transmembrane peptide and nanoparticle technologies promote more effective intake and delivery of antigens. Consequently, considerable evolution from universal to personalized peptide vaccines has taken place, and such vaccines induce an efficient and specific immune response targeting tumour neoantigens. Recently, genomic analysis and bioinformatics approaches have greatly facilitated the breakthrough of personalized peptide vaccines targeting neoantigens, resulting in a renewed interest in this field. Further, the combination of tumour peptide vaccines with checkpoint blockades may improve patient outcomes. In this review, we discuss the development of tumour peptide vaccines and the new technological progress, from universalization to personalization, to highlight the substantial promise of tumour peptide vaccines in clinical cancer immunotherapy.

Precise detection of low-level somatic mutation in resected epilepsy brain tissue

Low-level somatic mutations have been shown to be the major genetic etiology of intractable epilepsy. The extents thereof, however, have yet to be systematically and accurately explored in a large cohort of resected epilepsy brain tissues. Moreover, clinically useful and precise analysis tools for detecting low-level somatic mutations from unmatched formalin-fixed paraffin-embedded (FFPE) brain samples, the most clinically relevant samples, are still lacking. In total, 446 tissues samples from 232 intractable epilepsy patients with various brain pathologies were analyzed using deep sequencing (average read depth, 1112x) of known epilepsy-related genes (up to 28 genes) followed by confirmatory site-specific amplicon sequencing. Pathogenic mutations were discovered in 31.9% (74 of 232) of the resected epilepsy brain tissues and were recurrently found in only eight major focal epilepsy genes, including AKT3, DEPDC5, MTOR, PIK3CA, TSC1, TSC2, SCL35A2, and BRAF. Somatic mutations, two-hit mutations, and germline mutations accounted for 22.0% (51), 0.9% (2), and 9.1% (21) of the patients with intractable epilepsy, respectively. The majority of pathogenic somatic mutations (62.3%, 33 of 53) had a low variant allelic frequency of less than 5%. The use of deep sequencing replicates in the eight major focal epilepsy genes robustly increased PPVs to 50-100% and sensitivities to 71-100%. In an independent FCDII cohort of only unmatched FFPE brain tissues, deep sequencing replicates in the eight major focal epilepsy genes identified pathogenic somatic mutations in 33.3% (5 of 15) of FCDII individuals (similar to the genetic detecting rate in the entire FCDII cohort) without any false-positive calls. Deep sequencing replicates of major focal epilepsy genes in unmatched FFPE brain tissues can be used to accurately and efficiently detect low-level somatic mutations, thereby improving overall patient care by enriching genetic counseling and informing treatment decisions.

Dissecting the genetic basis of focal cortical dysplasia: a large cohort study

Genetic malformations of cortical development (MCDs), such as mild MCDs (mMCD), focal cortical dysplasia (FCD), and hemimegalencephaly (HME), are major causes of severe pediatric refractory epilepsies subjected to neurosurgery. FCD2 are characterized by neuropathological hallmarks that include enlarged dysmorphic neurons (DNs) and balloon cells (BCs). Here, we provide a comprehensive assessment of the contribution of germline and somatic variants in a large cohort of surgical MCD cases. We enrolled in a monocentric study 80 children with drug-resistant epilepsy and a postsurgical neuropathological diagnosis of mMCD, FCD1, FCD2, or HME. We performed targeted gene sequencing ( ≥ 2000X read depth) on matched blood-brain samples to search for low-allele frequency variants in mTOR pathway and FCD genes. We were able to elucidate 29% of mMCD/FCD1 patients and 63% of FCD2/HME patients. Somatic loss-of-function variants in the N-glycosylation pathway-associated SLC35A2 gene were found in mMCD/FCD1 cases. Somatic gain-of-function variants in MTOR and its activators (AKT3, PIK3CA, RHEB), as well as germline, somatic and two-hit loss-of-function variants in its repressors (DEPDC5, TSC1, TSC2) were found exclusively in FCD2/HME cases. We show that panel-negative FCD2 cases display strong pS6-immunostaining, stressing that all FCD2 are mTORopathies. Analysis of microdissected cells demonstrated that DNs and BCs carry the pathogenic variants. We further observed a correlation between the density of pathological cells and the variant-detection likelihood. Single-cell microdissection followed by sequencing of enriched pools of DNs unveiled a somatic second-hit loss-of-heterozygosity in a DEPDC5 germline case. In conclusion, this study indicates that mMCD/FCD1 and FCD2/HME are two distinct genetic entities: while all FCD2/HME are mosaic mTORopathies, mMCD/FCD1 are not caused by mTOR-pathway-hyperactivating variants, and ~ 30% of the cases are related to glycosylation defects. We provide a framework for efficient genetic testing in FCD/HME, linking neuropathology to genetic findings and emphasizing the usefulness of molecular evaluation in the pediatric epileptic neurosurgical population.

Genomic profiling of the residual disease of advanced high-grade serous ovarian cancer after neoadjuvant chemotherapy

The goal of our study was to demonstrate the spectrum of genomic alterations present in the residual disease of patients with advanced high-grade serous ovarian cancer (HGSOC) after neoadjuvant chemotherapy (NAC), including matched pretreatment biopsies. During the study period between 2006 and 2017, we collected pre-NAC and post-NAC tumor tissue samples from patients with advanced HGSOC. We performed combined next-generation sequencing and immunohistochemistry to identify actionable targets and pathway activation in post-NAC residual tumors. We also examined whether post-NAC profiling of residual HGSOC identified targetable molecular lesions in the chemotherapy-resistant component of tumors. Among 102 post-NAC samples, 41 (40%) of patients had mutations in homologous recombination repair (HRR) genes (HRR deficiency). Patients with HRR mutations had higher tumor mutation burdens (p < 0.001) and higher alterations in the PI3K-AKT-mTOR pathway (p = 0.004) than patients without these HRR mutations. Nevertheless, we found no significant differences in progression-free survival (p = 0.662) and overall survival (OS; p = 0.828) between the two groups. Most patients (91%) had alterations in at least one of the targetable pathways, and those patients with cell cycle (p = 0.004) and PI3K-AKT-mTOR signaling (p = 0.005) pathway alterations had poorer OS (Bonferroni-corrected threshold = 0.0083, 0.05/6). We showed the genomic landscape of tumor cells remaining in advanced HGSOC after NAC. Once validated, these data can help inform biomarker-driven adjuvant studies in targeting residual tumors to improve the outcomes of patients with advanced HGSOC after NAC.

Impact of mouse contamination in genomic profiling of patient-derived models and best practice for robust analysis

BACKGROUND

Patient-derived xenograft and cell line models are popular models for clinical cancer research. However, the inevitable inclusion of a mouse genome in a patient-derived model is a remaining concern in the analysis. Although multiple tools and filtering strategies have been developed to account for this, research has yet to demonstrate the exact impact of the mouse genome and the optimal use of these tools and filtering strategies in an analysis pipeline.

RESULTS

We construct a benchmark dataset of 5 liver tissues from 3 mouse strains using human whole-exome sequencing kit. Next-generation sequencing reads from mouse tissues are mappable to 49% of the human genome and 409 cancer genes. In total, 1,207,556 mouse-specific alleles are aligned to the human genome reference, including 467,232 (38.7%) alleles with high sensitivity to contamination, which are pervasive causes of false cancer mutations in public databases and are signatures for predicting global contamination. Next, we assess the performance of 8 filtering methods in terms of mouse read filtration and reduction of mouse-specific alleles. All filtering tools generally perform well, although differences in algorithm strictness and efficiency of mouse allele removal are observed. Therefore, we develop a best practice pipeline that contains the estimation of contamination level, mouse read filtration, and variant filtration.

CONCLUSIONS

The inclusion of mouse cells in patient-derived models hinders genomic analysis and should be addressed carefully. Our suggested guidelines improve the robustness and maximize the utility of genomic analysis of these models.

Brain somatic mutations observed in Alzheimer's disease associated with aging and dysregulation of tau phosphorylation

The role of brain somatic mutations in Alzheimer’s disease (AD) is not well understood. Here, we perform deep whole-exome sequencing (average read depth 584×) in 111 postmortem hippocampal formation and matched blood samples from 52 patients with AD and 11 individuals not affected by AD. The number of somatic single nucleotide variations (SNVs) in AD brain specimens increases significantly with aging, and the rate of mutation accumulation in the brain is 4.8-fold slower than that in AD blood. The putatively pathogenic brain somatic mutations identified in 26.9% (14 of 52) of AD individuals are enriched in PI3K-AKT, MAPK, and AMPK pathway genes known to contribute to hyperphosphorylation of tau. We show that a pathogenic brain somatic mutation in PIN1 leads to a loss-of-function mutation. In vitro mimicking of haploinsufficiency of PIN1 aberrantly increases tau phosphorylation and aggregation. This study provides new insights into the genetic architecture underlying the pathogenesis of AD.

The role of brain somatic mutations in neurodegenerative diseases such as Alzheimer’s disease (AD) is not well understood. Here the authors carry out high-depth exome sequencing ~500× on brain tissue from patients with AD and controls, and identify mutations in a number of genes that are known to contribute to phosphorylation and aggregation of tau, including PIN1.