The somatic mutation landscape of the human body

Single cell spatial biology over developmental time can decipher pediatric brain pathologies

Pediatric low grade brain tumors and neurodevelopmental disorders share proteins, signaling pathways, and networks. They also share germline mutations and an impaired prenatal differentiation origin. They may differ in the timing of the events and proliferation. We suggest that their pivotal distinct, albeit partially overlapping, outcomes relate to the cell states, which depend on their spatial location, and timing of gene expression during brain development. These attributes are crucial as the brain develops sequentially, and single-cell spatial organization influences cell state, thus function. Our underlying premise is that the root cause in neurodevelopmental disorders and pediatric tumors is impaired prenatal differentiation. Data related to pediatric brain tumors, neurodevelopmental disorders, brain cell (sub)types, locations, and timing of expression in the developing brain are scant. However, emerging single cell technologies, including transcriptomic, spatial biology, spatial high-resolution imaging performed over the brain developmental time, could be transformational in deciphering brain pathologies thereby pharmacology.

KDM4B mutations in human cancers

Homologous recombination (HR) is essential for repair of DNA double-strand breaks (DSBs) and restart of stalled or collapsed replication forks. Most cancers are characterized by mutations in components of the DSB repair pathways. Redundant DSB repair pathways exist in eukaryotes from yeast to humans and recent evidence has shown that complete loss of HR function appears to be lethal. Recent evidence has also shown that cancer cells with mutations in one DSB repair pathway can be killed by inhibiting one or more parallel pathways, a strategy that is currently aggressively explored as a cancer therapy. KDM4B is a histone demethylase with pleiotropic functions, which participates in preparing DSBs for repair by contributing to chromatin remodeling. In this report we carried out a pan-cancer analysis of KDM4B mutations with the goal of understanding their distribution and interaction with other DSB genes. We find that although KDM4B mutations co-occur with DSB repair genes, most KDM4B mutations are not drivers or pathogenic. A sequence conservation analysis from yeast to humans shows that highly conserved residues are resistant to mutation. Finally, all mutations occur in a heterozygous state. A single mutation, R986L, was predicted to significantly affect protein structure using computational modeling. This analysis suggests that KDM4B makes contributions to DSB repair but is not a key player.

DNA Damage Responses in Tumors Are Not Proliferative Stimuli, but Rather They Are DNA Repair Actions Requiring Supportive Medical Care

BACKGROUND

In tumors, somatic mutagenesis presumably drives the DNA damage response (DDR) via altered regulatory pathways, increasing genomic instability and proliferative activity. These considerations led to the standard therapeutic strategy against cancer: the disruption of mutation-activated DNA repair pathways of tumors.

PURPOSE

Justifying that cancer cells are not enemies to be killed, but rather that they are ill human cells which have the remnants of physiologic regulatory pathways.

RESULTS

1. Genomic instability and cancer development may be originated from a flaw in estrogen signaling rather than excessive estrogen signaling; 2. Healthy cells with genomic instability exhibit somatic mutations, helping DNA restitution; 3. Somatic mutations in tumor cells aim for the restoration of DNA damage, rather than further genomic derangement; 4. In tumors, estrogen signaling drives the pathways of DNA stabilization, leading to apoptotic death; 5. In peritumoral cellular infiltration, the genomic damage of the tumor induces inflammatory cytokine secretion and increased estrogen synthesis. In the inflammatory cells, an increased growth factor receptor (GFR) signaling confers the unliganded activation of estrogen receptors (ERs); 6. In breast cancer cells responsive to genotoxic therapy, constitutive mutations help the upregulation of estrogen signaling and consequential apoptosis. In breast tumors non-responsive to genotoxic therapy, the possibilities for ER activation via either liganded or unliganded pathways are exhausted, leading to farther genomic instability and unrestrained proliferation.

CONCLUSIONS

Understanding the real character and behavior of human tumors at the molecular level suggests that we should learn the genome repairing methods of tumors and follow them by supportive therapy, rather than provoking additional genomic damages.

Functional roles and cancer variants of the bifunctional glycosylase NEIL2

Over 70,000 DNA lesions occur in the cell every day, and the inability to properly repair them can lead to mutations and destabilize the genome, resulting in carcinogenesis. The base excision repair (BER) pathway is critical for maintaining genomic integrity by repairing small base lesions, abasic sites and single-stranded breaks. Monofunctional and bifunctional glycosylases initiate the first step of BER by recognizing and excising specific base lesions, followed by DNA end processing, gap filling, and finally nick sealing. The Nei-like 2 (NEIL2) enzyme is a critical bifunctional DNA glycosylase in BER that preferentially excises cytosine oxidation products and abasic sites from single-stranded, double-stranded, and bubble-structured DNA. NEIL2 has been implicated to have important roles in several cellular functions, including genome maintenance, participation in active demethylation, and modulation of the immune response. Several germline and somatic variants of NEIL2 with altered expression and enzymatic activity have been reported in the literature linking them to cancers. In this review, we provide an overview of NEIL2 cellular functions and summarize current findings on NEIL2 variants and their relationship to cancer.

Somatic mutations in aging and disease

Time always leaves its mark, and our genome is no exception. Mutations in the genome of somatic cells were first hypothesized to be the cause of aging in the 1950s, shortly after the molecular structure of DNA had been described. Somatic mutation theories of aging are based on the fact that mutations in DNA as the ultimate template for all cellular functions are irreversible. However, it took until the 1990s to develop the methods to test if DNA mutations accumulate with age in different organs and tissues and estimate the severity of the problem. By now, numerous studies have documented the accumulation of somatic mutations with age in normal cells and tissues of mice, humans, and other animals, showing clock-like mutational signatures that provide information on the underlying causes of the mutations. In this review, we will first briefly discuss the recent advances in next-generation sequencing that now allow quantitative analysis of somatic mutations. Second, we will provide evidence that the mutation rate differs between cell types, with a focus on differences between germline and somatic mutation rate. Third, we will discuss somatic mutational signatures as measures of aging, environmental exposure, and activities of DNA repair processes. Fourth, we will explain the concept of clonally amplified somatic mutations, with a focus on clonal hematopoiesis. Fifth, we will briefly discuss somatic mutations in the transcriptome and in our other genome, i.e., the genome of mitochondria. We will end with a brief discussion of a possible causal contribution of somatic mutations to the aging process.

Glutathione amino acid precursors protect skin from UVB-induced damage and improve skin tone

BACKGROUND

UV radiation exposure causes skin irritation, erythema, darkening and barrier disruption by inducing oxidative stress and inflammation. Glutathione, a master antioxidant, plays an important role in the antioxidant defence network of the skin.

OBJECTIVE

This study aimed to assess the in vitro protective effects of the glutathione amino acid precursors blend (GAP) on transcriptomic and phenotypic endpoints against UVB-induced challenges.

METHODS

Normal human epidermal melanocytes (NHEMs) were exposed to GAP, ascorbic acid (AA) and its derivatives. Viability was assessed using the CCK8 method. Melakutis®, a pigmented living skin equivalent (pLSE) model, underwent repeated 50 mJ/cm2 UVB irradiation with or without GAP treatment. Images of the model were captured with consistent camera parameters, and the model's light intensity was measured using a spectrophotometer. Melanin content was determined by measuring absorbance at 405 nm. Confirmation of melanin deposition and distribution was achieved through Fontana-Masson staining. Transcriptomic analysis was conducted using RNA sequencing (RNA-Seq), and a machine learning approach was employed for transcriptomic aging clock analysis.

RESULTS

In NHEMs, all tested compounds exhibited over 85% viability compared to the vehicle control, indicating no heightened risk of cytotoxicity. Notably, GAP demonstrated greater efficacy in inhibiting melanin production than AA derivatives at equivalent concentrations. In pLSE models, GAP notably enhanced model lightness, and reduced melanin content and deposition following the UVB challenge, whereas AA showed minimal impact. GAP effectively counteracted UVB-induced alterations in gene expression linked to pigmentation, inflammation and aging. Moreover, recurrent UVB exposure substantially elevated the biological age of pLSE models, a phenomenon mitigated by GAP treatment.

CONCLUSIONS

In NHEMs, GAP exhibited enhanced effectiveness in inhibiting melanin production at identical tested doses in comparison to AA derivatives. Noteworthy protective effects of GAP against UVB irradiation were observed in the pLSE models, as evidenced by skin pigmentation measurements and transcriptomic changes.

Somatic mutations inferred from RNA-seq data highlight the contribution of replication timing to mutation rate variation in a model plant

Variation in the rates and characteristics of germline and somatic mutations across the genome of an organism is informative about DNA damage and repair processes and can also shed light on aspects of organism physiology and evolution. We adapted a recently developed method for inferring somatic mutations from bulk RNA-seq data and applied it to a large collection of Arabidopsis thaliana accessions. The wide range of genomic data types available for A. thaliana enabled us to investigate the relationships of multiple genomic features with the variation in the somatic mutation rate across the genome of this model plant. We observed that late replicated regions showed evidence of an elevated rate of somatic mutation compared to genomic regions that are replicated early. We identified transcriptional strand asymmetries, consistent with the effects of transcription-coupled damage and/or repair. We also observed a negative relationship between the inferred somatic mutation count and the H3K36me3 histone mark which is well documented in the literature of human systems. In addition, we were able to support previous reports of an inverse relationship between inferred somatic mutation count and guanine-cytosine content as well as a positive relationship between inferred somatic mutation count and DNA methylation for both cytosine and noncytosine mutations.

Tumors produce glucocorticoids by metabolite recycling, not synthesis, and activate Tregs to promote growth

Glucocorticoids are steroid hormones with potent immunosuppressive properties. Their primary source is the adrenals, where they are generated via de novo synthesis from cholesterol. In addition, many tissues have a recycling pathway in which glucocorticoids are regenerated from inactive metabolites by the enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1, encoded by Hsd11b1). Here, we find that multiple tumor types express Hsd11b1 and produce active glucocorticoids. Genetic ablation of Hsd11b1 in such cells had no effect on in vitro growth, but reduced in vivo tumor progression, which corresponded with increased frequencies of CD8+ tumor-infiltrating lymphocytes (TILs) expressing activation markers and producing effector cytokines. Tumor-derived glucocorticoids were found to promote signatures of Treg activation and suppress signatures of conventional T cell activation in tumor-infiltrating Tregs. Indeed, CD8+ T cell activation was restored and tumor growth reduced in mice with Treg-specific glucocorticoid receptor deficiency. Importantly, pharmacologic inhibition of 11β-HSD1 reduced tumor growth to the same degree as gene knockout and rendered immunotherapy-resistant tumors susceptible to PD-1 blockade. Given that HSD11B1 expression is upregulated in many human tumors and that inhibition of 11β-HSD1 is well tolerated in clinical studies, these data suggest that targeting 11β-HSD1 may be a beneficial adjunct in cancer therapy.

Developmental priming of cancer susceptibility

DNA mutations are necessary drivers of cancer, yet only a small subset of mutated cells go on to cause the disease. To date, the mechanisms that determine which rare subset of cells transform and initiate tumorigenesis remain unclear. Here, we take advantage of a unique model of intrinsic developmental heterogeneity (Trim28+/D9) and demonstrate that stochastic early life epigenetic variation can trigger distinct cancer-susceptibility 'states' in adulthood. We show that these developmentally primed states are characterized by differential methylation patterns at typically silenced heterochromatin, and that these epigenetic signatures are detectable as early as 10 days of age. The differentially methylated loci are enriched for genes with known oncogenic potential. These same genes are frequently mutated in human cancers, and their dysregulation correlates with poor prognosis. These results provide proof-of-concept that intrinsic developmental heterogeneity can prime individual, life-long cancer risk.

Commonalities and differences in the mutational signature and somatic driver mutation landscape across solid and hollow viscus organs

Advances in sequencing have revealed a highly variegated landscape of mutational signatures and somatic driver mutations in a range of normal tissues. Normal tissues accumulate mutations at varying rates ranging from 11 per cell per year in the liver, to 1879 per cell per year in the bladder. In addition, some normal tissues are also comprised of a large proportion of cells which possess driver mutations while appearing phenotypically normal, as in the oesophagus where a majority of cells harbour driver mutations. Individual tissue proliferation and mutation rate, unique mutagenic stimuli, and local tissue architecture contribute to this highly variegated landscape which confounds the functional characterization of driver mutations found in normal tissue. In particular, our understanding of the relationship between normal tissue somatic mutations and tumour initiation or future cancer risk remains poor. Here, we describe the mutational signatures and somatic driver mutations in solid and hollow viscus organs, highlighting unique characteristics in a tissue-specific manner, while simultaneously seeking to describe commonalities which can bring forward a basic unified theory on the role of these driver mutations in tumour initiation. We discuss novel findings which can be used to inform future research in this field.

A Clonal Evolution Simulator for Planning Somatic Evolution Studies

Somatic evolution plays a key role in development, cell differentiation, and normal aging, but also in diseases such as cancer. Understanding mechanisms of somatic mutability and how they can vary between cell lineages will likely play a crucial role in biological discovery and medical applications. This need has led to a proliferation of new technologies for profiling single-cell variation, each with distinctive capabilities and limitations that can be leveraged alone or in combination with other technologies. The enormous space of options for assaying somatic variation, however, presents unsolved informatics problems with regard to selecting optimal combinations of technologies for designing appropriate studies for any particular scientific questions. Versatile simulation tools are needed to explore and optimize potential study designs if researchers are to deploy multiomic technologies most effectively. In this study, we present a simulator allowing for the generation of synthetic data from a wide range of clonal lineages, variant classes, and sequencing technology choices, intended to provide a platform for effective study design in somatic lineage analysis. Users can input various properties of the somatic evolutionary system, mutation classes, and biotechnology options, and then generate samples of synthetic sequence reads and their corresponding ground truth parameters for a given study design. We demonstrate the utility of the simulator for testing and optimizing study designs for various experimental queries.

CRISPR-detector: fast and accurate detection, visualization, and annotation of genome-wide mutations induced by genome editing events

The leading-edge CRISPR/CRISPR-associated technology is revolutionizing biotechnologies through genome editing. To track on/off-target events with emerging new editing techniques, improved bioinformatic tools are indispensable. Existing tools suffer from limitations in speed and scalability, especially with whole-genome sequencing (WGS) data analysis. To address these limitations, we have developed a comprehensive tool called CRISPR-detector, a web-based and locally deployable pipeline for genome editing sequence analysis. The core analysis module of CRISPR-detector is based on the Sentieon TNscope pipeline, with additional novel annotation and visualization modules designed to fit CRISPR applications. Co-analysis of the treated and control samples is performed to remove existing background variants prior to genome editing. CRISPR-detector offers optimized scalability, enabling WGS data analysis beyond Browser Extensible Data file-defined regions, with improved accuracy due to haplotype-based variant calling to handle sequencing errors. In addition, the tool also provides integrated structural variation calling and includes functional and clinical annotations of editing-induced mutations appreciated by users. These advantages facilitate rapid and efficient detection of mutations induced by genome editing events, especially for datasets generated from WGS. The web-based version of CRISPR-detector is available at https://db.cngb.org/crispr-detector, and the locally deployable version is available at https://github.com/hlcas/CRISPR-detector.

Amphioxus adenosine-to-inosine tRNA-editing enzyme that can perform C-to-U and A-to-I deamination of DNA

Adenosine-to-inosine tRNA-editing enzyme has been identified for more than two decades, but the study on its DNA editing activity is rather scarce. We show that amphioxus (Branchiostoma japonicum) ADAT2 (BjADAT2) contains the active site 'HxE-PCxxC' and the key residues for target-base-binding, and amphioxus ADAT3 (BjADAT3) harbors both the N-terminal positively charged region and the C-terminal pseudo-catalytic domain important for recognition of substrates. The sequencing of BjADAT2-transformed Escherichia coli genome suggests that BjADAT2 has the potential to target E. coli DNA and can deaminate at TCG and GAA sites in the E. coli genome. Biochemical analyses further demonstrate that BjADAT2, in complex with BjADAT3, can perform A-to-I editing of tRNA and convert C-to-U and A-to-I deamination of DNA. We also show that BjADAT2 preferentially deaminates adenosines and cytidines in the loop of DNA hairpin structures of substrates, and BjADAT3 also affects the type of DNA substrate targeted by BjADAT2. Finally, we find that C89, N113, C148 and Y156 play critical roles in the DNA editing activity of BjADAT2. Collectively, our study indicates that BjADAT2/3 is the sole naturally occurring deaminase with both tRNA and DNA editing capacity identified so far in Metazoa.

Next-generation sequencing methodologies to detect low-frequency mutations: "Catch me if you can"

Mutations, the irreversible changes in an organism's DNA sequence, are present in tissues at a variant allele frequency (VAF) ranging from ∼10-8 per bp for a founder mutation to ∼10-3 for a histologically normal tissue sample containing several independent clones - compared to 1%- 50% for a heterozygous tumor mutation or a polymorphism. The rarity of these events poses a challenge for accurate clinical diagnosis and prognosis, toxicology, and discovering new disease etiologies. Standard Next-Generation Sequencing (NGS) technologies report VAFs as low as 0.5% per nt, but reliably observing rarer precursor events requires additional sophistication to measure ultralow-frequency mutations. We detail the challenge; define terms used to characterize the results, which vary between laboratories and sometimes conflict between biologists and bioinformaticists; and describe recent innovations to improve standard NGS methodologies including: single-strand consensus sequence methods such as Safe-SeqS and SiMSen-Seq; tandem-strand consensus sequence methods such as o2n-Seq and SMM-Seq; and ultrasensitive parent-strand consensus sequence methods such as DuplexSeq, PacBio HiFi, SinoDuplex, OPUSeq, EcoSeq, BotSeqS, Hawk-Seq, NanoSeq, SaferSeq, and CODEC. Practical applications are also noted. Several methods quantify VAF down to 10-5 at a nt and mutation frequency (MF) in a target region down to 10-7 per nt. By expanding to > 1 Mb of sites never observed twice, thus forgoing VAF, other methods quantify MF < 10-9 per nt or < 15 errors per haploid genome. Clonal expansion cannot be directly distinguished from independent mutations by sequencing, so it is essential for a paper to report whether its MF counted only different mutations - the minimum independent-mutation frequency MFminI - or all mutations observed including recurrences - the larger maximum independent-mutation frequency MFmaxI which may reflect clonal expansion. Ultrasensitive methods reveal that, without their use, even mutations with VAF 0.5-1% are usually spurious.

A Multi-omic Analysis of the Human Lung Reveals Distinct Cell Specific Aging and Senescence Molecular Programs

Age is a major risk factor for lung disease. To understand the mechanisms underlying this association, we characterized the changing cellular, genomic, transcriptional, and epigenetic landscape of lung aging using bulk and single-cell RNAseq (scRNAseq) data. Our analysis revealed age-associated gene networks that reflected hallmarks of aging, including mitochondrial dysfunction, inflammation, and cellular senescence. Cell type deconvolution revealed age-associated changes in the cellular composition of the lung: decreased alveolar epithelial cells and increased fibroblasts and endothelial cells. In the alveolar microenvironment, aging is characterized by decreased AT2B cells and reduced surfactant production, a finding that was validated by scRNAseq and IHC. We showed that a previously reported senescence signature, SenMayo, captures cells expressing canonical senescence markers. SenMayo signature also identified cell-type specific senescence-associated co-expression modules that have distinct molecular functions, including ECM regulation, cell signaling, and damage response pathways. Analysis of somatic mutations showed that burden was highest in lymphocytes and endothelial cells and was associated with high expression of senescence signature. Finally, aging and senescence gene expression modules were associated with differentially methylated regions, with inflammatory markers such as IL1B, IL6R, and TNF being significantly regulated with age. Our findings provide new insights into the mechanisms underlying lung aging and may have implications for the development of interventions to prevent or treat age-related lung diseases.

Familial CCM Genes Might Not Be Main Drivers for Pathogenesis of Sporadic CCMs-Genetic Similarity between Cancers and Vascular Malformations

Cerebral cavernous malformations (CCMs) are abnormally dilated intracranial capillaries that form cerebrovascular lesions with a high risk of hemorrhagic stroke. Recently, several somatic "activating" gain-of-function (GOF) point mutations in PIK3CA (phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit p110α) were discovered as a dominant mutation in the lesions of sporadic forms of cerebral cavernous malformation (sCCM), raising the possibility that CCMs, like other types of vascular malformations, fall in the PIK3CA-related overgrowth spectrum (PROS). However, this possibility has been challenged with different interpretations. In this review, we will continue our efforts to expound the phenomenon of the coexistence of gain-of-function (GOF) point mutations in the PIK3CA gene and loss-of-function (LOF) mutations in CCM genes in the CCM lesions of sCCM and try to delineate the relationship between mutagenic events with CCM lesions in a temporospatial manner. Since GOF PIK3CA point mutations have been well studied in reproductive cancers, especially breast cancer as a driver oncogene, we will perform a comparative meta-analysis for GOF PIK3CA point mutations in an attempt to demonstrate the genetic similarities shared by both cancers and vascular anomalies.

The origins and functional effects of postzygotic mutations throughout the human life span

Postzygotic mutations (PZMs) begin to accrue in the human genome immediately after fertilization, but how and when PZMs affect development and lifetime health remain unclear. To study the origins and functional consequences of PZMs, we generated a multitissue atlas of PZMs spanning 54 tissue and cell types from 948 donors. Nearly half the variation in mutation burden among tissue samples can be explained by measured technical and biological effects, and 9% can be attributed to donor-specific effects. Through phylogenetic reconstruction of PZMs, we found that their type and predicted functional impact vary during prenatal development, across tissues, and through the germ cell life cycle. Thus, methods for interpreting effects across the body and the life span are needed to fully understand the consequences of genetic variants.

Deciphering gene contributions and etiologies of somatic mutational signatures of cancer

Somatic mutational signatures (MSs) identified by genome sequencing play important roles in exploring the cause and development of cancer. Thus far, many such signatures have been identified, and some of them do imply causes of cancer. However, a major bottleneck is that we do not know the potential meanings (i.e. carcinogenesis or biological functions) and contributing genes for most of them. Here, we presented a computational framework, Gene Somatic Genome Pattern (GSGP), which can decipher the molecular mechanisms of the MSs. More importantly, it is the first time that the GSGP is able to process MSs from ribonucleic acid (RNA) sequencing, which greatly extended the applications of both MS analysis and RNA sequencing (RNAseq). As a result, GSGP analyses match consistently with previous reports and identify the etiologies for a number of novel signatures. Notably, we applied GSGP to RNAseq data and revealed an RNA-derived MS involved in deficient deoxyribonucleic acid mismatch repair and microsatellite instability in colorectal cancer. Researchers can perform customized GSGP analysis using the web tools or scripts we provide.

The Molecular Mechanism of Polyphenols in the Regulation of Ageing Hallmarks

Ageing is a complex process characterized mainly by a decline in the function of cells, tissues, and organs, resulting in an increased risk of mortality. This process involves several changes, described as hallmarks of ageing, which include genomic instability, telomere attrition, epigenetic changes, loss of proteostasis, dysregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell depletion, and altered intracellular communication. The determining role that environmental factors such as diet and lifestyle play on health, life expectancy, and susceptibility to diseases, including cancer and neurodegenerative diseases, is wellestablished. In view of the growing interest in the beneficial effects of phytochemicals in the prevention of chronic diseases, several studies have been conducted, and they strongly suggest that the intake of dietary polyphenols may bring numerous benefits due to their antioxidant and anti-inflammatory properties, and their intake has been associated with impaired ageing in humans. Polyphenol intake has been shown to be effective in ameliorating several age-related phenotypes, including oxidative stress, inflammatory processes, impaired proteostasis, and cellular senescence, among other features, which contribute to an increased risk of ageing-associated diseases. This review aims to address, in a general way, the main findings described in the literature about the benefits of polyphenols in each of the hallmarks of ageing, as well as the main regulatory mechanisms responsible for the observed antiageing effects.

Mutations in coral soma and sperm imply lifelong stem cell renewal and cell lineage selection

In many animals, the germline differentiates early in embryogenesis, so only mutations that accumulate in germ cells are inherited by offspring. Exceptions to this developmental process may indicate other mechanisms have evolved to limit the effects of deleterious mutation accumulation. Stony corals are animals that can live for hundreds of years and have been thought to produce gametes from somatic tissue. To clarify conflicting evidence about germline-soma distinction in corals, we sequenced high coverage, full genomes with technical replicates for parent coral branches and their sperm pools. We identified post-embryonic single nucleotide variants (SNVs) unique to each parent branch, then checked if each SNV was shared by the respective sperm pool. Twenty-six per cent of post-embryonic SNVs were shared by the sperm and 74% were not. We also identified germline SNVs, those that were present in the sperm but not in the parent. These data suggest that self-renewing stem cells differentiate into germ and soma throughout the adult life of the colony, with SNV rates and patterns differing markedly in stem, soma and germ lineages. In addition to informing the evolution of germlines in metazoans, these insights inform how corals may generate adaptive diversity necessary in the face of global climate change.

Clonal hematopoiesis, somatic mosaicism, and age-associated disease

Somatic mosaicism, the occurrence of multiple genetically distinct cell clones within the same tissue, is an evitable consequence of human aging. The hematopoietic system is no exception to this, where studies have revealed the presence of expanded blood cell clones carrying mutations in preleukemic driver genes and/or genetic alterations in chromosomes. This phenomenon is referred to as clonal hematopoiesis and is remarkably prevalent in elderly individuals. While clonal hematopoiesis represents an early step toward a hematological malignancy, most individuals will never develop blood cancer. Somewhat unexpectedly, epidemiological studies have found that clonal hematopoiesis is associated with an increase in the risk of all-cause mortality and age-related disease, particularly in the cardiovascular system. Studies using murine models of clonal hematopoiesis have begun to shed light on this relationship, suggesting that driver mutations in mature blood cells can causally contribute to aging and disease by augmenting inflammatory processes. Here we provide an up-to-date review of clonal hematopoiesis within the context of somatic mosaicism and aging and describe recent epidemiological studies that have reported associations with age-related disease. We will also discuss the experimental studies that have provided important mechanistic insight into how driver mutations promote age-related disease and how this knowledge could be leveraged to treat individuals with clonal hematopoiesis.

Microenvironmental changes co-occur with mosaic somatic clonal expansions in normal skin and esophagus tissues

The presence of somatic mutations, previously identified in cancers, are being increasingly recognized in normal tissues. While the role of microenvironment (ME) in tumor progression is well understood, the changes that occur in the microenvironment of normal tissues that harbor somatic mutations has not been systematically studied. Here, using normal RNA-Seq data accrued from 6544 samples across 27 tissue types from Genotype-Tissue Expression (GTEx) project, we studied the association of microenvironmental changes in the presence of somatic clonal expansions of previously implicated cancer genes. We focused our analysis on skin and esophagus since they have the highest number of samples and mutation burden together. We observed changes in microenvironmental cell-types previously implicated in tumor progression including endothelial cells, epithelial cells, pericytes, fibroblasts, chondrocytes, among others. The Epithelial-Mesenchymal-Transition (EMT) pathway is dysregulated in both skin and esophagus, along with increased hypoxia scores in samples with clonal expansions. These results suggest that microenvironmental changes play an important role in clonal expansions and potentially the initiating stages of cancer progression. Studying these changes may provide new avenues for early intervention of cancer, for targeted therapies, or enhance activities of conventional therapies.

Clinical characteristics and gene mutation profiles of chronic obstructive pulmonary disease in non-small cell lung cancer

Purpose

The coexistence of chronic obstructive pulmonary disease (COPD) often leads to a worse prognosis in patients with non-small cell lung cancer (NSCLC). Meanwhile, approaches targeting specific genetic alterations have been shown to significantly improve the diagnosis and treatment outcomes of patients with NSCLC. Herein, we sought to evaluate the impact of COPD on the clinical manifestations and gene mutation profiles of NSCLC patients with both circulating tumor (ctDNA) and tumor DNA (tDNA).

Materials and methods

The influence of COPD on clinical features was observed in 285 NSCLC cohorts suffering from NSCLC alone, NSCLC coexisting with COPD, or NSCLC coexisting with prodromal changes in COPD (with emphysema, bullae, or chronic bronchitis). The gene mutation profiles of specific 168 NSCLC-related genes were further analyzed in the NSCLC sub-cohorts with formalin-fixed and paraffin-embedded tumor DNA (FFPE tDNA) samples and plasma circulating tumor DNA (PLA ctDNA) samples. Moreover, mutation concordance was assessed in tDNA and paired ctDNA of 110 NSCLC patients.

Results

Relative to patients with NSCLC alone, patients with NSCLC coexisting with COPD and prodromal changes presented with worse lung functions, more clinical symptoms, signs and comorbidities, and inconsistent gene mutation profiles. In addition, patients in the latter two groups exhibited a higher average frequency of gene mutation. Lastly, mutation concordance between tDNA and ctDNA samples was significantly reduced in NSCLC patients coexisting with COPD.

Conclusions

Collectively, our findings revealed that coexistence of COPD leads to worse clinical manifestations and altered gene mutation profiles in patients with NSCLC. Additionally, for NSCLC patients with COPD, the use of ctDNA instead of tDNA may not be the most efficient approach to identifying gene mutations.

Somatic variation in normal tissues: friend or foe of cancer early detection?

BACKGROUND

Seemingly normal tissues progressively become populated by mutant clones over time. Most of these clones bear mutations in well-known cancer genes but only rarely do they transform into cancer. This poses questions on what triggers cancer initiation and what implications somatic variation has for cancer early detection.

DESIGN

We analysed recent mutational screens of healthy and cancer-free diseased tissues to compare somatic drivers and the causes of somatic variation across tissues. We then reviewed the mechanisms of clonal expansion and their relationships with age and diseases other than cancer. We finally discussed the relevance of somatic variation for cancer initiation and how it can help or hinder cancer detection and prevention.

RESULTS

The extent of somatic variation is highly variable across tissues and depends on intrinsic features, such as tissue architecture and turnover, as well as the exposure to endogenous and exogenous insults. Most somatic mutations driving clonal expansion are tissue-specific and inactivate tumor suppressor genes involved in chromatin modification and cell growth signaling. Some of these genes are more frequently mutated in normal tissues than cancer, indicating a context-dependent cancer promoting or protective role. Mutant clones can persist over a long time or disappear rapidly, suggesting that their fitness depends on the dynamic equilibrium with the environment. The disruption of this equilibrium is likely responsible for their transformation into malignant clones and knowing what triggers this process is key for cancer prevention and early detection. Somatic variation should be considered in liquid biopsy, where it may contribute cancer-independent mutations, and in the identification of cancer drivers, since not all mutated genes favoring clonal expansion also drive tumorigenesis.

CONCLUSIONS

Somatic variation and the factors governing homeostasis of normal tissues should be taken into account when devising strategies for cancer prevention and early detection.

Age-related somatic mutation burden in human tissues

The genome of multicellular organisms carries the hereditary information necessary for the development of all organs and tissues and to maintain function in adulthood. To ensure the genetic stability of the species, genomes are protected against changes in sequence information. However, genomes are not static. De novo mutations in germline cells are passed on to offspring and generate the variation needed in evolution. Moreover, postzygotic mutations occur in all somatic cells during development and aging. These somatic mutations remain limited to the individual, generating tissues that are genome mosaics. Insight into such mutations and their consequences has been limited due to their extremely low abundance, with most mutations unique for each cell. Recent advances in sequencing, including whole genome sequencing at the single-cell level, have now led to the first insights into somatic mutation burdens in human tissues. Here, we will first briefly describe the latest methodology for somatic mutation analysis, then review our current knowledge of somatic mutation burden in human tissues and, finally, briefly discuss the possible functional impact of somatic mutations on the aging process and age-related diseases, including cancer and diseases other than cancer.

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.

Individual Genetic Heterogeneity

Genetic variation has been widely covered in literature, however, not from the perspective of an individual in any species. Here, a synthesis of genetic concepts and variations relevant for individual genetic constitution is provided. All the different levels of genetic information and variation are covered, ranging from whether an organism is unmixed or hybrid, has variations in genome, chromosomes, and more locally in DNA regions, to epigenetic variants or alterations in selfish genetic elements. Genetic constitution and heterogeneity of microbiota are highly relevant for health and wellbeing of an individual. Mutation rates vary widely for variation types, e.g., due to the sequence context. Genetic information guides numerous aspects in organisms. Types of inheritance, whether Mendelian or non-Mendelian, zygosity, sexual reproduction, and sex determination are covered. Functions of DNA and functional effects of variations are introduced, along with mechanism that reduce and modulate functional effects, including TARAR countermeasures and intraindividual genetic conflict. TARAR countermeasures for tolerance, avoidance, repair, attenuation, and resistance are essential for life, integrity of genetic information, and gene expression. The genetic composition, effects of variations, and their expression are considered also in diseases and personalized medicine. The text synthesizes knowledge and insight on individual genetic heterogeneity and organizes and systematizes the central concepts.

Genetic Variation among Pharmacogenes in the Sardinian Population

Pharmacogenetics (PGx) aims to identify the genetic factors that determine inter-individual differences in response to drug treatment maximizing efficacy while decreasing the risk of adverse events. Estimating the prevalence of PGx variants involved in drug response, is a critical preparatory step for large-scale implementation of a personalized medicine program in a target population. Here, we profiled pharmacogenetic variation in fourteen clinically relevant genes in a representative sample set of 1577 unrelated sequenced Sardinians, an ancient island population that accounts for genetic variation in Europe as a whole, and, at the same time is enriched in genetic variants that are very rare elsewhere. To this end, we used PGxPOP, a PGx allele caller based on the guidelines created by the Clinical Pharmacogenetics Implementation Consortium (CPIC), to identify the main phenotypes associated with the PGx alleles most represented in Sardinians. We estimated that 99.43% of Sardinian individuals might potentially respond atypically to at least one drug, that on average each individual is expected to have an abnormal response to about 17 drugs, and that for 27 drugs the fraction of the population at risk of atypical responses to therapy is more than 40%. Finally, we identified 174 pharmacogenetic variants for which the minor allele frequency was at least 10% higher among Sardinians as compared to other European populations, a fact that may contribute to substantial interpopulation variability in drug response phenotypes. This study provides baseline information for further large-scale pharmacogenomic investigations in the Sardinian population and underlines the importance of PGx characterization of diverse European populations, such as Sardinians.

Strategies for Mammalian Mesenchymal Stem Cells Differentiation into Primordial Germ Cell-Like Cells: A Review

Primordial germ cells develop into oocytes and sperm cells. These cells are useful resources in reproductive biology and regenerative medicine. The mesenchymal stem cells (MSCs) have been examined for in vitro production of primordial germ cell-like cells. This study aimed to summarize the existing protocols for MSCs differentiation into primordial germ cell-like cells (PGLCs). In the limited identified studies, various models of mesenchymal stem cells, including those derived from adipose tissue, bone marrow, and Wharton's jelly, have been successfully differentiated into primordial germ cell-like cells. Although the protocols of specification induction are basically very similar, they have been adjusted to the mesenchymal cell type and the species of origin. The availability of MSCs has made it possible to customize conditions for their differentiation into primordial germ cell-like cells in several models, including humans. Refining germ cell-related signaling pathways during induced differentiation of MSCs will help define extension to the protocols for primordial germ cell-like cells production.

Postzygotic mutations and where to find them - Recent advances and future implications in the field of non-neoplastic somatic mosaicism

The technological progress of massively parallel sequencing (MPS) has triggered a remarkable development in the research on postzygotic mutations. Although the overwhelming majority of studies in the field focus on oncogenesis, non-neoplastic diseases are attracting more and more attention. The aim of this review was to summarize some of the most recent findings in the field of somatic mosaicism in diseases other than neoplastic events. We discuss the abundance and role of postzygotic mutations, with a special emphasis on disorders which occur only in a mosaic form (obligatory mosaic diseases; OMDs). Based on the list of OMDs compiled from the published literature and three databases (OMIM, Orphanet and MosaicBase), we demonstrate the prevalence of cancer-related genes across OMDs and suggest other sources to further explore OMDs and OMD-related genes. Additionally, we comment on some practical aspects related to mosaic diseases, such as approaches to tissue sampling, the MPS coverage required to detect variants at a very low frequency, as well as on bioinformatic and molecular tools dedicated to detect somatic mutations in MPS data.

RNA-SSNV: A Reliable Somatic Single Nucleotide Variant Identification Framework for Bulk RNA-Seq Data

The usage of expressed somatic mutations may have a unique advantage in identifying active cancer driver mutations. However, accurately calling mutations from RNA-seq data is difficult due to confounding factors such as RNA-editing, reverse transcription, and gap alignment. In the present study, we proposed a framework (named RNA-SSNV, https://github.com/pmglab/RNA-SSNV) to call somatic single nucleotide variants (SSNV) from tumor bulk RNA-seq data. Based on a comprehensive multi-filtering strategy and a machine-learning classification model trained with comprehensively curated features, RNA-SSNV achieved the best precision–recall rate (0.880–0.884) in a testing dataset and robustly retained 0.94 AUC for the precision–recall curve in three validation adult-based TCGA (The Cancer Genome Atlas) datasets. We further showed that the somatic mutations called by RNA-SSNV tended to have a higher functional impact and therapeutic power in known driver genes. Furthermore, VAF (variant allele fraction) analysis revealed that subclonal harboring expressed mutations had evolutional selection advantage and RNA had higher detection power to rescue DNA-omitted mutations. In sum, RNA-SSNV will be a useful approach to accurately call expressed somatic mutations for a more insightful analysis of cancer drive genes and carcinogenic mechanisms.

Two different aging paths in human blood revealed by integrated analysis of gene Expression, mutation and alternative splicing

Aging is a complex life process that human organs and tissues steadily and continuously decline. Aging has huge heterogeneity, which shows different aging rates among different individuals and in different tissues of the same individual. Many studies of aging are often contradictory and show little common signature. The integrated analysis of these transcriptome datasets will provide an unbiased global view of the aging process. Here, we integrated 8 transcriptome datasets including 757 samples from healthy human blood to study aging from three aspects of gene expression, mutations, and alternative splicing. Surprisingly, we found that transcriptome changes in blood are relatively independent of the chronological age. Further pseudotime analysis revealed two different aging paths (AgingPath1 and AgingPath2) in human blood. The differentially expressed genes (DEGs) along the two paths showed a limited overlap and are enriched in different biological processes. The mutations of DEGs in AgingPath1 are significantly increased in the aging process, while the opposite trend was observed in AgingPath2. Expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) analysis identified 304 important mutations that can affect both gene expression and alternative splicing during aging. Finally, by comparison between aging and Alzheimer's disease, we identified 37 common DEGs in AgingPath1, AgingPath2 and Alzheimer's disease. These genes may contribute to the shift from aging state to Alzheimer's disease. In summary, this study revealed the two aging paths and the related genes and mutations, which provides a new insight into aging and aging-related disease.

A new deep learning technique reveals the exclusive functional contributions of individual cancer mutations

Cancers are caused by genomic alterations that may be inherited, induced by environmental carcinogens, or caused due to random replication errors. Postinduction of carcinogenicity, mutations further propagate and drastically alter the cancer genomes. Although a subset of driver mutations has been identified and characterized to date, most cancer-related somatic mutations are indistinguishable from germline variants or other noncancerous somatic mutations. Thus, such overlap impedes appreciation of many deleterious but previously uncharacterized somatic mutations. The major bottleneck arises due to patient-to-patient variability in mutational profiles, making it difficult to associate specific mutations with a given disease outcome. Here, we describe a newly developed technique Continuous Representation of Codon Switches (CRCS), a deep learning-based method that allows us to generate numerical vector representations of mutations, thereby enabling numerous machine learning-based tasks. We demonstrate three major applications of CRCS; first, we show how CRCS can help detect cancer-related somatic mutations in the absence of matched normal samples, which has applications in cell-free DNA–based assessment of tumor mutation burden. Second, the proposed approach also enables identification and exploration of driver genes; our analyses implicate DMD, RSK4, OFD1, WDR44, and AFF2 as potential cancer drivers. Finally, we used CRCS to score individual mutations in a tumor sample, which was found to be predictive of patient survival in bladder urothelial carcinoma, hepatocellular carcinoma, and lung adenocarcinoma. Taken together, we propose CRCS as a valuable computational tool for analysis of the functional significance of individual cancer mutations.

OPUSeq simplifies detection of low-frequency DNA variants and uncovers fragmentase-associated artifacts

Detection of low-frequency DNA variants (below 1%) is becoming increasingly important in biomedical research and clinical practice, but is challenging to do with standard sequencing approaches due to high error rates. The use of double-stranded unique molecular identifiers (dsUMIs) allows correction of errors by comparing reads arising from the same original DNA duplex. However, the implementation of such approaches is still challenging. Here, we present a novel method, one-pot dsUMI sequencing (OPUSeq), which allows incorporation of dsUMIs in the same reaction as the library PCR. This obviates the need for adapter pre-synthesis or additional enzymatic steps. OPUSeq can be incorporated into standard DNA library preparation approaches and coupled with hybridization target capture. We demonstrate successful error correction and detection of variants down to allele frequency of 0.01%. Using OPUSeq, we also show that the use of enzymatic fragmentation can lead to the appearance of spurious double-stranded variants, interfering with detection of variant fractions below 0.1%.

Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes

Largely, cancer development is driven by acquisition and positive selection of somatic mutations that increase proliferation and survival of tumor cells. As a result, genes related to cancer development tend to have an excess of somatic mutations in them. An excess of missense and/or nonsense mutations in a gene is an indicator of its cancer relevance. To identify genes with an excess of potentially functional missense or nonsense mutations one needs to compare the observed and expected numbers of mutations in the gene. We estimated the expected numbers of missense and nonsense mutations in individual human genes using (i) the number of potential sites for missense and nonsense mutations in individual transcripts and (ii) histology-specific nucleotide context-dependent mutation rates. To estimate mutation rates defined as the number of mutations per site per tumor we used silent mutations reported in the Catalog Of Somatic Mutations In Cancer (COSMIC). The estimates were nucleotide context dependent. We have identified 26 genes with an excess of missense and/or nonsense mutations for lung adenocarcinoma, 18 genes for small cell lung cancer, and 26 genes for squamous cell carcinoma of the lung. These genes include known genes and novel lung cancer gene candidates.

Ultrasensitive profiling of UV-induced mutations identifies thousands of subclinical facial tumors in tuberous sclerosis complex

BackgroundTuberous sclerosis complex (TSC) is a neurogenetic syndrome due to loss-of-function mutations in TSC2 or TSC1, characterized by tumors at multiple body sites, including facial angiofibroma (FAF). Here, an ultrasensitive assessment of the extent and range of UV-induced mutations in TSC facial skin was performed.MethodsA multiplex high-sensitivity PCR assay (MHPA) was developed, enabling mutation detection at extremely low (<0.1%) variant allele frequencies (VAFs).ResultsMHPA assays were developed for both TSC2 and TP53, and applied to 81 samples, including 66 skin biopsies. UV-induced second-hit mutation causing inactivation of TSC2 was pervasive in TSC facial skin with an average of 4.8 mutations per 2-mm biopsy at median VAF 0.08%, generating more than 150,000 incipient facial tumors (subclinical "micro-FAFs") in the average TSC subject. The MHPA analysis also led to the identification of a refined UV-related indel signature and a recurrent complex mutation pattern, consisting of both a single-nucleotide or dinucleotide variant and a 1- to 9-nucleotide deletion, in cis.ConclusionTSC facial skin can be viewed as harboring a patchwork of clonal fibroblast proliferations (micro-FAFs) with indolent growth, a small proportion of which develop into clinically observable FAF. Our observations also expand the spectrum of UV-related mutation signatures.FundingThis work was supported by the TSC Alliance; the Engles Family Fund for Research in TSC and LAM; and the NIH, National Heart, Lung, and Blood Institute (U01HL131022-04 and Intramural Research Program).

The translational challenges of precision oncology

The translational challenges in the field of precision oncology are in part related to the biological complexity and diversity of this disease. Technological advances in genomics have facilitated large sequencing efforts and discoveries that have further supported this notion. In this review, we reflect on the impact of these discoveries on our understanding of several concepts: cancer initiation, cancer prevention, early detection, adjuvant therapy and minimal residual disease monitoring, cancer drug resistance, and cancer evolution in metastasis. We discuss key areas of focus for improving cancer outcomes, from biological insights to clinical application, and suggest where the development of these technologies will lead us. Finally, we discuss practical challenges to the wider adoption of molecular profiling in the clinic and the need for robust translational infrastructure.

Differential ETS1 binding to T:G mismatches within a CpG dinucleotide contributes to C-to-T somatic mutation rate of the IDH2 hotspot at codon Arg140

Cytosine to thymine (C>T) somatic mutation is highly enriched in certain types of cancer, and most commonly occurs via deamination of a 5-methylcytosine (5mC) to thymine, in the context of a CpG dinucleotide. In theory, deamination should occur at equal rates to both 5mC nucleotides on opposite strands. In most cases, the resulting T:G or G:T mismatch can be repaired by thymine DNA glycosylase activities. However, while some hotspot-associated CpG mutations have approximately equal numbers of mutations that resulted either from C>T or G>A in a CpG dinucleotide, many showed strand bias, being skewed toward C>T of the first base pair or G>A of the second base pair. Using the IDH2 Arg140 codon as a case study, we show that the two possible T:G mismatches at the codon-specific CpG site have differing effects on transcription factor ETS1 binding affinity, differentially affecting access of a repair enzyme (MBD4) to the deamination-caused T:G mismatch. Our study thus provides a plausible mechanism for exclusion of repair enzymes by the differential binding of transcription factors affecting the rate at which the antecedent opposite-strand mutations occur.

Human induced pluripotent stem cells: From cell origin, genomic stability and epigenetic memory to translational medicine

The potential of human induced pluripotent stem cells (iPSCs) to self-renew indefinitely and to differentiate virtually into any cell type in unlimited quantities makes them attractive for in-vitro disease modeling, drug screening, personalized medicine, and regenerative therapies. As the genome of iPSCs thoroughly reproduces that of the somatic cells from which they are derived, they may possess genetic abnormalities, which would seriously compromise their utility and safety. Genetic aberrations could be present in donor somatic cells and then transferred during iPSC generation, or they could occur as de novo mutations during reprogramming or prolonged cell culture. Therefore, to warrant safety of human iPSCs for clinical applications, analysis of genetic integrity, particularly during iPSC generation and differentiation, should be carried out on a regular basis. On the other hand, reprogramming of somatic cells to iPSCs requires profound modifications in the epigenetic landscape. Changes in chromatin structure by DNA methylations and histone tail modifications aim to reset the gene expression pattern of somatic cells to facilitate and establish self-renewal and pluripotency. However, residual epigenetic memory influences the iPSC phenotype, which may affect their application in disease therapeutics. The present review discusses the somatic cell origin, genetic stability, and epigenetic memory of iPSCs and their impact on basic and translational research.

Exploring the Associations Between Clonal Hematopoiesis of Indeterminate Potential, Myeloid Malignancy, and Atherosclerosis

Outgrowth of a mutated hematopoietic stem/progenitor clone and its descendants, also known as clonal hematopoiesis, has long been considered as either a potential forerunner to hematologic malignancy or as a clinically silent phase in leukemia that antedates symptomatic disease. That definition of clonal hematopoiesis has now been expanded to encompass patients who harbor specific genetic/epigenetic mutations that lead to clonal hematopoiesis of indeterminate potential (CHIP) and, with it, a relatively heightened risk for both myeloid malignancy and atherosclerosis during aging. In this review, we provide contemporary insights into the cellular and molecular basis for CHIP and explore the relationship of CHIP to myeloid malignancy and atherosclerosis. We also discuss emerging strategies to explore CHIP biology and clinical targeting of CHIP related malignancy and cardiovascular disease.

Impact of CDKN2A/B Homozygous Deletion on the Prognosis and Biology of IDH-Mutant Glioma

Although hotspot mutations in isocitrate dehydrogenase (IDH) genes are associated with favorable clinical outcomes in glioma, CDKN2A/B homozygous deletion has been identified as an independent predicator of poor prognosis. Accordingly, the 2021 edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) has adopted this molecular feature by upgrading IDH-mutant astrocytoma to CNS WHO grade IV, even in the absence of glioblastoma-specific histological features—necrosis and microvascular proliferation. This new entity of IDH-mutant astrocytoma not only signifies an exception to the generally favorable outcome of IDH-mutant glioma, but also brings into question whether, and, if so, how, CDKN2A/B homozygous deletion overrides the anti-tumor activity of IDH mutation by promoting the proliferation of stem/neural progenitor-like cells. Understanding the mechanism by which IDH mutation requires intact tumor-suppressor genes for conferring favorable outcome may improve therapeutics.

Whole genome deep sequencing analysis of cell-free DNA in samples with low tumour content

Background

Circulating cell-free DNA (cfDNA) in the plasma of cancer patients contains cell-free tumour DNA (ctDNA) derived from tumour cells and it has been widely recognized as a non-invasive source of tumour DNA for diagnosis and prognosis of cancer. Molecular profiling of ctDNA is often performed using targeted sequencing or low-coverage whole genome sequencing (WGS) to identify tumour specific somatic mutations or somatic copy number aberrations (sCNAs). However, these approaches cannot efficiently detect all tumour-derived genomic changes in ctDNA.

Methods

We performed WGS analysis of cfDNA from 4 breast cancer patients and 2 patients with benign tumours. We sequenced matched germline DNA for all 6 patients and tumour samples from the breast cancer patients. All samples were sequenced on Illumina HiSeqXTen sequencing platform and achieved approximately 30x, 60x and 100x coverage on germline, tumour and plasma DNA samples, respectively.

Results

The mutational burden of the plasma samples (1.44 somatic mutations/Mb of genome) was higher than the matched tumour samples. However, 90% of high confidence somatic cfDNA variants were not detected in matched tumour samples and were found to comprise two background plasma mutational signatures. In contrast, cfDNA from the di-nucleosome fraction (300 bp–350 bp) had much higher proportion (30%) of variants shared with tumour. Despite high coverage sequencing we were unable to detect sCNAs in plasma samples.

Conclusions

Deep sequencing analysis of plasma samples revealed higher fraction of unique somatic mutations in plasma samples, which were not detected in matched tumour samples. Sequencing of di-nucleosome bound cfDNA fragments may increase recovery of tumour mutations from plasma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09160-1.

Driving mosaicism: somatic variants in reference population databases and effect on variant interpretation in rare genetic disease

BACKGROUND

Genetic variation databases provide invaluable information on the presence and frequency of genetic variants in the 'untargeted' human population, aggregated with the primary goal to facilitate the interpretation of clinically important variants. The presence of somatic variants in such databases can affect variant assessment in undiagnosed rare disease (RD) patients. Previously, the impact of somatic mosaicism was only considered in relation to two Mendelian disease-associated genes. Here, we expand the analyses to identify additional mosaicism-prone genes in blood-derived reference population databases.

RESULTS

To identify additional mosaicism-prone genes relevant to RDs, we focused on known/previously established ClinVar pathogenic and likely pathogenic single-nucleotide variants, residing in genes associated with early onset, severe autosomal dominant diseases. We asked whether any of these variants are present in a higher-than-expected frequency in the reference population databases and whether there is evidence of somatic origin (i.e., allelic imbalance) rather than germline heterozygosity (~ half of the reads supporting alternative allele). The mosaicism-prone genes identified were further categorized according to the processes they are involved in. Beyond the previously reported ASXL1 and DNMT3A, we identified 7 additional autosomal dominant RD-associated genes with known pathogenic single-nucleotide variants present in the reference population databases and good evidence of allelic imbalance: BRAF, CBL, FGFR3, IDH2, KRAS, PTPN11 and SETBP1. From this group of 9 genes, the majority (n = 7) was important for hematopoiesis. In addition, 4 of these genes were involved in cell proliferation. Further assessment of the known 156 hematopoietic genes led to identification of 48 genes (21 not yet associated with RDs) with at least some evidence of mosaicism detectable in reference population databases.

CONCLUSIONS

These results stress the importance of considering genes involved in hematopoiesis and cell proliferation when interpreting the presence and frequency of genetic variants in blood-derived reference population databases, both public and private. This is especially important when considering new variants of uncertain significance in known hematopoietic/cell proliferation RD genes and future novel gene-disease associations involving this class of genes.

One Cell, Two Gears: Extensive Somatic Genome Plasticity Accompanies High Germline Genome Stability in Paramecium

Mutation accumulation (MA) experiments are conventionally employed to study spontaneous germline mutations. However, MA experiments can also shed light on somatic genome plasticity in a habitual and genetic drift-maximizing environment. Here, we revisit an MA experiment that uncovered extraordinary germline genome stability in Paramecium tetraurelia, a single-celled eukaryote with nuclear dimorphism. Our re-examination of isogenic P. tetraurelia MA lines propagated in nutrient-rich medium for >40 sexual cycles reveals that their polyploid somatic genome accrued hundreds of intervening DNA segments (IESs), which are normally eliminated during germline-soma differentiation. These IESs frequently occupy a fraction of the somatic DNA copies of a given locus, producing IES excision/retention polymorphisms, and preferentially fall into a class of epigenetically controlled sequences. Relative to control lines, retained IESs are flanked by stronger cis-acting signals and interrupt an excess of highly expressed coding exons. These findings suggest that P. tetraurelia’s elevated germline DNA replication fidelity is associated with pervasive somatic genome plasticity. They show that MA regimes are powerful tools for investigating the role that developmental plasticity, somatic mutations, and epimutations have in ecology and evolution.

Genomics of Alzheimer's disease implicates the innate and adaptive immune systems

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterised by cognitive impairment, behavioural alteration, and functional decline. Over 130 AD-associated susceptibility loci have been identified by genome-wide association studies (GWAS), while whole genome sequencing (WGS) and whole exome sequencing (WES) studies have identified AD-associated rare variants. These variants are enriched in APOE, TREM2, CR1, CD33, CLU, BIN1, CD2AP, PILRA, SCIMP, PICALM, SORL1, SPI1, RIN3, and more genes. Given that aging is the single largest risk factor for late-onset AD (LOAD), the accumulation of somatic mutations in the brain and blood of AD patients have also been explored. Collectively, these genetic findings implicate the role of innate and adaptive immunity in LOAD pathogenesis and suggest that a systemic failure of cell-mediated amyloid-β (Aβ) clearance contributes to AD onset and progression. AD-associated variants are particularly enriched in myeloid-specific regulatory regions, implying that AD risk variants are likely to perturbate the expression of myeloid-specific AD-associated genes to interfere Aβ clearance. Defective phagocytosis, endocytosis, and autophagy may drive Aβ accumulation, which may be related to naturally-occurring antibodies to Aβ (Nabs-Aβ) produced by adaptive responses. Passive immunisation is providing efficiency in clearing Aβ and slowing cognitive decline, such as aducanumab, donanemab, and lecanemab (ban2401). Causation of AD by impairment of the innate immunity and treatment using the tools of adaptive immunity is emerging as a new paradigm for AD, but immunotherapy that boosts the innate immune functions of myeloid cells is highly expected to modulate disease progression at asymptomatic stage.

Host-specific asymmetric accumulation of mutation types reveals that the origin of SARS-CoV-2 is consistent with a natural process

The capacity of RNA viruses to adapt to new hosts and rapidly escape the host immune system is largely attributable to de novo genetic diversity that emerges through mutations in RNA. Although the molecular spectrum of de novo mutations—the relative rates at which various base substitutions occur—are widely recognized as informative toward understanding the evolution of a viral genome, little attention has been paid to the possibility of using molecular spectra to infer the host origins of a virus. Here, we characterize the molecular spectrum of de novo mutations for SARS-CoV-2 from transcriptomic data obtained from virus-infected cell lines, enabled by the use of sporadic junctions formed during discontinuous transcription as molecular barcodes. We find that de novo mutations are generated in a replication-independent manner, typically on the genomic strand, and highly dependent on mutagenic mechanisms specific to the host cellular environment. De novo mutations will then strongly influence the types of base substitutions accumulated during SARS-CoV-2 evolution, in an asymmetric manner favoring specific mutation types. Consequently, similarities between the mutation spectra of SARS-CoV-2 and the bat coronavirus RaTG13, which have accumulated since their divergence strongly suggest that SARS-CoV-2 evolved in a host cellular environment highly similar to that of bats before its zoonotic transfer into humans. Collectively, our findings provide data-driven support for the natural origin of SARS-CoV-2.

•

The asymmetric de novo mutations in SARS-CoV-2 are induced by mutagenic mechanisms in the host cellular environment

•

De novo mutations determine the molecular spectrum of accumulated mutations during SARS-CoV-2 evolution

•

Molecular spectra of accumulated mutations in betacoronaviruses cluster according to the host species instead of the phylogenetic relationship

•

The mutations accumulated in SARS-CoV-2 prior to its transmission to humans are consistent with an evolutionary process in a bat host

Machine-learning algorithms predict breast cancer patient survival from UK Biobank whole-exome sequencing data

Aim: We tested whether machine-learning algorithm could find biomarkers predicting overall survival in breast cancer patients using blood-based whole-exome sequencing data. Materials & methods: Whole-exome sequencing data derived from 1181 female breast cancer patients within the UK Biobank was collected. We found feature genes (n = 50) regarding total mutation burden using the long short-term memory model. Then, we developed the XGBoost survival model with selected feature genes. Results: The XGBoost survival model performed acceptably, with a concordance index of 0.75 and a scaled Brier score of 0.146 in terms of overall survival prediction. The high-mutation group exhibited inferior overall survival compared with the low-mutation group in patients ≥56 years (log-rank test, p = 0.042). Conclusion: We showed that machine-learning algorithms can be used to predict overall survival in breast cancer patients from blood-based whole-exome sequencing data.

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

Cells with Cancer-associated Mutations Overtake Our Tissues as We Age

BACKGROUND

To shed light on the earliest events in oncogenesis, there is growing interest in understanding the mutational landscapes of normal tissues across ages. In the last decade, next-generation sequencing of human tissues has revealed a surprising abundance of cells with what would be considered oncogenic mutations.

AIMS

We performed meta-analysis on previously published sequencing data on normal tissues to categorize mutations based on their presence in cancer and showcase the quantity of cells with cancer-associated mutations in cancer-free individuals.

METHODS AND RESULTS

We analyzed sequencing data from these studies of normal tissues to determine the prevalence of cells with mutations in three different categories across multiple age groups: 1) mutations in genes designated as drivers, 2) mutations that are in the Cancer Gene Census (CGC), and 3) mutations in the CGC that are considered pathogenic. As we age, the percentage of cells in all three levels increase significantly, reaching over 50% of cells having oncogenic mutations for multiple tissues in the older age groups. The clear enrichment for these mutations, particularly at older ages, likely indicates strong selection for the resulting phenotypes. Combined with an estimation of the number of cells in tissues, we calculate that most older, cancer-free individuals possess at least a 100 billion cells that harbor at least one oncogenic mutation, presumably emanating from a fitness advantage conferred by these mutations that promotes clonal expansion.

CONCLUSIONS

These studies of normal tissues have highlighted the specific drivers of clonal expansion and how frequently they appear in us. Their high prevalence throughout cancer-free individuals necessitates reconsideration of the oncogenicity of these mutations, which could shape methods of detection, prevention and treatment of cancer, as well as of the potential impact of these mutations on tissue function and our health.