VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.     

Targeted gene therapies: tools, applications, optimization

Many devastating human diseases are caused by mutations in a single gene that prevent a somatic cell from carrying out its essential functions, or by genetic changes acquired as a result of infectious disease or in the course of cell transformation. Targeted gene therapies have emerged as potential strategies for treatment of such diseases. These therapies depend upon rare-cutting endonucleases to cleave at specific sites in or near disease genes. Targeted gene correction provides a template for homology-directed repair, enabling the cell's own repair pathways to erase the mutation and replace it with the correct sequence. Targeted gene disruption ablates the disease gene, disabling its function. Gene targeting can also promote other kinds of genome engineering, including mutation, insertion, or gene deletion. Targeted gene therapies present significant advantages compared to approaches to gene therapy that depend upon delivery of stably expressing transgenes. Recent progress has been fueled by advances in nuclease discovery and design, and by new strategies that maximize efficiency of targeting and minimize off-target damage. Future progress will build on deeper mechanistic understanding of critical factors and pathways.     

Highly efficient proteolysis accelerated by electromagnetic waves for Peptide mapping

Proteomics will contribute greatly to the understanding of gene functions in the post-genomic era. In proteome research, protein digestion is a key procedure prior to mass spectrometry identification. During the past decade, a variety of electromagnetic waves have been employed to accelerate proteolysis. This review focuses on the recent advances and the key strategies of these novel proteolysis approaches for digesting and identifying proteins. The subjects covered include microwave-accelerated protein digestion, infrared-assisted proteolysis, ultraviolet-enhanced protein digestion, laser-assisted proteolysis, and future prospects. It is expected that these novel proteolysis strategies accelerated by various electromagnetic waves will become powerful tools in proteome research and will find wide applications in high throughput protein digestion and identification.     

Targeted massive parallel sequencing: the effective detection of novel causative mutations associated with hearing loss in small families

ABSTRACT: BACKGROUND: Hereditary hearing loss is one of the most common heterogeneous disorders, and genetic variants that can cause hearing loss have been identified in over fifty genes. Most of these hearing loss genes have been detected using classical genetic methods, typically starting with linkage analysis in large families with hereditary hearing loss. However, these classical strategies are not well suited for mutation analysis in smaller families who have insufficient genetic information. METHODS: Eighty known hearing loss genes were selected and simultaneously sequenced by targeted next-generation sequencing (NGS) in 8 Korean families with autosomal dominant non-syndromic sensorineural hearing loss. RESULTS: Five mutations in known hearing loss genes, including 1 nonsense and 4 missense mutations, were identified in 5 different genes (ACTG1, MYO1F, DIAPH1, POU4F3 and EYA4), and the genotypes for these mutations were consistent with the autosomal dominant inheritance pattern of hearing loss in each family. No mutational hot-spots were revealed in these Korean families. CONCLUSION: Targeted NGS allowed for the detection of pathogenic mutations in affected individuals who were not candidates for classical genetic studies. This report is the first documenting the effective use of an NGS technique to detect pathogenic mutations that underlie hearing loss in an East Asian population. Using this NGS technique to establish a database of common mutations in Korean patients with hearing loss and further data accumulation will contribute to the early diagnosis and fundamental therapies for hereditary hearing loss.     

Hedgehog signaling in skin cancers

An increasing progress on the role of Hedgehog (Hh) signaling for carcinogenesis has been achieved since the link of Hh pathway to human cancer was firstly established. In particular, the critical role of Hh signaling in the development of Basal cell carcinoma (BCC) has been convincingly demonstrated by genetic mutation analyses, mouse models of BCCs, and successful clinical trials of BCCs using Hh signaling inhibitors. In addition, the Hh pathway activity is also reported to be involved in the pathogenesis of Squamous Cell Carcinoma (SCC), melanoma and Merkel Cell Carcinoma. These findings have significant new paradigm on Hh signaling transduction, its mechanisms in skin cancer and even therapeutic approaches for BCC. In this review, we will summarize the major advances in the understanding of Hh signaling transduction, the roles of Hh signaling in skin cancer development, and the current implications of “mechanism-based” therapeutic strategies.     

Confidence-based Somatic Mutation Evaluation and Prioritization

Next generation sequencing (NGS) has enabled high throughput discovery of somatic mutations. Detection depends on experimental design, lab platforms, parameters and analysis algorithms. However, NGS-based somatic mutation detection is prone to erroneous calls, with reported validation rates near 54% and congruence between algorithms less than 50%. Here, we developed an algorithm to assign a single statistic, a false discovery rate (FDR), to each somatic mutation identified by NGS. This FDR confidence value accurately discriminates true mutations from erroneous calls. Using sequencing data generated from triplicate exome profiling of C57BL/6 mice and B16-F10 melanoma cells, we used the existing algorithms GATK, SAMtools and SomaticSNiPer to identify somatic mutations. For each identified mutation, our algorithm assigned an FDR. We selected 139 mutations for validation, including 50 somatic mutations assigned a low FDR (high confidence) and 44 mutations assigned a high FDR (low confidence). All of the high confidence somatic mutations validated (50 of 50), none of the 44 low confidence somatic mutations validated, and 15 of 45 mutations with an intermediate FDR validated. Furthermore, the assignment of a single FDR to individual mutations enables statistical comparisons of lab and computation methodologies, including ROC curves and AUC metrics. Using the HiSeq 2000, single end 50 nt reads from replicates generate the highest confidence somatic mutation call set.     

Targeted gene therapies: tools,applications, optimization

Many devastating human diseases are caused by mutations in a single gene that prevent a somatic cell from carrying out its essential functions, or by genetic changes acquired as a result of infectious disease or in the course of cell transformation. Targeted gene therapies have emerged as potential strategies for treatment of such diseases. These therapies depend upon rare-cutting endonucleases to cleave at specific sites in or near disease genes. Targeted gene correction provides a template for homology-directed repair, enabling the cell’s own repair pathways to erase the mutation and replace it with the correct sequence. Targeted gene disruption ablates the disease gene, disabling its function. Gene targeting can also promote other kinds of genome engineering, including mutation, insertion, or gene deletion. Targeted gene therapies present significant advantages compared to approaches to gene therapy that depend upon delivery of stably expressing transgenes. Recent progress has been fueled by advances in nuclease discovery and design, and by new strategies that maximize efficiency of targeting and minimize off-target damage. Future progress will build on deeper mechanistic understanding of critical factors and pathways.     

Implications of disease-related mutations at protein–protein interfaces

Protein–protein interfaces have been attracting great attention owing to their critical roles in protein–protein interactions and the fact that human disease-related mutations are generally enriched in them. Recently, substantial research progress has been made in this field, which has significantly promoted the understanding and treatment of various human diseases. For example, many studies have discovered the properties of disease-related mutations. Besides, as more large-scale experimental data become available, various computational approaches have been proposed to advance our understanding of disease mutations from the data. Here, we overview recent advances in characteristics of disease-related mutations at protein–protein interfaces, mutation effects on protein interactions, and investigation of mutations on specific diseases.     

Genetic mutation analysis at early stages of cell line development using next generation sequencing

A central goal for most biopharmaceutical companies is to reduce the development timeline to reach clinical proof of concept. This objective requires the development of tools that ensure the quality of biotherapeutic material destined for the clinic. Recent advances in high throughput protein analytics provide confidence in our ability to assess productivity and product quality attributes at early stages of cell line development. However, one quality attribute has, until recently, been absent from the standard battery of analytical tests facilitating informed choices early in cell line selection: genetic sequence confirmation. Techniques historically used for mutation analysis, such as detailed mass spectrometry, have limitations on the sample number and turnaround times making it less attractive at early stages. Thus, we explored the utility of Next‐Generation Sequencing (NGS) as a solution to address these limitations. Amplicon sequencing is one such NGS technique that is robust, rapid, sensitive, and amenable to multiplexing, all of which are essential attributes for our purposes. Here we report a NGS method based upon amplicon sequencing that has been successfully incorporated into our cell line development workflow alongside other high‐throughput protein analytical assays. The NGS method has demonstrated its value by identifying at least one Chinese hamster ovary (CHO) clone expressing a variant form of the biotherapeutic in each of the four clinical programs in which it has been utilized. We believe this sequence confirmation method is essential to safely accelerating the time to clinical proof of concept of biotherapeutics, and guard against delays related to sequence mutations. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:813–817, 2016     

A proliferative melanoma cell phenotype is responsive to RAF/MEK inhibition independent of BRAF mutation status

Oncogenic mutations within the MAPK pathway are frequent in melanoma, and targeting of MAPK signaling has yielded spectacular responses in a significant number of patients that last for several months before relapsing. We investigated the effects of two different inhibitors of MAPK signaling in proliferative and invasive melanoma cell cultures with various mutations in the MAPK pathway. Proliferative melanoma cells were more susceptible to pathway inhibition than invasive phenotype cells, irrespective of BRAF mutation status, while invasive phenotype cell response was dependent on BRAF mutation status. Critically, MAPK pathway inhibition of proliferative phenotype cells resulted in acquisition of invasive phenotype characteristics. These results show that melanoma cell phenotype is an important factor in MAPK pathway inhibition response. This suggests that while current therapeutic strategies target proliferative melanoma cells, future approaches should also account for the invasive phenotype population.     

Targeted next generation sequencing identifies clinically actionable mutations in patients with melanoma

Somatic sequencing of cancers has produced new insight into tumorigenesis, tumor heterogeneity, and disease progression, but the vast majority of genetic events identified are of indeterminate clinical significance. Here, we describe a NextGen sequencing approach to fully analyzing 248 genes, including all those of known clinical significance in melanoma. This strategy features solution capture of DNA followed by multiplexed, high‐throughput sequencing and was evaluated in 31 melanoma cell lines and 18 tumor tissues from patients with metastatic melanoma. Mutations in melanoma cell lines correlated with their sensitivity to corresponding small molecule inhibitors, confirming, for example, lapatinib sensitivity in ERBB4 mutant lines and identifying a novel activating mutation of BRAF. The latter event would not have been identified by clinical sequencing and was associated with responsiveness to a BRAF kinase inhibitor. This approach identified focal copy number changes of PTEN not found by standard methods, such as comparative genomic hybridization (CGH). Actionable mutations were found in 89% of the tumor tissues analyzed, 56% of which would not be identified by standard‐of‐care approaches. This work shows that targeted sequencing is an attractive approach for clinical use in melanoma.     

Combination of targeted therapy and immunotherapy in melanoma

The treatment of human melanoma has progressed markedly in recent years. Building on the observation that immune recognition is a frequent event in melanoma, a series of immunotherapeutic approaches have been evaluated in clinical trials, culminating in the first phase III study improving overall survival of melanoma patients since 20 years. However, the response rates seen upon immunotherapeutic interventions such as anti-CTLA4 treatment are often low. Furthermore, clinical responses can take several weeks to develop, during which time stage IV melanoma patients often deteriorate. Recent advances in our understanding of the genetic lesions in human melanoma now also allow the specific targeting of the signaling pathway alterations in this disease. Such targeted therapies can lead to high response rates, although the duration of these responses is thus far relatively short. We suggest that the combination of immuno and targeted therapy offers potential for synergy for both conceptual and practical reasons. In this review, we will discuss the potential and possible limitations for such combination therapy, and we describe the most promising combinations of targeted therapy and immunotherapy that can be tested in the clinic in the coming years. The concept of induction therapy by small molecule administration and consolidation by immunotherapeutics also has potential for the treatment of other human cancers.     

Cyclin‐dependent kinases as therapeutic targets in melanoma

Decades of scientific insights have led to a recent expansion of the therapeutic menu for melanoma. Despite these advances, the current targeted therapies and immune checkpoint agents continue to yield suboptimal response and cure rates. Hitherto, the most effective targeted therapy strategies have centered on effectors in the mitogen‐activated protein kinase (MAPK) pathway. This review focuses on the emerging evidence of combinatorial approaches targeting both MAPK signaling and dysregulations in cell‐cycle checkpoints. We discuss the prospects and limitations of utilizing strategies that promote cellular senescence, such as inhibition of the interphase cyclin‐dependent kinases (CDKs) and highlight the current state of CDK drug discovery in melanoma.     

Somatic mutations and aging: a re-evaluation

Aging has been explained in terms of an accumulation of mutations in the genome of somatic cells, leading to tissue atrophy and neoplasms, as well as increased loss of function. Recent advances in transgenic mouse modeling and genomics technology have created, for the first time, the opportunity to begin testing this theory. In this paper the existing evidence for a possible role of somatic mutation accumulation in aging will be re-evaluated on the basis of the evolutionary logic of aging and recent insights in genome structure and function. New strategies for investigating the relationship between genome instability, mutation accumulation and aging will be discussed.     

Genetics of colon cancer.

Strikingly rapid advances in the identification of genetic events that are important in colonic carcinogenesis have been made in the past several years. Specific inherited (adenomatous polyposis coli gene) and acquired (ras gene point mutations; c-myc gene amplification; allelic deletion at specific sites on chromosomes 5, 17, and 18) genetic abnormalities appear to be capable of mediating steps in the progression from normal to malignant colonic mucosa. Understanding these genetic factors and how they influence cellular function will have a profound effect on medical practice. High-risk populations will be (and are being) identified by genetic markers, thus allowing prevention and screening to be more precisely targeted to the population at risk; intervention strategies will be designed on the basis of the known cellular defects of neoplastic colonic mucosa; and new molecular preventive and therapeutic approaches can be developed.     

A new mutational mechanism for hypertrophic cardiomyopathy

We describe a male patient affected by hypertrophic cardiomyopathy (HCM) with no point mutations in the eight sarcomeric genes most commonly involved in the disease. By multiple ligation-dependent probe amplification (MLPA) we have identified a multi-exons C-terminus deletion in the cardiac myosin binding protein C (MYBPC3) gene. The rearrangement has been confirmed by long PCR and breakpoints have been defined by sequencing. The 3.5kb terminal deletion is mediated by Alu-repeat elements and is predicted to result in haploinsufficiency of MYBPC3. To exclude the presence of other rare pathogenic variants in additional HCM genes, we performed targeted next-generation sequencing (NGS) of 88 cardiomyopathy-associated genes but we did not identify any further mutation. Interestingly, the MYBPC3 multi-exons deletion was detectable by NGS. This finding broadens the range of mutational spectrum observed in HCM, contributing to understanding the genetic basis of the most common inherited cardiovascular disease. Moreover, our data suggest that NGS may represent a new tool to achieve a deeper insight into molecular basis of complex diseases, allowing to detect in a single experiment both point mutations and gene rearrangements.     

Direct mutation analysis by high-throughput sequencing: from germline to low-abundant, somatic variants

DNA mutations are the source of genetic variation within populations. The majority of mutations with observable effects are deleterious. In humans mutations in the germ line can cause genetic disease. In somatic cells multiple rounds of mutations and selection lead to cancer. The study of genetic variation has progressed rapidly since the completion of the draft sequence of the human genome. Recent advances in sequencing technology, most importantly the introduction of massively parallel sequencing (MPS), have resulted in more than a hundred-fold reduction in the time and cost required for sequencing nucleic acids. These improvements have greatly expanded the use of sequencing as a practical tool for mutation analysis. While in the past the high cost of sequencing limited mutation analysis to selectable markers or small forward mutation targets assumed to be representative for the genome overall, current platforms allow whole genome sequencing for less than $5000. This has already given rise to direct estimates of germline mutation rates in multiple organisms including humans by comparing whole genome sequences between parents and offspring. Here we present a brief history of the field of mutation research, with a focus on classical tools for the measurement of mutation rates. We then review MPS, how it is currently applied and the new insight into human and animal mutation frequencies and spectra that has been obtained from whole genome sequencing. While great progress has been made, we note that the single most important limitation of current MPS approaches for mutation analysis is the inability to address low-abundance mutations that turn somatic tissues into mosaics of cells. Such mutations are at the basis of intra-tumor heterogeneity, with important implications for clinical diagnosis, and could also contribute to somatic diseases other than cancer, including aging. Some possible approaches to gain access to low-abundance mutations are discussed, with a brief overview of new sequencing platforms that are currently waiting in the wings to advance this exploding field even further.     

Genetic risk factors for melanoma

The genetic basis of melanoma is complex and has both inherited and acquired components. Different genomic approaches have been used to identify a number of inherited risk factors, which can be stratified by penetrance and prevalence. Rare high-penetrance factors are expressed in familial clustering of melanoma and include mutations in CDKN2A (encoding p16^INK4a and p14^ARF) and CDK4. These genes are involved in cell-cycle arrest and melanocyte senescence and are nearly invariably targeted by somatic mutations during melanoma progression. Low-penetrance factors are common in the general population and include single-nucleotide polymorphisms in or near MC1R, ASIP, TYR and TYRP1. These genes are major determinants of hair and skin pigmentation, but their role in melanoma development remains unclear. This review describes the efforts that have led to the current understanding of melanoma susceptibility as the result of complex gene–gene and gene–environment interactions. Despite the significant advances, the majority of familial cases remain unaccounted for.     

Next‐generation sequencing (NGS)‐based identification of induced mutations in a doubly mutagenized tomato (Solanum lycopersicum) population

The identification of mutations in targeted genes has been significantly simplified by the advent of TILLING (Targeting Induced Local Lesions In Genomes), speeding up the functional genomic analysis of animals and plants. Next‐generation sequencing (NGS) is gradually replacing classical TILLING for mutation detection, as it allows the analysis of a large number of amplicons in short durations. The NGS approach was used to identify mutations in a population of Solanum lycopersicum (tomato) that was doubly mutagenized by ethylmethane sulphonate (EMS). Twenty‐five genes belonging to carotenoids and folate metabolism were PCR‐amplified and screened to identify potentially beneficial alleles. To augment efficiency, the 600‐bp amplicons were directly sequenced in a non‐overlapping manner in Illumina MiSeq, obviating the need for a fragmentation step before library preparation. A comparison of the different pooling depths revealed that heterozygous mutations could be identified up to 128‐fold pooling. An evaluation of six different software programs (camba , crisp , gatk unified genotyper , lofreq , snver and vipr ) revealed that no software program was robust enough to predict mutations with high fidelity. Among these, crisp and camba predicted mutations with lower false discovery rates. The false positives were largely eliminated by considering only mutations commonly predicted by two different software programs. The screening of 23.47 Mb of tomato genome yielded 75 predicted mutations, 64 of which were confirmed by Sanger sequencing with an average mutation density of 1/367 Kb. Our results indicate that NGS combined with multiple variant detection tools can reduce false positives and significantly speed up the mutation discovery rate.