Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench ("wet bench") and data analyses conducted using bioinformatics pipelines ("dry bench"). Both elements are essential to produce accurate and reliable results, which are particularly critical for clinical laboratories. Targeted NGS technologies have increasingly found favor in oncology applications to help advance precision medicine objectives, yet the methods often involve disconnected and variable wet and dry bench workflows and uncoordinated reagent sets. In this report, we describe a method for sequencing challenging cancer specimens with a 21-gene panel as an example of a comprehensive targeted NGS system. The system integrates functional DNA quantification and qualification, single-tube multiplexed PCR enrichment, and library purification and normalization using analytically-verified, single-source reagents with a standalone bioinformatics suite. As a result, accurate variant calls from low-quality and low-quantity formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration (FNA) tumor biopsies can be achieved. The method can routinely assess cancer-associated variants from an input of 400 amplifiable DNA copies, and is modular in design to accommodate new gene content. Two different types of analytically-defined controls provide quality assurance and help safeguard call accuracy with clinically-relevant samples. A flexible "tag" PCR step embeds platform-specific adaptors and index codes to allow sample barcoding and compatibility with common benchtop NGS instruments. Importantly, the protocol is streamlined and can produce 24 sequence-ready libraries in a single day. Finally, the approach links wet and dry bench processes by incorporating pre-analytical sample quality control results directly into the variant calling algorithms to improve mutation detection accuracy and differentiate false-negative and indeterminate calls. This targeted NGS method uses advances in both wetware and software to achieve high-depth, multiplexed sequencing and sensitive analysis of heterogeneous cancer samples for diagnostic applications.     

Next-Generation Sequencing-Based HPV Genotyping Assay Validated in Formalin-Fixed,Paraffin-Embedded Oropharyngeal and Cervical Cancer Specimens

Available clinical human papilloma virus (HPV) diagnostics for head and neck cancer have limited sensitivity and/or fail to define the HPV genotype. Common HPV genotyping assays are costly and labor intensive. We sought to develop a next-generation sequencing (NGS)-based HPV genotyping assay that was sensitive enough to work on formalin-fixed paraffin-embedded (FFPE) samples. We developed an ion torrent NGS HPV genotyping assay using barcoded HPV PCR broad-spectrum general primers 5⁺/6⁺ (BSGP)5⁺/6⁺. To validate genotype specificity and use in archived clinical FFPE tumor samples, we compared NGS HPV genotyping at 2 sequencing centers with typing by Roche Linear Array assay in 42 oropharyngeal and cervical cancer specimens representing 10 HPV genotypes, as well as HPV-negative cases. To demonstrate the detection of a broad range of HPV genotypes, we genotyped a cohort of 266 cervical cancers. A comparison of NGS genotyping of FFPE cancer specimens with genotyping by Linear Array showed concordant results in 34/37 samples (92%) at sequencing site 1 and 39/42 samples (93%) at sequencing site 2. Concordance between sites was 92%. Designed for use with 10 ng genomic DNA, the assay detected HPV using as little as 1.25 ng FFPE-derived genomic DNA. In 266 cervical cancer specimens, the NGS assay identified 20 different HPV genotypes, including all 13 carcinogenic genotypes. This novel NGS assay provides a sensitive and specific high-throughput method to detect and genotype HPV in a range of clinical specimens derived from FFPE with low per-sample cost.     

Targeted Next Generation Sequencing as a Reliable Diagnostic Assay for the Detection of Somatic Mutations in Tumours Using Minimal DNA Amounts from Formalin Fixed Paraffin Embedded Material

Background

Targeted Next Generation Sequencing (NGS) offers a way to implement testing of multiple genetic aberrations in diagnostic pathology practice, which is necessary for personalized cancer treatment. However, no standards regarding input material have been defined. This study therefore aimed to determine the effect of the type of input material (e.g. formalin fixed paraffin embedded (FFPE) versus fresh frozen (FF) tissue) on NGS derived results. Moreover, this study aimed to explore a standardized analysis pipeline to support consistent clinical decision-making.

Method

We used the Ion Torrent PGM sequencing platform in combination with the Ion AmpliSeq Cancer Hotspot Panel v2 to sequence frequently mutated regions in 50 cancer related genes, and validated the NGS detected variants in 250 FFPE samples using standard diagnostic assays. Next, 386 tumour samples were sequenced to explore the effect of input material on variant detection variables. For variant calling, Ion Torrent analysis software was supplemented with additional variant annotation and filtering.

Results

Both FFPE and FF tissue could be sequenced reliably with a sensitivity of 99.1%. Validation showed a 98.5% concordance between NGS and conventional sequencing techniques, where NGS provided both the advantage of low input DNA concentration and the detection of low-frequency variants. The reliability of mutation analysis could be further improved with manual inspection of sequence data.

Conclusion

Targeted NGS can be reliably implemented in cancer diagnostics using both FFPE and FF tissue when using appropriate analysis settings, even with low input DNA.     

multiSNV: a probabilistic approach for improving detection of somatic point mutations from multiple related tumour samples

Somatic variant analysis of a tumour sample and its matched normal has been widely used in cancer research to distinguish germline polymorphisms from somatic mutations. However, due to the extensive intratumour heterogeneity of cancer, sequencing data from a single tumour sample may greatly underestimate the overall mutational landscape. In recent studies, multiple spatially or temporally separated tumour samples from the same patient were sequenced to identify the regional distribution of somatic mutations and study intratumour heterogeneity. There are a number of tools to perform somatic variant calling from matched tumour-normal next-generation sequencing (NGS) data; however none of these allow joint analysis of multiple same-patient samples. We discuss the benefits and challenges of multisample somatic variant calling and present multiSNV, a software package for calling single nucleotide variants (SNVs) using NGS data from multiple same-patient samples. Instead of performing multiple pairwise analyses of a single tumour sample and a matched normal, multiSNV jointly considers all available samples under a Bayesian framework to increase sensitivity of calling shared SNVs. By leveraging information from all available samples, multiSNV is able to detect rare mutations with variant allele frequencies down to 3% from whole-exome sequencing experiments.     

Detailed evaluation of cancer sequencing pipelines in different microenvironments and heterogeneity levels

The importance of next generation sequencing (NGS) rises in cancer research as accessing this key technology becomes easier for researchers. The sequence data created by NGS technologies must be processed by various bioinformatics algorithms within a pipeline in order to convert raw data to meaningful information. Mapping and variant calling are the two main steps of these analysis pipelines, and many algorithms are available for these steps. Therefore, detailed benchmarking of these algorithms in different scenarios is crucial for the efficient utilization of sequencing technologies. In this study, we compared the performance of twelve pipelines (three mapping and four variant discovery algorithms) with recommended settings to capture single nucleotide variants. We observed significant discrepancy in variant calls among tested pipelines for different heterogeneity levels in real and simulated samples with overall high specificity and low sensitivity. Additional to the individual evaluation of pipelines, we also constructed and tested the performance of pipeline combinations. In these analyses, we observed that certain pipelines complement each other much better than others and display superior performance than individual pipelines. This suggests that adhering to a single pipeline is not optimal for cancer sequencing analysis and sample heterogeneity should be considered in algorithm optimization.     

Paired analysis of tumor mutation burden calculated by targeted deep sequencing panel and whole exome sequencing in non-small cell lung cancer

Owing to rapid advancements in NGS (next generation sequen-cing), genomic alteration is now considered an essential pre-dictive biomarkers that impact the treatment decision in many cases of cancer. Among the various predictive biomarkers, tumor mutation burden (TMB) was identified by NGS and was con-sidered to be useful in predicting a clinical response in cancer cases treated by immunotherapy. In this study, we directly com-pared the lab-developed-test (LDT) results by target sequencing panel, K-MASTER panel v3.0 and whole-exome sequencing (WES) to evaluate the concordance of TMB. As an initial step, the reference materials (n = 3) with known TMB status were used as an exploratory test. To validate and evaluate TMB, we used one hundred samples that were acquired from surgically resected tissues of non-small cell lung cancer (NSCLC) patients. The TMB of each sample was tested by using both LDT and WES methods, which extracted the DNA from samples at the same time. In addition, we evaluated the impact of capture re-gion, which might lead to different values of TMB; the evalu-ation of capture region was based on the size of NGS and target sequencing panels. In this pilot study, TMB was evalu-ated by LDT and WES by using duplicated reference samples; the results of TMB showed high concordance rate (R² = 0.887). This was also reflected in clinical samples (n = 100), which showed R² of 0.71. The difference between the coding sequence ratio (3.49%) and the ratio of mutations (4.8%) indicated that the LDT panel identified a relatively higher number of mutations. It was feasible to calculate TMB with LDT panel, which can be useful in clinical practice. Furthermore, a customized approach must be developed for calculating TMB, which differs according to cancer types and specific clinical settings.     

PCR-Free Enrichment of Mitochondrial DNA from Human Blood and Cell Lines for High Quality Next-Generation DNA Sequencing

Recent advances in sequencing technology allow for accurate detection of mitochondrial sequence variants, even those in low abundance at heteroplasmic sites. Considerable sequencing cost savings can be achieved by enriching samples for mitochondrial (relative to nuclear) DNA. Reduction in nuclear DNA (nDNA) content can also help to avoid false positive variants resulting from nuclear mitochondrial sequences (numts). We isolate intact mitochondrial organelles from both human cell lines and blood components using two separate methods: a magnetic bead binding protocol and differential centrifugation. DNA is extracted and further enriched for mitochondrial DNA (mtDNA) by an enzyme digest. Only 1 ng of the purified DNA is necessary for library preparation and next generation sequence (NGS) analysis. Enrichment methods are assessed and compared using mtDNA (versus nDNA) content as a metric, measured by using real-time quantitative PCR and NGS read analysis. Among the various strategies examined, the optimal is differential centrifugation isolation followed by exonuclease digest. This strategy yields >35% mtDNA reads in blood and cell lines, which corresponds to hundreds-fold enrichment over baseline. The strategy also avoids false variant calls that, as we show, can be induced by the long-range PCR approaches that are the current standard in enrichment procedures. This optimization procedure allows mtDNA enrichment for efficient and accurate massively parallel sequencing, enabling NGS from samples with small amounts of starting material. This will decrease costs by increasing the number of samples that may be multiplexed, ultimately facilitating efforts to better understand mitochondria-related diseases.     

Amplicon Sequencing of Colorectal Cancer: Variant Calling in Frozen and Formalin-Fixed Samples

Next generation sequencing (NGS) is an emerging technology becoming relevant for genotyping of clinical samples. Here, we assessed the stability of amplicon sequencing from formalin-fixed paraffin-embedded (FFPE) and paired frozen samples from colorectal cancer metastases with different analysis pipelines. 212 amplicon regions in 48 cancer related genes were sequenced with Illumina MiSeq using DNA isolated from resection specimens from 17 patients with colorectal cancer liver metastases. From ten of these patients, paired fresh frozen and routinely processed FFPE tissue was available for comparative study. Sample quality of FFPE tissues was determined by the amount of amplifiable DNA using qPCR, sequencing libraries were evaluated using Bioanalyzer. Three bioinformatic pipelines were compared for analysis of amplicon sequencing data. Selected hot spot mutations were reviewed using Sanger sequencing. In the sequenced samples from 16 patients, 29 non-synonymous coding mutations were identified in eleven genes. Most frequent were mutations in TP53 (10), APC (7), PIK3CA (3) and KRAS (2). A high concordance of FFPE and paired frozen tissue samples was observed in ten matched samples, revealing 21 identical mutation calls and only two mutations differing. Comparison of these results with two other commonly used variant calling tools, however, showed high discrepancies. Hence, amplicon sequencing can potentially be used to identify hot spot mutations in colorectal cancer metastases in frozen and FFPE tissue. However, remarkable differences exist among results of different variant calling tools, which are not only related to DNA sample quality. Our study highlights the need for standardization and benchmarking of variant calling pipelines, which will be required for translational and clinical applications.     

Bacterial Community and Diversity from the Watermelon Cultivated Soils through Next Generation Sequencing Approach

Knowledge and better understanding of functions of the microbial community are pivotal for crop management. This study was conducted to study bacterial structures including Acidovorax species community structures and diversity from the watermelon cultivated soils in different regions of South Korea. In this study, soil samples were collected from watermelon cultivation areas from various places of South Korea and microbiome analysis was performed to analyze bacterial communities including Acidovorax species community. Next generation sequencing (NGS) was performed by extracting genomic DNA from 92 soil samples from 8 different provinces using a fast genomic DNA extraction kit. NGS data analysis results revealed that, total, 39,367 operational taxonomic unit (OTU), were obtained. NGS data results revealed that, most dominant phylum in all the soil samples was Proteobacteria (37.3%). In addition, most abundant genus was Acidobacterium (1.8%) in all the samples. In order to analyze species diversity among the collected soil samples, OTUs, community diversity, and Shannon index were measured. Shannon (9.297) and inverse Simpson (0.996) were found to have the highest diversity scores in the greenhouse soil sample of Gyeonggi-do province (GG4). Results from NGS sequencing suggest that, most of the soil samples consists of similar trend of bacterial community and diversity. Environmental factors play a key role in shaping the bacterial community and diversity. In order to address this statement, further correlation analysis between soil physical and chemical parameters with dominant bacterial community will be carried out to observe their interactions.     

Next-generation sequencing for cancer diagnostics: a practical perspective

Next-generation sequencing (NGS) is arguably one of the most significant technological advances in the biological sciences of the last 30 years. The second generation sequencing platforms have advanced rapidly to the point that several genomes can now be sequenced simultaneously in a single instrument run in under two weeks. Targeted DNA enrichment methods allow even higher genome throughput at a reduced cost per sample. Medical research has embraced the technology and the cancer field is at the forefront of these efforts given the genetic aspects of the disease. World-wide efforts to catalogue mutations in multiple cancer types are underway and this is likely to lead to new discoveries that will be translated to new diagnostic, prognostic and therapeutic targets. NGS is now maturing to the point where it is being considered by many laboratories for routine diagnostic use. The sensitivity, speed and reduced cost per sample make it a highly attractive platform compared to other sequencing modalities. Moreover, as we identify more genetic determinants of cancer there is a greater need to adopt multi-gene assays that can quickly and reliably sequence complete genes from individual patient samples. Whilst widespread and routine use of whole genome sequencing is likely to be a few years away, there are immediate opportunities to implement NGS for clinical use. Here we review the technology, methods and applications that can be immediately considered and some of the challenges that lie ahead.     

Identification of canine circulating miRNAs as tumor biospecific markers using Next-Generation Sequencing and Q-RT-PCR

Delay in cancer diagnosis often results in metastasis and an inability to successfully treat the tumor. The use of broadly cancer-specific biomarkers at an early stage may improve cancer treatment and staging. This study has explored circulatory exosomal miRNAs as potential diagnostic biomarkers to identify cancer patients. Secretory exosomal miRNAs were isolated from 13 canine cancer cell lines (lymphoma, mast cell tumor, histiocytic cell line, osteosarcoma, melanoma, and breast tumor) and were sequenced by Next-Generation sequencing (NGS). We have identified 6 miRNAs (cfa-miR-9, -1841, ?1306, ?345, ?132, and ?26b) by NGS that were elevated in all cancer cell types. The miRNAs identified by NGS were then examined by Q-RT-PCR. The PCR data demonstrated similar expression patterns to those seen with NGS but provided fold differences that were much lower than those seen for NGS. Cfa-miR-9 was found to be the most consistently elevated miRNA in NGS and PCR, making it the most likely miRNA to prove diagnostic. In this study, we have demonstrated that it is possible to identify exosomal miRNAs with elevated secretion across multiple tumor types that could be used as circulatory diagnostic biomarkers for liquid biopsy in the future.     

Complex Mutations & Subpopulations of Deletions at Exon 19 of EGFR in NSCLC Revealed by Next Generation Sequencing: Potential Clinical Implications

Microdeletions at exon 19 are the most frequent genetic alterations affecting the Epidermal Growth Factor Receptor (EGFR) gene in non-small cell lung cancer (NSCLC) and they are strongly associated with response to treatment with tyrosine kinase inhibitors. A series of 116 NSCLC DNA samples investigated by Sanger Sequencing (SS), including 106 samples carrying exon 19 EGFR deletions and 10 without deletions (control samples), were subjected to deep next generation sequencing (NGS). All samples with deletions at SS showed deletions with NGS. No deletions were seen in control cases. In 93 (88%) cases, deletions detected by NGS were exactly corresponding to those identified by SS. In 13 cases (12%) NGS resolved deletions not accurately characterized by SS. In 21 (20%) cases the NGS showed presence of complex (double/multiple) frameshift deletions producing a net in-frame change. In 5 of these cases the SS could not define the exact sequence of mutant alleles, in the other 16 cases the results obtained by SS were conventionally considered as deletions plus insertions. Different interpretative hypotheses for complex mutations are discussed. In 46 (43%) tumors deep NGS showed, for the first time to our knowledge, subpopulations of DNA molecules carrying EGFR deletions different from the main one. Each of these subpopulations accounted for 0.1% to 17% of the genomic DNA in the different tumors investigated. Our findings suggest that a region in exon 19 is highly unstable in a large proportion of patients carrying EGFR deletions. As a corollary to this study, NGS data were compared with those obtained by immunohistochemistry using the 6B6 anti-mutant EGFR antibody. The immunoreaction was E746-A750del specific. In conclusion, NGS analysis of EGFR exon 19 in NSCLCs allowed us to formulate a new interpretative hypothesis for complex mutations and revealed the presence of subpopulations of deletions with potential pathogenetic and clinical impact.     

When to use next generation sequencing or diagnostic PCR in diet analyses

Next‐generation sequencing (NGS) is increasingly used for diet analyses; however, it may not always describe diet samples well. A reason for this is that diet samples contain mixtures of food DNA in different amounts as well as consumer DNA which can reduce the food DNA characterized. Because of this, detections will depend on the relative amount and identity of each type of DNA. For such samples, diagnostic PCR will most likely give more reliable results, as detection probability is only marginally dependent on other copresent DNA. We investigated the reliability of each method to test (a) whether predatory beetle regurgitates, supposed to be low in consumer DNA, allow to retrieve prey sequences using general barcoding primers that co‐amplify the consumer DNA, and (b) to assess the sequencing depth or replication needed for NGS and diagnostic PCR to give stable results. When consumer DNA is co‐amplified, NGS is better suited to discover the range of possible prey, than for comparing co‐occurrences of diet species between samples, as retested samples were repeatedly different in prey detections with this approach. This shows that samples were incompletely described, as prey detected by diagnostic PCR frequently were missed by NGS. As the sequencing depth needed to reliably describe the diet in such samples becomes very high, the cost‐efficiency and reliability of diagnostic PCR make diagnostic PCR better suited for testing large sample‐sets. Especially if the targeted prey taxa are thought to be of ecological importance, as diagnostic PCR gave more nested and consistent results in repeated testing of the same sample.     

SeqSQC: A Bioconductor Package for Evaluating the Sample Quality of Next-generation Sequencing Data

As next-generation sequencing (NGS) technology has become widely used to identify genetic causal variants for various diseases and traits,a number of packages for checking NGS data quality have sprung up in public domains. In addition to the quality of sequencing data,sample quality issues,such as gender mismatch,abnormal inbreeding coefficient,cryptic relatedness,and population outliers,can also have fundamental impact on downstream analysis. However,there is a lack of tools specialized in identifying problematic samples from NGS data,often due to the limitation of sample size and variant counts. We developed SeqSQC,a Bioconductor package,to automate and accelerate sample cleaning in NGS data of any scale. SeqSQC is designed for efficient data storage and access,and equipped with interactive plots for intuitive data visualization to expedite the identification of problematic samples. SeqSQC is available at http://bioconductor. org/packages/SeqSQC.     

Next-generation teaching: a template for bringing genomic and bioinformatic tools into the classroom

The recent increase in accessibility and scale of genetic data available through next-generation sequencing (NGS) technology has transformed biological inquiry. As a direct result, the application and analysis of NGS data has quickly become an important skill for future scientists. However, the steep learning curve for applying NGS technology to biological questions, including the complexity of sample preparation for sequencing and the analysis of large data sets, are deterrents to the integration of NGS into undergraduate education. Here, we present a course-based undergraduate research experience (CURE) designed to aid in overcoming these limitations through NGS investigations of prokaryotic diversity. Specifically, we use 16S rRNA sequencing to explore patterns of diversity stemming from student-directed hypothesis development. This CURE addresses three learning objectives: (1) it provides a forum for experimental design hypothesis generation, (2) it introduces modern genomic tools through a hands-on experience generating an NGS data-set, and (3) it provides students with an introductory experience in bioinformatics.     

Measuring KRAS Mutations in Circulating Tumor DNA by Droplet Digital PCR and Next-Generation Sequencing

Measuring total cell-free DNA (cfDNA) or cancer-specific mutations herein has presented as new tools in aiding the treatment of cancer patients. Studies show that total cfDNA bears prognostic value in metastatic colorectal cancer (mCRC) and that measuring cancer-specific mutations could supplement biopsies. However, limited information is available on the performance of different methods. Blood samples from 28 patients with mCRC and known KRAS mutation status were included. cfDNA was extracted and quantified with droplet digital polymerase chain reaction (ddPCR) measuring Beta-2 Microglobulin. KRAS mutation detection was performed using ddPCR (Bio-Rad) and next-generation sequencing (NGS, Ion Torrent PGM). Comparing KRAS mutation status in plasma and tissue revealed concordance rates of 79% and 89% for NGS and ddPCR. Strong correlation between the methods was observed. Most KRAS mutations were also detectable in 10-fold diluted samples using the ddPCR. We find that for detection of KRAS mutations in ctDNA ddPCR was superior to NGS both in analysis success rate and concordance to tissue. We further present results indicating that lower amount of plasma may be used for detection of KRAS mutations in mCRC.     

Comparative results of preimplantation genetic screening by array comparative genomic hybridization and new-generation sequencing

Aneuploidies as quantitative chromosome abnormalities are a main cause of failed development of morphologically normal embryos, implantation failures, and early reproductive losses. Preimplantation genetic screening (PGS) allows a preselection of embryos with a normal karyotype, thus increasing the implantation rate and reducing the frequency of early pregnancy loss after IVF. Modern PGS technologies are based on a genome-wide analysis of the embryo. The first pilot study in Russia was performed to assess the possibility of using semiconductor new-generation sequencing (NGS) as a PGS method. NGS data were collected for 38 biopsied embryos and compared with the data from array comparative genomic hybridization (array-CGH). The concordance between the NGS and array-CGH data was 94.8%. Two samples showed the karyotype 47,XXY by array-CGH and a normal karyotype by NGS. The discrepancies may be explained by loss of efficiency of array-CGH amplicon labeling.     

Recent novel approaches for population genomics data analysis

Next‐generation sequencing (NGS) technology is revolutionizing the fields of population genetics, molecular ecology and conservation biology. But it can be challenging for researchers to learn the new and rapidly evolving techniques required to use NGS data. A recent workshop entitled ‘Population Genomic Data Analysis’ was held to provide training in conceptual and practical aspects of data production and analysis for population genomics, with an emphasis on NGS data analysis. This workshop brought together 16 instructors who were experts in the field of population genomics and 31 student participants. Instructors provided helpful and often entertaining advice regarding how to choose and use a NGS method for a given research question, and regarding critical aspects of NGS data production and analysis such as library preparation, filtering to remove sequencing errors and outlier loci, and genotype calling. In addition, instructors provided general advice about how to approach population genomics data analysis and how to build a career in science. The overarching messages of the workshop were that NGS data analysis should be approached with a keen understanding of the theoretical models underlying the analyses, and with analyses tailored to each research question and project. When analysed carefully, NGS data provide extremely powerful tools for answering crucial questions in disciplines ranging from evolution and ecology to conservation and agriculture, including questions that could not be answered prior to the development of NGS technology.     

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.