Genome-wide Somatic Mutations Research Articles

Genome-wide somatic mutation analysis of sinonasal adenocarcinoma with and without wood dust exposure

BackgroundSinonasal adenocarcinoma is a rare cancer, encompassing two different entities, the intestinal-type sinonasal adenocarcinoma (ITAC) and the non-intestinal-type sinonasal adenocarcinoma (non-ITAC). Occurrence of ITAC is strongly associated with exposure to hardwood dusts. In countries with predominant exposure to softwood dust the occurrence of sinonasal adenocarcinomas is lower and the relative amount of non-ITACs to ITACs is higher. The molecular mechanisms behind the tumorigenic effects of wood dust remain largely unknown.MethodsWe carried out whole-genome sequencing of formalin-fixed paraffin-embedded (FFPE) samples of sinonasal adenocarcinomas from ten wood dust-exposed and six non-exposed individuals, with partial tobacco exposure data. Sequences were analyzed for the presence of mutational signatures matching COSMIC database signatures. Driver mutations and CN variant regions were characterized.ResultsMutation burden was higher in samples of wood dust-exposed patients (p = 0.016). Reactive oxygen species (ROS) damage-related mutational signatures were almost exclusively identified in ITAC subtype samples (p = 0.00055). Tobacco smoke mutational signatures were observed in samples of patients with tobacco exposure or missing information, but not in samples from non-exposed patients. A tetraploidy copy number (CN) signature was enriched in ITAC subtype (p = 0.042). CN variation included recurrent gains in COSMIC Cancer Gene Census genes TERT, SDHA, RAC1, ETV1, PCM1, and MYC. Pathogenic variants were observed most frequently in TP53, NF1, CHD2, BRAF, APC, and LRP1B. Driver mutations and copy number gains did not segregate by subtype.ConclusionsOur analysis identified distinct mutational characteristics in ITAC and non-ITAC. Mutational signature analysis may eventually become useful for documentation of occupation-related cancer, while the exact mechanisms behind wood dust-driven carcinogenesis remain elusive. The presence of homologous recombination deficiency signatures implies a novel opportunity for treatment, but further studies are needed.

Topical hidden genome: discovering latent cancer mutational topics using a Bayesian multilevel context-learning approach.

Inferring the cancer-type specificities of ultra-rare, genome-wide somatic mutations is an open problem. Traditional statistical methods cannot handle such data due to their ultra-high dimensionality and extreme data sparsity. To harness information in rare mutations, we have recently proposed a formal multilevel multilogistic "hidden genome" model. Through its hierarchical layers, the model condenses information in ultra-rare mutations through meta-features embodying mutation contexts to characterize cancer types. Consistent, scalable point estimation of the model can incorporate 10s of millions of variants across thousands of tumors and permit impressive prediction and attribution. However, principled statistical inference is infeasible due to the volume, correlation, and noninterpretability of mutation contexts. In this paper, we propose a novel framework that leverages topic models from computational linguistics to effectuate dimension reduction of mutation contexts producing interpretable, decorrelated meta-feature topics. We propose an efficient MCMC algorithm for implementation that permits rigorous full Bayesian inference at a scale that is orders of magnitude beyond the capability of existing out-of-the-box inferential high-dimensional multi-class regression methods and software. Applying our model to the Pan Cancer Analysis of Whole Genomes dataset reveals interesting biological insights including somatic mutational topics associated with UV exposure in skin cancer, aging in colorectal cancer, and strong influence of epigenome organization in liver cancer. Under cross-validation, our model demonstrates highly competitive predictive performance against blackbox methods of random forest and deep learning.

Reconstructing phylogenetic trees from genome-wide somatic mutations in clonal samples.

Phylogenetic trees are a powerful means to display the evolutionary history of species, pathogens and, more recently, individual cells of the human body. Whole-genome sequencing of laser capture microdissections or expanded stem cells has allowed the discovery of somatic mutations in clones, which can be used as natural barcodes to reconstruct the developmental history of individual cells. Here we describe Sequoia, our pipeline to reconstruct lineage trees from clones of normal cells. Candidate somatic mutations are called against the human reference genome and filtered to exclude germline mutations and artifactual variants. These filtered somatic mutations form the basis for phylogeny reconstruction using a maximum parsimony framework. Lastly, we use a maximum likelihood framework to explicitly map mutations to branches in the phylogenetic tree. The resulting phylogenies can then serve as a basis for many subsequent analyses, including investigating embryonic development, tissue dynamics in health and disease, and mutational signatures. Sequoia can be readily applied to any clonal somatic mutation dataset, including single-cell DNA sequencing datasets, using the commands and scripts provided. Moreover, Sequoia is highly flexible and can be easily customized. Typically, the runtime of the core script ranges from minutes to an hour for datasets with a moderate number (50,000-150,000) of variants. Competent bioinformatic skills, including in-depth knowledge of the R programming language, are required. A high-performance computing cluster (one that is capable of running mutation-calling algorithms and other aspects of the analysis at scale) is also required, especially if handling large datasets.

Genome-wide direct quantification of in vivo mutagenesis using high-accuracy paired-end and complementary consensus sequencing.

Error-corrected next-generation sequencing (ecNGS) is an emerging technology for accurately measuring somatic mutations. Here, we report paired-end and complementary consensus sequencing (PECC-Seq), a high-accuracy ecNGS approach for genome-wide somatic mutation detection. We characterize a novel 2-aminoimidazolone lesion besides 7,8-dihydro-8-oxoguanine and the resulting end-repair artifacts originating from NGS library preparation that obscure the sequencing accuracy of NGS. We modify library preparation protocol for the enzymatic removal of end-repair artifacts and improve the accuracy of our previously developed duplex consensus sequencing method. Optimized PECC-Seq shows an error rate of<5×10-8 with consensus bases compressed from approximately 25 Gb of raw sequencing data, enabling the accurate detection of low-abundance somatic mutations. We apply PECC-Seq to the quantification of in vivo mutagenesis. Compared with the classic gpt gene mutation assay using gpt delta transgenic mice, PECC-Seq exhibits high sensitivity in quantitatively measuring dose-dependent mutagenesis induced by Aristolochic acid I (AAI). Moreover, PECC-Seq specifically characterizes the distinct genome-wide mutational signatures of AAI, Benzo[a]pyrene, N-Nitroso-N-ethylurea and N-nitrosodiethylamine and reveals the mutational signature of Quinoline in common mouse models. Overall, our findings demonstrate that high-accuracy PECC-Seq is a promising tool for genome-wide somatic mutagenesis quantification and for invivo mutagenicity testing.

Genome-wide cfDNA Mutation Profiles Allow for Noninvasive Cancer Detection.

Low-coverage sequencing of genome-wide somatic mutations in cfDNA can noninvasively detect cancer.

Scrutiny of genome-wide somatic mutation profiles in centenarians identifies the key genomic regions for human longevity.

Somatic mutations accumulate with age and are associated closely with human health, their characterization in longevity cohorts remains largely unknown. Here, by analyzing whole genome somatic mutation profiles in 73 centenarians and 51 younger controls in China, we found that centenarian genomes are characterized by a markedly skewed distribution of somatic mutations, with many genomic regions being specifically conserved but displaying a high function potential. This, together with the observed more efficient DNA repair ability in the long-lived individuals, supports the existence of key genomic regions for human survival during aging, with their integrity being of essential to human longevity.

Whole genome sequencing for more accurate TMB and mutational signatures in common cancers.

e15173 Background: Due to the dramatic decrease in cost of genome sequencing, we are entering the era of whole genome sequencing (WGS) at $100. Tumor mutational burden (TMB) and mutational signatures have been introduced as potential prognostic/predictive cancer biomarkers and mostly assessed by targeted cancer gene sequencing panels. However, they are truly whole genome-wide events and thus more accurately estimated by whole genome sequencing data. Methods: We analyzed WGS data produced by Genome Insight Inc. that encompass &gt; 1,300 breast, lung, and hepatocellular carcinoma samples, collectively. Our genome-wide TMBs (wgsTMB) were systematically compared with the TMB estimates by targeted sequencing methods, such as conventional whole-exome sequencing (WES) and targeted panel sequencing from FoundationOne CDx (F1CDx). In parallel, we leveraged genome-wide somatic mutations for validating mutational signatures projected from the targeted sequencing methods. Results: Pembrolizumab is FDA approved for solid tumors with high TMB (≥ 10 mutations/Mb) assessed by F1CDx. This criterion classified that 546 of the tumors (41%) in our cohort as high F1CDx TMB (f1TMB), who may benefit from immunotherapy. However, the high f1TMB classification was inconsistent to the genome-wide TMB classification ( p &lt; 2.2e-16). For example, 132 high f1TMB tumors (24.1%; 132/546) showed lower than the median wgsTMB estimate. On the flip side, 32% of the low f1TMB tumors (251/784) demonstrate higher than median wgsTMB estimate (see table). Although there is no approved criterion in WGS that defines hypermutators, our data illustrates that WGS will be helpful for redefining the criteria for selecting patients for immune checkpoint inhibitors. The wgsTMB was also an essential factor for accurate estimation of mutational signatures from targeted sequencing. For example, in high TMB tumors, mutational signature estimated from WES showed on average 0.87 cosine similarity with signatures from WGS. However, the correlation was substantially reduced in low TMB tumors, showing only ~0.64 on average. Particularly, ~12% of breast tumors with considerable levels of homologous recombination deficiency (HRD) signatures by WGS were not captured by whole-exome sequencing based approaches. Further exploration should be performed with WGS to select proper patients for targeted therapies, including PARP inhibitors. Conclusions: Despite the current guidelines depending on targeted sequencing in precision oncology, we showed that whole-genome sequencing can deliver more accurate cancer genome profiles, such as, but not limited to, TMB and mutational signatures. Given its more comprehensive capabilities and affordable cost, we believe that WGS-based precision oncology is medically necessary. [Table: see text]

Single-neuron whole genome sequencing identifies increased somatic mutation burden in Alzheimer's disease related genes

Accumulation of somatic mutations in human neurons is associated with aging and neurodegeneration. To shed light on the somatic mutational burden in Alzheimer's disease (AD) neurons and get more insight into the role of somatic mutations in AD pathogenesis, we performed single-neuron whole genome sequencing to detect genome-wide somatic mutations (single nucleotide variants (SNVs) and Indels) in 96 single prefrontal cortex neurons from 8 AD patients and 8 elderly controls. We found that the mutational burden is ∼3000 somatic mutations per neuron genome in elderly subjects. AD patients have increased somatic mutation burden in AD-related annotation categories, including AD risk genes and differentially expressed genes in AD neurons. Mutational signature analysis showed somatic SNVs (sSNVs) primarily caused by aging and oxidative DNA damage processes but no significant difference was detected between AD and controls. Additionally, functional somatic mutations identified in AD patients showed significant enrichment in several AD-related pathways, including AD pathway, Notch-signaling pathway and Calcium-signaling pathway. These findings provide genetic insights into how somatic mutations may alter the function of single neurons and exert their potential roles in the pathogenesis of AD.

Estimating somatic mutation rates by bottlenecked duplex sequencing in non-model organisms: Daphnia magna as a case study.

Somatic mutations are evolutionarily important as determinants of individual organismal fitness, as well as being a focus of clinical research on age-related disease, such as cancer. Identifying somatic mutations and quantifying mutation rates, however, is extremely challenging and genome-wide somatic mutation rates have only been reported for a few model organisms. Here, we describe the application of Duplex Sequencing on bottlenecked WGS libraries to quantify somatic nuclear genome-wide base substitution rates in Daphnia magna. Daphnia, historically an ecological model system, has more recently been the focus of mutation studies, in part because of its high germline mutation rates. Using our protocol and pipeline, we estimate a somatic mutation rate of 5.6 × 10-7 substitutions per site (in a genotype where the germline rate is 3.60 × 10-9 substitutions per site per generation). To obtain this estimate, we tested multiple dilution levels to maximize sequencing efficiency and developed bioinformatic filters needed to minimize false positives when a high-quality reference genome is not available. In addition to laying the groundwork for estimating genotypic variation in rates of somatic mutations within D. magna, we provide a framework for quantifying somatic mutations in other non-model systems, and also highlight recent innovations to single molecule sequencing that will help to further refine such estimates.

Common anti-cancer therapies induce somatic mutations in stem cells of healthy tissue

Genome-wide mutation analyses have revealed that specific anti-cancer drugs are highly mutagenic to cancer cells, but the mutational impact of anti-cancer therapies on normal cells is not known. Here, we examine genome-wide somatic mutation patterns in 42 healthy adult stem cells (ASCs) of the colon or the liver from 14 cancer patients (mean of 3.2 ASC per donor) that received systemic chemotherapy and/or local radiotherapy. The platinum-based chemo-drug Oxaliplatin induces on average 535 ± 260 mutations in colon ASC, while 5-FU shows a complete mutagenic absence in most, but not all colon ASCs. In contrast with the colon, normal liver ASCs escape mutagenesis from systemic treatment with Oxaliplatin and 5-FU. Thus, while chemotherapies are highly effective at killing cancer cells, their systemic use also increases the mutational burden of long-lived normal stem cells responsible for tissue renewal thereby increasing the risk for developing second cancers.

Genome-wide detection of ultralow-frequency substitution mutations in cultures of mouse lymphoma L5178Y cells and Caenorhabditis elegans worms by PacBio sequencing.

Many conventional genetic toxicology assays require specialized cell cultures or animals and can only detect mutations that inactivate the function of a reporter gene. These limitations make such assays incompatible with many toxicological models but could be overcome by the development of techniques capable of directly detecting genome-wide somatic mutations through DNA sequencing. PacBio sequencing can generate almost error-free consensus reads by repeatedly inspecting both DNA strands from circularized molecules (a method known as PacBio HiFi). In this study, we show that PacBio HiFi can detect genome-wide ultralow-frequency substitution mutations in cultures of mouse lymphoma L5178Y cells and Caenorhabditis elegans worms. The mutation frequencies (MFs) of unexposed samples in both models were ~1 × 10-7 mutations per base pair. Compared to these controls, PacBio HiFi detected MF increases of 23-fold in cultures of L5178Y cells exposed to 5 mM ethyl methanosulfonate (EMS) for 4h, and 5-, 12-, and 29-fold in cultures of C. elegans worms exposed to 12.5, 25, and 50 mM EMS for 4h, respectively. In both models, the mutation spectra of controls were diverse, while those derived from EMS-exposed samples were dominated by C:G → T:A transitions. To validate these results, clone sequencing analyses were performed on the same cultures of L5178Y cells. The results obtained by clone sequencing and PacBio HiFi were almost identical. Our results suggest that PacBio sequencing could be used for the detection, quantitation, and characterization of mutations in any DNA-containing sample, including those that are not compatible with conventional mutation detection approaches.

Multi-omics analyses reveal MdMYB10 hypermethylation being responsible for a bud sport of apple fruit color.

Apple bud sports offer a rich resource for clonal selection of numerous elite cultivars. The accumulation of somatic mutations as plants develop may potentially impact the emergence of bud sports. Previous studies focused on somatic mutation in the essential genes associated with bud sports. However, the rate and function of genome-wide somatic mutations that accumulate when a bud sport arises remain unclear. In this study, we identified a branch from a 10-year-old tree of the apple cultivar 'Oregon SpurII' as a bud sport. The mutant branch showed reduced red coloration on fruit skin. Using this plant material, we assembled a high-quality haplotype reference genome consisting of 649.61Mb sequences with a contig N50 value of 2.04Mb. We then estimated the somatic mutation rate of the apple tree to be 4.56 × 10 -8 per base per year, and further identified 253 somatic single-nucleotide polymorphisms (SNPs), including five non-synonymous SNPs, between the original type and mutant samples. Transcriptome analyses showed that 69 differentially expressed genes between the original type and mutant fruit skin were highly correlated with anthocyanin content. DNA methylation in the promoter of five anthocyanin-associated genes was increased in the mutant compared with the original type as determined using DNA methylation profiling. Among the genetic and epigenetic factors that directly and indirectly influence anthocyanin content in the mutant apple fruit skin, the hypermethylated promoter of MdMYB10 is important. This study indicated that numerous somatic mutations accumulated at the emergence of a bud sport from a genome-wide perspective, some of which contribute to the low coloration of the bud sport.

Genome-wide somatic mutation analysis via Hawk-Seq\u2122 reveals mutation profiles associated with chemical mutagens

It is difficult to identify mutagen-induced genome-wide somatic mutations using next generation sequencing; hence, mutagenic features of each mutagen and their roles in cancer development require further elucidation. We described Hawk-Seq™, a highly accurate genome sequencing method and the optimal conditions, for using it to construct libraries that would enable the accurate (c.a. 1 error/107–108 bp) and efficient survey of genome-wide mutations. Genomic mutations in gpt delta mice or Salmonella typhimurium TA100 exposed to methylnitrosourea (MNU), ethylnitrosourea (ENU), diethylnitrosamine (DEN), benzo[a]pyrene (BP), and aristolochic acid (AA) were profiled using Hawk-Seq™ to analyse positions, substitution patterns, or frequencies. The resultant vast mutation data provided high-resolution mutational signatures, including for minor mutational fractions (e.g. G:C>A:T by AA), which enabled the clarification of the mutagenic features of all mutagens. The 96-type mutational signatures of MNU, AA, and BP indicate their partial similarity to signature 11, 22, and 4 or 29, respectively. Meanwhile, signatures attributable to ENU and DEN were highly similar to each other, but not to signature 11, suggesting that the mechanisms of these agents differed from those of typical alkylating agents. Thus, Hawk-Seq™ can clarify genome-wide chemical mutagenicity profiles at extraordinary resolutions, thereby providing insight into mutagen mechanisms and their roles in cancer development.

Population dynamics of normal human blood inferred from somatic mutations.

Haematopoietic stem cells drive blood production, but their population size and lifetime dynamics have not been directly quantified in humans. We identified 129,582 spontaneous, genome-wide somatic mutations in 140 single-cell–derived haematopoietic stem and progenitor colonies from a normal 59 year-old man and applied population genetics approaches to reconstruct clonal dynamics. Cell divisions from early embryogenesis were evident in the phylogenetic tree, with all blood deriving from a common ancestor that preceded gastrulation. Stem cell population size grew steadily in early life, reaching a stable plateau by adolescence. We estimate numbers of haematopoietic stem cells actively making white blood cells at any one time to be in the range 50,000-200,000. We observed adult haematopoietic stem cell clones that generate multilineage output, including granulocytes and B lymphocytes. Harnessing naturally occurring mutations to report an organ’s clonal architecture provides high-resolution reconstruction of somatic cell dynamics in humans.

Nuclear topology modulates the mutational landscapes of cancer genomes.

Nuclear organization of genomic DNA affects DNA damage and repair processes, and yet its impact on mutational landscapes in cancer genomes remains unclear. Here we analyzed genome-wide somatic mutations from 366 samples of 6 cancer types. We found that lamina-associated regions, which are typically localized at the nuclear periphery, displayed higher somatic mutation frequencies compared to the inter-lamina regions at the nuclear core. This effect remained even after adjusting for features such as GC%, chromatin, and replication timing. Furthermore, mutational signatures differed between the nuclear core and periphery, indicating differences in the patterns of DNA damage and/or DNA repair processes. For instance, smoking and UV-related signatures were more enriched in the nuclear periphery. Substitutions at certain motifs were also more common in the nuclear periphery. Taken together, we found that the nuclear architecture influences mutational landscapes in cancer genomes beyond the effects already captured by chromatin and replication timing.

Characterisation of the changing genomic landscape of metastatic melanoma using cell free DNA

Cancer is characterised by complex somatically acquired genetic aberrations that manifest as intra-tumour and inter-tumour genetic heterogeneity and can lead to treatment resistance. In this case study, we characterise the genome-wide somatic mutation dynamics in a metastatic melanoma patient during therapy using low-input (50 ng) PCR-free whole genome sequencing of cell-free DNA from pre-treatment and post-relapse blood samples. We identify de novo tumour-specific somatic mutations from cell-free DNA, while the sequence context of single nucleotide variants showed the characteristic UV-damage mutation signature of melanoma. To investigate the behaviour of individual somatic mutations during proto-oncogene B-Raf -targeted and immune checkpoint inhibition, amplicon-based deep sequencing was used to verify and track frequencies of 212 single nucleotide variants at 10 distinct time points over 13 months of treatment. Under checkpoint inhibition therapy, we observed an increase in mutant allele frequencies indicating progression on therapy 88 days before clinical determination of non-response positron emission tomogrophy-computed tomography. We also revealed mutations from whole genome sequencing of cell-free DNA that were not present in the tissue biopsy, but that later contributed to relapse. Our findings have potential clinical applications where high quality tumour-tissue derived DNA is not available.

Abstract 2473: Breast cancer whole genomes link homologous recombination deficiency (HRD) with therapeutic outcomes

Abstract Background: Homologous recombination deficiency (HRD) is common in cancer - germline BRCA1 &amp; BRCA2 mutations account for 5-10% of breast cancers and confer 85% lifetime risk. HRD cancers exhibit genomic instability and sensitivity to platinum-based therapy and PARP inhibitors. While not all causes of HRD are known, recent sequencing efforts have revealed genome-wide somatic mutation signatures that characterize the HRD genomic instability phenotype, also known as “BRCA-ness”. This provides a promising new assay to predict sensitivity to platinum-based therapy. Here, we integrate two whole-genome sequencing metrics to assess their association with therapeutic outcomes in a breast cancer cohort. Methods: Whole-genome sequencing of 47 breast cancer tumors (100x coverage) and matched normals (60x) was performed on an Illumina HiSeq. Alignment, assembly, SNV calling, and loss of heterozygosity (LOH) detection were performed with BWA, ABySS, Strelka, and APOLLOH respectively. SNV signatures were deciphered by non-negative matrix factorization with Monte Carlo resampling. An HRD score comprised of LOH, telomeric allelic imbalance (TAI), and large scale transition (LST) counts was computed. Clinical endpoints were obtained by retrospective review of treatment and imaging reports. Analysis is ongoing in an independent validation cohort of 62 sequenced cases. Results: The HRD-linked SNV signature was significantly associated with radiographic clinical response (CR) to platinum-based therapy (p=0.015). Logistic regression demonstrated a 59% improved odds of CR to platinum-based therapy per 1000 somatic SNVs attributed to HRD (odds ratio 1.16-2.50). Tumors carried up to 10,246 such SNVs and all patients with CR were among the top quartile. The LOH-TAI-LST score was correlated with SNV signature (r=0.6, p=7×10-6) and associated with CR (p=0.025). Notably, elevated HRD signatures associated with CR were identified in tumors with wild-type BRCA1/BRCA2 or variants of unknown significance. Tumors with above median HRD signatures were associated with a 69-day longer time to treatment failure and an 18% daily decreased probability of treatment failure per 1000 HRD-attributed SNVs (hazard ratio 0.71-0.95, p = 0.007). Discussion: We found that HRD mutation signatures are associated with clinical response and longer time to treatment failure with platinum-based therapy. While similar benefits were observed in patients with somatic bi-allelic loss of BRCA1/BRCA2, such cases are less common (8% of our cohort) compared to those with elevated HRD signature. Thus, mutation signature methods may identify patients who stand to benefit from platinum-based therapy missed by BRCA screening alone. Citation Format: Eric Y. Zhao, Yaoqing Shen, Erin Pleasance, Katayoon Kasaian, Martin R. Jones, Carolyn Ch'ng, Caralyn Reisle, Peter Eirew, Karen Mungall, Nina Thiessen, Yussanne Ma, Alexandra Fok, Andrew J. Mungall, Yongjun Zhao, Richard Moore, Diego Villa, Tamara Shenkier, Caroline Lohrisch, Stephen Chia, Stephen Yip, Karen Gelmon, Howard Lim, Sophie Sun, Kasmintan A. Schrader, Sean Young, Aly Karsan, Robyn Roscoe, Janessa Laskin, Marco A. Marra, Steven J. Jones. Breast cancer whole genomes link homologous recombination deficiency (HRD) with therapeutic outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2473. doi:10.1158/1538-7445.AM2017-2473

NetNorM: Capturing cancer-relevant information in somatic exome mutation data with gene networks for cancer stratification and prognosis.

Genome-wide somatic mutation profiles of tumours can now be assessed efficiently and promise to move precision medicine forward. Statistical analysis of mutation profiles is however challenging due to the low frequency of most mutations, the varying mutation rates across tumours, and the presence of a majority of passenger events that hide the contribution of driver events. Here we propose a method, NetNorM, to represent whole-exome somatic mutation data in a form that enhances cancer-relevant information using a gene network as background knowledge. We evaluate its relevance for two tasks: survival prediction and unsupervised patient stratification. Using data from 8 cancer types from The Cancer Genome Atlas (TCGA), we show that it improves over the raw binary mutation data and network diffusion for these two tasks. In doing so, we also provide a thorough assessment of somatic mutations prognostic power which has been overlooked by previous studies because of the sparse and binary nature of mutations.

A new unsupervised clustering algorithm applied to genome-wide profiles of breast cancers in The Cancer Genome Atlas proper subsets triple-negative samples.

e23195 Background: Clustering algorithms have identified subtypes of major cancers from analysis of genome-wide gene expression (GE) and somatic mutation (SM) profiles. These algorithms almost never discover a proper subset cluster, a recovered cluster that includes all the samples of a specific subtype. For breast cancer (BC), clustering of genome-wide profiles has been unable to proper subset triple negatives (TNs), TN subtypes, or other major subtypes. Methods: To search for a proper subset cluster for TNs, we applied a new clustering algorithm to the public domain GE and SM data of BC samples in The Cancer Genome Atlas (TCGA). A module of Medidata’s Clinical Trial Genomics (CTG) platform for automated clinical and genomic data integration and analysis, it uses a hierarchical component with tree learned cut points applied to a principal component dimension reduced similarity matrix calculated from a genome-wide data profile. Results: Our analysis of 540 TCGA BC samples run without human supervision produced a proper subset cluster that included all 55 TN samples and only 74 non-TN samples. GE data have previously indicated TN status, but this is the first demonstration that these TCGA BC data contain enough information to proper subset TNs, implying that this broad BC subtype has a strong, quantifiable impact on GE. We show that the genome-wide SMs of TCGA BC samples can be used to proper subset 4 novel subtypes distinguished as classes “TP53 mutated”, “PIK3CA mutated”, “both TP53 and PIK3CA mutated”, and “neither mutated”, signifying an important role for these known driver mutations in producing the subtypes’ genome-wide mutation profiles. We find that most ( &gt; 80%) TN BCs are in “TP53 mutated” but only 1 TN sample ( &lt; 2%) is in “PIK3CA mutated”, indicating distinct biology for these TNs with potential implications for TN therapy. Conclusions: CTG clustering achieves proper subset cancer subtype clustering of TCGA BC samples. These results illustrate the therapeutic discovery potential possible from genomic data of the high quality present in TCGA if combined with detailed clinical data with the Medidata CTG integration and annotation platform.

Identifying the clonal relationship model of multifocal papillary thyroid carcinoma by whole genome sequencing

PurposeTo evaluate the application of whole genome sequencing (WGS) in determining the inter-foci clonal relationship of multifocal papillary thyroid carcinoma (mPTC). MethodsAfter reviewing PTC patient profiles, 8 cancer foci and germline control samples from 3 mPTC patients were analyzed by WGS. Single nucleotide variations (SNVs), copy number variation (CNV), structural variation and mutational signature were examined. ResultsThe multifocality rate of PTC was 35.1% and mPTC were shown to have larger primary tumor diameter, higher rate of lymph node metastasis and less number of accompanying non-cancerous lesions than single PTC in one or both gender groups. Out of the 8 cancer foci, 5 foci were identified as clonal-independent model with the rest 3 foci as clonal-derived model according to exonic SNVs spectrum. Non-exonic mutations provided compelling evidence at the genome-wide level for the classification. Specific CNV and 12 mutational signatures were also identified. ConclusionsWGS could be an impressive tool in clonal relationship determination of PTC by providing a panoramic view of genome-wide somatic mutations. The substantial sequencing data provided additional information that could help studying the mechanism of carcinogenesis.