Evolution and impact of subclonal mutations in chronic lymphocytic leukemia.

Clonal evolution is a key feature of cancer progression and relapse. We studied intratumoral heterogeneity in 149 chronic lymphocytic leukemia (CLL) cases by integrating whole-exome sequence and copy number to measure the fraction of cancer cells harboring each somatic mutation. We identified driver mutations as predominantly clonal (e.g., MYD88, trisomy 12, and del(13q)) or subclonal (e.g., SF3B1 and TP53), corresponding to earlier and later events in CLL evolution. We sampled leukemia cells from 18 patients at two time points. Ten of twelve CLL cases treated with chemotherapy (but only one of six without treatment) underwent clonal evolution, predominantly involving subclones with driver mutations (e.g., SF3B1 and TP53) that expanded over time. Furthermore, presence of a subclonal driver mutation was an independent risk factor for rapid disease progression. Our study thus uncovers patterns of clonal evolution in CLL, providing insights into its stepwise transformation, and links the presence of subclones with adverse clinical outcomes.

Punctuated evolution of prostate cancer genomes.

The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term "chromoplexy," frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis.

Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.

Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, is responsible for more than 500,000 deaths per year worldwide. Here, we report exome and genome sequences of 183 lung adenocarcinoma tumor/normal DNA pairs. These analyses revealed a mean exonic somatic mutation rate of 12.0 events/megabase and identified the majority of genes previously reported as significantly mutated in lung adenocarcinoma. In addition, we identified statistically recurrent somatic mutations in the splicing factor gene U2AF1 and truncating mutations affecting RBM10 and ARID1A. Analysis of nucleotide context-specific mutation signatures grouped the sample set into distinct clusters that correlated with smoking history and alterations of reported lung adenocarcinoma genes. Whole-genome sequence analysis revealed frequent structural rearrangements, including in-frame exonic alterations within EGFR and SIK2 kinases. The candidate genes identified in this study are attractive targets for biological characterization and therapeutic targeting of lung adenocarcinoma.

A landscape of driver mutations in melanoma.

Despite recent insights into melanoma genetics, systematic surveys for driver mutations are challenged by an abundance of passenger mutations caused by carcinogenic UV light exposure. We developed a permutation-based framework to address this challenge, employing mutation data from intronic sequences to control for passenger mutational load on a per gene basis. Analysis of large-scale melanoma exome data by this approach discovered six novel melanoma genes (PPP6C, RAC1, SNX31, TACC1, STK19, and ARID2), three of which-RAC1, PPP6C, and STK19-harbored recurrent and potentially targetable mutations. Integration with chromosomal copy number data contextualized the landscape of driver mutations, providing oncogenic insights in BRAF- and NRAS-driven melanoma as well as those without known NRAS/BRAF mutations. The landscape also clarified a mutational basis for RB and p53 pathway deregulation in this malignancy. Finally, the spectrum of driver mutations provided unequivocal genomic evidence for a direct mutagenic role of UV light in melanoma pathogenesis.

Mutational heterogeneity in cancer and the search for new cancer-associated genes.

Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour-normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour-normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.

Melanoma genome sequencing reveals frequent PREX2 mutations.

Melanoma is notable for its metastatic propensity, lethality in the advanced setting and association with ultraviolet exposure early in life. To obtain a comprehensive genomic view of melanoma in humans, we sequenced the genomes of 25 metastatic melanomas and matched germline DNA. A wide range of point mutation rates was observed: lowest in melanomas whose primaries arose on non-ultraviolet-exposed hairless skin of the extremities (3 and 14 per megabase (Mb) of genome), intermediate in those originating from hair-bearing skin of the trunk (5-55 per Mb), and highest in a patient with a documented history of chronic sun exposure (111 per Mb). Analysis of whole-genome sequence data identified PREX2 (phosphatidylinositol-3,4,5-trisphosphate-dependent Rac exchange factor 2)--a PTEN-interacting protein and negative regulator of PTEN in breast cancer--as a significantly mutated gene with a mutation frequency of approximately 14% in an independent extension cohort of 107 human melanomas. PREX2 mutations are biologically relevant, as ectopic expression of mutant PREX2 accelerated tumour formation of immortalized human melanocytes in vivo. Thus, whole-genome sequencing of human melanoma tumours revealed genomic evidence of ultraviolet pathogenesis and discovered a new recurrently mutated gene in melanoma.

Medulloblastoma exome sequencing uncovers subtype-specific somatic mutations.

Medulloblastomas are the most common malignant brain tumours in children. Identifying and understanding the genetic events that drive these tumours is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma on the basis of transcriptional and copy number profiles. Here we use whole-exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas have low mutation rates consistent with other paediatric tumours, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were newly identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR and LDB1. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant, but not wild-type, ß-catenin. Together, our study reveals the alteration of WNT, hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic ß-catenin signalling in medulloblastoma.

Sequence analysis of mutations and translocations across breast cancer subtypes.

Breast carcinoma is the leading cause of cancer-related mortality in women worldwide, with an estimated 1.38 million new cases and 458,000 deaths in 2008 alone. This malignancy represents a heterogeneous group of tumours with characteristic molecular features, prognosis and responses to available therapy. Recurrent somatic alterations in breast cancer have been described, including mutations and copy number alterations, notably ERBB2 amplifications, the first successful therapy target defined by a genomic aberration. Previous DNA sequencing studies of breast cancer genomes have revealed additional candidate mutations and gene rearrangements. Here we report the whole-exome sequences of DNA from 103 human breast cancers of diverse subtypes from patients in Mexico and Vietnam compared to matched-normal DNA, together with whole-genome sequences of 22 breast cancer/normal pairs. Beyond confirming recurrent somatic mutations in PIK3CA, TP53, AKT1, GATA3 and MAP3K1, we discovered recurrent mutations in the CBFB transcription factor gene and deletions of its partner RUNX1. Furthermore, we have identified a recurrent MAGI3-AKT3 fusion enriched in triple-negative breast cancer lacking oestrogen and progesterone receptors and ERBB2 expression. The MAGI3-AKT3 fusion leads to constitutive activation of AKT kinase, which is abolished by treatment with an ATP-competitive AKT small-molecule inhibitor.

The genomic complexity of primary human prostate cancer.

Prostate cancer is the second most common cause of male cancer deaths in the United States. However, the full range of prostate cancer genomic alterations is incompletely characterized. Here we present the complete sequence of seven primary human prostate cancers and their paired normal counterparts. Several tumours contained complex chains of balanced (that is, 'copy-neutral') rearrangements that occurred within or adjacent to known cancer genes. Rearrangement breakpoints were enriched near open chromatin, androgen receptor and ERG DNA binding sites in the setting of the ETS gene fusion TMPRSS2-ERG, but inversely correlated with these regions in tumours lacking ETS fusions. This observation suggests a link between chromatin or transcriptional regulation and the genesis of genomic aberrations. Three tumours contained rearrangements that disrupted CADM2, and four harboured events disrupting either PTEN (unbalanced events), a prostate tumour suppressor, or MAGI2 (balanced events), a PTEN interacting protein not previously implicated in prostate tumorigenesis. Thus, genomic rearrangements may arise from transcriptional or chromatin aberrancies and engage prostate tumorigenic mechanisms.

Initial genome sequencing and analysis of multiple myeloma.

Multiple myeloma is an incurable malignancy of plasma cells, and its pathogenesis is poorly understood. Here we report the massively parallel sequencing of 38 tumour genomes and their comparison to matched normal DNAs. Several new and unexpected oncogenic mechanisms were suggested by the pattern of somatic mutation across the data set. These include the mutation of genes involved in protein translation (seen in nearly half of the patients), genes involved in histone methylation, and genes involved in blood coagulation. In addition, a broader than anticipated role of NF-κB signalling was indicated by mutations in 11 members of the NF-κB pathway. Of potential immediate clinical relevance, activating mutations of the kinase BRAF were observed in 4% of patients, suggesting the evaluation of BRAF inhibitors in multiple myeloma clinical trials. These results indicate that cancer genome sequencing of large collections of samples will yield new insights into cancer not anticipated by existing knowledge.

Complementary genomic approaches highlight the PI3K/mTOR pathway as a common vulnerability in osteosarcoma.

Osteosarcoma is the most common primary bone tumor, yet there have been no substantial advances in treatment or survival in three decades. We examined 59 tumor/normal pairs by whole-exome, whole-genome, and RNA-sequencing. Only the TP53 gene was mutated at significant frequency across all samples. The mean nonsilent somatic mutation rate was 1.2 mutations per megabase, and there was a median of 230 somatic rearrangements per tumor. Complex chains of rearrangements and localized hypermutation were detected in almost all cases. Given the intertumor heterogeneity, the extent of genomic instability, and the difficulty in acquiring a large sample size in a rare tumor, we used several methods to identify genomic events contributing to osteosarcoma survival. Pathway analysis, a heuristic analytic algorithm, a comparative oncology approach, and an shRNA screen converged on the phosphatidylinositol 3-kinase/mammalian target of rapamycin (PI3K/mTOR) pathway as a central vulnerability for therapeutic exploitation in osteosarcoma. Osteosarcoma cell lines are responsive to pharmacologic and genetic inhibition of the PI3K/mTOR pathway both in vitro and in vivo.

Comparative analysis of RNA sequencing methods for degraded or low-input samples.

RNA-seq is an effective method for studying the transcriptome, but it can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations or cadavers. Recent studies have proposed several methods for RNA-seq of low-quality and/or low-quantity samples, but the relative merits of these methods have not been systematically analyzed. Here we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and compared them against two control libraries. We found that the RNase H method performed best for chemically fragmented, low-quality RNA, and we confirmed this through analysis of actual degraded samples. RNase H can even effectively replace oligo(dT)-based methods for standard RNA-seq. SMART and NuGEN had distinct strengths for measuring low-quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.

PRADA: pipeline for RNA sequencing data analysis.

SUMMARY: Technological advances in high-throughput sequencing necessitate improved computational tools for processing and analyzing large-scale datasets in a systematic automated manner. For that purpose, we have developed PRADA (Pipeline for RNA-Sequencing Data Analysis), a flexible, modular and highly scalable software platform that provides many different types of information available by multifaceted analysis starting from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification. PRADA uses a dual-mapping strategy that increases sensitivity and refines the analytical endpoints. PRADA has been used extensively and successfully in the glioblastoma and renal clear cell projects of The Cancer Genome Atlas program. AVAILABILITY AND IMPLEMENTATION: http://sourceforge.net/projects/prada/ CONTACT: gadgetz@broadinstitute.org or rverhaak@mdanderson.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SF3B1 and other novel cancer genes in chronic lymphocytic leukemia.

BACKGROUND: The somatic genetic basis of chronic lymphocytic leukemia, a common and clinically heterogeneous leukemia occurring in adults, remains poorly understood. METHODS: We obtained DNA samples from leukemia cells in 91 patients with chronic lymphocytic leukemia and performed massively parallel sequencing of 88 whole exomes and whole genomes, together with sequencing of matched germline DNA, to characterize the spectrum of somatic mutations in this disease. RESULTS: Nine genes that are mutated at significant frequencies were identified, including four with established roles in chronic lymphocytic leukemia (TP53 in 15% of patients, ATM in 9%, MYD88 in 10%, and NOTCH1 in 4%) and five with unestablished roles (SF3B1, ZMYM3, MAPK1, FBXW7, and DDX3X). SF3B1, which functions at the catalytic core of the spliceosome, was the second most frequently mutated gene (with mutations occurring in 15% of patients). SF3B1 mutations occurred primarily in tumors with deletions in chromosome 11q, which are associated with a poor prognosis in patients with chronic lymphocytic leukemia. We further discovered that tumor samples with mutations in SF3B1 had alterations in pre-messenger RNA (mRNA) splicing. CONCLUSIONS: Our study defines the landscape of somatic mutations in chronic lymphocytic leukemia and highlights pre-mRNA splicing as a critical cellular process contributing to chronic lymphocytic leukemia.

Genome-scale DNA methylation maps of pluripotent and differentiated cells.

DNA methylation is essential for normal development and has been implicated in many pathologies including cancer. Our knowledge about the genome-wide distribution of DNA methylation, how it changes during cellular differentiation and how it relates to histone methylation and other chromatin modifications in mammals remains limited. Here we report the generation and analysis of genome-scale DNA methylation profiles at nucleotide resolution in mammalian cells. Using high-throughput reduced representation bisulphite sequencing and single-molecule-based sequencing, we generated DNA methylation maps covering most CpG islands, and a representative sampling of conserved non-coding elements, transposons and other genomic features, for mouse embryonic stem cells, embryonic-stem-cell-derived and primary neural cells, and eight other primary tissues. Several key findings emerge from the data. First, DNA methylation patterns are better correlated with histone methylation patterns than with the underlying genome sequence context. Second, methylation of CpGs are dynamic epigenetic marks that undergo extensive changes during cellular differentiation, particularly in regulatory regions outside of core promoters. Third, analysis of embryonic-stem-cell-derived and primary cells reveals that 'weak' CpG islands associated with a specific set of developmentally regulated genes undergo aberrant hypermethylation during extended proliferation in vitro, in a pattern reminiscent of that reported in some primary tumours. More generally, the results establish reduced representation bisulphite sequencing as a powerful technology for epigenetic profiling of cell populations relevant to developmental biology, cancer and regenerative medicine.

In vitro modulator responsiveness of 655 CFTR variants found in people with cystic fibrosis.

BACKGROUND: In 2017, the US Food and Drug Administration initiated expansion of drug labels for the treatment of cystic fibrosis (CF) to include CF transmembrane conductance regulator (CFTR) gene variants based on in vitro functional studies. This study aims to identify CFTR variants that result in increased chloride (Cl-) transport function by the CFTR protein after treatment with the CFTR modulator combination elexacaftor/tezacaftor/ivacaftor (ELX/TEZ/IVA). These data may benefit people with CF (pwCF) who are not currently eligible for modulator therapies. METHODS: Plasmid DNA encoding 655 CFTR variants and wild-type (WT) CFTR were transfected into Fisher Rat Thyroid cells that do not natively express CFTR. After 24 h of incubation with control or TEZ and ELX, and acute addition of IVA, CFTR function was assessed using the transepithelial current clamp conductance assay. Each variant's forskolin/cAMP-induced baseline Cl- transport activity, responsiveness to IVA alone, and responsiveness to the TEZ/ELX/IVA combination were measured in three different laboratories. Western blots were conducted to evaluate CFTR protein maturation and complement the functional data. RESULTS AND CONCLUSIONS: 253 variants not currently approved for CFTR modulator therapy showed low baseline activity (<10 % of normal CFTR Cl- transport activity). For 152 of these variants, treatment with ELX/TEZ/IVA improved the Cl- transport activity by ≥10 % of normal CFTR function, which is suggestive of clinical benefit. ELX/TEZ/IVA increased CFTR function by ≥10 percentage points for an additional 140 unapproved variants with ≥10 % but <50 % of normal CFTR function at baseline. These findings significantly expand the number of rare CFTR variants for which ELX/TEZ/IVA treatment should result in clinical benefit.

The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

Integrative analysis of the melanoma transcriptome.

Global studies of transcript structure and abundance in cancer cells enable the systematic discovery of aberrations that contribute to carcinogenesis, including gene fusions, alternative splice isoforms, and somatic mutations. We developed a systematic approach to characterize the spectrum of cancer-associated mRNA alterations through integration of transcriptomic and structural genomic data, and we applied this approach to generate new insights into melanoma biology. Using paired-end massively parallel sequencing of cDNA (RNA-seq) together with analyses of high-resolution chromosomal copy number data, we identified 11 novel melanoma gene fusions produced by underlying genomic rearrangements, as well as 12 novel readthrough transcripts. We mapped these chimeric transcripts to base-pair resolution and traced them to their genomic origins using matched chromosomal copy number information. We also used these data to discover and validate base-pair mutations that accumulated in these melanomas, revealing a surprisingly high rate of somatic mutation and lending support to the notion that point mutations constitute the major driver of melanoma progression. Taken together, these results may indicate new avenues for target discovery in melanoma, while also providing a template for large-scale transcriptome studies across many tumor types.

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

UNLABELLED: RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis. AVAILABILITY AND IMPLEMENTATION: See www.genepattern.org to run online, or www.broadinstitute.org/rna-seqc/ for a command line tool.

Isogenic cell models of cystic fibrosis-causing variants in natively expressing pulmonary epithelial cells.

BACKGROUND: Assessment of approved drugs and developmental drug candidates for rare cystic fibrosis (CF)-causing variants of the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) requires abundant material from relevant models. METHODS: Isogenic cell lines harboring CFTR variants in the native genomic context were created through the development and utilization of a footprint-less, CRISPR/Cas9 gene editing pipeline in 16HBE14o- immortalized bronchial epithelial cells. RESULTS: Isogenic, homozygous cell lines for three CFTR variants (F508del and the two most common CF-causing nonsense variants, G542X and W1282X) were established and characterized. The F508del model recapitulates the known molecular pathology and pharmacology. The two models of nonsense variants (G542X and W1282X) are sensitive to Nonsense Mediated mRNA Decay (NMD) and responsive to reference compounds that inhibit NMD and promote ribosomal readthrough. CONCLUSIONS: We present a versatile, efficient gene editing pipeline that can be used to create CFTR variants in the native genomic context and the utilization of this pipeline to create homozygous cell models for the CF-causing variants F508del, G542X, and W1282X. The resulting cell lines provide a virtually unlimited source of material with specific pathogenic mutations that can be used in a variety of assays, including functional assays.