Prospective derivation of a living organoid biobank of colorectal cancer patients.

In Rspondin-based 3D cultures, Lgr5 stem cells from multiple organs form ever-expanding epithelial organoids that retain their tissue identity. We report the establishment of tumor organoid cultures from 20 consecutive colorectal carcinoma (CRC) patients. For most, organoids were also generated from adjacent normal tissue. Organoids closely recapitulate several properties of the original tumor. The spectrum of genetic changes within the "living biobank" agrees well with previous large-scale mutational analyses of CRC. Gene expression analysis indicates that the major CRC molecular subtypes are represented. Tumor organoids are amenable to high-throughput drug screens allowing detection of gene-drug associations. As an example, a single organoid culture was exquisitely sensitive to Wnt secretion (porcupine) inhibitors and carried a mutation in the negative Wnt feedback regulator RNF43, rather than in APC. Organoid technology may fill the gap between cancer genetics and patient trials, complement cell-line- and xenograft-based drug studies, and allow personalized therapy design. PAPERCLIP.

Genetic and clonal dissection of murine small cell lung carcinoma progression by genome sequencing.

Small cell lung carcinoma (SCLC) is a highly lethal, smoking-associated cancer with few known targetable genetic alterations. Using genome sequencing, we characterized the somatic evolution of a genetically engineered mouse model (GEMM) of SCLC initiated by loss of Trp53 and Rb1. We identified alterations in DNA copy number and complex genomic rearrangements and demonstrated a low somatic point mutation frequency in the absence of tobacco mutagens. Alterations targeting the tumor suppressor Pten occurred in the majority of murine SCLC studied, and engineered Pten deletion accelerated murine SCLC and abrogated loss of Chr19 in Trp53; Rb1; Pten compound mutant tumors. Finally, we found evidence for polyclonal and sequential metastatic spread of murine SCLC by comparative sequencing of families of related primary tumors and metastases. We propose a temporal model of SCLC tumorigenesis with implications for human SCLC therapeutics and the nature of cancer-genome evolution in GEMMs.

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.

Growth dynamics in naturally progressing chronic lymphocytic leukaemia.

How the genomic features of a patient's cancer relate to individual disease kinetics remains poorly understood. Here we used the indolent growth dynamics of chronic lymphocytic leukaemia (CLL) to analyse the growth rates and corresponding genomic patterns of leukaemia cells from 107 patients with CLL, spanning decades-long disease courses. We found that CLL commonly demonstrates not only exponential expansion but also logistic growth, which is sigmoidal and reaches a certain steady-state level. Each growth pattern was associated with marked differences in genetic composition, the pace of disease progression and the extent of clonal evolution. In a subset of patients, whose serial samples underwent next-generation sequencing, we found that dynamic changes in the disease course of CLL were shaped by the genetic events that were already present in the early slow-growing stages. Finally, by analysing the growth rates of subclones compared with their parental clones, we quantified the growth advantage conferred by putative CLL drivers in vivo.

Recurrent and functional regulatory mutations in breast cancer.

Genomic analysis of tumours has led to the identification of hundreds of cancer genes on the basis of the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here we perform deep sequencing in 360 primary breast cancers and develop computational methods to identify significantly mutated promoters. Clear signals are found in the promoters of three genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbours a mutational hotspot in its promoter leading to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that affect protein binding to their promoters and alter expression levels. Our study shows that promoter regions harbour recurrent mutations in cancer with functional consequences and that the mutations occur at similar frequencies as in coding regions. Power analyses indicate that more such regions remain to be discovered through deep sequencing of adequately sized cohorts of patients.

SvABA: genome-wide detection of structural variants and indels by local assembly.

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (<1000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types and found that short templated-sequence insertions occur in ∼4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized (50-300 bp) SVs.

DeTiN: overcoming tumor-in-normal contamination.

Comparison of sequencing data from a tumor sample with data from a matched germline control is a key step for accurate detection of somatic mutations. Detection sensitivity for somatic variants is greatly reduced when the matched normal sample is contaminated with tumor cells. To overcome this limitation, we developed deTiN, a method that estimates the tumor-in-normal (TiN) contamination level and, in cases affected by contamination, improves sensitivity by reclassifying initially discarded variants as somatic.

Genomic analyses of PMBL reveal new drivers and mechanisms of sensitivity to PD-1 blockade.

Primary mediastinal large B-cell lymphomas (PMBLs) are aggressive tumors that typically present as large mediastinal masses in young women. PMBLs share clinical, transcriptional, and molecular features with classical Hodgkin lymphoma (cHL), including constitutive activation of nuclear factor κB (NF-κB), JAK/STAT signaling, and programmed cell death protein 1 (PD-1)-mediated immune evasion. The demonstrated efficacy of PD-1 blockade in relapsed/refractory PMBLs led to recent approval by the US Food and Drug Administration and underscored the importance of characterizing targetable genetic vulnerabilities in this disease. Here, we report a comprehensive analysis of recurrent genetic alterations -somatic mutations, somatic copy number alterations, and structural variants-in a cohort of 37 newly diagnosed PMBLs. We identified a median of 9 genetic drivers per PMBL, including known and newly identified components of the JAK/STAT and NF-κB signaling pathways and frequent B2M alterations that limit major histocompatibility complex class I expression, as in cHL. PMBL also exhibited frequent, newly identified driver mutations in ZNF217 and an additional epigenetic modifier, EZH2. The majority of these alterations were clonal, which supports their role as early drivers. In PMBL, we identified several previously uncharacterized molecular features that may increase sensitivity to PD-1 blockade, including high tumor mutational burden, microsatellite instability, and an apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) mutational signature. The shared genetic features between PMBL and cHL provide a framework for analyzing the mechanism of action of PD-1 blockade in these related lymphoid malignancies.

Mutations driving CLL and their evolution in progression and relapse.

Which genetic alterations drive tumorigenesis and how they evolve over the course of disease and therapy are central questions in cancer biology. Here we identify 44 recurrently mutated genes and 11 recurrent somatic copy number variations through whole-exome sequencing of 538 chronic lymphocytic leukaemia (CLL) and matched germline DNA samples, 278 of which were collected in a prospective clinical trial. These include previously unrecognized putative cancer drivers (RPS15, IKZF3), and collectively identify RNA processing and export, MYC activity, and MAPK signalling as central pathways involved in CLL. Clonality analysis of this large data set further enabled reconstruction of temporal relationships between driver events. Direct comparison between matched pre-treatment and relapse samples from 59 patients demonstrated highly frequent clonal evolution. Thus, large sequencing data sets of clinically informative samples enable the discovery of novel genes associated with cancer, the network of relationships between the driver events, and their impact on disease relapse and clinical outcome.

Landscape of genomic alterations in cervical carcinomas.

Cervical cancer is responsible for 10-15% of cancer-related deaths in women worldwide. The aetiological role of infection with high-risk human papilloma viruses (HPVs) in cervical carcinomas is well established. Previous studies have also implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS as well as several copy-number alterations in the pathogenesis of cervical carcinomas. Here we report whole-exome sequencing analysis of 115 cervical carcinoma-normal paired samples, transcriptome sequencing of 79 cases and whole-genome sequencing of 14 tumour-normal pairs. Previously unknown somatic mutations in 79 primary squamous cell carcinomas include recurrent E322K substitutions in the MAPK1 gene (8%), inactivating mutations in the HLA-B gene (9%), and mutations in EP300 (16%), FBXW7 (15%), NFE2L2 (4%), TP53 (5%) and ERBB2 (6%). We also observe somatic ELF3 (13%) and CBFB (8%) mutations in 24 adenocarcinomas. Squamous cell carcinomas have higher frequencies of somatic nucleotide substitutions occurring at cytosines preceded by thymines (Tp*C sites) than adenocarcinomas. Gene expression levels at HPV integration sites were statistically significantly higher in tumours with HPV integration compared with expression of the same genes in tumours without viral integration at the same site. These data demonstrate several recurrent genomic alterations in cervical carcinomas that suggest new strategies to combat this disease.

A (fire)cloud-based DNA methylation data preprocessing and quality control platform.

BACKGROUND: Bisulfite sequencing allows base-pair resolution profiling of DNA methylation and has recently been adapted for use in single-cells. Analyzing these data, including making comparisons with existing data, remains challenging due to the scale of the data and differences in preprocessing methods between published datasets. RESULTS: We present a set of preprocessing pipelines for bisulfite sequencing DNA methylation data that include a new R/Bioconductor package, scmeth, for a series of efficient QC analyses of large datasets. The pipelines go from raw data to CpG-level methylation estimates and can be run, with identical results, either on a single computer, in an HPC cluster or on Google Cloud Compute resources. These pipelines are designed to allow users to 1) ensure reproducibility of analyses, 2) achieve scalability to large whole genome datasets with 100 GB+ of raw data per sample and to single-cell datasets with thousands of cells, 3) enable integration and comparison between user-provided data and publicly available data, as all samples can be processed through the same pipeline, and 4) access to best-practice analysis pipelines. Pipelines are provided for whole genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS) and hybrid selection (capture) bisulfite sequencing (HSBS). CONCLUSIONS: The workflows produce data quality metrics, visualization tracks, and aggregated output for further downstream analysis. Optional use of cloud computing resources facilitates analysis of large datasets, and integration with existing methylome profiles. The workflow design principles are applicable to other genomic data types.

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.

Sporadic Early-Onset Diffuse Gastric Cancers Have High Frequency of Somatic CDH1 Alterations, but Low Frequency of Somatic RHOA Mutations Compared With Late-Onset Cancers.

BACKGROUND & AIMS: Early-onset gastric cancer, which develops in patients younger than most gastric cancers, is usually detected at advanced stages, has diffuse histologic features, and occurs more frequently in women. We investigated somatic genomic alterations associated with the unique characteristics of sporadic diffuse gastric cancers (DGCs) from younger patients. METHODS: We conducted whole exome and RNA sequence analyses of 80 resected DGC samples from patients 45 years old or younger in Korea. Patients with pathogenic germline mutations in CDH1, TP53, and ATM were excluded from the onset of this analysis, given our focus on somatic alterations. We used MutSig2CV to evaluate the significance of mutated genes. We recruited 29 additional early-onset Korean DGC samples and performed SNP6.0 array and targeted sequencing analyses of these 109 early-onset DGC samples (54.1% female, median age, 38 years). We compared the SNP6.0 array and targeted sequencing data of the 109 early-onset DGC samples with those from diffuse-type stomach tumor samples collected from 115 patients in Korea who were 46 years or older (late onset) at the time of diagnosis (controls; 29.6% female, median age, 67 years). We compared patient survival times among tumors from different subgroups and with different somatic mutations. We performed gene silencing of RHOA or CDH1 in DGC cells with small interfering RNAs for cell-based assays. RESULTS: We identified somatic mutations in the following genes in a significant number of early-onset DGCs: the cadherin 1 gene (CDH1), TP53, ARID1A, KRAS, PIK3CA, ERBB3, TGFBR1, FBXW7, RHOA, and MAP2K1. None of 109 early-onset DGC cases had pathogenic germline CDH1 mutations. A higher proportion of early-onset DGCs had mutations in CDH1 (42.2%) or TGFBR1 (7.3%) compared with control DGCs (17.4% and 0.9%, respectively) (P < .001 and P = .014 for CDH1 and TGFBR1, respectively). In contrast, a smaller proportion of early-onset DGCs contained mutations in RHOA (9.2%) than control DGCs (19.1%) (P = .033). Late-onset DGCs in The Cancer Genome Atlas also contained less frequent mutations in CDH1 and TGFBR1 and more frequent RHOA mutations, compared with early-onset DGCs. Early-onset DGCs from women contained significantly more mutations in CDH1 or TGFBR1 than early-onset DGCs from men. CDH1 alterations, but not RHOA mutations, were associated with shorter survival times in patients with early-onset DGCs (hazard ratio, 3.4; 95% confidence interval, 1.5-7.7). RHOA activity was reduced by an R5W substitution-the RHOA mutation most frequently detected in early-onset DGCs. Silencing of CDH1, but not RHOA, increased migratory activity of DGC cells. CONCLUSIONS: In an integrative genomic analysis, we found higher proportions of early-onset DGCs to contain somatic mutations in CDH1 or TGFBR1 compared with late-onset DGCs. However, a smaller proportion of early-onset DGCs contained somatic mutations in RHOA than late-onset DGCs. CDH1 alterations, but not RHOA mutations, were associated with shorter survival times of patients, which might account for the aggressive clinical course of early-onset gastric cancer. Female predominance in early-onset gastric cancer may be related to relatively high rates of somatic CDH1 and TGFBR1 mutations in this population.

Exome sequencing of lymphomas from three dog breeds reveals somatic mutation patterns reflecting genetic background.

Lymphoma is the most common hematological malignancy in developed countries. Outcome is strongly determined by molecular subtype, reflecting a need for new and improved treatment options. Dogs spontaneously develop lymphoma, and the predisposition of certain breeds indicates genetic risk factors. Using the dog breed structure, we selected three lymphoma predisposed breeds developing primarily T-cell (boxer), primarily B-cell (cocker spaniel), and with equal distribution of B- and T-cell lymphoma (golden retriever), respectively. We investigated the somatic mutations in B- and T-cell lymphomas from these breeds by exome sequencing of tumor and normal pairs. Strong similarities were evident between B-cell lymphomas from golden retrievers and cocker spaniels, with recurrent mutations in TRAF3-MAP3K14 (28% of all cases), FBXW7 (25%), and POT1 (17%). The FBXW7 mutations recurrently occur in a specific codon; the corresponding codon is recurrently mutated in human cancer. In contrast, T-cell lymphomas from the predisposed breeds, boxers and golden retrievers, show little overlap in their mutation pattern, sharing only one of their 15 most recurrently mutated genes. Boxers, which develop aggressive T-cell lymphomas, are typically mutated in the PTEN-mTOR pathway. T-cell lymphomas in golden retrievers are often less aggressive, and their tumors typically showed mutations in genes involved in cellular metabolism. We identify genes with known involvement in human lymphoma and leukemia, genes implicated in other human cancers, as well as novel genes that could allow new therapeutic options.

Targetable genetic features of primary testicular and primary central nervous system lymphomas.

Primary central nervous system lymphomas (PCNSLs) and primary testicular lymphomas (PTLs) are extranodal large B-cell lymphomas (LBCLs) with inferior responses to current empiric treatment regimens. To identify targetable genetic features of PCNSL and PTL, we characterized their recurrent somatic mutations, chromosomal rearrangements, copy number alterations (CNAs), and associated driver genes, and compared these comprehensive genetic signatures to those of diffuse LBCL and primary mediastinal large B-cell lymphoma (PMBL). These studies identify unique combinations of genetic alterations in discrete LBCL subtypes and subtype-selective bases for targeted therapy. PCNSLs and PTLs frequently exhibit genomic instability, and near-uniform, often biallelic, CDKN2A loss with rare TP53 mutations. PCNSLs and PTLs also use multiple genetic mechanisms to target key genes and pathways and exhibit near-uniform oncogenic Toll-like receptor signaling as a result of MYD88 mutation and/or NFKBIZ amplification, frequent concurrent B-cell receptor pathway activation, and deregulation of BCL6. Of great interest, PCNSLs and PTLs also have frequent 9p24.1/PD-L1/PD-L2 CNAs and additional translocations of these loci, structural bases of immune evasion that are shared with PMBL.

Somatic retrotransposition in human cancer revealed by whole-genome and exome sequencing.

Retrotransposons constitute a major source of genetic variation, and somatic retrotransposon insertions have been reported in cancer. Here, we applied TranspoSeq, a computational framework that identifies retrotransposon insertions from sequencing data, to whole genomes from 200 tumor/normal pairs across 11 tumor types as part of The Cancer Genome Atlas (TCGA) Pan-Cancer Project. In addition to novel germline polymorphisms, we find 810 somatic retrotransposon insertions primarily in lung squamous, head and neck, colorectal, and endometrial carcinomas. Many somatic retrotransposon insertions occur in known cancer genes. We find that high somatic retrotransposition rates in tumors are associated with high rates of genomic rearrangement and somatic mutation. Finally, we developed TranspoSeq-Exome to interrogate an additional 767 tumor samples with hybrid-capture exome data and discovered 35 novel somatic retrotransposon insertions into exonic regions, including an insertion into an exon of the PTEN tumor suppressor gene. The results of this large-scale, comprehensive analysis of retrotransposon movement across tumor types suggest that somatic retrotransposon insertions may represent an important class of structural variation in cancer.

Mapping copy number variation by population-scale genome sequencing.

Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.

Somatic rearrangements across cancer reveal classes of samples with distinct patterns of DNA breakage and rearrangement-induced hypermutability.

Whole-genome sequencing using massively parallel sequencing technologies enables accurate detection of somatic rearrangements in cancer. Pinpointing large numbers of rearrangement breakpoints to base-pair resolution allows analysis of rearrangement microhomology and genomic location for every sample. Here we analyze 95 tumor genome sequences from breast, head and neck, colorectal, and prostate carcinomas, and from melanoma, multiple myeloma, and chronic lymphocytic leukemia. We discover three genomic factors that are significantly correlated with the distribution of rearrangements: replication time, transcription rate, and GC content. The correlation is complex, and different patterns are observed between tumor types, within tumor types, and even between different types of rearrangements. Mutations in the APC gene correlate with and, hence, potentially contribute to DNA breakage in late-replicating, low %GC, untranscribed regions of the genome. We show that somatic rearrangements display less microhomology than germline rearrangements, and that breakpoint loci are correlated with local hypermutability with a particular enrichment for transversions.

Discovery and characterization of artifactual mutations in deep coverage targeted capture sequencing data due to oxidative DNA damage during sample preparation.

As researchers begin probing deep coverage sequencing data for increasingly rare mutations and subclonal events, the fidelity of next generation sequencing (NGS) laboratory methods will become increasingly critical. Although error rates for sequencing and polymerase chain reaction (PCR) are well documented, the effects that DNA extraction and other library preparation steps could have on downstream sequence integrity have not been thoroughly evaluated. Here, we describe the discovery of novel C > A/G > T transversion artifacts found at low allelic fractions in targeted capture data. Characteristics such as sequencer read orientation and presence in both tumor and normal samples strongly indicated a non-biological mechanism. We identified the source as oxidation of DNA during acoustic shearing in samples containing reactive contaminants from the extraction process. We show generation of 8-oxoguanine (8-oxoG) lesions during DNA shearing, present analysis tools to detect oxidation in sequencing data and suggest methods to reduce DNA oxidation through the introduction of antioxidants. Further, informatics methods are presented to confidently filter these artifacts from sequencing data sets. Though only seen in a low percentage of reads in affected samples, such artifacts could have profoundly deleterious effects on the ability to confidently call rare mutations, and eliminating other possible sources of artifacts should become a priority for the research community.

Scotty: a web tool for designing RNA-Seq experiments to measure differential gene expression.

MOTIVATION: A common question arises at the beginning of every experiment where RNA-Seq is used to detect differential gene expression between two conditions: How many reads should we sequence? RESULTS: Scotty is an interactive web-based application that assists biologists to design an experiment with an appropriate sample size and read depth to satisfy the user-defined experimental objectives. This design can be based on data available from either pilot samples or publicly available datasets. AVAILABILITY: Scotty can be freely accessed on the web at http://euler.bc.edu/marthlab/scotty/scotty.php