About half of all cancers have somatic integrations of retrotransposons. To characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,774 cancer genomes from 37 histological cancer subtypes. We identified 20,230 somatically acquired retrotransposition events, affecting 43% of samples, and spanning a range of event types. L1 insertions emerged as the third most frequent type of somatic structural variation in cancer. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, sometimes removing tumour suppressor genes, as well as inducing complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles of genomic instability, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications in the initiation and/or development of human tumours.
Targeted next-generation sequencing (NGS) is increasingly being adopted in clinical laboratories for genomic diagnostic tests.
We developed a new computational method, DeviCNV, intended for the detection of exon-level copy number variants (CNVs) in targeted NGS data. DeviCNV builds linear regression models with bootstrapping for every probe to capture the relationship between read depth of an individual probe and the median of read depth values of all probes in the sample. From the regression models, it estimates the read depth ratio of the observed and predicted read depth with confidence interval for each probe which is applied to a circular binary segmentation (CBS) algorithm to obtain CNV candidates. Then, it assigns confidence scores to those candidates based on the reliability and strength of the CNV signals inferred from the read depth ratios of the probes within them. Finally, it also provides gene-centric plots with confidence levels of CNV candidates for visual inspection. We applied DeviCNV to targeted NGS data generated for newborn screening and demonstrated its ability to detect novel pathogenic CNVs from clinical samples.
We propose a new pragmatic method for detecting CNVs in targeted NGS data with an intuitive visualization and a systematic method to assign confidence scores for candidate CNVs. Since DeviCNV was developed for use in clinical diagnosis, sensitivity is increased by the detection of exon-level CNVs.
A systematic cataloguing of genes impacted by genomic rearrangement, using multiple patient cohorts and cancer types, can provide insight into cancer-relevant alterations outside of exome boundaries. By integrative analysis of whole genome sequencing (predominantly low pass) and gene expression data from 1448 cancers involving 18 histopathological types in The Cancer Genome Atlas, we identified hundreds of genes for which the nearby presence (within 100kb) of a somatic Structural Variant (SV) breakpoint was associated with altered expression. While genomic rearrangements were associated with widespread copy number alteration (CNA) patterns, approximately 1100 genes—including over-expressed cancer driver genes (e.g. TERT, ERBB2, CDK12, CDK4) and under-expressed tumor suppressors (e.g. TP53, RB1, PTEN, STK11)—showed SV-associated deregulation independent of CNA. SVs associated with disruption of topologically-associated domains, enhancer hijacking, or fusion transcripts were implicated in gene up-regulation patterns. For cancer-relevant pathways, SVs considerably extended upon how genes are impacted, beyond point mutation or CNA.
Long interspersed nuclear element-1 (LINE-1 or L1) retrotransposons are normally suppressed in somatic tissues mainly due to DNA methylation and antiviral defense. However, the mechanism to suppress L1s may be disrupted in cancers, thus allowing L1s to act as insertional mutagens and cause genomic rearrangement and instability. Whereas the frequency of somatic L1 insertions varies greatly among individual tumors, much remains to be learned about underlying genetic, cellular, or environmental factors. Here, we report multiple correlates of L1 activity in stomach, colorectal, and esophageal tumors through an integrative analysis of cancer whole genome and matched RNA sequencing profiles. Clinical indicators of tumor progression, such as tumor grade and patient age, showed positive association. A potential L1 expression suppressor, TP53, was mutated in tumors with frequent L1 insertions. We characterized the effects of somatic L1 insertions on mRNA splicing and expression, and demonstrated an increased risk of gene disruption in retrotransposition-prone cancers. In particular, we found that a cancer-specific L1 insertion in an exon of MOV10, a key L1 suppressor, caused exon skipping and decreased expression of the affected allele due to nonsense-mediated decay in a tumor with a high L1 insertion load. Importantly, tumors with high immune activity, for example, those associated with Epstein-Barr virus infection or microsatellite instability, tended to carry a low number of L1 insertions in genomes with high expression levels of L1 suppressors such as APOBEC3s and SAMHD1. Our results indicate that cancer immunity may contribute to genome stability by suppressing L1 retrotransposition in gastrointestinal cancers.
McConnell MJ*, Moran JV*, Abyzov A, Akbarian S, Bae T, Cortes-Ciriano I, Erwin JA, Fasching L, Flasch DA, Freed D, Ganz J, Jaffe AE, Kwan KY, Kwon M, Lodato MA, Mills RE, Paquola ACM, Rodin RE, Rosenbluh C, Sestan N, Sherman MA, Shin JH, Song S, Straub RE, Thorpe J, Weinberger DR, Urban AE, Zhou B, Gage FH, Lehner T, Senthil G, Walsh CA, Chess A, Courchesne E, Gleeson JG, Kidd JM, Park PJ, Pevsner J, Vaccarino FM, Brain Somatic Mosaicism Network (incl. Lee EA). Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. Science 2017;356(6336)Abstract
Neuropsychiatric disorders have a complex genetic architecture. Human genetic population-based studies have identified numerous heritable sequence and structural genomic variants associated with susceptibility to neuropsychiatric disease. However, these germline variants do not fully account for disease risk. During brain development, progenitor cells undergo billions of cell divisions to generate the ~80 billion neurons in the brain. The failure to accurately repair DNA damage arising during replication, transcription, and cellular metabolism amid this dramatic cellular expansion can lead to somatic mutations. Somatic mutations that alter subsets of neuronal transcriptomes and proteomes can, in turn, affect cell proliferation and survival and lead to neurodevelopmental disorders. The long life span of individual neurons and the direct relationship between neural circuits and behavior suggest that somatic mutations in small populations of neurons can significantly affect individual neurodevelopment. The Brain Somatic Mosaicism Network has been founded to study somatic mosaicism both in neurotypical human brains and in the context of complex neuropsychiatric disorders.
We performed an integrated analysis of proteomic and transcriptomic datasets to develop potential diagnostic markers for early pancreatic cancer. In the discovery phase, a multiple reaction monitoring assay of 90 proteins identified by either gene expression analysis or global serum proteome profiling was established and applied to 182 clinical specimens. Nine proteins (P < 0.05) were selected for the independent validation phase and quantified using stable isotope dilution-multiple reaction monitoring-mass spectrometry in 456 specimens. Of these proteins, four proteins (apolipoprotein A-IV, apolipoprotein CIII, insulin-like growth factor binding protein 2 and tissue inhibitor of metalloproteinase 1) were significantly altered in pancreatic cancer in both the discovery and validation phase (P < 0.01). Moreover, a panel including carbohydrate antigen 19-9, apolipoprotein A-IV and tissue inhibitor of metalloproteinase 1 showed better performance for distinguishing early pancreatic cancer from pancreatitis (Area under the curve = 0.934, 86% sensitivity at fixed 90% specificity) than carbohydrate antigen 19-9 alone (71% sensitivity).Overall, we present the panel of robust biomarkers for early pancreatic cancer diagnosis through bioinformatics analysis that combined transcriptomic and proteomic data as well as rigorous validation on a large number of independent clinical samples.
In many next-generation sequencing (NGS) studies, multiple samples or data types are profiled for each individual. An important quality control (QC) step in these studies is to ensure that datasets from the same subject are properly paired. Given the heterogeneity of data types, file types and sequencing depths in a multi-dimensional study, a robust program that provides a standardized metric for genotype comparisons would be useful. Here, we describe NGSCheckMate, a user-friendly software package for verifying sample identities from FASTQ, BAM or VCF files. This tool uses a model-based method to compare allele read fractions at known single-nucleotide polymorphisms, considering depth-dependent behavior of similarity metrics for identical and unrelated samples. Our evaluation shows that NGSCheckMate is effective for a variety of data types, including exome sequencing, whole-genome sequencing, RNA-seq, ChIP-seq, targeted sequencing and single-cell whole-genome sequencing, with a minimal requirement for sequencing depth (>0.5X). An alignment-free module can be run directly on FASTQ files for a quick initial check. We recommend using this software as a QC step in NGS studies. AVAILABILITY: https://github.com/parklab/NGSCheckMate.
Zhang Y, Kwok-Shing Ng P, Kucherlapati M, Chen F, Liu Y, Tsang YH, de Velasco G, Jeong KJ, Akbani R, Hadjipanayis A, Pantazi A, Bristow CA, Lee E, Mahadeshwar HS, Tang J, Zhang J, Yang L, Seth S, Lee S, Ren X, Song X, Sun H, Seidman J, Luquette LJ, Xi R, Chin L, Protopopov A, Westbrook TF, Shelley CS, Choueiri TK, Ittmann M, Van Waes C, Weinstein JN, Liang H, Henske EP, Godwin AK, Park PJ, Kucherlapati R, Scott KL, Mills GB, Kwiatkowski DJ, Creighton CJ. A Pan-Cancer Proteogenomic Atlas of PI3K/AKT/mTOR Pathway Alterations. Cancer Cell 2017;31(6):820-832.e3.Abstract
Molecular alterations involving the PI3K/AKT/mTOR pathway (including mutation, copy number, protein, or RNA) were examined across 11,219 human cancers representing 32 major types. Within specific mutated genes, frequency, mutation hotspot residues, in silico predictions, and functional assays were all informative in distinguishing the subset of genetic variants more likely to have functional relevance. Multiple oncogenic pathways including PI3K/AKT/mTOR converged on similar sets of downstream transcriptional targets. In addition to mutation, structural variations and partial copy losses involving PTEN and STK11 showed evidence for having functional relevance. A substantial fraction of cancers showed high mTOR pathway activity without an associated canonical genetic or genomic alteration, including cancers harboring IDH1 or VHL mutations, suggesting multiple mechanisms for pathway activation.
Stem cells determine homeostasis and repair of many tissues and are increasingly recognized as functionally heterogeneous. To define the extent of-and molecular basis for-heterogeneity, we overlaid functional, transcriptional, and epigenetic attributes of hematopoietic stem cells (HSCs) at a clonal level using endogenous fluorescent tagging. Endogenous HSC had clone-specific functional attributes over time in vivo. The intra-clonal behaviors were highly stereotypic, conserved under the stress of transplantation, inflammation, and genotoxic injury, and associated with distinctive transcriptional, DNA methylation, and chromatin accessibility patterns. Further, HSC function corresponded to epigenetic configuration but not always to transcriptional state. Therefore, hematopoiesis under homeostatic and stress conditions represents the integrated action of highly heterogeneous clones of HSC with epigenetically scripted behaviors. This high degree of epigenetically driven cell autonomy among HSCs implies that refinement of the concepts of stem cell plasticity and of the stem cell niche is warranted.
Accumulation of somatic changes, due to environmental and endogenous lesions, in the human genome is associated with aging and cancer. Understanding the impacts of these processes on mutagenesis is fundamental to understanding the etiology, and improving the prognosis and prevention of cancers and other genetic diseases. Previous methods relying on either the generation of induced pluripotent stem cells, or sequencing of single-cell genomes were inherently error-prone and did not allow independent validation of the mutations. In the current study we eliminated these potential sources of error by high coverage genome sequencing of single-cell derived clonal fibroblast lineages, obtained after minimal propagation in culture, prepared from skin biopsies of two healthy adult humans. We report here accurate measurement of genome-wide magnitude and spectra of mutations accrued in skin fibroblasts of healthy adult humans. We found that every cell contains at least one chromosomal rearrangement and 600–13,000 base substitutions. The spectra and correlation of base substitutions with epigenomic features resemble many cancers. Moreover, because biopsies were taken from body parts differing by sun exposure, we can delineate the precise contributions of environmental and endogenous factors to the accrual of genetic changes within the same individual. We show here that UV-induced and endogenous DNA damage can have a comparable impact on the somatic mutation loads in skin fibroblasts. Trial Registration: ClinicalTrials.gov NCT01087307.
BACKGROUND: While active LINE-1 (L1) elements possess the ability to mobilize flanking sequences to different genomic loci through a process termed transduction influencing genomic content and structure, an approach for detecting polymorphic germline non-reference transductions in massively-parallel sequencing data has been lacking. RESULTS: Here we present the computational approach TIGER (Transduction Inference in GERmline genomes), enabling the discovery of non-reference L1-mediated transductions by combining L1 discovery with detection of unique insertion sequences and detailed characterization of insertion sites. We employed TIGER to characterize polymorphic transductions in fifteen genomes from non-human primate species (chimpanzee, orangutan and rhesus macaque), as well as in a human genome. We achieved high accuracy as confirmed by PCR and two single molecule DNA sequencing techniques, and uncovered differences in relative rates of transduction between primate species. CONCLUSIONS: By enabling detection of polymorphic transductions, TIGER makes this form of relevant structural variation amenable for population and personal genome analysis.
Whether somatic mutations contribute functional diversity to brain cells is a long-standing question. Single-neuron genomics enables direct measurement of somatic mutation rates in human brain and promises to answer this question. A recent study (Upton et al., 2015) reported high rates of somatic LINE-1 element (L1) retrotransposition in the hippocampus and cerebral cortex that would have major implications for normal brain function, and suggested that these events preferentially impact genes important for neuronal function. We identify aspects of the single-cell sequencing approach, bioinformatic analysis, and validation methods that led to thousands of artifacts being interpreted as somatic mutation events. Our reanalysis supports a mutation frequency of approximately 0.2 events per cell, which is about fifty-fold lower than reported, confirming that L1 elements mobilize in some human neurons but indicating that L1 mosaicism is not ubiquitous. Through consideration of the challenges identified, we provide a foundation and framework for designing single-cell genomics studies.
Somatic mutations occur during brain development and are increasingly implicated as a cause of neurogenetic disease. However, the patterns in which somatic mutations distribute in the human brain are unknown. We used high-coverage whole-genome sequencing of single neurons from a normal individual to identify spontaneous somatic mutations as clonal marks to track cell lineages in human brain. Somatic mutation analyses in >30 locations throughout the nervous system identified multiple lineages and sublineages of cells marked by different LINE-1 (L1) retrotransposition events and subsequent mutation of poly-A microsatellites within L1. One clone contained thousands of cells limited to the left middle frontal gyrus, whereas a second distinct clone contained millions of cells distributed over the entire left hemisphere. These patterns mirror known somatic mutation disorders of brain development and suggest that focally distributed mutations are also prevalent in normal brains. Single-cell analysis of somatic mutation enables tracing of cell lineage clones in human brain.
A substantial fraction of disease-causing mutations are pathogenic through aberrant splicing. Although genome profiling studies have identified somatic single-nucleotide variants (SNVs) in cancer, the extent to which these variants trigger abnormal splicing has not been systematically examined. Here we analyzed RNA sequencing and exome data from 1,812 patients with cancer and identified ∼900 somatic exonic SNVs that disrupt splicing. At least 163 SNVs, including 31 synonymous ones, were shown to cause intron retention or exon skipping in an allele-specific manner, with ∼70% of the SNVs occurring on the last base of exons. Notably, SNVs causing intron retention were enriched in tumor suppressors, and 97% of these SNVs generated a premature termination codon, leading to loss of function through nonsense-mediated decay or truncated protein. We also characterized the genomic features predictive of such splicing defects. Overall, this work demonstrates that intron retention is a common mechanism of tumor-suppressor inactivation.
Aberrant transcription of the pericentromeric human satellite II (HSATII) repeat is present in a wide variety of epithelial cancers. In deriving experimental systems to study its deregulation, we observed that HSATII expression is induced in colon cancer cells cultured as xenografts or under nonadherent conditions in vitro, but it is rapidly lost in standard 2D cultures. Unexpectedly, physiological induction of endogenous HSATII RNA, as well as introduction of synthetic HSATII transcripts, generated cDNA intermediates in the form of DNA/RNA hybrids. Single molecule sequencing of tumor xenografts showed that HSATII RNA-derived DNA (rdDNA) molecules are stably incorporated within pericentromeric loci. Suppression of RT activity using small molecule inhibitors reduced HSATII copy gain. Analysis of whole-genome sequencing data revealed that HSATII copy number gain is a common feature in primary human colon tumors and is associated with a lower overall survival. Together, our observations suggest that cancer-associated derepression of specific repetitive sequences can promote their RNA-driven genomic expansion, with potential implications on pericentromeric architecture.
Neurons live for decades in a postmitotic state, their genomes susceptible to DNA damage. Here we survey the landscape of somatic single-nucleotide variants (SNVs) in the human brain. We identified thousands of somatic SNVs by single-cell sequencing of 36 neurons from the cerebral cortex of three normal individuals. Unlike germline and cancer SNVs, which are often caused by errors in DNA replication, neuronal mutations appear to reflect damage during active transcription. Somatic mutations create nested lineage trees, allowing them to be dated relative to developmental landmarks and revealing a polyclonal architecture of the human cerebral cortex. Thus, somatic mutations in the brain represent a durable and ongoing record of neuronal life history, from development through postmitotic function.
Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Here, we describe the genomic landscape of 496 PTCs. We observed a low frequency of somatic alterations (relative to other carcinomas) and extended the set of known PTC driver alterations to include EIF1AX, PPM1D, and CHEK2 and diverse gene fusions. These discoveries reduced the fraction of PTC cases with unknown oncogenic driver from 25% to 3.5%. Combined analyses of genomic variants, gene expression, and methylation demonstrated that different driver groups lead to different pathologies with distinct signaling and differentiation characteristics. Similarly, we identified distinct molecular subgroups of BRAF-mutant tumors, and multidimensional analyses highlighted a potential involvement of oncomiRs in less-differentiated subgroups. Our results propose a reclassification of thyroid cancers into molecular subtypes that better reflect their underlying signaling and differentiation properties, which has the potential to improve their pathological classification and better inform the management of the disease.
Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies.
Davis CF, Ricketts CJ, Wang M, Yang L, Cherniack AD, Shen H, Buhay C, Kang H, Kim SC, Fahey CC, Hacker KE, Bhanot G, Gordenin DA, Chu A, Gunaratne PH, Biehl M, Seth S, Kaipparettu BA, Bristow CA, Donehower LA, Wallen EM, Smith AB, Tickoo SK, Tamboli P, Reuter V, Schmidt LS, Hsieh JJ, Choueiri TK, Hakimi AA, The Cancer Genome Atlas Research Network (incl. Lee E), Chin L, Meyerson M, Kucherlapati R, Park W-Y, Robertson GA, Laird PW, Henske EP, Kwiatkowski DJ, Park PJ, Morgan M, Shuch B, Muzny D, Wheeler DA, Linehan MW, Gibbs RA, Rathmell KW, Creighton CJ. The somatic genomic landscape of chromophobe renal cell carcinoma. Cancer Cell 2014;26(3):319-330.Abstract
We describe the landscape of somatic genomic alterations of 66 chromophobe renal cell carcinomas (ChRCCs) on the basis of multidimensional and comprehensive characterization, including mtDNA and whole-genome sequencing. The result is consistent that ChRCC originates from the distal nephron compared with other kidney cancers with more proximal origins. Combined mtDNA and gene expression analysis implicates changes in mitochondrial function as a component of the disease biology, while suggesting alternative roles for mtDNA mutations in cancers relying on oxidative phosphorylation. Genomic rearrangements lead to recurrent structural breakpoints within TERT promoter region, which correlates with highly elevated TERT expression and manifestation of kataegis, representing a mechanism of TERT upregulation in cancer distinct from previously observed amplifications and point mutations.
The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.