Cancer genomics

Cortés-Ciriano I, Lee JJK, Xi R, Jain D, Jung YL, Yang L, Gordenin D, Klimczak LJ, Zhang CZ, Pellman DS, Group PCAWGSVW, Park PJ, Consortium PCAWG. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing [Internet]. Nature Genetics 2020;52(3):331-341. Publisher's VersionAbstract
Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer.
Luquette JL, Bohrson CL, Sherman M, Park PJ. Identification of somatic mutations in single cell DNA sequencing data using a spatial model of allelic imbalance. Nature Communications 2019;10(1):3908.Abstract
Recent advances in single cell technology have enabled dissection of cellular heterogeneity in great detail. However, analysis of single cell DNA sequencing data remains challenging due to bias and artifacts that arise during DNA extraction and whole-genome amplification, including allelic imbalance and dropout. Here, we present a framework for statistical estimation of allele-specific amplification imbalance at any given position in single cell whole-genome sequencing data by utilizing the allele frequencies of heterozygous single nucleotide polymorphisms in the neighborhood. The resulting allelic imbalance profile is critical for determining whether the variant allele fraction of an observed mutation is consistent with the expected fraction for a true variant. This method, implemented in SCAN-SNV (Single Cell ANalysis of SNVs), substantially improves the identification of somatic variants in single cells. Our allele balance framework is broadly applicable to genotype analysis of any variant type in any data that might exhibit allelic imbalance.
Gulhan DC, Lee JJ-K, Melloni GEM, Cortés-Ciriano I, Park PJ. Detecting the mutational signature of homologous recombination deficiency in clinical samples. Nature Genetics 2019;51(5):912-919.Abstract
Mutations in BRCA1 and/or BRCA2 (BRCA1/2) are the most common indication of deficiency in the homologous recombination (HR) DNA repair pathway. However, recent genome-wide analyses have shown that the same pattern of mutations found in BRCA1/2-mutant tumors is also present in several other tumors. Here, we present a new computational tool called Signature Multivariate Analysis (SigMA), which can be used to accurately detect the mutational signature associated with HR deficiency from targeted gene panels. Whereas previous methods require whole-genome or whole-exome data, our method detects the HR-deficiency signature even from low mutation counts, by using a likelihood-based measure combined with machine-learning techniques. Cell lines that we identify as HR deficient show a significant response to poly (ADP-ribose) polymerase (PARP) inhibitors; patients with ovarian cancer whom we found to be HR deficient show a significantly longer overall survival with platinum regimens. By enabling panel-based identification of mutational signatures, our method substantially increases the number of patients that may be considered for treatments targeting HR deficiency.
Cortes-Ciriano I*, Lee S*, Park W-Y, Kim T-M**, Park PJ**. A molecular portrait of microsatellite instability across multiple cancers. Nat Commun 2017;8:15180.Abstract
Microsatellite instability (MSI) refers to the hypermutability of short repetitive sequences in the genome caused by impaired DNA mismatch repair. Although MSI has been studied for decades, large amounts of sequencing data now available allows us to examine the molecular fingerprints of MSI in greater detail. Here, we analyse ∼8,000 exomes and ∼1,000 whole genomes of cancer patients across 23 cancer types. Our analysis reveals that the frequency of MSI events is highly variable within and across tumour types. We also identify genes in DNA repair and oncogenic pathways recurrently subject to MSI and uncover non-coding loci that frequently display MSI. Finally, we propose a highly accurate exome-based predictive model for the MSI phenotype. These results advance our understanding of the genomic drivers and consequences of MSI, and our comprehensive catalogue of tumour-type-specific MSI loci will enable panel-based MSI testing to identify patients who are likely to benefit from immunotherapy.
Xi R, Lee S, Xia Y, Kim T-M, Park PJ. Copy number analysis of whole-genome data using BIC-seq2 and its application to detection of cancer susceptibility variants. Nucleic Acids Res 2016;Abstract

Whole-genome sequencing data allow detection of copy number variation (CNV) at high resolution. However, estimation based on read coverage along the genome suffers from bias due to GC content and other factors. Here, we develop an algorithm called BIC-seq2 that combines normalization of the data at the nucleotide level and Bayesian information criterion-based segmentation to detect both somatic and germline CNVs accurately. Analysis of simulation data showed that this method outperforms existing methods. We apply this algorithm to low coverage whole-genome sequencing data from peripheral blood of nearly a thousand patients across eleven cancer types in The Cancer Genome Atlas (TCGA) to identify cancer-predisposing CNV regions. We confirm known regions and discover new ones including those covering KMT2C, GOLPH3, ERBB2 and PLAG1 Analysis of colorectal cancer genomes in particular reveals novel recurrent CNVs including deletions at two chromatin-remodeling genes RERE and NPM2 This method will be useful to many researchers interested in profiling CNVs from whole-genome sequencing data.

Yang L*, Lee M-S*, Lu H*, Oh D-Y, Kim YJ, Park D, Park G, Ren X, Bristow CA, Haseley PS, Lee S, Pantazi A, Kucherlapati R, Park W-Y, Scott KL**, Choi Y-L**, Park PJ**. Analyzing Somatic Genome Rearrangements in Human Cancers by Using Whole-Exome Sequencing. Am J Hum Genet 2016;98(5):843-56.Abstract

Although exome sequencing data are generated primarily to detect single-nucleotide variants and indels, they can also be used to identify a subset of genomic rearrangements whose breakpoints are located in or near exons. Using >4,600 tumor and normal pairs across 15 cancer types, we identified over 9,000 high confidence somatic rearrangements, including a large number of gene fusions. We find that the 5' fusion partners of functional fusions are often housekeeping genes, whereas the 3' fusion partners are enriched in tyrosine kinases. We establish the oncogenic potential of ROR1-DNAJC6 and CEP85L-ROS1 fusions by showing that they can promote cell proliferation in vitro and tumor formation in vivo. Furthermore, we found that ∼4% of the samples have massively rearranged chromosomes, many of which are associated with upregulation of oncogenes such as ERBB2 and TERT. Although the sensitivity of detecting structural alterations from exomes is considerably lower than that from whole genomes, this approach will be fruitful for the multitude of exomes that have been and will be generated, both in cancer and in other diseases.

Tica J*, Lee E*, Untergasser A, Meiers S, Garfield DA, Gokcumen O, Furlong EEM, Park PJ, Stütz AM**, Korbel JO**. Next-generation sequencing-based detection of germline L1-mediated transductions. BMC Genomics 2016;17(1):342.Abstract

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.

Lee J-K, Choi Y-L, Kwon M, Park PJ. Mechanisms and Consequences of Cancer Genome Instability: Lessons from Genome Sequencing Studies. Annu Rev Pathol 2016;Abstract

During tumor evolution, cancer cells can accumulate numerous genetic alterations, ranging from single nucleotide mutations to whole-chromosomal changes. Although a great deal of progress has been made in the past decades in characterizing genomic alterations, recent cancer genome sequencing studies have provided a wealth of information on the detailed molecular profiles of such alterations in various types of cancers. Here, we review our current understanding of the mechanisms and consequences of cancer genome instability, focusing on the findings uncovered through analysis of exome and whole-genome sequencing data. These analyses have shown that most cancers have evidence of genome instability, and the degree of instability is variable within and between cancer types. Importantly, we describe some recent evidence supporting the idea that chromosomal instability could be a major driving force in tumorigenesis and cancer evolution, actively shaping the genomes of cancer cells to maximize their survival advantage. Expected final online publication date for the Annual Review of Pathology: Mechanisms of Disease Volume 11 is May 23, 2016. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

Bersani F, Lee E, Kharchenko PV, Xu AW, Liu M, Xega K, MacKenzie OC, Brannigan BW, Wittner BS, Jung H, Ramaswamy S, Park PJ, Maheswaran S, Ting DT, Haber DA. Pericentromeric satellite repeat expansions through RNA-derived DNA intermediates in cancer. Proc Natl Acad Sci U S A 2015;112(49):15148-53.Abstract

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.

Cancer Genome Atlas Research Network TCGA. The Molecular Taxonomy of Primary Prostate Cancer. Cell 2015;163(4):1011-25.Abstract

There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, and FLI1) or mutations (SPOP, FOXA1, and IDH1). Epigenetic profiles showed substantial heterogeneity, including an IDH1 mutant subset with a methylator phenotype. Androgen receptor (AR) activity varied widely and in a subtype-specific manner, with SPOP and FOXA1 mutant tumors having the highest levels of AR-induced transcripts. 25% of the prostate cancers had a presumed actionable lesion in the PI3K or MAPK signaling pathways, and DNA repair genes were inactivated in 19%. Our analysis reveals molecular heterogeneity among primary prostate cancers, as well as potentially actionable molecular defects.

Jung H, Lee D, Lee J, Park D, Kim YJ, Park W-Y, Hong D**, Park PJ**, Lee E**. Intron retention is a widespread mechanism of tumor-suppressor inactivation. Nat Genet 2015;47(11):1242-8.Abstract

-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.

Cancer Genome Atlas Research Network TCGA. Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med 2015;372(26):2481-98.Abstract

BACKGROUND: Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas.

METHODS: We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes.

RESULTS: Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma.

CONCLUSIONS: The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).

Chu C, Borges-Monroy R, Viswanadham VV, Lee S, Li H, Lee EA**, Park PJ**. Comprehensive identification of transposable element insertions using multiple sequencing technologies. Nat Commun 2021;12(1):3836.Abstract
Transposable elements (TEs) help shape the structure and function of the human genome. When inserted into some locations, TEs may disrupt gene regulation and cause diseases. Here, we present xTea (x-Transposable element analyzer), a tool for identifying TE insertions in whole-genome sequencing data. Whereas existing methods are mostly designed for short-read data, xTea can be applied to both short-read and long-read data. Our analysis shows that xTea outperforms other short read-based methods for both germline and somatic TE insertion discovery. With long-read data, we created a catalogue of polymorphic insertions with full assembly and annotation of insertional sequences for various types of retroelements, including pseudogenes and endogenous retroviruses. Notably, we find that individual genomes have an average of nine groups of full-length L1s in centromeres, suggesting that centromeres and other highly repetitive regions such as telomeres are a significant yet unexplored source of active L1s. xTea is available at https://github.com/parklab/xTea .
Jain D, Chu C, Alver BH, Lee S, Lee EA, Park PJ*. HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data. Bioinformatics 2021;37(8):1045-1051.Abstract
Hi-C is a common technique for assessing 3D chromatin conformation. Recent studies have shown that long-range interaction information in Hi-C data can be used to generate chromosome-length genome assemblies and identify large-scale structural variations. Here, we demonstrate the use of Hi-C data in detecting mobile transposable element (TE) insertions genome-wide. Our pipeline Hi-C-based TE analyzer (HiTea) capitalizes on clipped Hi-C reads and is aided by a high proportion of discordant read pairs in Hi-C data to detect insertions of three major families of active human TEs. Despite the uneven genome coverage in Hi-C data, HiTea is competitive with the existing callers based on whole-genome sequencing (WGS) data and can supplement the WGS-based characterization of the TE-insertion landscape. We employ the pipeline to identify TE-insertions from human cell-line Hi-C samples. AVAILABILITY AND IMPLEMENTATION: HiTea is available at https://github.com/parklab/HiTea and as a Docker image. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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