Nathan D. Dees

Genome remodelling in a basal-like breast cancer metastasis and xenograft.

Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumour progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The metastasis contained two de novo mutations and a large deletion not present in the primary tumour, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumour mutations and displayed a mutation enrichment pattern that resembled the metastasis. Two overlapping large deletions, encompassing CTNNA1, were present in all three tumour samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared with the primary tumour indicate that secondary tumours may arise from a minority of cells within the primary tumour.

GENOMIC LANDSCAPE OF NON-SMALL CELL LUNG CANCER IN SMOKERS AND NEVER SMOKERS

We report the results of whole-genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and more than 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatin modification and DNA repair pathways were identified, along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never-smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions, including ROS1 and ALK, as well as novel metabolic enzymes. Cell-cycle and JAK-STAT pathways are significantly altered in lung cancer, along with perturbations in 54 genes that are potentially targetable with currently available drugs.

MuSiC: Identifying mutational significance in cancer genomes

Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery.

Clonal diversity of recurrently mutated genes in myelodysplastic syndromes

Recent studies suggest that most cases of myelodysplastic syndrome (MDS) are clonally heterogeneous, with a founding clone and multiple subclones. It is not known whether specific gene mutations typically occur in founding clones or subclones. We screened a panel of 94 candidate genes in a cohort of 157 patients with MDS or secondary acute myeloid leukemia (sAML). This included 150 cases with samples obtained at MDS diagnosis and 15 cases with samples obtained at sAML transformation (8 were also analyzed at the MDS stage). We performed whole-genome sequencing (WGS) to define the clonal architecture in eight sAML genomes and identified the range of variant allele frequencies (VAFs) for founding clone mutations. At least one mutation or cytogenetic abnormality was detected in 83% of the 150 MDS patients and 17 genes were significantly mutated (false discovery rate ⩽0.05). Individual genes and patient samples displayed a wide range of VAFs for recurrently mutated genes, indicating that no single gene is exclusively mutated in the founding clone. The VAFs of recurrently mutated genes did not fully recapitulate the clonal architecture defined by WGS, suggesting that comprehensive sequencing may be required to accurately assess the clonal status of recurrently mutated genes in MDS.

SciClone: Inferring clonal architecture and tracking the spatial and temporal patterns of tumor evolution

The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all of which may have clinical implications. Single tumor analysis already contributes to understanding these phenomena. However, cryptic subclones are frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating that accurately characterizing a tumor requires analyzing multiple samples from the same patient. To address this need, we present SciClone, a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations. We use it to detect subclones in acute myeloid leukemia and breast cancer samples that, though present at disease onset, are not evident from a single primary tumor sample. By doing so, we can track tumor evolution and identify the spatial origins of cells resisting therapy.

Clonal Architectures and Driver Mutations in Metastatic Melanomas

To reveal the clonal architecture of melanoma and associated driver mutations, whole genome sequencing (WGS) and targeted extension sequencing were used to characterize 124 melanoma cases. Significantly mutated gene analysis using 13 WGS cases and 15 additional paired extension cases identified known melanoma genes such as BRAF, NRAS, and CDKN2A, as well as a novel gene EPHA3, previously implicated in other cancer types. Extension studies using tumors from another 96 patients discovered a large number of truncation mutations in tumor suppressors (TP53 and RB1), protein phosphatases (e.g., PTEN, PTPRB, PTPRD, and PTPRT), as well as chromatin remodeling genes (e.g., ASXL3, MLL2, and ARID2). Deep sequencing of mutations revealed subclones in the majority of metastatic tumors from 13 WGS cases. Validated mutations from 12 out of 13 WGS patients exhibited a predominant UV signature characterized by a high frequency of C->T transitions occurring at the 3′ base of dipyrimidine sequences while one patient (MEL9) with a hypermutator phenotype lacked this signature. Strikingly, a subclonal mutation signature analysis revealed that the founding clone in MEL9 exhibited UV signature but the secondary clone did not, suggesting different mutational mechanisms for two clonal populations from the same tumor. Further analysis of four metastases from different geographic locations in 2 melanoma cases revealed phylogenetic relationships and highlighted the genetic alterations responsible for differential drug resistance among metastatic tumors. Our study suggests that clonal evaluation is crucial for understanding tumor etiology and drug resistance in melanoma.

Genome Modeling System: A Knowledge Management Platform for Genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Inactivation of RASA1 promotes melanoma tumorigenesis via R-Ras activation

Inactivation of Ras GTPase activating proteins (RasGAPs) can activate Ras, increasing the risk for tumor development. Utilizing a melanoma whole genome sequencing (WGS) data from 13 patients, we identified two novel, clustered somatic missense mutations (Y472H and L481F) in RASA1 (RAS p21 protein activator 1, also called p120RasGAP). We have shown that wild type RASA1, but not identified mutants, suppresses soft agar colony formation and tumor growth of BRAF mutated melanoma cell lines via its RasGAP activity toward R-Ras (related RAS viral (r-ras) oncogene homolog) isoform. Moreover, R-Ras increased and RASA1 suppressed Ral-A activation among Ras downstream effectors. In addition to mutations, loss of RASA1 expression was frequently observed in metastatic melanoma samples on melanoma tissue microarray (TMA) and a low level of RASA1 mRNA expression was associated with decreased overall survival in melanoma patients with BRAF mutations. Thus, these data support that RASA1 is inactivated by mutation or by suppressed expression in melanoma and that RASA1 plays a tumor suppressive role by inhibiting R-Ras, a previously less appreciated member of the Ras small GTPases.

Abstract LB-239: Mutational and clonal analyses across TCGA cancer types using the MuSiC suite of tools.

Within the field of cancer genomics, advances in next-generation sequencing and variant detection methods have tremendously reduced the costs of generating genomic data for large cohorts of patients in translational cancer research. These large datasets have enabled statistical analyses of somatic events in tumor-normal pairs, with the ultimate goal of understanding the molecular mechanisms underlying various cancer phenotypes. Here, we present results from the suite of tools collectively called MuSiC (Mutational Significance in Cancer), specifically designed towards this goal. Somatic alterations of more than 5000 tumors across 20 cancer types are now publicly available as part of The Cancer Genome Atlas (TCGA). This includes point mutations and small indels from exome sequencing, copy-number variants from SNP arrays, and gene and allele-specific expression from mRNA sequencing. We present results from the suite that integrates these data types to identify significantly altered genes, gene families, protein domains, and pathways. Also presented are the distribution of mutation types, frequencies, and patterns across cancer types, or across histological subtypes of tumors. Further, we identify mutations that can distinguish broader expression and/or methylation subtypes and clinically relevant phenotypes across the combined pan-cancer data set. Finally, we perform clonality analysis across several cancer types by integrating copy number data to identify important mutations that drive the development of new clones. Citation Format: Cyriac Kandoth, Michael D. McLellan, Christopher A. Miller, Charles Lu, Nathan Dees, Kai Ye, Beifang Niu, Michael C. Wendl, Richard K. Wilson, Li Ding. Mutational and clonal analyses across TCGA cancer types using the MuSiC suite of tools. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-239. doi:10.1158/1538-7445.AM2013-LB-239

Abstract 3170: Identification of novel genetic alterations driving melanoma tumorigenesis.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Recent high-throughput sequencing efforts have provided a comprehensive view of cancer genomes, revealing their complexity and heterogeneity. However, most of these studies remain descriptive without further functional and clinical validation of the candidate alterations, mainly due to the overwhelming number of somatic alterations present. To discover novel driver mutations of melanoma, massively parallel whole genome sequencing (WGS) was used to characterize 15 metastatic melanomas derived from 13 patients. A large number of somatic alterations were discovered in these tumors and hybridization capture-based validation confirmed 17,361 tier 1 point mutations, 84 tier 1 indels, and 411 somatic structural variants. As a pilot study to exploit this genomic data in order to identify novel genetic alterations driving melanoma tumorigenesis, we performed mutation proximity analysis to select candidates for further analysis. In this study, we addressed possible roles of DBC1 (Deleted in Bladder Cancer 1) and RASA1 (RAS p21 protein activator 1), which showed previously undocumented neighboring mutations. RASA1 is a GTPase activation protein that acts as a suppressor of RAS function. RASA1 has been implicated in actin filament polymerization, vascular development, cellular apoptosis, and cell motility. Our whole-genome analyses of melanomas identified two somatic missense mutations, targeting highly conserved neighboring Y472 and L481 in or around the PH domain in RASA1 in two samples. DBC1, also called BRINP, DBCCR1, and FAM5A, was previously shown to undergo loss of heterozygosity at 9q32-q33 in bladder cancer, and methylation silencing in bladder, breast, and lung cancers. Ectopic expression of DBC1 in bladder and lung cancer cells was reported to cause cell death and to inhibit cell proliferation, respectively. We observed six DBC1 missense mutations by whole genome analyses in four patients, including 2 neighboring mutations targeting S688 and S690. The shRNA-mediated knock down of DBC1 and RASA1 in melanocyte derived from Ink4a/Arf deletion/BRAF mutation background promoted proliferation, soft agar colony formation, and invasion. Ectopic expression of wild type DBC1 and RASA1 in human melanoma cell lines SKmel28 and WM983C (all with BRAFV600E), respectively, decreased soft agar colony formation, supporting their tumor suppressive roles. Various mutant forms of RASA1 and DBC1 were addressed for their roles. Interestingly, loss of RASA1 conferred decreased sensitivity to BRAF inhibitor Vemurafenib. In order to address the mutation frequency of DBC1 and RASA1, we analyzed additional melanoma samples and observed mutation rates of 21% for DBC1 (20/96 patients) and 9% for RASA1 (20/221). Therefore, our findings support that DBC1 and RASA1 play roles in melanoma suppression and the utility of genomic data for the identification of novel genes involved in tumorigenesis. Citation Format: Minjung Kim, Li Ding, Nathan Dees, Krishna L. Kanchi, Hyeran Sung, David Fenstermacher, Malachi Griffith, Gerry Linette, Lynn Cornelius, Vernon K. Sondak, James J. Mule, Richard K. Wilson, Jeffrey S. Weber. Identification of novel genetic alterations driving melanoma tumorigenesis. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3170. doi:10.1158/1538-7445.AM2013-3170