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1.  Methods and challenges in timing chromosomal abnormalities within cancer samples 
Bioinformatics  2013;29(24):3113-3120.
Motivation: Tumors acquire many chromosomal amplifications, and those acquired early in the lifespan of the tumor may be not only important for tumor growth but also can be used for diagnostic purposes. Many methods infer the order of the accumulation of abnormalities based on their occurrence in a large cohort of patients. Recently, Durinck et al. (2011) and Greenman et al. (2012) developed methods to order a single tumor’s chromosomal amplifications based on the patterns of mutations accumulated within those regions. This method offers an unprecedented opportunity to assess the etiology of a single tumor sample, but has not been widely evaluated.
Results: We show that the model for timing chromosomal amplifications is limited in scope, particularly for regions with high levels of amplification. We also show that the estimation of the order of events can be sensitive for events that occur early in the progression of the tumor and that the partial maximum likelihood method of Greenman et al. (2012) can give biased estimates, particularly for moderate read coverage or normal contamination. We propose a maximum-likelihood estimation procedure that fully accounts for sequencing variability and show that it outperforms the partial maximum-likelihood estimation method. We also propose a Bayesian estimation procedure that stabilizes the estimates in certain settings. We implement these methods on a small number of ovarian tumors, and the results suggest possible differences in how the tumors acquired amplifications.
Availability and implementation: We provide implementation of these methods in an R package cancerTiming, which is available from the Comprehensive R Archive Network (CRAN) at http://CRAN.R-project.org/.
Contact: epurdom@stat.Berkeley.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btt546
PMCID: PMC3842754  PMID: 24064421
2.  The Mutational Landscape of Lethal Castrate Resistant Prostate Cancer 
Nature  2012;487(7406):239-243.
Characterization of the prostate cancer transcriptome and genome has identified chromosomal rearrangements and copy number gains/losses, including ETS gene fusions, PTEN loss and androgen receptor (AR) amplification, that drive prostate cancer development and progression to lethal, metastatic castrate resistant prostate cancer (CRPC)1. As less is known about the role of mutations2–4, here we sequenced the exomes of 50 lethal, heavily-pretreated metastatic CRPCs obtained at rapid autopsy (including three different foci from the same patient) and 11 treatment naïve, high-grade localized prostate cancers. We identified low overall mutation rates even in heavily treated CRPC (2.00/Mb) and confirmed the monoclonal origin of lethal CRPC. Integrating exome copy number analysis identified disruptions of CHD1, which define a subtype of ETS fusionnegative prostate cancer. Similarly, we demonstrate that ETS2, which is deleted in ~1/3 of CRPCs (commonly through TMPRSS2:ERG fusions), is also deregulated through mutation. Further, we identified recurrent mutations in multiple chromatin/histone modifying genes, including MLL2 (mutated in 8.6% of prostate cancers), and demonstrate interaction of the MLL complex with AR, which is required for AR-mediated signaling. We also identified novel recurrent mutations in the AR collaborating factor FOXA1, which is mutated in 5 of 147 (3.4%) prostate cancers (both untreated localized prostate cancer and CRPC), and showed that mutated FOXA1 represses androgen signaling and increases tumour growth. Proteins that physically interact with AR, such as the ERG gene fusion product, FOXA1, MLL2, UTX, and ASXL1 were found to be mutated in CRPC. In summary, we describe the mutational landscape of a heavily treated metastatic cancer, identify novel mechanisms of AR signaling deregulated in prostate cancer, and prioritize candidates for future study.
doi:10.1038/nature11125
PMCID: PMC3396711  PMID: 22722839
3.  Personalized Oncology Through Integrative High-Throughput Sequencing: A Pilot Study 
Science translational medicine  2011;3(111):111ra121.
Individual cancers harbor a set of genetic aberrations that can be informative for identifying rational therapies currently available or in clinical trials. We implemented a pilot study to explore the practical challenges of applying high-throughput sequencing in clinical oncology. We enrolled patients with advanced or refractory cancer who were eligible for clinical trials. For each patient, we performed whole-genome sequencing of the tumor, targeted whole-exome sequencing of tumor and normal DNA, and transcriptome sequencing (RNA-Seq) of the tumor to identify potentially informative mutations in a clinically relevant time frame of 3 to 4 weeks. With this approach, we detected several classes of cancer mutations including structural rearrangements, copy number alterations, point mutations, and gene expression alterations. A multidisciplinary Sequencing Tumor Board (STB) deliberated on the clinical interpretation of the sequencing results obtained. We tested our sequencing strategy on human prostate cancer xenografts. Next, we enrolled two patients into the clinical protocol and were able to review the results at our STB within 24 days of biopsy. The first patient had metastatic colorectal cancer in which we identified somatic point mutations in NRAS, TP53, AURKA, FAS, and MYH11, plus amplification and overexpression of cyclin-dependent kinase 8 (CDK8). The second patient had malignant melanoma, in which we identified a somatic point mutation in HRAS and a structural rearrangement affecting CDKN2C. The STB identified the CDK8 amplification and Ras mutation as providing a rationale for clinical trials with CDK inhibitors or MEK (mitogenactivated or extracellular signal–regulated protein kinase kinase) and PI3K (phosphatidylinositol 3-kinase) inhibitors, respectively. Integrative high-throughput sequencing of patients with advanced cancer generates a comprehensive, individual mutational landscape to facilitate biomarker-driven clinical trials in oncology.
doi:10.1126/scitranslmed.3003161
PMCID: PMC3476478  PMID: 22133722
4.  Detection of Somatic Copy Number Alterations in Cancer Using Targeted Exome Capture Sequencing12 
Neoplasia (New York, N.Y.)  2011;13(11):1019-1025.
The research community at large is expending considerable resources to sequence the coding region of the genomes of tumors and other human diseases using targeted exome capture (i.e., “whole exome sequencing”). The primary goal of targeted exome sequencing is to identify nonsynonymous mutations that potentially have functional consequences. Here, we demonstrate that whole-exome sequencing data can also be analyzed for comprehensively monitoring somatic copy number alterations (CNAs) by benchmarking the technique against conventional array CGH. A series of 17 matched tumor and normal tissues from patients with metastatic castrate-resistant prostate cancer was used for this assessment. We show that targeted exome sequencing reliably identifies CNAs that are common in advanced prostate cancer, such as androgen receptor (AR) gain and PTEN loss. Taken together, these data suggest that targeted exome sequencing data can be effectively leveraged for the detection of somatic CNAs in cancer.
PMCID: PMC3223606  PMID: 22131877

Results 1-4 (4)