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Enrichment of Immune signaling in the integrated pan-cancer cluster. Different level of evidence support the association of the integrated pan-cancer cluster with an immune phenotype. (A) Enrichment of T- and B-cell signaling shown on the integrated map, yellow gradient (see Supplemental Methods). (B) Enrichment of high ESTIMATE scores in the pan-cancer samples, waterfall plot with pan-cancer cluster samples in red. (C) Enrichment of the immune-related pathways identified by differential expression analysis. (D) Unsupervised analysis of master regulator activities inferred by the MARINa method. Gene clusters enriched for T- and B-cell signaling, interferon signaling, and TNFA via NFKB signaling, red font. (E) The top enriched pathways based on the output of master regulator scores derived with MARINa are immune-related. (F) Copy number events in the integrated pan-cancer cluster compared to other samples in the full cohort. The pan-cancer cluster shows a lower number of copy number events in both arm-level events and focal events. Arm-level events (pan-cancer group on the right, background cohort on the left). (G) Same as F but focal events (pan-cancer group on the right, background cohort on the left). (H) Purity estimates in the integrated pan-cancer cluster compared to all other samples in the cohort. The pan-cancer cluster (green box) shows lower purity when compared to the whole cohort as a background (yellow box). This finding is consistent with other analyses indicating high immune signaling in the pan-cancer cluster.

Supplemental Figure 1: RSS transformed correlations correct for platform-specific inflation biases. Maps produced from different molecular data types. Samples in the maps are colored by tissue of origin. (A) Similarity score distributions for every pair of samples for each individual data platform. Spearman Rho was computed for mRNA, miRNA, RPPA, SCNV, and methylation platforms. HOCUS score was used for mutation data. (B) RSS-standardized similarity scores for every pair of samples for each individual data platform. The density curves demonstrate that RSS transformation corrects for platform-specific inflation biases. (C) (i)-(vi) Maps produced from each of the six molecular data types using OpenOrd layout. (vii) mRNA expression map produced using Principal Component Analysis method. Principal components 1 and 2 are used to represent the mRNA expression space. (viii) mRNA expression map produced using tSNE method. Dimensions 1 and 2 are used to represent the mRNA expression space. (D) Maps produced from inferred gene activities using the PARADIGM and SPIA methods. (E) Maps integrating more than one molecular data type.

Molecular subtype visualization. Known biology recapitulated by the mRNA expression map. (A) BRCA molecular subtypes and their layout in the map. The map shows that tumors of the same molecular subtype tend to cluster together, with very little mixing of those subtypes, indicating that those subtypes are indeed molecularly different. (B) Estrogen signaling (yellow) and basal signaling (blue) are the top differentiating programs between the basal and non-basal BRCA tumors. Very few tumors exhibit signals of both programs (green). The group of samples labeled as Basal subtype in part A predominantly exhibits the basal signaling program and the group of samples consisting of LumA (for luminal A) and LumB (for luminal B) in part A predominantly exhibits the estrogen signaling program. (C) Association of TP53 mutations (blue) with basal breast tumors and PIK3CA mutations (yellow) with luminal tumors demonstrates at-a-glance view of genomic event association with molecular subtypes in the map. Samples that exhibit both mutations are shown in green. (D) COAD and READ tumors cluster together (left) and the map separates genomically stable and unstable tumors (right). (E) BLCA tumors separate into three previously discovered molecular subtypes. These subtypes are BLCA-core, BLCA-lung-like, and BLCA-squamous-like. (F) KIRC tumors are deficient in MSH2 (activity level indicated by the intensity of yellow), a component of the DNA mismatch repair pathway. This is a known characterization of KIRC tumors. (G) Co-occurrence of VHL mutations (green) and high HIF1A activity (indicated by the intensity of yellow) in KIRC tumors. Samples colored in yellow indicate an absence of VHL mutation but high HIF1A activity. Samples colored in green indicate both the presence of VHL mutation and high HIF1A activity. No samples show a presence of VHL mutation and low HIF1A activity (such samples would be colored in blue). (H) Spatial correlation analysis (SCA). Mutual exclusivity of RB1 mutations and CDKN2A deletions. These two events do not co-occur in the same patients even when they occur in patients clustering in the same regions of the map. (I) SCA - positive spatial correlation of RB1 mutations and PTEN mutations. In regions of the map where both of these events occur, they tend to occur in the same patients. (J) The overlap in gene signatures distinctive of the Tumor Map's relative positioning of BRCA molecular subtypes. HER2+ tumors share more differentially expressed genes in common between luminal than basal tumors. The subtype groupings are defined by BRCA sample annotations. Differential expression analysis resulted in 150-gene signatures for each subtype. Venn-diagram of these gene signatures shows the overlap between gene sets for each of the subtype.

More detail into the methodology behind the resource are provided as well as proof-of-concept benchmarks.

Vast amounts of molecular data are being collected on tumor samples, which provide unique opportunities for discovering trends within and between cancer subtypes. Such cross-cancer analyses require computational methods that enable intuitive and interactive browsing of thousands of samples based on their molecular similarity. We created a portal called TumorMap to assist in exploration and statistical interrogation of high-dimensional complex “omics” data in an interactive and easily interpretable way. In the TumorMap, samples are arranged on a hexagonal grid based on their similarity to one another in the original genomic space and are rendered with Google's Map technology. While the important feature of this public portal is the ability for the users to build maps from their own data, we pre-built genomic maps from several previously published projects. We demonstrate the utility of this portal by presenting results obtained from The Cancer Genome Atlas project data. Cancer Res; 77(21); e111–4. ©2017 AACR.

Video showing basic functionality of the TumorMap for the first-time user.

Supplemental Table 1A: Differential expression scores used in the pan-cancer cluster GSEA analysis. These scores represent integrated t-statistic scores from the differential analysis within each tissue (see Supplemental Methods). Supplemental Table 1B: Full results of the GSEA analysis of the pan-cancer cluster, based on differential expression scores. Supplemental Table 1C: Per-sample ESTIMATE scores used in analysis of the pan-cancer cluster. Supplemental Table 1D: Per-sample surrogate purity scores used in analysis of the pan-cancer cluster. Supplemental Table 1E: List of genes located on sex chromosomes that were excluded from the methylation dataset in order to analyze only autosomal gene features. Supplemental Table 1F: Attributes available in the TumorMap that annotate metadata of the samples, along with descriptions of those attributes. Supplemental Table 1G: Statistical tests computed by different attribute enrichment analysis (AEA) tools available in the TumorMap. Supplemental Table 1H: List of 82 samples in the pan-cancer cluster in the integrated map as well as tissue composition, along with the number of samples, in the integrated pan-cancer cluster. Supplemental Table 1I: Input data for the LAML survival analysis.

Supplemental Figure 5: (A) Overview of the method to compute differential expression for samples in the integrated pan-cancer group vs. other samples in the TCGA cohort. Tissue composition imbalance was corrected for by performing t-tests within each tissue. For each gene, t-statistics were computed within each tumor type separately and then summarized per-gene t-statistics were calculated as an arithmetic mean, weighted by the inverse variance of the all the tissue-specific t-statistics values. (B) The distribution of log-transformed TPM values estimated from the mRNA-Seq data showing a normal-like distribution. (C) Comparing the log-transformed TPM values of the mRNA-Seq data to a normal distribution shows a reasonable agreement with the tumor data having slightly heavier tails. (D) Venn diagram representing the innate and adaptive immune systems and different levels of evidence supporting higher activity of each of the components of those systems in the pan-cancer cluster when compared to the rest of the TCGA cohort. We found evidence of both innate and adaptive immune system signaling with a number of different analyses. (E) Detailed version of the immune-related pathway characterizing the integrated pan-cancer cluster. This version of the pathway shows additional genes and their connections that are not shown in the summarized version of the immune signaling pathway of Figure 1D of the main text.

Tissue and molecular subtype distribution among the samples in the entire cohort (A-B), and in the pan-cancer cluster (C-D). The pie charts represent the number of samples from each tissue of origin in the entire cohort (A) and the integrated pan-cancer cluster (C). Black and white matrices illustrate the presence of molecular features of each platform (x-axis) across samples (y-axis), in the entire cohort (B) or in the integrated pan-cancer cluster (D). Data available for this sample for a given platform is marked black, otherwise the entry is white.

BACKGROUND:Metastatic castration resistant prostate cancer (mCRPC) is incurable and progression after drugs that target the androgen receptor-signaling axis is inevitable. Thus, there is an urgent need to develop more effective treatments beyond hormonal manipulation. We sought to identify activated kinases in mCRPC as therapeutic targets for existing, approved agents, with the goal of identifying candidate drugs for rapid translation into proof of concept Phase II trials in mCRPC. METHODS:To identify evidence of activation of druggable kinases in these patients, we compared mRNA expression from metastatic biopsies of patients with mCRPC (n = 101) to mRNA expression in localized prostate from TCGA and used this analysis to infer differential kinase activity. In addition, we assessed the differential phosphorylation levels for key MAPK pathway kinases between mCRPC and localized prostate cancers. RESULTS:Transcriptomic profiling of 101 patients with mCRPC as compared to patients with localized prostate cancer identified evidence of hyperactive ERK1, and whole genome sequencing revealed frequent amplifications of members of the MAPK pathway in 32% of this cohort. Next, we confirmed elevated levels of phosphorylated ERK1/2 in castration resistant prostate cancer as compared to untreated primary prostate cancer. We observed that the presence of detectable phosphorylated ERK1/2 in the primary tumor is associated with biochemical failure after radical prostatectomy independent of clinicopathologic features. ERK1 is the immediate downstream target of MEK1/2, which is druggable with trametinib, an approved therapeutic for melanoma. Trametinib elicited a profound biochemical and clinical response in a patient who had failed multiple prior treatments for mCRPC. CONCLUSIONS:We conclude that pharmacologic targeting of the MEK/ERK pathway may be a viable treatment strategy for patients with refractory metastatic prostate cancer. An ongoing Phase II trial tests this hypothesis.

Vast amounts of molecular data are being collected on tumor samples, which provide unique opportunities for discovering trends within and between cancer subtypes. Such cross-cancer analyses require computational methods that enable intuitive and interactive browsing of thousands of samples based on their molecular similarity. We created a portal called TumorMap to assist in exploration and statistical interrogation of high-dimensional complex “omics” data in an interactive and easily interpretable way. In the TumorMap, samples are arranged on a hexagonal grid based on their similarity to one another in the original genomic space and are rendered with Google's Map technology. While the important feature of this public portal is the ability for the users to build maps from their own data, we pre-built genomic maps from several previously published projects. We demonstrate the utility of this portal by presenting results obtained from The Cancer Genome Atlas project data. Cancer Res; 77(21); e111–4. ©2017 AACR.

Background: Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interestnamely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trialENTHUSE M1in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·394·62, p, European Union within the ERC grant LatentCauses supported the work of C.F and I.K. German Research Foundation (DFG) within the Collaborative Research Centre 1243, subproject A17 awarded to C.F. German Federal Ministry of Education and Research (BMBF) through the Research Consortium e:AtheroMED (Systems medicine of myocardial infarction and stroke) under the auspices of the e:Med Programme (grant # 01ZX1313C) supported the work of D.P.A., P.D., C.F., C.K., I.K., N.K., M.L., H.S. and J.F.S. at the Institute of Computational Biology. NIH Grants RR025747-01, MH086633 and 1UL1TR001111, and NSF Grants SES-1357666, DMS-14-07655 and BCS0826844 supported the work of C.H., J.I., E.L., Y.W., H.Y., H.Z. and J.Z. NSFC Grant Nos. 61332013, 61572139 supported the work of X.L, Y.L, Y.Z., and S.Z. National Natural Science Foundation of China grants [Nos. 61422309, 61379092] was awarded to S.Z. The Patrick C. Walsh Prostate Research Fund and the Johns Hopkins Individualized Health Initiative supported the work of R.Y.C., D.D., Y.D., Z.J., K.R., Z.W. and Y.Z. FCT Ph.D. Grant SFRH/BD/80925/2011 was awarded to S.C. Clinical Persona Inc., East Palo Alto, CA supported the work of L.B. and D.K. The Finnish Cultural Foundation and the Drug Research Doctoral Programme (DRDP) at the University of Turku supported T.D.L. The National Research Foundation Singapore and the Singapore Ministry of Education, under its Research Centres of Excellence initiative, supported the work of J.G. and K.T. A grant from the Russian Science Foundation 14-24-00155 was awarded to M.D.K. A*MIDEX grant (no. ANR-11-IDEX-0001-02) was awarded to P.J.B. NSERC supported the work of R.G. The Israeli Centers of Research Excellence (I-CORE) program (Center No. 4/11) supported the work of E.G. Academy of Finland (grants 292611, 269862, 272437, 279163, 295504), National Cancer Institute (16X064), and Cancer Society of Finland supported the work of T.A. Academy of Finland (grant 268531) supported the work of T.M

MYCN amplification and overexpression are common in neuroendocrine prostate cancer (NEPC). However, the impact of aberrant N-Myc expression in prostate tumorigenesis and the cellular origin of NEPC have not been established. We define N-Myc and activated AKT1 as oncogenic components sufficient to transform human prostate epithelial cells to prostate adenocarcinoma and NEPC with phenotypic and molecular features of aggressive, late-stage human disease. We directly show that prostate adenocarcinoma and NEPC can arise from a common epithelial clone. Further, N-Myc is required for tumor maintenance, and destabilization of N-Myc through Aurora A kinase inhibition reduces tumor burden. Our findings establish N-Myc as a driver of NEPC and a target for therapeutic intervention.

Background: We describe a prototype implementation of a platform that could underlie a Precision Oncology Rapid Learning system. Results: We describe the prototype platform, and examine some important issues and details. In the Appendix we provide a complete walk-through of the prototype platform. Conclusions: The design choices made in this implementation rest upon ten constitutive hypotheses, which, taken together, define a particular view of how a rapid learning medical platform might be defined, organized, and implemented. Keywords: Natural language processing, Precision oncology, Controlled natural language, Nanopublication, Treatment reasoning, Rapid learning, Tumor boards, Targeted therapies, Cancer Commons, Deloitte Touche Tohmatsu (Firm)

Background: Molecular-based subtypes most certainly play a role in cancer progression and treatment. The recent results from the The Cancer Genome Atlas (TCGA) Pan-Cancer-12 analyses revealed connections between the cell of origin and patient outcomes. For example, bladder cancers were found to relate to three major Pan-Cancer integrative subtypes, with adeno-like and squamous-like bladder cancers associated with poorer prognosis than tumors with bladder-distinct profiles. Furthermore, both adeno-like lung and squamous-like bladder cancers were found to be associated with the most aggressive form of the disease. Methods: We are collecting a catalog of molecular signatures for each subtype found from Pan-Cancer analyses in TCGA and from relevant external datasets. Our goal is to map every tumor sample to one or more signatures in this collection using machine-learning methods. This mapping will allow us to predict the subclonal composition of primary tumor biopsies and to compare them to inferences from the variant allele frequency analysis, shedding light on the gene expression changes associated with key events in tumor evolution. As a pilot study, we compared signatures derived from metastatic prostate samples to subtypes of primary prostate tumors. Our goal is to test whether a molecular profile of metastatic disease can be recognized early on in primary tumors. To do so, we used unsupervised classification of mRNA expression profiles to define clusters of metastatic disease from external datasets as well as separately for primary tumors including the TCGA prostate adenocarcinoma dataset. We then performed an all-against-all comparison of signatures derived from metastatic subtypes to signatures derived from primary tumor subtypes. Results: The majority of metastatic tumors are most closely associated with one out of four primary subtypes, suggesting we have identified a possible primary signature associated with more aggressive disease. The finding is supported by enrichment analysis of clinical variables in the primary subtypes. Specifically, the primary subtype most often associated with the metastatic tumors have higher Gleason scores and higher tumor grade. In addition, several molecular pathways (e.g. BioCarta Vitamin D Receptor and KEGG Integrins in Angiogenesis pathways) and genes (e.g. MMP9, FGA, and LYZ) were found to be associated with the location of metastasis. Conclusions: Training molecular subtype recognizers may hold promise for detecting minor populations of subclones in primary and metastatic tumors. The subclone decomposition can be used to detect the presence of more aggressive disease that may resist standard treatment regimens. We are now expanding our signature catalog to include a more comprehensive collection and applying to additional subtypes of interest. We will make all datasets and signatures available through a mature version of the UCSC TumorMap portal. Citation Format: Kiley Graim, Yulia Newton, Adrian Bivol, Artem Sokolov, Kyle Ellrott, Robert Baertsch, Joshua Stuart. A signature catalog to classify tumor mixtures: Application to recognition of metastatic disease in prostate cancer. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-64.

Background: Molecular-based subtypes most certainly play a role in cancer progression and treatment. The recent results from the The Cancer Genome Atlas (TCGA) Pan-Cancer-12 analyses revealed connections between the cell of origin and patient outcomes. For example, bladder cancers were found to relate to three major Pan-Cancer integrative subtypes, with adeno-like and squamous-like bladder cancers associated with poorer prognosis than tumors with bladder-distinct profiles. Furthermore, both adeno-like lung and squamous-like bladder cancers were found to be associated with the most aggressive form of the disease. Methods: We are collecting a catalog of molecular signatures for each subtype found from Pan-Cancer analyses in TCGA and from relevant external datasets. Our goal is to map every tumor sample to one or more signatures in this collection using machine-learning methods. This mapping will allow us to predict the subclonal composition of primary tumor biopsies and to compare them to inferences from the variant allele frequency analysis, shedding light on the gene expression changes associated with key events in tumor evolution. As a pilot study, we compared signatures derived from metastatic prostate samples to subtypes of primary prostate tumors. Our goal is to test whether a molecular profile of metastatic disease can be recognized early on in primary tumors. To do so, we used unsupervised classification of mRNA expression profiles to define clusters of metastatic disease from external datasets as well as separately for primary tumors including the TCGA prostate adenocarcinoma dataset. We then performed an all-against-all comparison of signatures derived from metastatic subtypes to signatures derived from primary tumor subtypes. Results: The majority of metastatic tumors are most closely associated with one out of four primary subtypes, suggesting we have identified a possible primary signature associated with more aggressive disease. The finding is supported by enrichment analysis of clinical variables in the primary subtypes. Specifically, the primary subtype most often associated with the metastatic tumors have higher Gleason scores and higher tumor grade. In addition, several molecular pathways (e.g. BioCarta Vitamin D Receptor and KEGG Integrins in Angiogenesis pathways) and genes (e.g. MMP9, FGA, and LYZ) were found to be associated with the location of metastasis. Conclusions: Training molecular subtype recognizers may hold promise for detecting minor populations of subclones in primary and metastatic tumors. The subclone decomposition can be used to detect the presence of more aggressive disease that may resist standard treatment regimens. We are now expanding our signature catalog to include a more comprehensive collection and applying to additional subtypes of interest. We will make all datasets and signatures available through a mature version of the UCSC TumorMap portal. Citation Format: Kiley Graim, Yulia Newton, Adrian Bivol, Artem Sokolov, Kyle Ellrott, Robert Baertsch, Joshua Stuart. A signature catalog to classify tumor mixtures: application to recognition of metastatic disease in prostate cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-37.

Rapid species radiation due to adaptive changes or occupation of new ecospaces challenges our understanding of ancestral speciation and the relationships of modern species. At the molecular level, rapid radiation with successive speciations over short time periods—too short to fix polymorphic alleles—is described as incomplete lineage sorting. Incomplete lineage sorting leads to random fixation of genetic markers and hence, random signals of relationships in phylogenetic reconstructions. The situation is further complicated when you consider that the genome is a mosaic of ancestral and modern incompletely sorted sequence blocks that leads to reconstructed affiliations to one or the other relative, depending on the fixation of their shared ancestral polymorphic alleles. The laurasiatherian relationships among Chiroptera, Perissodactyla, Cetartiodactyla, and Carnivora present a prime example for such enigmatic affiliations. We performed whole-genome screenings for phylogenetically diagnostic retrotransposon insertions involving the representatives bat (Chiroptera), horse (Perissodactyla), cow (Cetartiodactyla), and dog (Carnivora), and extracted among 162,000 preselected cases 102 virtually homoplasy-free, phylogenetically informative retroelements to draw a complete picture of the highly complex evolutionary relations within Laurasiatheria. All possible evolutionary scenarios received considerable retrotransposon support, leaving us with a network of affiliations. However, the Cetartiodactyla–Carnivora relationship as well as the basal position of Chiroptera and an ancestral laurasiatherian hybridization process did exhibit some very clear, distinct signals. The significant accordance of retrotransposon presence/absence patterns and flanking nucleotide changes suggest an important influence of mosaic genome structures in the reconstruction of species histories.

We report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine., National Institutes of Health (U.S.) (Grant U54HG003273), National Institutes of Health (U.S.) (Grant U54HG003067), National Institutes of Health (U.S.) (Grant U54HG003079), National Institutes of Health (U.S.) (Grant U24CA143799), National Institutes of Health (U.S.) (Grant U24CA143835), National Institutes of Health (U.S.) (Grant U24CA143840), National Institutes of Health (U.S.) (Grant U24CA143843), National Institutes of Health (U.S.) (Grant U24CA143845), National Institutes of Health (U.S.) (Grant U24CA143848), National Institutes of Health (U.S.) (Grant U24CA143858), National Institutes of Health (U.S.) (Grant U24CA143866), National Institutes of Health (U.S.) (Grant U24CA143867), National Institutes of Health (U.S.) (Grant U24CA143882), National Institutes of Health (U.S.) (Grant U24CA143883), National Institutes of Health (U.S.) (Grant U24CA144025), National Institutes of Health (U.S.) (Grant P30CA016672)

We present a novel regularization scheme called The Generalized Elastic Net (GELnet) that incorporates gene pathway information into feature selection. The proposed formulation is applicable to a wide variety of problems in which the interpretation of predictive features using known molecular interactions is desired. The method naturally steers solutions toward sets of mechanistically interlinked genes. Using experiments on synthetic data, we demonstrate that pathway-guided results maintain, and often improve, the accuracy of predictors even in cases where the full gene network is unknown. We apply the method to predict the drug response of breast cancer cell lines. GELnet is able to reveal genetic determinants of sensitivity and resistance for several compounds. In particular, for an EGFR/HER2 inhibitor, it finds a possible trans-differentiation resistance mechanism missed by the corresponding pathway agnostic approach., Author Summary The low costs of sequencing and other high-throughput technologies have made available large amounts of data to address molecular biology problems. However, often this means thousands of measurements, for example on gene expression, are assayed for a much smaller number of samples. The imbalance complicates the identification of genes that generalize to new samples and in finding a collection of genes that suggest a theme for interpreting the data. Pathway and network-based approaches have proven their worth in these situations. They force solutions onto known biology and they produce more robust predictors. In this manuscript, we describe a new formulation of statistical learning approaches that naturally incorporates gene-gene relationships, like those found in gene network databases. The theory we present helps unify and codify an explicit formulation for gene pathway-informed machine-learning that should have wide reach.

This article describes a set of alignments of 28 vertebrate genome sequences that is provided by the UCSC Genome Browser. The alignments can be viewed on the Human Genome Browser (March 2006 assembly) at http://genome.ucsc.edu, downloaded in bulk by anonymous FTP from http://hgdownload.cse.ucsc.edu/goldenPath/hg18/multiz28way, or analyzed with the Galaxy server at http://g2.bx.psu.edu. This article illustrates the power of this resource for exploring vertebrate and mammalian evolution, using three examples. First, we present several vignettes involving insertions and deletions within protein-coding regions, including a look at some human-specific indels. Then we study the extent to which start codons and stop codons in the human sequence are conserved in other species, showing that start codons are in general more poorly conserved than stop codons. Finally, an investigation of the phylogenetic depth of conservation for several classes of functional elements in the human genome reveals striking differences in the rates and modes of decay in alignability. Each functional class has a distinctive period of stringent constraint, followed by decays that allow (for the case of regulatory regions) or reject (for coding regions and ultraconserved elements) insertions and deletions.

GeneHub-GEPIS is a web application that performs digital expression analysis in human and mouse tissues based on an integrated gene database. Using aggregated expressed sequence tag (EST) library information and EST counts, the application calculates the normalized gene expression levels across a large panel of normal and tumor tissues, thus providing rapid expression profiling for a given gene. The backend GeneHub component of the application contains pre-defined gene structures derived from mRNA transcript sequences from major databases and includes extensive cross references for commonly used gene identifiers. ESTs are then linked to genes based on their precise genomic locations as determined by GMAP. This genome-based approach reduces incorrect matches between ESTs and genes, thus minimizing the noise seen with previous tools. In addition, the gene-centric design makes it possible to add several important features, including text searching capabilities, the ability to accept diverse input values, expression analysis for microRNAs, basic gene annotation, batch analysis and linking between mouse and human genes. GeneHub-GEPIS is available at http://www.cgl.ucsf.edu/Research/genentech/genehub-gepis/ or http://www.gepis.org/.

We present a new, low-cost, low-power, half/full-duplex passive integrated transponder (PIT) tag interrogation antenna for use in detecting fish movements in small streams. New technology by Allflex-USA allowed us to develop a reading system with an antenna 279.4 cm wide × 60.9 cm high that reads both common tag types used in fisheries today for about US$1,000. An instream antenna of this size and price makes high-resolution tracking of fish movement in small streams feasible where cost and tag-type restrictions were prohibitive. For evaluation, we placed the antenna upstream of a small estuary on the central California coast to observe the diel movements of juvenile steelhead Oncorhynchus mykiss between the estuary and upstream habitats in both spring and fall months.

The rhesus macaque ( Macaca mulatta ) is an abundant primate species that diverged from the ancestors of Homo sapiens about 25 million years ago. Because they are genetically and physiologically similar to humans, rhesus monkeys are the most widely used nonhuman primate in basic and applied biomedical research. We determined the genome sequence of an Indian-origin Macaca mulatta female and compared the data with chimpanzees and humans to reveal the structure of ancestral primate genomes and to identify evidence for positive selection and lineage-specific expansions and contractions of gene families. A comparison of sequences from individual animals was used to investigate their underlying genetic diversity. The complete description of the macaque genome blueprint enhances the utility of this animal model for biomedical research and improves our understanding of the basic biology of the species.

Evidence from numerous cancers suggests that increased aggressiveness is accompanied by up-regulation of signaling pathways and acquisition of properties common to stem cells. It is unclear if different subtypes of late-stage cancer vary in stemness properties and whether or not these subtypes are transcriptionally similar to normal tissue stem cells. We report a gene signature specific for human prostate basal cells that is differentially enriched in various phenotypes of late-stage metastatic prostate cancer. We FACS-purified and transcriptionally profiled basal and luminal epithelial populations from the benign and cancerous regions of primary human prostates. High-throughput RNA sequencing showed the basal population to be defined by genes associated with stem cell signaling programs and invasiveness. Application of a 91-gene basal signature to gene expression datasets from patients with organ-confined or hormone-refractory metastatic prostate cancer revealed that metastatic small cell neuroendocrine carcinoma was molecularly more stem-like than either metastatic adenocarcinoma or organ-confined adenocarcinoma. Bioinformatic analysis of the basal cell and two human small cell gene signatures identified a set of E2F target genes common between prostate small cell neuroendocrine carcinoma and primary prostate basal cells. Taken together, our data suggest that aggressive prostate cancer shares a conserved transcriptional program with normal adult prostate basal stem cells.

The vacuolar ATPase has been implicated in a variety of physiological processes in eukaryotic cells. Bafilomycin and concanamycin, highly potent and specific inhibitors of the vacuolar ATPase, have been widely used to investigate the enzyme. Derivatives have been developed as possible therapeutic drugs. We have used random mutagenesis and site-directed mutagenesis to identify 23 residues in the c subunit involved in binding these drugs. We generated a model for the structure of the ring of c subunits in Neurospora crassa by using data from the crystal structure of the homologous subunits of the bacterium Enterococcus hirae (Murata, T., Yamato, I., Kakinuma, Y., Leslie, A. G., and Walker, J. E. (2005) Science 308, 654-659). In the model 10 of the 11 mutation sites that confer the highest degree of resistance are closely clustered. They form a putative drug-binding pocket at the interface between helices 1 and 2 on one c subunit and helix 4 of the adjacent c subunit. The excellent fit of the N. crassa sequence to the E. hirae structure and the degree to which the structural model predicts the clustering of these residues suggest that the folding of the bacterial and eukaryotic polypeptides is very similar.

As more archaeal genomes are sequenced, effective research and analysis tools are needed to integrate the diverse information available for any given locus. The feature-rich UCSC Genome Browser, created originally to annotate the human genome, can be applied to any sequenced organism. We have created a UCSC Archaeal Genome Browser, available at http://archaea.ucsc.edu/, currently with 26 archaeal genomes. It displays G/C content, gene and operon annotation from multiple sources, sequence motifs (promoters and Shine-Dalgarno), microarray data, multi-genome alignments and protein conservation across phylogenetic and habitat categories. We encourage submission of new experimental and bioinformatic analysis from contributors. The purpose of this tool is to aid biological discovery and facilitate greater collaboration within the archaeal research community.

We define a “threaded blockset,” which is a novel generalization of the classic notion of a multiple alignment. A new computer program called TBA (for “threaded blockset aligner”) builds a threaded blockset under the assumption that all matching segments occur in the same order and orientation in the given sequences; inversions and duplications are not addressed. TBA is designed to be appropriate for aligning many, but by no means all, megabase-sized regions of multiple mammalian genomes. The output of TBA can be projected onto any genome chosen as a reference, thus guaranteeing that different projections present consistent predictions of which genomic positions are orthologous. This capability is illustrated using a new visualization tool to view TBA-generated alignments of vertebrate Hox clusters from both the mammalian and fish perspectives. Experimental evaluation of alignment quality, using a program that simulates evolutionary change in genomic sequences, indicates that TBA is more accurate than earlier programs. To perform the dynamic-programming alignment step, TBA runs a stand-alone program called MULTIZ, which can be used to align highly rearranged or incompletely sequenced genomes. We describe our use of MULTIZ to produce the whole-genome multiple alignments at the Santa Cruz Genome Browser.

This study examines genomic duplications, deletions, and rearrangements that have happened at scales ranging from a single base to complete chromosomes by comparing the mouse and human genomes. From whole-genome sequence alignments, 344 large (>100-kb) blocks of conserved synteny are evident, but these are further fragmented by smaller-scale evolutionary events. Excluding transposon insertions, on average in each megabase of genomic alignment we observe two inversions, 17 duplications (five tandem or nearly tandem), seven transpositions, and 200 deletions of 100 bases or more. This includes 160 inversions and 75 duplications or transpositions of length >100 kb. The frequencies of these smaller events are not substantially higher in finished portions in the assembly. Many of the smaller transpositions are processed pseudogenes; we define a “syntenic” subset of the alignments that excludes these and other small-scale transpositions. These alignments provide evidence that ≈2% of the genes in the human/mouse common ancestor have been deleted or partially deleted in the mouse. There also appears to be slightly less nontransposon-induced genome duplication in the mouse than in the human lineage. Although some of the events we detect are possibly due to misassemblies or missing data in the current genome sequence or to the limitations of our methods, most are likely to represent genuine evolutionary events. To make these observations, we developed new alignment techniques that can handle large gaps in a robust fashion and discriminate between orthologous and paralogous alignments.

Human chromosome 7 has historically received prominent attention in the human genetics community, primarily related to the search for the cystic fibrosis gene and the frequent cytogenetic changes associated with various forms of cancer. Here we present more than 153 million base pairs representing 99.4% of the euchromatic sequence of chromosome 7, the first metacentric chromosome completed so far. The sequence has excellent concordance with previously established physical and genetic maps, and it exhibits an unusual amount of segmentally duplicated sequence (8.2%), with marked differences between the two arms. Our initial analyses have identified 1,150 protein-coding genes, 605 of which have been confirmed by complementary DNA sequences, and an additional 941 pseudogenes. Of genes confirmed by transcript sequences, some are polymorphic for mutations that disrupt the reading frame.

The University of California Santa Cruz (UCSC) Genome Browser Database is an up to date source for genome sequence data integrated with a large collection of related annotations. The database is optimized to support fast interactive performance with the web-based UCSC Genome Browser, a tool built on top of the database for rapid visualization and querying of the data at many levels. The annotations for a given genome are displayed in the browser as a series of tracks aligned with the genomic sequence. Sequence data and annotations may also be viewed in a text-based tabular format or downloaded as tab-delimited flat files. The Genome Browser Database, browsing tools and downloadable data files can all be found on the UCSC Genome Bioinformatics website (http://genome.ucsc.edu), which also contains links to documentation and related technical information.

The Consensus Coding Sequence (CCDS) project (http://www.ncbi.nlm.nih.gov/CCDS/) is a collaborative effort to maintain a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assemblies by the National Center for Biotechnology Information (NCBI) and Ensembl genome annotation pipelines. Identical annotations that pass quality assurance tests are tracked with a stable identifier (CCDS ID). Members of the collaboration, who are from NCBI, the Wellcome Trust Sanger Institute and the University of California Santa Cruz, provide coordinated and continuous review of the dataset to ensure high-quality CCDS representations. We describe here the current status and recent growth in the CCDS dataset, as well as recent changes to the CCDS web and FTP sites. These changes include more explicit reporting about the NCBI and Ensembl annotation releases being compared, new search and display options, the addition of biologically descriptive information and our approach to representing genes for which support evidence is incomplete. We also present a summary of recent and future curation targets.

e16598Background: Aberrant androgen receptor (AR) phenotypes (e.g. splice variants, amplification) are strongly correlated with abiraterone (Abi) and enzalutamide (Enz) resistance. Low serum DHEA i...

179 Background: Aberrant androgen receptor (AR) phenotypes (e.g. splice variants, amplification) are strongly correlated with abiraterone (Abi) and enzalutamide (Enz) resistance. Low serum dehydroepiandrosterone (DHEA) is also associated with poor outcomes to AR-targeted therapy. Here, we investigate the relationship between serum DHEA, AR phenotype, and treatment efficacy in the WCDT. Methods: Patients (pts) with progressive mCRPC enrolled to the WCDT from UCSF, OHSU, UCLA, UBC, and UCD were included in this analysis. Serum DHEA was analyzed via high-pressure liquid chromatography and tandem mass spectrometry. Limit of quantitation (LQ) of DHEA was 0.2ng/mL. Full-length AR (AR-FL) and AR-v7 expression, obtained via RNAseq of metastatic tumor biopsies, was expressed as total reads mapped to gene. PSA response (PSAr) was defined as ≥ 50% PSA decline. Results: 35 pts were included in this analysis: 15 had treatment-naïve mCRPC, and 20 had prior AR-targeted therapy (14 Abi, 6 Enz). All pts were docetaxel-naïve. 11 pts had DHEA < LQ; of these, 10 had received prior AR-targeted therapy. 12 pts received subsequent chemotherapy, and 23 received subsequent Abi/Enz (7 Abi, 16 Enz). In pts with DHEA < LQ, 4/5 (80%) chemotherapy-treated pts had PSAr, while 1/6 (17%) Abi/Enz-treated pts had PSAr. In pts with DHEA ≥ LQ, 2/7 (27%) chemotherapy-treated pts had PSAr, while 9/16 (56%) Abi/Enz-treated pts had PSAr. The relationship between DHEA and PSAr was significantly different between the treatment groups (p = 0.0285). DHEA was higher in patients with PSAr to Abi/Enz versus those without PSAr (median, 0.871 versus 0.275ng/mL, p = 0.006). In an analysis of 27 pts with RNAseq data, the AR-v7/AR-FL ratio was significantly higher in those with DHEA < LQ (median ratio 8.91, versus 3.38 in DHEA ≥ LQ, p = 0.032). Conclusions: In this exploratory analysis, there is a significant difference in the relationship between DHEA and PSAr in chemotherapy- versus Abi/Enz-treated patients. DHEA < LQ was also associated with a higher AR-v7/AR-FL ratio, a potential avenue for further exploration of tumor biology. These results support a larger study to evaluate DHEA as a potential biomarker in mCRPC. Clinical trial information: NCT02432001.

Maglev personal rapid transit (MPRT) is a personal rapid transit (PRT) system that uses renewable energy in usage, distribution, and generation. A PRT system provides on-demand service in a manner similar to the automobile. Different types of PRT have different impacts on the electrical grid load. Recent advances in power electronics and maglev technology allow for the design of a novel MPRT system characterized not only by exceptionally low power requirements but also by a unique capacity to incorporate energy distribution and storage infrastructure into the greater transportation architecture. A hypothetical hybrid MPRT design incorporating energy storage and transmission capabilities is described. In addition, thorough carbon dioxide and cost analyses are undertaken to more fully understand the spectrum of benefits of an MPRT solution, in comparison to conventional vehicle and plug-in hybrid electric vehicle approaches. An MPRT system not only offers significant advantages over other technologies in efficiently using renewable energy but also represents the unique potential to address urgent energy challenges by incorporating power transmission, storage, and generation infrastructure.

Since its start, the Mammalian Gene Collection (MGC) has sought to provide at least one full-protein-coding sequence cDNA clone for every human and mouse gene with a RefSeq transcript, and at least 6200 rat genes. The MGC cloning effort initially relied on random expressed sequence tag screening of cDNA libraries. Here, we summarize our recent progress using directed RT-PCR cloning and DNA synthesis. The MGC now contains clones with the entire protein-coding sequence for 92% of human and 89% of mouse genes with curated RefSeq (NM-accession) transcripts, and for 97% of human and 96% of mouse genes with curated RefSeq transcripts that have one or more PubMed publications, in addition to clones for more than 6300 rat genes. These high-quality MGC clones and their sequences are accessible without restriction to researchers worldwide.

Genomic variation is based on genetic convertibility and is amplified by gene flow and sexual recombination. While only a small fraction of genetic variation is directly exposed to the natural selection driving the evolution of species, the majority of changes are neutral (Kimura 1968). In the molecular Darwinian and post-genomic age when such variations are now directly observable in prodigious numbers, one still needs only compare the volumes of controversy in scientific reports to dispel the notion that all the mysteries of evolutionary history are now an open book. The basal node of the placental mammals is a prime example of such a controversy. After continuous morphological inconsistencies and a lack of resolution due to narrow temporal speciation events at the deeper divergences of the placental mammalian tree, the hope was that large-scale DNA sequencing and an increasing number of sampled species might resolve the higher-level mammalian relationships by reducing systematic biases. But the extraction and analysis of molecular traces of evolutionary history has been no less sensitive to misinterpretation than was the understanding of dusty specimens 150 years ago. The reliability of sequence data in genome-scale phylogenetic approaches is subject to unequal evolutionary rates among lineages, regional- or lineage-specific compositional biases, shifts in site-specific evolutionary rates over time and sequence regions (e.g., Nishihara et al. 2007), variable accuracies of multisequence alignments and analytical tools, and last but not least, the general liability of such data to homoplasy. In a seminal work, Murphy et al. (2001a) investigated ∼10 kb of sequence information to substantiate the previously proposed (Waddell et al. 1999) major mammalian groups Afrotheria, Xenarthra, Laurasiatheria, and Euarchontoglires. Moderate support was found for Afrotheria as the basal split of placentals (Exafroplacentalia; Fig. 1A). A subsequent combination and expansion of previously published data (Madsen et al. 2001; Murphy et al. 2001a) found significant support for a basal split between Afrotheria and other placentals (Murphy et al. 2001b). Nikolaev et al. (2007) also found support for the Afrotheria as the first placental split, drawing on ∼200 kb of protein-coding sequences from the 1% of the human genome studied in the ENCODE pilot project (The ENCODE Project Consortium 2007). However, other studies of large-scale sequences (e.g., Hallstrom et al. 2007) and previous studies of smaller data sets could not significantly confirm an Afrotherian root (e.g., Madsen et al. 2001; Waddell et al. 2001; Delsuc et al. 2002; Amrine-Madsen et al. 2003). A sister-group relationship of Afrotheria and Xenarthra (Atlantogenata) also received significant support in analyses of sequences from ∼1700 conserved genome loci (Wildman et al. 2007), 2840 protein-coding genes (Hallstrom et al. 2007), and mitochondrial genomes (Kjer and Honeycutt 2007); and this was recently confirmed by large-scale analyses of 2.8 Mbp of protein-coding data (Hallstrom and Janke 2008) and large-scale genomic sequences (Prasad et al. 2008). Thus, despite many different molecular studies, the basal origin of placental mammals remains controversial and unresolved. Unfortunately, pure sequence data cannot resolve these apparent contradictions. Figure 1. Different hypotheses of the placental origin. (A) The Exafroplacentalia hypothesis proposes a mammalian clade merging Boreotheria (Supraprimates plus Laurasiathera) and Xenarthra, with Afrotheria as the sister group. (B) The Epitheria hypothesis merges ... By contrast, the presence/absence patterns of inserted retroelements constitute a virtually homoplasy-free marker system with theoretically infinite character states (Steel and Penny 2000). Specific genomic insertions of such elements in the ancestor of two species reliably document their common ancestry. The very few known examples of discordance in retroelement presence/absence data can be explained by deletion via illegitimate recombination between perfect direct repeats flanking each insertion (van de Lagemaat et al. 2005), exact parallel insertions (Cantrell et al. 2001), or lineage sorting, a phenomenon related to incomplete allele fixation and frequent intervals of speciation events (Shedlock et al. 2004; Ray et al. 2006). Analyses of a smaller number of retroelements as phylogenetic markers in mammals validated the four superordinal mammalian clades (Nishihara et al. 2005; Kriegs et al. 2006; Moller-Krull et al. 2007). However, in support of Shoshani and McKenna (1998), but in contradiction to most other molecular investigations, we found the first evidence, two L1MB5 retroelements, that placed Xenarthra (Epitheria hypothesis) (Fig. 1B) instead of Afrotheria at the base of the placental tree (Kriegs et al. 2006). Meanwhile, Murphy et al. (2007) presented two L1MB5 retroelements and four additional indels that favored a sister group relationship of Afrotheria and Xenarthra (Atlantogenata) (Fig. 1C) at the base of the placental tree. Thus, to date, even retroposon insertion patterns have not satisfactorily resolved the basal split of placental mammals. With the intention of resolving the conflicting topologies of placental lineages, we aimed to examine a much larger sample of retroposed elements and in more species. For this study we took a slightly different tack and aligned whole genomes of three representative placental species, including additional species for informative loci to represent a maximum divergence within each of the groups, and scanned them for diagnostic retroelement insertions. In an analysis of ∼2 million potential phylogenetically informative loci, we found multiple retroposon insertion patterns significantly supporting all three placental speciation hypotheses, indicating a complex ancestral speciation scenario including successive early divergences in close temporal proximity and hybridization and/or lineage sorting events as viable sources for an effective “soft” polytomy. This very rare example of multiple retroposon incongruence goes a long way toward explaining the decades-long stream of apparently conflicting evidence for one or the other placental evolutionary history based on multiple marker systems including both morphological and molecular sequence evidence.

Effective use of the human and mouse genomes requires reliable identification of genes and their products. Although multiple public resources provide annotation, different methods are used that can result in similar but not identical representation of genes, transcripts, and proteins. The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers. Importantly, the project coordinates on manually reviewing inconsistent protein annotations between sites, as well as annotations for which new evidence suggests a revision is needed, to progressively converge on a complete protein-coding set for the human and mouse reference genomes, while maintaining a high standard of reliability and biological accuracy. To date, the project has identified 20,159 human and 17,707 mouse consensus coding regions from 17,052 human and 16,893 mouse genes. Three evaluation methods indicate that the entries in the CCDS set are highly likely to represent real proteins, more so than annotations from contributing groups not included in CCDS. The CCDS database thus centralizes the function of identifying well-supported, identically-annotated, protein-coding regions., National Human Genome Research Institute (U.S.) (Grant number 1U54HG004555-01), Wellcome Trust (London, England) (Grant number WT062023), Wellcome Trust (London, England) (Grant number WT077198)

A new two mirror concentrating photovoltaic module making use of Kohler integration optics is introduced. A brief design background is included. First test results from a 15 Watt prototype are given.

Motivation: Computational annotation of protein coding genes in genomic DNA is a widely used and essential tool for analyzing newly sequenced genomes. However, current methods suffer from inaccuracy and do poorly with certain types of genes. Including additional sources of evidence of the existence and structure of genes can improve the quality of gene predictions. For many eukaryotic genomes, expressed sequence tags (ESTs) are available as evidence for genes. Related genomes that have been sequenced, annotated, and aligned to the target genome provide evidence of existence and structure of genes. Results: We incorporate several different evidence sources into the gene finder AUGUSTUS. The sources of evidence are gene and transcript annotations from related species syntenically mapped to the target genome using TransMap, evolutionary conservation of DNA, mRNA and ESTs of the target species, and retroposed genes. The predictions include alternative splice variants where evidence supports it. Using only ESTs we were able to correctly predict at least one splice form exactly correct in 57% of human genes. Also using evidence from other species and human mRNAs, this number rises to 77%. Syntenic mapping is well-suited to annotate genomes closely related to genomes that are already annotated or for which extensive transcript evidence is available. Native cDNA evidence is most helpful when the alignments are used as compound information rather than independent positionwise information. Availability: AUGUSTUS is open source and available at http://augustus.gobics.de. The gene predictions for human can be browsed and downloaded at the UCSC Genome Browser (http://genome.ucsc.edu) Contact: mstanke@gwdg.de Supplementary information: Supplementary data are available at Bioinformatics online.

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view about chromatin structure has emerged, including its interrelationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded novel mechanistic and evolutionary insights about the functional landscape of the human genome. Together, these studies are defining a path forward to pursue a more-comprehensive characterisation of human genome function.

Arising from either retrotransposition or genomic duplication of functional genes, pseudogenes are “genomic fossils” valuable for exploring the dynamics and evolution of genes and genomes. Pseudogene identification is an important problem in computational genomics, and is also critical for obtaining an accurate picture of a genome’s structure and function. However, no consensus computational scheme for defining and detecting pseudogenes has been developed thus far. As part of the ENCyclopedia Of DNA Elements (ENCODE) project, we have compared several distinct pseudogene annotation strategies and found that different approaches and parameters often resulted in rather distinct sets of pseudogenes. We subsequently developed a consensus approach for annotating pseudogenes (derived from protein coding genes) in the ENCODE regions, resulting in 201 pseudogenes, two-thirds of which originated from retrotransposition. A survey of orthologs for these pseudogenes in 28 vertebrate genomes showed that a significant fraction (∼80%) of the processed pseudogenes are primate-specific sequences, highlighting the increasing retrotransposition activity in primates. Analysis of sequence conservation and variation also demonstrated that most pseudogenes evolve neutrally, and processed pseudogenes appear to have lost their coding potential immediately or soon after their emergence. In order to explore the functional implication of pseudogene prevalence, we have extensively examined the transcriptional activity of the ENCODE pseudogenes. We performed systematic series of pseudogene-specific RACE analyses. These, together with complementary evidence derived from tiling microarrays and high throughput sequencing, demonstrated that at least a fifth of the 201 pseudogenes are transcribed in one or more cell lines or tissues.

Human small cell prostate carcinoma (SCPC) represents up to 25% of lethal castration-resistant prostate cancer. Molecular characterization of a panel of SCPCs recently identified frequent genomic amplification of both MYCN and AURKA. The oncogenic function of N-Myc has been characterized in many cancer types but its role in the initiation of human SCPC has not been defined. To investigate the function of N-Myc in human prostate transformation, we utilized a tissue regeneration model of human prostate cancer. Human prostate basal epithelial cells were isolated from benign primary prostate tissue from four independent human donors, infected with lentiviruses expressing the oncogenes N-Myc and activated (myristoylated) AKT1, mixed with mouse urogenital sinus mesenchyme, and grafted subcutaneously in immunodeficient NOD-SCID-IL2Rγnull mice. Palpable tumors were appreciated within 2-3 months and histological evaluation revealed regions of mixed high-grade adenocarcinoma and small cell carcinoma. The small cell carcinoma histology showed typical findings of high nuclear-to-cytoplasmic ratio, nuclear molding, stippled chromatin, and frequent mitotic and apoptotic features. Immunohistochemical analysis demonstrated low to absent androgen receptor (AR) staining in both the adenocarcinoma and small cell carcinoma. Further, we found heterogeneous staining for neuroendocrine markers including neural cell adhesion molecule 1, chromogranin A, synaptophysin, thyroid transcription factor 1, and forkhead box A2 in the regions of small cell carcinoma in support of the histological diagnosis. To assess the androgen dependence of tumor growth, regenerated N-Myc and activated AKT1 tumors derived from the lentiviral infection of primary human prostate basal cells were passaged in either intact or castrate immunodeficient mice. Tumors were propagated both in the presence and absence of androgens and showed a small but progressive enrichment of the small cell carcinoma over the adenocarcinoma with successive passage in castrate hosts. Molecular profiling by RNA-Seq of three regenerated N-Myc and activated AKT1 tumors showed a significant resemblance to a subset of human SCPC clinical specimens. Further, the adenocarcinoma and small cell carcinoma components of each tumor were remarkably similar at the transcriptional level despite their differences in histological appearance. In conclusion, we have established a novel model of human small cell prostate cancer arising from benign human prostate basal cells. Overexpression of N-Myc and activated AKT1 in basal cells produces tumors that recapitulate the histology, immunophenotype, and transcriptional profile of human SCPC. These findings support a direct role for N-Myc in the neuroendocrine transformation of basal cells in the human prostate. Further studies are ongoing to elucidate the mechanisms by which N-Myc induces a neuroendocrine differentiation program in prostate cancer. Citation Format: John K. Lee, Bryan A. Smith, John W. Phillips, Jungwook Park, Tanya I. Stoyanova, Robert Baertsch, Artem Sokolov, Colleen Mathis, Donghui Cheng, Joshua M. Stuart, Jiaoti Huang, Owen N. Witte. N-Myc drives small cell neuroendocrine cancer initiated from human prostate basal cells. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr A28.

Freed from the competition of large raptors, Paleocene carnivores could expand their newly acquired habitats in search of prey. Such changing conditions might have led to their successful distribution and rapid radiation. Today, molecular evolutionary biologists are faced, however, with the consequences of such accelerated adaptive radiations, because they led to sequential speciation more rapidly than phylogenetic markers could be fixed. The repercussions being that current genealogies based on such markers are incongruent with species trees.Our aim was to explore such conflicting phylogenetic zones of evolution during the early arctoid radiation, especially to distinguish diagnostic from misleading phylogenetic signals, and to examine other carnivore-related speciation events. We applied a combination of high-throughput computational strategies to screen carnivore and related genomes in silico for randomly inserted retroposed elements that we then used to identify inconsistent phylogenetic patterns in the Arctoidea group, which is well known for phylogenetic discordances.Our combined retrophylogenomic and in vitro wet lab approach detected hundreds of carnivore-specific insertions, many of them confirming well-established splits or identifying and solving conflicting species distributions. Our systematic genome-wide screens for Long INterspersed Elements detected homoplasy-free markers with insertion-specific truncation points that we used to distinguish phylogenetically informative markers from conflicting signals. The results were independently confirmed by phylogenetic diagnostic Short INterspersed Elements. As statistical analysis ruled out ancestral hybridization, these doubly verified but still conflicting patterns were statistically determined to be genomic remnants from a time of ancestral incomplete lineage sorting that especially accompanied large parts of Arctoidea evolution.

5003 Background: Mechanisms of resistance to androgen signaling inhibitors such as Abi or Enz are poorly understood. An increasing % of these pts develop NEPC. Pathologic (path), clinical, and geno...