Yevgeniy Antipin

The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data

The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.

Integrative Genomic Profiling of Human Prostate Cancer

Annotation of prostate cancer genomes provides a foundation for discoveries that can impact disease understanding and treatment. Concordant assessment of DNA copy number, mRNA expression, and focused exon resequencing in 218 prostate cancer tumors identified the nuclear receptor coactivator NCOA2 as an oncogene in approximately 11% of tumors. Additionally, the androgen-driven TMPRSS2-ERG fusion was associated with a previously unrecognized, prostate-specific deletion at chromosome 3p14 that implicates FOXP1, RYBP, and SHQ1 as potential cooperative tumor suppressors. DNA copy-number data from primary tumors revealed that copy-number alterations robustly define clusters of low- and high-risk disease beyond that achieved by Gleason score. The genomic and clinical outcome data from these patients are now made available as a public resource.

Predicting the functional impact of protein mutations: application to cancer genomics

As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (∼19 200), assumed to be strongly functional, from common polymorphisms (∼35 600), assumed to be weakly functional (area under the receiver operating characteristic curve of ∼0.86). In cancer, using recurrence, multiplicity and annotation for ∼10 000 mutations in the COSMIC database, the method does well in assigning higher scores to more likely functional mutations (‘drivers’). To guide experimental prioritization, we report a list of about 1000 top human cancer genes frequently mutated in one or more cancer types ranked by likely functional impact; and, an additional 1000 candidate cancer genes with rare but likely functional mutations. In addition, we estimate that at least 5% of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function.

Determinants of protein function revealed by combinatorial entropy optimization

We use a new algorithm (combinatorial entropy optimization [CEO]) to identify specificity residues and functional subfamilies in sets of proteins related by evolution. Specificity residues are conserved within a subfamily but differ between subfamilies, and they typically encode functional diversity. We obtain good agreement between predicted specificity residues and experimentally known functional residues in protein interfaces. Such predicted functional determinants are useful for interpreting the functional consequences of mutations in natural evolution and disease.

Necdin, a p53 target gene, regulates the quiescence and response to genotoxic stress of hematopoietic stem/progenitor cells

We recently defined a critical role for p53 in regulating the quiescence of adult hematopoietic stem cells (HSCs) and identified necdin as a candidate p53 target gene. Necdin is a growth-suppressing protein and the gene encoding it is one of several that are deleted in patients with Prader-Willi syndrome. To define the intrinsic role of necdin in adult hematopoiesis, in the present study, we transplanted necdin-null fetal liver cells into lethally irradiated recipients. We show that necdin-null adult HSCs are less quiescent and more proliferative than normal HSCs, demonstrating the similar role of necdin and p53 in promoting HSC quiescence during steady-state conditions. However, wild-type recipients repopulated with necdin-null hematopoietic stem/progenitor cells show enhanced sensitivity to irradiation and chemotherapy, with increased p53-dependent apoptosis, myelosuppression, and mortality. Necdin controls the HSC response to genotoxic stress via both cell-cycle-dependent and cell-cycle-independent mechanisms, with the latter occurring in a Gas2L3-dependent manner. We conclude that necdin functions as a molecular switch in adult hematopoiesis, acting in a p53-like manner to promote HSC quiescence in the steady state, but suppressing p53-dependent apoptosis in response to genotoxic stress.

Genetic Variation in DNA Repair Pathways and Risk of Non-Hodgkin's Lymphoma

Molecular and genetic evidence suggests that DNA repair pathways may contribute to lymphoma susceptibility. Several studies have examined the association of DNA repair genes with lymphoma risk, but the findings from these reports have been inconsistent. Here we provide the results of a focused analysis of genetic variation in DNA repair genes and their association with the risk of non-Hodgkins lymphoma (NHL). With a population of 1,297 NHL cases and 1,946 controls, we have performed a two-stage case/control association analysis of 446 single nucleotide polymorphisms (SNPs) tagging the genetic variation in 81 DNA repair genes. We found the most significant association with NHL risk in the ATM locus for rs227060 (OR = 1.27, 95% CI: 1.13–1.43, p = 6.77×10−5), which remained significant after adjustment for multiple testing. In a subtype-specific analysis, associations were also observed for the ATM locus among both diffuse large B-cell lymphomas (DLBCL) and small lymphocytic lymphomas (SLL), however there was no association observed among follicular lymphomas (FL). In addition, our study provides suggestive evidence of an interaction between SNPs in MRE11A and NBS1 associated with NHL risk (OR = 0.51, 95% CI: 0.34–0.77, p = 0.0002). Finally, an imputation analysis using the 1,000 Genomes Project data combined with a functional prediction analysis revealed the presence of biologically relevant variants that correlate with the observed association signals. While the findings generated here warrant independent validation, the results of our large study suggest that ATM may be a novel locus associated with the risk of multiple subtypes of NHL.

EVfold.org: Evolutionary Couplings and Protein 3D Structure Prediction

Recently developed maximum entropy methods infer evolutionary constraints on protein function and structure from the millions of protein sequences available in genomic databases. The EVfold web server (at EVfold.org) makes these methods available to predict functional and structural interactions in proteins. The key algorithmic development has been to disentangle direct and indirect residue-residue correlations in large multiple sequence alignments and derive direct residue-residue evolutionary couplings (EVcouplings or ECs). For proteins of unknown structure, distance constraints obtained from evolutionarily couplings between residue pairs are used to de novo predict all-atom 3D structures, often to good accuracy. Given sufficient sequence information in a protein family, this is a major advance toward solving the problem of computing the native 3D fold of proteins from sequence information alone. Availability EVfold server at http://evfold.org/ Contact evfoldtest@gmail.com Abbreviations DI direct information EC evolutionary coupling EV evolutionary MSA multiple sequence alignment PLM pseudo-likelihood maximization PPV positive predictive value (number of true positives divided by the sum of true and false positives) TM-score template modeling score

Abstract 5061: Genomic and functional analysis of Myxofibrosarcoma identifies novel prognostic markers and promising therapeutic targets

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Introduction: Myxofibrosarcoma (MXF), which primarily affects the limbs of older patients, has few effective systemic therapies. Little is known about the MXF genome or the genes that drive tumorigenesis. We sought to identify subgroups and to identify genes that associate with outcome and could serve as therapeutic targets. Methods: Copy number alterations (CNAs) and gene expression profiles were measured in 73 MXF, 11 normal muscle, and 22 normal fat samples using Agilent 1M CGH and Affymetrix U133A arrays. Profiles were analyzed by unsupervised clustering and correlated with disease-specific survival (DSS) and distant recurrence-free survival (DRFS). Associations with disease-specific survival (DSS) and distant recurrence-free survival (DRFS) were analyzed for the 68 patients with primary disease; this cohort included 21 patients who had distant recurrence and 15 who died of disease during follow-up (mean, 2.7 years). [ss1] Genes of interest were assayed using shRNA knockdown (for ITGA10) or serum ELISA levels (for HGF). Results: MXF samples had highly complex CNAs, some spanning entire chromosome arms. Unsupervised clustering based on CGH divided samples into 4 main groups driven by a loss at 1q and a gain at 5p. Unsupervised clustering based on U133A profiles divided samples into 3 main groups, 2 of which had a 3-year DSS of 85% while the third had a DSS of 31% (p<0.02). This third group was defined in part by high expression of integrin alpha-10 (ITGA10) and hepatocyte growth factor (HGF). Expression of ITGA10 was associated with worse DRFS (HR=2.7, p=0.03), and particularly strongly associated with worse DSS (HR=8.2, p=0.006). HGF expression was also associated with worse outcomes for both DRFS (HR=3.2, p=0.01) and DSS (HR=3.5, p=0.01). Knockdown of ITGA10 inhibited proliferation and induced apoptosis in an MXF cell line, but not in a normal fat cell line. Patients with high expression of both HGF and its receptor MET had a 3-year DRFS of 25%, vs approximately 60% for those with low expression of one of these genes and 85% for those with low expression of both genes (p=0.0016). Serum HGF was elevated in preoperative patients with MXF (n=38) compared to healthy volunteers (n=8): mean ± SD 1626 pg/mL ± 725 vs. 771 ± 110 (p=0.002). Patients with low serum HGF (≤mean +3 SD of normal [1101 pg/mL], n=10) tended to have better DSS (100% vs. 64%, p=0.14) and better DRFS (83% vs. 55%, p=0.08). Conclusions: MXF is genomically complex and diverse, but gene expression profiles cluster patients into groups associated with outcome. Levels of ITGA10, HGF and MET associate with outcome, and ITGA10 overexpression in a MXF cell line contributes to cell proliferation and survival. All three of these genes may be useful as therapeutic targets. Preoperative serum HGF levels may be a useful prognostic indicator in patients with MXF. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5061. doi:1538-7445.AM2012-5061