Association analysis identifies 65 new breast cancer risk loci

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Integrated analysis of proteome, phosphotyrosine-proteome, tyrosine-kinome, and tyrosine-phosphatome in acute myeloid leukemia

Reversible protein-tyrosine phosphorylation is catalyzed by the antagonistic actions of protein-tyrosine kinases (PTKs) and phosphatases (PTPs), and represents a major form of cell regulation. Acute myeloid leukemia (AML) is an aggressive hematological malignancy that results from the acquisition of multiple genetic alterations, which in some instances are associated with deregulated protein-phosphotyrosine (pY) mediated signaling networks. However, although individual PTKs and PTPs have been linked to AML and other malignancies, analysis of protein-pY networks as a function of activated PTKs and PTPs has not been done. In this study, MS was used to characterize AML proteomes, and phospho-proteome-subsets including pY proteins, PTKs, and PTPs. AML proteomes resolved into two groups related to high or low degrees of maturation according to French-American-British classification, and reflecting differential expression of cell surface antigens. AML pY proteomes reflect canonical, spatially organized signaling networks, unrelated to maturation, with heterogeneous expression of activated receptor and nonreceptor PTKs. We present the first integrated analysis of the pY-proteome, activated PTKs, and PTPs. Every PTP and most PTKs have both positive and negative associations with the pY-proteome. pY proteins resolve into groups with shared PTK and PTP correlations. These findings highlight the importance of pY turnover and the PTP phosphatome in shaping the pY-proteome in AML.

microRNA-143/145 loss induces Ras signaling to promote aggressive Pten-deficient basal-like breast cancer

The tumor suppressor PTEN is frequently inactivated in breast and other cancers; yet, germ-line mutations in this gene induce nonmalignant hamartomas, indicating dependency on additional cooperating events. Here we show that most tumors derived from conditional deletion of mouse pten in mammary epithelium are highly differentiated and lack transplantable tumor-initiating cells (TICs) capable of seeding new tumors following orthotopic injection of FACS-sorted or tumorsphere cells. A rare group of poorly differentiated tumors did harbor transplantable TICs. These transplantable tumors exhibited distinct molecular classification, signaling pathways, chromosomal aberrations, and mutational landscape, as well as reduced expression of microRNA-143/145 (miR-143/145). Stable knockdown of miR-143/145 conferred tumorigenic potential upon poorly transplantable pten-deficient tumor cells through a mechanism involving induction of RAS signaling, leading to increased sensitivity to MEK inhibition. In humans, miR-145 deficiency significantly correlated with elevated RAS-pathway activity in basal-like breast cancer, and patients with combined PTEN/miR-145 loss or PTEN-loss/high RAS-pathway activity exhibited poor clinical outcome. These results underscore a selective pressure for combined PTEN loss together with RAS-pathway activation, either through miR-145 loss or other mechanisms, in basal-like breast cancer, and a need to identify and prioritize these tumors for aggressive therapy.

Intertumoral Heterogeneity within Medulloblastoma Subgroups

While molecular subgrouping has revolutionized medulloblastoma classification, the extent of heterogeneity within subgroups is unknown. Similarity network fusion (SNF) applied to genome-wide DNA methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes. After integration of somatic copy-number alterations, and clinical features specific to each cluster, we identify 12 different subtypes of medulloblastoma. Integrative analysis using SNF further delineates group 3 from group 4 medulloblastoma, which is not as readily apparent through analyses of individual data types. Two clear subtypes of infants with Sonic Hedgehog medulloblastoma with disparate outcomes and biology are identified. Medulloblastoma subtypes identified through integrative clustering have important implications for stratification of future clinical trials.

Integrative Cancer Pharmacogenomics to Infer Large-Scale Drug Taxonomy

Identification of drug targets and mechanism of action (MoA) for new and uncharacterized anticancer drugs is important for optimization of treatment efficacy. Current MoA prediction largely relies on prior information including side effects, therapeutic indication, and chemoinformatics. Such information is not transferable or applicable for newly identified, previously uncharacterized small molecules. Therefore, a shift in the paradigm of MoA predictions is necessary toward development of unbiased approaches that can elucidate drug relationships and efficiently classify new compounds with basic input data. We propose here a new integrative computational pharmacogenomic approach, referred to as Drug Network Fusion (DNF), to infer scalable drug taxonomies that rely only on basic drug characteristics toward elucidating drug-drug relationships. DNF is the first framework to integrate drug structural information, high-throughput drug perturbation, and drug sensitivity profiles, enabling drug classification of new experimental compounds with minimal prior information. DNF taxonomy succeeded in identifying pertinent and novel drug-drug relationships, making it suitable for investigating experimental drugs with potential new targets or MoA. The scalability of DNF facilitated identification of key drug relationships across different drug categories, providing a flexible tool for potential clinical applications in precision medicine. Our results support DNF as a valuable resource to the cancer research community by providing new hypotheses on compound MoA and potential insights for drug repurposing. Cancer Res; 77(11); 3057-69. ©2017 AACR.

Integrated (epi)-Genomic Analyses Identify Subgroup-Specific Therapeutic Targets in CNS Rhabdoid Tumors

We recently reported that atypical teratoid rhabdoid tumors (ATRTs) comprise at least two transcriptional subtypes with different clinical outcomes; however, the mechanisms underlying therapeutic heterogeneity remained unclear. In this study, we analyzed 191 primary ATRTs and 10 ATRT cell lines to define the genomic and epigenomic landscape of ATRTs and identify subgroup-specific therapeutic targets. We found ATRTs segregated into three epigenetic subgroups with distinct genomic profiles, SMARCB1 genotypes, and chromatin landscape that correlated with differential cellular responses to a panel of signaling and epigenetic inhibitors. Significantly, we discovered that differential methylation of a PDGFRB-associated enhancer confers specific sensitivity of group 2 ATRT cells to dasatinib and nilotinib, and suggest that these are promising therapies for this highly lethal ATRT subtype.

Identification of CD146 as a marker enriched for tumor-propagating capacity reveals targetable pathways in primary human sarcoma

Tumor-propagating cells (TPCs) are believed to drive cancer initiation, progression and recurrence. These cells are characterized by enhanced tumorigenicity and self-renewal. The ability to identify such cells in primary human sarcomas relies on the dye exclusion ability of tumor side population (SP) cells. Here, we performed a high-throughput cell surface antigen screen and found that CD146 is enriched in the SP population. In vivo serial transplantation assays showed that CD146+ cells are highly tumorigenic, capable of self-renewal and thus enriches for the TPC population. In addition, depletion of SP cells from the CD146+ population show that CD146+ cells and SP cells are a distinct and overlapping TPC populations. Gene expression profiling of CD146+ and SP cells revealed multiple pathways commonly upregulated in both of these populations. Inhibition of one of these upregulated pathways, Notch signaling, significantly reduced tumor growth and self-renewal. Our data demonstrate that CD146 is an effective cell surface marker for enriching TPCs in primary human sarcomas. Targeting differentially activated pathways in TPCs may provide new therapeutic strategies for treating sarcoma.

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them.

RB1 deficiency in triple-negative breast cancer induces mitochondrial protein translation

Triple-negative breast cancer (TNBC) includes basal-like and claudin-low subtypes for which no specific treatment is currently available. Although the retinoblastoma tumor-suppressor gene (RB1) is frequently lost together with TP53 in TNBC, it is not directly targetable. There is thus great interest in identifying vulnerabilities downstream of RB1 that can be therapeutically exploited. Here, we determined that combined inactivation of murine Rb and p53 in diverse mammary epithelial cells induced claudin-low-like TNBC with Met, Birc2/3-Mmp13-Yap1, and Pvt1-Myc amplifications. Gene set enrichment analysis revealed that Rb/p53-deficient tumors showed elevated expression of the mitochondrial protein translation (MPT) gene pathway relative to tumors harboring p53 deletion alone. Accordingly, bioinformatic, functional, and biochemical analyses showed that RB1-E2F complexes bind to MPT gene promoters to regulate transcription and control MPT. Additionally, a screen of US Food and Drug Administration-approved (FDA-approved) drugs identified the MPT antagonist tigecycline (TIG) as a potent inhibitor of Rb/p53-deficient tumor cell proliferation. TIG preferentially suppressed RB1-deficient TNBC cell proliferation, targeted both the bulk and cancer stem cell fraction, and strongly attenuated xenograft growth. It also cooperated with sulfasalazine, an FDA-approved inhibitor of cystine xCT antiporter, in culture and xenograft assays. Our results suggest that RB1 deficiency promotes cancer cell proliferation in part by enhancing mitochondrial function and identify TIG as a clinically approved drug for RB1-deficient TNBC.

Antitumor activity of the novel multi-kinase inhibitor EC-70124 in triple negative breast cancer

Disseminated triple negative breast cancer (TNBC) is an incurable disease with limited therapeutic options beyond chemotherapy. Therefore, identification of druggable vulnerabilities is an important aim. Protein kinases play a central role in cancer and particularly in TNBC. They are involved in many oncogenic functions including migration, proliferation, genetic stability or maintenance of stem-cell like properties. In this article we describe a novel multi-kinase inhibitor with antitumor activity in this cancer subtype. EC-70124 is a hybrid indolocarbazole analog obtained by combinatorial biosynthesis of Rebeccamycin and Staurosporine genes that showed antiproliferative effect and in vivo antitumoral activity. Biochemical experiments demonstrated the inhibition of the PI3K/mTOR and JAK/STAT pathways. EC-70124 mediated DNA damage leading to cell cycle arrest at the G2/M phase. Pathway analyses identified several deregulated functions including cell proliferation, migration, DNA damage, regulation of stem cell differentiation and reversion of the epithelial-mesenchymal transition (EMT) phenotype, among others. Combination studies showed a synergistic interaction of EC-70124 with docetaxel, and an enhanced activity in vivo. Furthermore, EC-70124 had a good pharmacokinetic profile. In conclusion these experiments demonstrate the antitumor activity of EC-70124 in TNBC paving the way for the future clinical development of this drug alone or in combination with chemotherapy.

AutoAnnotate: A Cytoscape app for summarizing networks with semantic annotations

Networks often contain regions of tightly connected nodes, or clusters, that highlight their shared relationships. An effective way to create a visual summary of a network is to identify clusters and annotate them with an enclosing shape and a summarizing label. Cytoscape provides the ability to annotate a network with shapes and labels, however these annotations must be created manually one at a time, which can be a laborious process. AutoAnnotate is a Cytoscape 3 App that automates the process of identifying clusters and visually annotating them. It greatly reduces the time and effort required to fully annotate clusters in a network, and provides freedom to experiment with different strategies for identifying and labelling clusters. Many customization options are available that enable the user to refine the generated annotations as required. Annotated clusters may be collapsed into single nodes using the Cytoscape groups feature, which helps simplify a network by making its overall structure more visible. AutoAnnotate is applicable to any type of network, including enrichment maps, protein-protein interactions, pathways, or social networks.

Ectopic miR-125a Expression Induces Long-Term Repopulating Stem Cell Capacity in Mouse and Human Hematopoietic Progenitors

Umbilical cord blood (CB) is a convenient and broadly used source of hematopoietic stem cells (HSCs) for allogeneic stem cell transplantation. However, limiting numbers of HSCs remain a major constraint for its clinical application. Although one feasible option would be to expand HSCs to improve therapeutic outcome, available protocols and the molecular mechanisms governing the self-renewal of HSCs are unclear. Here, we show that ectopic expression of a single microRNA (miRNA), miR-125a, in purified murine and human multipotent progenitors (MPPs) resulted in increased self-renewal and robust long-term multi-lineage repopulation in transplanted recipient mice. Using quantitative proteomics and western blot analysis, we identified a restricted set of miR-125a targets involved in conferring long-term repopulating capacity to MPPs in humans and mice. Our findings offer the innovative potential to use MPPs with enhanced self-renewal activity to augment limited sources of HSCs to improve clinical protocols.

Predicting physiologically relevant SH3 domain mediated protein-protein interactions in yeast

MOTIVATION

Many intracellular signaling processes are mediated by interactions involving peptide recognition modules such as SH3 domains. These domains bind to small, linear protein sequence motifs which can be identified using high-throughput experimental screens such as phage display. Binding motif patterns can then be used to computationally predict protein interactions mediated by these domains. While many protein-protein interaction prediction methods exist, most do not work with peptide recognition module mediated interactions or do not consider many of the known constraints governing physiologically relevant interactions between two proteins.

RESULTS

A novel method for predicting physiologically relevant SH3 domain-peptide mediated protein-protein interactions in S. cerevisae using phage display data is presented. Like some previous similar methods, this method uses position weight matrix models of protein linear motif preference for individual SH3 domains to scan the proteome for potential hits and then filters these hits using a range of evidence sources related to sequence-based and cellular constraints on protein interactions. The novelty of this approach is the large number of evidence sources used and the method of combination of sequence based and protein pair based evidence sources. By combining different peptide and protein features using multiple Bayesian models we are able to predict high confidence interactions with an overall accuracy of 0.97.

AVAILABILITY AND IMPLEMENTATION

Domain-Motif Mediated Interaction Prediction (DoMo-Pred) command line tool and all relevant datasets are available under GNU LGPL license for download from http://www.baderlab.org/Software/DoMo-Pred The DoMo-Pred command line tool is implemented using Python 2.7 and C ++.

CONTACT

gary.bader@utoronto.ca

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors.

HOX gene complement and expression in the planarian Schmidtea mediterranea

Background

Freshwater planarians are well known for their regenerative abilities. Less well known is how planarians maintain spatial patterning in long-lived adult animals or how they re-pattern tissues during regeneration. HOX genes are good candidates to regulate planarian spatial patterning, yet the full complement or genomic clustering of planarian HOX genes has not yet been described, primarily because only a few have been detectable by in situ hybridization, and none have given morphological phenotypes when knocked down by RNAi.

Results

Because the planarian Schmidteamediterranea (S. mediterranea) is unsegmented, appendage less, and morphologically simple, it has been proposed that it may have a simplified HOX gene complement. Here, we argue against this hypothesis and show that S. mediterranea has a total of 13 HOX genes, which represent homologs to all major axial categories, and can be detected by whole-mount in situ hybridization using a highly sensitive method. In addition, we show that planarian HOX genes do not cluster in the genome, yet 5/13 have retained aspects of axially restricted expression. Finally, we confirm HOX gene axial expression by RNA deep-sequencing 6 anterior–posterior “zones” of the animal, which we provide as a dataset to the community to discover other axially restricted transcripts.

Conclusions

Freshwater planarians have an unappreciated HOX gene complexity, with all major axial categories represented. However, we conclude based on adult expression patterns that planarians have a derived body plan and their asexual lifestyle may have allowed for large changes in HOX expression from the last common ancestor between arthropods, flatworms, and vertebrates. Using our in situ method and axial zone RNAseq data, it should be possible to further understand the pathways that pattern the anterior–posterior axis of adult planarians.

Electronic supplementary material

The online version of this article (doi:10.1186/s13227-016-0044-8) contains supplementary material, which is available to authorized users.

miR-126 Regulates Distinct Self-Renewal Outcomes in Normal and Malignant Hematopoietic Stem Cells

To investigate miRNA function in human acute myeloid leukemia (AML) stem cells (LSC), we generated a prognostic LSC-associated miRNA signature derived from functionally validated subpopulations of AML samples. For one signature miRNA, miR-126, high bioactivity aggregated all in vivo patient sample LSC activity into a single sorted population, tightly coupling miR-126 expression to LSC function. Through functional studies, miR-126 was found to restrain cell cycle progression, prevent differentiation, and increase self-renewal of primary LSC in vivo. Compared with prior results showing miR-126 regulation of normal hematopoietic stem cell (HSC) cycling, these functional stem effects are opposite between LSC and HSC. Combined transcriptome and proteome analysis demonstrates that miR-126 targets the PI3K/AKT/MTOR signaling pathway, preserving LSC quiescence and promoting chemotherapy resistance.

Cytoscape.js: a graph theory library for visualisation and analysis

Summary: Cytoscape.js is an open-source JavaScript-based graph library. Its most common use case is as a visualization software component, so it can be used to render interactive graphs in a web browser. It also can be used in a headless manner, useful for graph operations on a server, such as Node.js.

Availability and implementation: Cytoscape.js is implemented in JavaScript. Documentation, downloads and source code are available at http://js.cytoscape.org.

Contact:gary.bader@utoronto.ca

Pathway and network analysis of cancer genomes

Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.

Erratum to: Inferring interaction type in gene regulatory networks using co-expression data

[This corrects the article DOI: 10.1186/s13015-015-0054-4.].

Social Network: a Cytoscape app for visualizing co-authorship networks

Networks that represent connections between individuals can be valuable analytic tools. The Social Network Cytoscape app is capable of creating a visual summary of connected individuals automatically. It does this by representing relationships as networks where each node denotes an individual and an edge linking two individuals represents a connection. The app focuses on creating visual summaries of individuals connected by co-authorship links in academia, created from bibliographic databases like PubMed, Scopus and InCites. The resulting co-authorship networks can be visualized and analyzed to better understand collaborative research networks or to communicate the extent of collaboration and publication productivity among a group of researchers, like in a grant application or departmental review report. It can also be useful as a research tool to identify important research topics, researchers and papers in a subject area.

NetMatchStar: an enhanced Cytoscape network querying app

We present NetMatchStar, a Cytoscape app to find all the occurrences of a query graph in a network and check for its significance as a motif with respect to seven different random models. The query can be uploaded or built from scratch using Cytoscape facilities. The app significantly enhances the previous NetMatch in style, performance and functionality. Notably NetMatchStar allows queries with wildcards.

Social Network: a Cytoscape app for visualizing co-publication networks

Networks that represent connections between individuals can be valuable analytic tools. The Social Network Cytoscape app is capable of creating a visual summary of connected individuals automatically. It does this by representing relationships as networks where each node denotes an individual and an edge linking two individuals represents a connection. The app focuses on creating visual summaries of individuals connected by co-publication links in academia, created from bibliographic databases like PubMed, Scopus and InCites. The resulting co-publication networks can be visualized and analyzed to better understand collaborative research networks or to communicate the extent of collaboration and publication productivity among a group of researchers, like in a grant application or departmental review report. It can also be useful as a research tool to identify important research topics, researchers and papers in a subject area.