Showing papers by "Institute for Systems Biology published in 2012"

Comprehensive molecular portraits of human breast tumours

Abstract: We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.

Comprehensive molecular characterization of human colon and rectal cancer

Abstract: To characterize somatic alterations in colorectal carcinoma, we conducted a genome-scale analysis of 276 samples, analysing exome sequence, DNA copy number, promoter methylation and messenger RNA and microRNA expression. A subset of these samples (97) underwent low-depth-of-coverage whole-genome sequencing. In total, 16% of colorectal carcinomas were found to be hypermutated: three-quarters of these had the expected high microsatellite instability, usually with hypermethylation and MLH1 silencing, and one-quarter had somatic mismatch-repair gene and polymerase e (POLE) mutations. Excluding the hypermutated cancers, colon and rectum cancers were found to have considerably similar patterns of genomic alteration. Twenty-four genes were significantly mutated, and in addition to the expected APC, TP53, SMAD4, PIK3CA and KRAS mutations, we found frequent mutations in ARID1A, SOX9 and FAM123B. Recurrent copy-number alterations include potentially drug-targetable amplifications of ERBB2 and newly discovered amplification of IGF2. Recurrent chromosomal translocations include the fusion of NAV2 and WNT pathway member TCF7L1. Integrative analyses suggest new markers for aggressive colorectal carcinoma and an important role for MYC-directed transcriptional activation and repression.

A cross-platform toolkit for mass spectrometry and proteomics

Abstract: Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2, and characterize protein complexes3. Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access4,5. In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.

An Overlapping Protein-Coding Region in Influenza A Virus Segment 3 Modulates the Host Response

Abstract: Influenza A virus (IAV) infection leads to variable and imperfectly understood pathogenicity. We report that segment 3 of the virus contains a second open reading frame ("X-ORF"), accessed via ribosomal frameshifting. The frameshift product, termed PA-X, comprises the endonuclease domain of the viral PA protein with a C-terminal domain encoded by the X-ORF and functions to repress cellular gene expression. PA-X also modulates IAV virulence in a mouse infection model, acting to decrease pathogenicity. Loss of PA-X expression leads to changes in the kinetics of the global host response, which notably includes increases in inflammatory, apoptotic, and T lymphocyte-signaling pathways. Thus, we have identified a previously unknown IAV protein that modulates the host response to infection, a finding with important implications for understanding IAV pathogenesis.

Comparing the MicroRNA spectrum between serum and plasma.

Abstract: MicroRNAs (miRNAs) are small, non-coding RNAs that regulate various biological processes, primarily through interaction with messenger RNAs. The levels of specific, circulating miRNAs in blood have been shown to associate with various pathological conditions including cancers. These miRNAs have great potential as biomarkers for various pathophysiological conditions. In this study we focused on different sample types' effects on the spectrum of circulating miRNA in blood. Using serum and corresponding plasma samples from the same individuals, we observed higher miRNA concentrations in serum samples compared to the corresponding plasma samples. The difference between serum and plasma miRNA concentration showed some associations with miRNA from platelets, which may indicate that the coagulation process may affect the spectrum of extracellular miRNA in blood. Several miRNAs also showed platform dependent variations in measurements. Our results suggest that there are a number of factors that might affect the measurement of circulating miRNA concentration. Caution must be taken when comparing miRNA data generated from different sample types or measurement platforms.

Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells.

Abstract: We describe a microchip designed to quantify the levels of a dozen cytoplasmic and membrane proteins from single cells. We use the platform to assess protein–protein interactions associated with the EGF-receptor-mediated PI3K signaling pathway. Single-cell sensitivity is achieved by isolating a defined number of cells (n = 0–5) in 2 nL volume chambers, each of which is patterned with two copies of a miniature antibody array. The cells are lysed on-chip, and the levels of released proteins are assayed using the antibody arrays. We investigate three isogenic cell lines representing the cancer glioblastoma multiforme, at the basal level, under EGF stimulation, and under erlotinib inhibition plus EGF stimulation. The measured protein abundances are consistent with previous work, and single-cell analysis uniquely reveals single-cell heterogeneity, and different types and strengths of protein–protein interactions. This platform helps provide a comprehensive picture of altered signal transduction networks in tumor cells and provides insight into the effect of targeted therapies on protein signaling networks.

The Chromosome-Centric Human Proteome Project for cataloging proteins encoded in the genome

Abstract: The Chromosome-Centric Human Proteome Project for cataloging proteins encoded in the genome

The Molecular and Mathematical Basis of Waddington's Epigenetic Landscape: A Framework for post-Darwinian Biology?

Abstract: The Neo-Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo-Darwinism. It needs to incorporate the non-linear, stochastic dynamics of gene networks. A first step is to consider the mathematical correspondence between gene regulatory networks and Waddington's metaphoric 'epigenetic landscape', which actually represents the quasi-potential function of global network dynamics. It explains the coexistence of multiple stable phenotypes within one genotype. The landscape's topography with its attractors is shaped by evolution through mutational re-wiring of regulatory interactions - offering a link between genetic mutation and sudden, broad evolutionary changes.

Reconstruction of genome-scale metabolic models for 126 human tissues using mCADRE.

Abstract: Background Human tissues perform diverse metabolic functions. Mapping out these tissue-specific functions in genome-scale models will advance our understanding of the metabolic basis of various physiological and pathological processes. The global knowledgebase of metabolic functions categorized for the human genome (Human Recon 1) coupled with abundant high-throughput data now makes possible the reconstruction of tissue-specific metabolic models. However, the number of available tissue-specific models remains incomplete compared with the large diversity of human tissues.

Epoxyeicosanoids stimulate multiorgan metastasis and tumor dormancy escape in mice

Abstract: Epoxyeicosatrienoic acids (EETs) are small molecules produced by cytochrome P450 epoxygenases. They are lipid mediators that act as autocrine or paracrine factors to regulate inflammation and vascular tone. As a result, drugs that raise EET levels are in clinical trials for the treatment of hypertension and many other diseases. However, despite their pleiotropic effects on cells, little is known about the role of these epoxyeicosanoids in cancer. Here, using genetic and pharmacological manipulation of endogenous EET levels, we demonstrate that EETs are critical for primary tumor growth and metastasis in a variety of mouse models of cancer. Remarkably, we found that EETs stimulated extensive multiorgan metastasis and escape from tumor dormancy in several tumor models. This systemic metastasis was not caused by excessive primary tumor growth but depended on endothelium-derived EETs at the site of metastasis. Administration of synthetic EETs recapitulated these results, while EET antagonists suppressed tumor growth and metastasis, demonstrating in vivo that pharmacological modulation of EETs can affect cancer growth. Furthermore, inhibitors of soluble epoxide hydrolase (sEH), the enzyme that metabolizes EETs, elevated endogenous EET levels and promoted primary tumor growth and metastasis. Thus, our data indicate a central role for EETs in tumorigenesis, offering a mechanistic link between lipid signaling and cancer and emphasizing the critical importance of considering possible effects of EET-modulating drugs on cancer.

Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics

Abstract: The rigorous testing of hypotheses on suitable sample cohorts is a major limitation in translational research. This is particularly the case for the validation of protein biomarkers; the lack of accurate, reproducible, and sensitive assays for most proteins has precluded the systematic assessment of hundreds of potential marker proteins described in the literature. Here, we describe a high-throughput method for the development and refinement of selected reaction monitoring (SRM) assays for human proteins. The method was applied to generate such assays for more than 1000 cancer-associated proteins, which are functionally related to candidate cancer driver mutations. We used the assays to determine the detectability of the target proteins in two clinically relevant samples: plasma and urine. One hundred eighty-two proteins were detected in depleted plasma, spanning five orders of magnitude in abundance and reaching below a concentration of 10 ng/ml. The narrower concentration range of proteins in urine allowed the detection of 408 proteins. Moreover, we demonstrate that these SRM assays allow reproducible quantification by monitoring 34 biomarker candidates across 83 patient plasma samples. Through public access to the entire assay library, researchers will be able to target their cancer-associated proteins of interest in any sample type using the detectability information in plasma and urine as a guide. The generated expandable reference map of SRM assays for cancer-associated proteins will be a valuable resource for accelerating and planning biomarker verification studies.

Bcl6 expression specifies the T follicular helper cell program in vivo

Abstract: T follicular helper cells (Tfh cells) play a pivotal role in germinal center reactions, which require B cell lymphoma 6 (Bcl6) transcription factor. To analyze their relationships with other effector T cell lineages and their stability in vivo, we developed and analyzed a new Bcl6 reporter mouse alone or together with other lineage reporter systems. Assisted with genome-wide transcriptome analysis, we show substantial plasticity of T cell differentiation in the early phase of immune response. At this stage, CXCR5 appears to be expressed in a Bcl6-independent manner. Once Bcl6 is highly expressed, Tfh cells can persist in vivo and some of them develop into memory cells. Together, our results indicate Bcl6 as a bona fide marker for Tfh polarized program.

Dfam: a database of repetitive DNA based on profile hidden Markov models

Abstract: We present a database of repetitive DNA elements, called Dfam (http://dfam.janelia.org). Many genomes contain a large fraction of repetitive DNA, much of which is made up of remnants of transposable elements (TEs). Accurate annotation of TEs enables research into their biology and can shed light on the evolutionary processes that shape genomes. Identification and masking of TEs can also greatly simplify many downstream genome annotation and sequence analysis tasks. The commonly used TE annotation tools RepeatMasker and Censor depend on sequence homology search tools such as cross_match and BLAST variants, as well as Repbase, a collection of known TE families each represented by a single consensus sequence. Dfam contains entries corresponding to all Repbase TE entries for which instances have been found in the human genome. Each Dfam entry is represented by a profile hidden Markov model, built from alignments generated using RepeatMasker and Repbase. When used in conjunction with the hidden Markov model search tool nhmmer, Dfam produces a 2.9% increase in coverage over consensus sequence search methods on a large human benchmark, while maintaining low false discovery rates, and coverage of the full human genome is 54.5%. The website provides a collection of tools and data views to support improved TE curation and annotation efforts. Dfam is also available for download in flat file format or in the form of MySQL table dumps.

Revolutionizing medicine in the 21st century through systems approaches

Abstract: Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term "personalized medicine", however, fails to reflect the enormous dimensionality of this new medicine that will be predictive, preventive, personalized, and participatory-a vision of medicine we have termed P4 medicine. This reflects a paradigm change in how medicine will be practiced that is revolutionary rather than evolutionary. P4 medicine arises from the confluence of a systems approach to medicine and from the digitalization of medicine that creates the large data sets necessary to deal with the complexities of disease. We predict that systems approaches will empower the transition from conventional reactive medical practice to a more proactive P4 medicine focused on wellness, and will reverse the escalating costs of drug development an will have enormous social and economic benefits. Our vision for P4 medicine in 10 years is that each patient will be associated with a virtual data cloud of billions of data points and that we will have the information technology for healthcare to reduce this enormous data dimensionality to simple hypotheses about health and/or disease for each individual. These data will be multi-scale across all levels of biological organization and extremely heterogeneous in type - this enormous amount of data represents a striking signal-to-noise (S/N) challenge. The key to dealing with this S/N challenge is to take a "holistic systems approach" to disease as we will discuss in this article.

Quasi-potential landscape in complex multi-stable systems

Abstract: The developmental dynamics of multicellular organisms is a process that takes place in a multi-stable system in which each attractor state represents a cell type, and attractor transitions correspond to cell differentiation paths. This new understanding has revived the idea of a quasi-potential landscape, first proposed by Waddington as a metaphor. To describe development, one is interested in the 'relative stabilities' of N attractors (N > 2). Existing theories of state transition between local minima on some potential landscape deal with the exit part in the transition between two attractors in pair-attractor systems but do not offer the notion of a global potential function that relates more than two attractors to each other. Several ad hoc methods have been used in systems biology to compute a landscape in non-gradient systems, such as gene regulatory networks. Here we present an overview of currently available methods, discuss their limitations and propose a new decomposition of vector fields that permits the computation of a quasi-potential function that is equivalent to the Freidlin-Wentzell potential but is not limited to two attractors. Several examples of decomposition are given, and the significance of such a quasi-potential function is discussed.

Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine.

Abstract: A grand challenge impeding optimal treatment outcomes for cancer patients arises from the complex nature of the disease: the cellular heterogeneity, the myriad of dysfunctional molecular and genetic networks as results of genetic (somatic) and environmental perturbations. Systems biology, with its holistic approach to understanding fundamental principles in biology, and the empowering technologies in genomics, proteomics, single-cell analysis, microfluidics, and computational strategies, enables a comprehensive approach to medicine, which strives to unveil the pathogenic mechanisms of diseases, identify disease biomarkers and begin thinking about new strategies for drug target discovery. The integration of multi-dimensional high throughput “omics” measurements from tumor tissues and corresponding blood specimens, together with new systems strategies for diagnostics, enables the identification of cancer biomarkers that will enable presymptomatic diagnosis, stratification of disease, assessment of disease progression, evaluation of patient response to therapy, and the identification of reoccurrences. While some aspects of systems medicine are being adopted in clinical oncology practice through companion molecular diagnostics for personalized therapy, the mounting influx of global quantitative data from both wellness and diseases, is shaping up a transformational paradigm in medicine we termed predictive, preventive, personalized, and participatory (P4) medicine, which requires new strategies, both scientific and organizational, to enable bringing this revolution in medicine to patients and to the healthcare system. P4 medicine will have a profound impact on society—transforming the healthcare system, turning around the ever escalating costs of healthcare, digitizing the practice of medicine and creating enormous economic opportunities for those organizations and nations that embrace this revolution

PASSEL: The PeptideAtlas SRMexperiment library

Abstract: Public repositories for proteomics data have accelerated proteomics research by enabling more efficient cross-analyses of datasets, supporting the creation of protein and peptide compendia of experimental results, supporting the development and testing of new software tools, and facilitating the manuscript review process. The repositories available to date have been designed to accommodate either shotgun experiments or generic proteomic data files. Here, we describe a new kind of proteomic data repository for the collection and representation of data from selected reaction monitoring (SRM) measurements. The PeptideAtlas SRM Experiment Library (PASSEL) allows researchers to easily submit proteomic data sets generated by SRM. The raw data are automatically processed in a uniform manner and the results are stored in a database, where they may be downloaded or browsed via a web interface that includes a chromatogram viewer. PASSELenables cross-analysis of SRMdata, supports optimization of SRMdata collection, and facilitates the review process of SRMdata. Further, PASSELwill help in the assessment of proteotypic peptide performance in a wide array of samples containing the same peptide, as well as across multiple experimental protocols.

Engineering a cyanobacterial cell factory for production of lactic acid.

Abstract: Metabolic engineering of microorganisms has become a versatile tool to facilitate production of bulk chemicals, fuels, etc. Accordingly, CO(2) has been exploited via cyanobacterial metabolism as a sustainable carbon source of biofuel and bioplastic precursors. Here we extended these observations by showing that integration of an ldh gene from Bacillus subtilis (encoding an l-lactate dehydrogenase) into the genome of Synechocystis sp. strain PCC6803 leads to l-lactic acid production, a phenotype which is shown to be stable for prolonged batch culturing. Coexpression of a heterologous soluble transhydrogenase leads to an even higher lactate production rate and yield (lactic acid accumulating up to a several-millimolar concentration in the extracellular medium) than those for the single ldh mutant. The expression of a transhydrogenase alone, however, appears to be harmful to the cells, and a mutant carrying such a gene is rapidly outcompeted by a revertant(s) with a wild-type growth phenotype. Furthermore, our results indicate that the introduction of a lactate dehydrogenase rescues this phenotype by preventing the reversion.

The complex exogenous RNA spectra in human plasma: an interface with human gut biota?

Abstract: Human plasma has long been a rich source for biomarker discovery. It has recently become clear that plasma RNA molecules, such as microRNA, in addition to proteins are common and can serve as biomarkers. Surveying human plasma for microRNA biomarkers using next generation sequencing technology, we observed that a significant fraction of the circulating RNA appear to originate from exogenous species. With careful analysis of sequence error statistics and other controls, we demonstrated that there is a wide range of RNA from many different organisms, including bacteria and fungi as well as from other species. These RNAs may be associated with protein, lipid or other molecules protecting them from RNase activity in plasma. Some of these RNAs are detected in intracellular complexes and may be able to influence cellular activities under in vitro conditions. These findings raise the possibility that plasma RNAs of exogenous origin may serve as signaling molecules mediating for example the human-microbiome interaction and may affect and/or indicate the state of human health.

LRRK2 Parkinson disease mutations enhance its microtubule association.

Abstract: Dominant missense mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common genetic causes of Parkinson disease (PD) and genome-wide association studies identify LRRK2 sequence variants as risk factors for sporadic PD. Intact kinase function appears critical for the toxicity of LRRK2 PD mutants, yet our understanding of how LRRK2 causes neurodegeneration remains limited. We find that most LRRK2 PD mutants abnormally enhance LRRK2 oligomerization, causing it to form filamentous structures in transfections of cell lines or primary neuronal cultures. Strikingly, ultrastructural analyses, including immuno-electron microscopy and electron microscopic tomography, demonstrate that these filaments consist of LRRK2 recruited onto part of the cellular microtubule network in a well-ordered, periodic fashion. Like LRRK2-related neurodegeneration, microtubule association requires intact kinase function and the WD40 domain, potentially linking microtubule binding and neurodegeneration. Our observations identify a novel effect of LRRK2 PD mutations and highlight a potential role for microtubules in the pathogenesis of LRRK2-related neurodegeneration.

Interferon-β therapy against EAE is effective only when development of the disease depends on the NLRP3 inflammasome.

Abstract: Interferon-β (IFN-β) is widely used to treat multiple sclerosis (MS), and its efficacy was demonstrated in the setting of experimental autoimmune encephalomyelitis (EAE), an animal model of MS; however, IFN-β is not effective in treating all cases of MS. Here, we demonstrate that signaling by IFNAR (the shared receptor for IFN-α and IFN-β) on macrophages inhibits activation of Rac1 and the generation of reactive oxygen species (ROS) through suppressor of cytokine signaling 1 (SOCS1). The inhibition of Rac1 activation and ROS generation suppressed the activity of the Nod-like receptor (NLR) family, pyrin domain-containing 3 (NLRP3) inflammasome, which resulted in attenuated EAE pathogenicity. We further found that two subsets of EAE could be defined on the basis of their dependency on the NLRP3 inflammasome and that IFN-β was not an effective therapy when EAE was induced in an NLRP3 inflammasome-independent fashion. Thus, our study demonstrates a previously uncharacterized signaling pathway that is involved in the suppression of EAE by IFN-β and characterizes NLRP3-independent EAE, which cannot be treated with IFN-β.

Quasi-potential landscape in complex multi-stable systems

Abstract: Developmental dynamics of multicellular organism is a process that takes place in a multi-stable system in which each attractor state represents a cell type and attractor transitions correspond to cell differentiation paths. This new understanding has revived the idea of a quasi-potential landscape, first proposed by Waddington as a metaphor. To describe development one is interested in the "relative stabilities" of N attractors (N>2). Existing theories of state transition between local minima on some potential landscape deal with the exit in the transition between a pair attractor but do not offer the notion of a global potential function that relate more than two attractors to each other. Several ad hoc methods have been used in systems biology to compute a landscape in non-gradient systems, such as gene regulatory networks. Here we present an overview of the currently available methods, discuss their limitations and propose a new decomposition of vector fields that permit the computation of a quasi-potential function that is equivalent to the Freidlin-Wentzell potential but is not limited to two attractors. Several examples of decomposition are given and the significance of such a quasi-potential function is discussed.

The Open Graph Drawing Framework (OGDF)

Abstract: Cluster Layout Planarity testing Booth/Lueker and Boyer/Myrvold Cluster (Feng et al) Upward (Bertolazzi et al) Customizable planarization method Edge insertion (fixed & variable embedding) Crossing Minimization optimal, minor-monotone, simultaneous Orthogonal layout Compaction (constructive + improvement) Customizable Sugiyama layout Energy-based layout (FM, ) Tree-, Circular-, Balloon-layout,

A miRNA-regulatory network explains how dysregulated miRNAs perturb oncogenic processes across diverse cancers

Abstract: MicroRNAs (miRNAs) mediate degradation (Baek et al. 2008) or translational repression (Selbach et al. 2008) of gene transcripts associated with an array of biological processes including many of the hallmarks of cancer (Hanahan and Weinberg 2000, 2011; Dalmay and Edwards 2006; Ruan et al. 2009). Not surprisingly, dysregulated miRNAs can be readily detected in tumor biopsies (Jiang et al. 2009) and are known to be diagnostic and prognostic indicators (Zen and Zhang 2012). In some cases miRNAs have also been shown to be potential therapeutic targets (Garofalo and Croce 2011; Nana-Sinkam and Croce 2011). Conservative estimates suggest that each human miRNA regulates several hundred transcripts (Baek et al. 2008; Selbach et al. 2008), and thus miRNA-mediated regulation results in statistically significant gene coexpression signatures that are readily discovered through transcriptome profiling (Lim et al. 2005; Wang and Wang 2006; Weber et al. 2006; Brueckner et al. 2007; Chang et al. 2007; Grimson et al. 2007; He et al. 2007; Johnson et al. 2007; Karginov et al. 2007; Linsley et al. 2007; Frankel et al. 2008; Georges et al. 2008; Hendrickson et al. 2008; Ozen et al. 2008; Sengupta et al. 2008; Ceppi et al. 2009; Fasanaro et al. 2009; Tan et al. 2009; Tsai et al. 2009; Valastyan et al. 2009; Malzkorn et al. 2010; Wang et al. 2010). Together these studies motivated us to build a generalized framework for the inference of miRNA regulatory networks for genes discovered to be coexpressed through analysis of genome-wide transcriptome profiles. There are two commonly used strategies to identify the miRNA regulator(s) responsible for the observed coexpression of a set of genes: (1) Enrichment of predicted 3′ UTR binding sites for a known miRNA (Kertesz et al. 2007; Betel et al. 2008, 2010; Friedman et al. 2009); or (2) de novo identification of a 3′ UTR motif that is complementary to a seed sequence of a miRNA in miRBase (Linhart et al. 2008; Fan et al. 2009; Goodarzi et al. 2009; Kozomara and Griffiths-Jones 2011). Algorithms utilizing the first strategy incorporate some combination of seed complementarity, cross-species conservation, and thermodynamic properties of the binding site. These algorithms include PITA (Kertesz et al. 2007), TargetScan (Friedman et al. 2009), and both miRanda (Betel et al. 2008) and miRSVR (Betel et al. 2010) from microRNA.org. While the combined modeling of two or more miRNA-binding properties within these algorithms boosts signal (Supplemental Table 1), the multiple hypotheses testing required to identify bona fide miRNA-binding sites unfortunately also simultaneously leads to high false-negative rates (∼32%–52%) (Sethupathy et al. 2006). Therefore, inference of a comprehensive miRNA regulatory network would require the integration of best-performing algorithms from this class with algorithms that utilize the second strategy. We have recently developed a novel algorithm miRvestigator to accurately associate 3′ UTR motifs to complementary miRNA seed sequences (Plaisier et al. 2011). However, for this algorithm to be effective it has to be coupled to a second algorithm Weeder (Pavesi et al. 2006) that can accurately detect de novo cis-regulatory motifs that are conserved within the 3′ UTRs of the coexpressed genes (Linhart et al. 2008; Fan et al. 2009). miRvestigator converts relative conservation of nucleotides at each position of a cis-regulatory motif discovered by Weeder into a profile hidden Markov model (HMM). Using this HMM, the Viterbi algorithm, and a background distribution of all possible k-mer sequences (6-, 7-, or 8-mer), miRvestigator accurately identifies the most likely miRNA that binds the conserved 3′ UTR element to mediate the observed coregulation (Plaisier et al. 2011). Here, we report the construction of a generalized framework for the inference of regulation by miRNAs (FIRM). First, we have compiled a compendium of transcriptome profiles from studies that had interrogated differential expression of genes in response to targeted perturbation of specific miRNAs (Lim et al. 2005; Weber et al. 2006; Brueckner et al. 2007; Chang et al. 2007; Grimson et al. 2007; He et al. 2007; Johnson et al. 2007; Karginov et al. 2007; Linsley et al. 2007; Frankel et al. 2008; Georges et al. 2008; Hendrickson et al. 2008; Ozen et al. 2008; Sengupta et al. 2008; Ceppi et al. 2009; Fasanaro et al. 2009; Tan et al. 2009; Tsai et al. 2009; Valastyan et al. 2009; Malzkorn et al. 2010; Wang et al. 2010). Second, using this compendium of miRNA-perturbed transcriptomes we demonstrate that functional miRNA-binding sites (8 bp of complementarity) preferentially reside in the 3′ UTRs. Further, we demonstrate that using preferential 3′ UTR localization as a heuristic significantly increases sensitivity and specificity of miRNA-binding site discovery by Weeder-miRvestigator. Third, using the compendium of miRNA-perturbed transcriptomes we have identified and integrated the best performing algorithms into a generalized framework for inference of miRNA regulatory networks. Finally, we demonstrate the utility of this framework by applying it to a set of 2240 coexpression signatures from 46 different cancers. The original study was able to associate only four signatures to putative regulation by a known miRNA (Goodarzi et al. 2009). In contrast, using the integrated framework we were able to explain 1324 signatures as potential outcomes of regulation by specific miRNAs in miRBase. By applying functional enrichment and semantic similarity we have identified within this expansive network specific miRNAs associated with hallmarks of cancer. Further, filtering gene coexpression signatures for specific hallmarks of cancer such as “tissue invasion and metastasis” generated a metastatic cancer–miRNA regulatory network of 33 miRNAs. Importantly, this revealed that a relatively small subset of miRNAs regulate multiple oncogenic processes across different cancers. Through in-depth analyses of data from prior studies as well as new data from targeted miRNA-perturbation experiments, we have experimentally validated the role of miR-29 family members in lung adenocarcinoma and discovered gene targets for regulation by the relatively unknown miR-767-5p. These analyses and validations demonstrate how the cancer–miRNA regulatory network can be used to accelerate discovery of miRNA-based biomarkers and potentially therapeutics.