Dynamic visual exploration of detailed pathway information can help researchers digest and interpret complex mechanisms and genomic datasets.
ChiBE is a free, open-source software tool for ...visualizing, querying, and analyzing human biological pathways in BioPAX format. The recently released version 2 can search for neighborhoods, paths between molecules, and common regulators/targets of molecules, on large integrated cellular networks in the Pathway Commons database as well as in local BioPAX models. Resulting networks can be automatically laid out for visualization using a graphically rich, process-centric notation. Profiling data from the cBioPortal for Cancer Genomics and expression data from the Gene Expression Omnibus can be overlaid on these networks.
ChiBE's new capabilities are organized around a genomics-oriented workflow and offer a unique comprehensive pathway analysis solution for genomics researchers. The software is freely available at http://code.google.com/p/chibe.
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The interaction between drugs and their targets, often proteins, and between antibodies and their targets, is important for planning and analyzing investigational and therapeutic interventions in ...many biological systems. Although drug-target and antibody-target datasets are available in separate databases, they are not publicly available in an integrated bioinformatics resource. As medical therapeutics, especially in cancer, increasingly uses targeted drugs and measures their effects on biomolecular profiles, there is an unmet need for a user-friendly toolset that allows researchers to comprehensively and conveniently access and query information about drugs, antibodies and their targets.
The PiHelper framework integrates human drug-target and antibody-target associations from publicly available resources to help meet the needs of researchers in systems pharmacology, perturbation biology and proteomics. PiHelper has utilities to (i) import drug- and antibody-target information; (ii) search the associations either programmatically or through a web user interface (UI); (iii) visualize the data interactively in a network; and (iv) export relationships for use in publications or other analysis tools.
PiHelper is a free software under the GNU Lesser General Public License (LGPL) v3.0. Source code and documentation are at http://bit.ly/pihelper. We plan to coordinate contributions from the community by managing future releases.
Abstract
The most prominent or most interesting genomic alteration events from an individual tumor sample can now be browsed and analyzed in the cBio Cancer Genomics Portal. With the rapid ...accumulation of detailed and comprehensive genomic maps of thousands of tumors in The Cancer Genome Atlas and other projects it has now become feasible to nominate the functionally most significant events affecting a tumor from an individual patient.
The cBio Cancer Genomics Portal (http://cbioportal.org) allows interactive exploration of multidimensional cancer genomics data sets, currently for more than 6,000 tumor samples from 20 cancer genomics studies, including all TCGA projects. This information gateway significantly lowers the barrier between complex genomic data and their efficient use by cancer researchers for the development of biologic insights and clinical applications.
In addition to gene-by-gene alteration maps across many samples and across diverse tumor types, one can now view genomic alterations in individual tumor samples. As there are potentially hundreds or thousands of genomic alterations in any single tumor sample, it is crucially important to select, for inspection and analysis, alteration events most likely to contribute to oncogenesis or affect the response to therapy. In the cBio portal patient view, this selection is done making use of recurrence statistics, background functional knowledge and predicted functional impact, under the control of the cancer researcher.
All relevant data about a tumor are displayed on a single page, including clinical characteristics, summaries of the extent of mutations and copy-number alterations, as well as details about mutated, amplified, and deleted genes. Genomic alterations are filtered by the following criteria: recurrence of mutations or copy-number alterations across the tumor cohort (MutSig and GISTIC), mutation occurrence in COSMIC, and by cancer gene annotation (via the Sanger Cancer Gene Census and other sources). The patient view also provides information about drugs that target the altered genes and lists relevant clinical trials.
The patient view is fully interactive and enables quick and easy assessment of all relevant genomic events in individual tumor samples. All data can be viewed in the context of the other tumors in the cohort, which facilitates classification of tumor samples by genomic criteria and can supplement standard pathology. Once characterization of genomic alterations in tumor samples becomes standard practice in patient care, this tool could be used to assess prognosis and guide treatment decisions, ideally the personalized choice of targeted therapies.
Citation Format: Jianjiong Gao, Selcuk Onur Sumer, Gideon Dresdner, Bülent Arman Aksoy, Chris Sander, Nikolaus Schultz. Individual patient cancer profiles in the cBio Cancer Genomic Portal. abstract. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5140. doi:10.1158/1538-7445.AM2013-5140
Across clinical trials, T cell expansion and persistence following adoptive cell transfer (ACT) have correlated with superior patient outcomes. Herein, we undertook a pan-cancer analysis to identify ...actionable ligand-receptor pairs capable of compromising T cell durability following ACT. We discovered that FASLG, the gene encoding the apoptosis-inducing ligand FasL, is overexpressed within the majority of human tumor microenvironments (TMEs). Further, we uncovered that Fas, the receptor for FasL, is highly expressed on patient-derived T cells used for clinical ACT. We hypothesized that a cognate Fas-FasL interaction within the TME might limit both T cell persistence and antitumor efficacy. We discovered that genetic engineering of Fas variants impaired in the ability to bind FADD functioned as dominant negative receptors (DNRs), preventing FasL-induced apoptosis in Fas-competent T cells. T cells coengineered with a Fas DNR and either a T cell receptor or chimeric antigen receptor exhibited enhanced persistence following ACT, resulting in superior antitumor efficacy against established solid and hematologic cancers. Despite increased longevity, Fas DNR-engineered T cells did not undergo aberrant expansion or mediate autoimmunity. Thus, T cell-intrinsic disruption of Fas signaling through genetic engineering represents a potentially universal strategy to enhance ACT efficacy across a broad range of human malignancies.
A rapidly growing corpus of formal, computable pathway information can be used to answer important biological questions including finding non-trivial connections between cellular processes, ...identifying significantly altered portions of the cellular network in a disease state and building predictive models that can be used for precision medicine. Due to its complexity and fragmented nature, however, working with pathway data is still difficult. We present Paxtools, a Java library that contains algorithms, software components and converters for biological pathways represented in the standard BioPAX language. Paxtools allows scientists to focus on their scientific problem by removing technical barriers to access and analyse pathway information. Paxtools can run on any platform that has a Java Runtime Environment and was tested on most modern operating systems. Paxtools is open source and is available under the Lesser GNU public license (LGPL), which allows users to freely use the code in their software systems with a requirement for attribution. Source code for the current release (4.2.0) can be found in Software S1. A detailed manual for obtaining and using Paxtools can be found in Protocol S1. The latest sources and release bundles can be obtained from biopax.org/paxtools.
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Antibodies targeting CTLA-4 induce durable responses in some patients with melanoma and are being tested in a variety of human cancers. However, these therapies are ineffective for a majority of ...patients across tumor types. Further understanding the immune alterations induced by these therapies may enable the development of novel strategies to enhance tumor control and biomarkers to identify patients most likely to respond. In several murine models, including colon26, MC38, CT26, and B16 tumors cotreated with GVAX, anti-CTLA-4 efficacy depends on interactions between the Fc region of CTLA-4 antibodies and Fc receptors (FcR). Anti-CTLA-4 binding to FcRs has been linked to depletion of intratumoral T regulatory cells (Treg). In agreement with previous studies, we found that Tregs infiltrating CT26, B16-F1, and autochthonous
melanoma tumors had higher expression of surface CTLA-4 (sCTLA-4) than other T-cell subsets, and anti-CTLA-4 treatment led to FcR-dependent depletion of Tregs infiltrating CT26 tumors. This Treg depletion coincided with activation and degranulation of intratumoral natural killer cells. Similarly, in non-small cell lung cancer (NSCLC) and melanoma patient-derived tumor tissue, Tregs had higher sCTLA-4 expression than other intratumoral T-cell subsets, and Tregs infiltrating NSCLC expressed more sCTLA-4 than circulating Tregs. Patients with cutaneous melanoma who benefited from ipilimumab, a mAb targeting CTLA-4, had higher intratumoral CD56 expression, compared with patients who received little to no benefit from this therapy. Furthermore, using the murine CT26 model we found that combination therapy with anti-CTLA-4 plus IL15/IL15Rα complexes enhanced tumor control compared with either monotherapy.
Although individual tumors show surprisingly diverse genomic alterations, these events tend to occur in a limited number of pathways, and alterations that affect the same pathway tend to not co-occur ...in the same patient. While pathway analysis has been a powerful tool in cancer genomics, our knowledge of oncogenic pathway modules is incomplete. To systematically identify such modules, we have developed a novel method, Mutual Exclusivity Modules in Cancer (MEMo). The method searches and identifies modules characterized by three properties: (1) member genes are recurrently altered across a set of tumor samples; (2) member genes are known to or are likely to participate in the same biological process; and (3) alteration events within the modules are mutually exclusive. MEMo integrates multiple data types and maps genomic alterations to biological pathways. MEMo's mutual exclusivity uses a statistical model that preserves the number of alterations per gene and per sample. The MEMo software, source code and sample data sets are available for download at: http://cbio.mskcc.org/memo.
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