Summary: Pathview is a novel tool set for pathway-based data integration and visualization. It maps and renders user data on relevant pathway graphs. Users only need to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps and integrates user data onto the pathway and renders pathway graphs with the mapped data. Although built as a stand-alone program, Pathview may seamlessly integrate with pathway and functional analysis tools for large-scale and fully automated analysis pipelines.Availability: The package is freely available under the GPLv3 license through Bioconductor and R-Forge. It is available at http://bioconductor.org/packages/release/bioc/html/pathview.html and at http://Pathview.r-forge.r-project.org/.Contact: luo_weijun@yahoo.comSupplementary information: Supplementary data are available at Bioinformatics online.

Background: Gene set analysis (GSA) is a widely used strategy for gene expression data analysis based on pathway knowledge. GSA focuses on sets of related genes and has established major advantages over individual gene analyses, including greater robustness, sensitivity and biological relevance. However, previous GSA methods have limited usage as they cannot handle datasets of different sample sizes or experimental designs.

Cellular senescence acts as a potent barrier to tumorigenesis and contributes to the anti-tumor activity of certain chemotherapeutic agents. Senescent cells undergo a stable cell cycle arrest controlled by RB and p53 and, in addition, display a senescence-associated secretory phenotype (SASP) involving the production of factors that reinforce the senescence arrest, alter the microenvironment, and trigger immune surveillance of the senescent cells. Through a proteomics analysis of senescent chromatin, we identified the nuclear factor-kB (NF-kB) subunit p65 as a major transcription factor that accumulates on chromatin of senescent cells. We found that NF-kB acts as a master regulator of the SASP, influencing the expression of more genes than RB and p53 combined. In cultured fibroblasts, NF-kB suppression causes escape from immune recognition by natural killer (NK) cells and cooperates with p53 inactivation to bypass senescence. In a mouse lymphoma model, NF-kB inhibition bypasses treatment-induced senescence, producing drug resistance, early relapse, and reduced survival. Our results demonstrate that NF-kB controls both cell-autonomous and non-cell-autonomous aspects of the senescence program and identify a tumor-suppressive function of NF-kB that contributes to the outcome of cancer therapy.

Although human cancers have complex genotypes and are genomically unstable, they often remain dependent on the continued presence of single-driver mutations-a phenomenon dubbed ''oncogene addiction.'' Such dependencies have been demonstrated in mouse models, where conditional expression systems have revealed that oncogenes able to initiate cancer are often required for tumor maintenance and progression, thus validating the pathways they control as therapeutic targets. Here, we implement an integrative approach that combines genetically defined mouse models, transcriptional profiling, and a novel inducible RNAi platform to characterize cellular programs that underlie addiction to MLL-AF9-a fusion oncoprotein involved in aggressive forms of acute myeloid leukemia (AML). We show that MLL-AF9 contributes to leukemia maintenance by enforcing a Mybcoordinated program of aberrant self-renewal involving genes linked to leukemia stem cell potential and poor prognosis in human AML. Accordingly, partial and transient Myb suppression precisely phenocopies MLL-AF9 withdrawal and eradicates aggressive AML in vivo without preventing normal myelopoiesis, indicating that strategies to inhibit Myb-dependent aberrant self-renewal programs hold promise as effective and cancer-specific therapeutics. Together, our results identify Myb as a critical mediator of oncogene addiction in AML, delineate relevant Myb target genes that are amenable to pharmacologic inhibition, and establish a general approach for dissecting oncogene addiction in vivo.

The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients.[Keywords: AML; AML1/ETO; MLL; chemotherapy; mouse models] Supplemental material is available at http://www.genesdev.org.

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/.

The large chromosomal deletions frequently observed in cancer genomes are often thought to arise as a "two-hit" mechanism in the process of tumor-suppressor gene (TSG) inactivation. Using a murine model system of hepatocellular carcinoma (HCC) and in vivo RNAi, we test an alternative hypothesis, that such deletions can arise from selective pressure to attenuate the activity of multiple genes. By targeting the mouse orthologs of genes frequently deleted on human 8p22 and adjacent regions, which are lost in approximately half of several other major epithelial cancers, we provide evidence suggesting that multiple genes on chromosome 8p can cooperatively inhibit tumorigenesis in mice, and that their cosuppression can synergistically promote tumor growth. In addition, in human HCC patients, the combined down-regulation of functionally validated 8p TSGs is associated with poor survival, in contrast to the down-regulation of any individual gene. Our data imply that large cancer-associated deletions can produce phenotypes distinct from those arising through loss of a single TSG, and as such should be considered and studied as distinct mutational events.cancer genomics | chromosome 8p deletion | RNAi screen

Telomere-associated position effect variegation (TPEV) in budding yeast has been used as a model for understanding epigenetic inheritance and gene silencing. A widely used assay to identify mutants with improper TPEV employs the URA3 gene at the telomere of chromosome VII-L that can be counter-selected with 5-fluoroorotic acid (5-FOA). 5-FOA resistance has been inferred to represent lack of transcription of URA3 and therefore to represent heterochromatin-induced gene silencing. For two genes implicated in telomere silencing, POL30 and DOT1, we show that the URA3 telomere reporter assay does not reflect their role in heterochromatin formation. Rather, an imbalance in ribonucleotide reductase (RNR), which is induced by 5-FOA, and the specific promoter of URA3 fused to ADH4 at telomere VII-L are jointly responsible for the variegated phenotype. We conclude that metabolic changes caused by the drug employed and certain mutants being studied are incompatible with the use of certain prototrophic markers for TPEV.