Software for the Integration of Multiomics Experiments in Bioconductor.

Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multiomics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide the unrestricted multiple 'omics data for each cancer tissue in The Cancer Genome Atlas as ready-to-analyze MultiAssayExperiment objects and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable, and reproducible statistical analysis of multiomics data and enhances data science applications of multiple omics datasets. Cancer Res; 77(21); e39-42. ©2017 AACR.

Resources for Interpreting Variants in Precision Genomic Oncology Applications.

Precision genomic oncology-applying high throughput sequencing (HTS) at the point-of-care to inform clinical decisions-is a developing precision medicine paradigm that is seeing increasing adoption. Simultaneously, new developments in targeted agents and immunotherapy, when informed by rich genomic characterization, offer potential benefit to a growing subset of patients. Multiple previous studies have commented on methods for identifying both germline and somatic variants. However, interpreting individual variants remains a significant challenge, relying in large part on the integration of observed variants with biological knowledge. A number of data and software resources have been developed to assist in interpreting observed variants, determining their potential clinical actionability, and augmenting them with ancillary information that can inform clinical decisions and even generate new hypotheses for exploration in the laboratory. Here, we review available variant catalogs, variant and functional annotation software and tools, and databases of clinically actionable variants that can be used in an ad hoc approach with research samples or incorporated into a data platform for interpreting and formally reporting clinical results.

Autoreactive T Cells and Chronic Fungal Infection Drive Esophageal Carcinogenesis.

Humans with autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED), a T cell-driven autoimmune disease caused by impaired central tolerance, are susceptible to chronic fungal infection and esophageal squamous cell carcinoma (ESCC). However, the relationship between autoreactive T cells and chronic fungal infection in ESCC development remains unclear. We find that kinase-dead Ikkα knockin mice develop APECED-like phenotypes, including impaired central tolerance, autoreactive T cells, chronic fungal infection, and ESCCs expressing specific human ESCC markers. Using this model, we investigated the link between ESCC and fungal infection. Autoreactive CD4 T cells permit fungal infection and incite tissue injury and inflammation. Antifungal treatment or autoreactive CD4 T cell depletion rescues, whereas oral fungal administration promotes, ESCC development. Inhibition of inflammation or epidermal growth factor receptor (EGFR) activity decreases fungal burden. Fungal infection is highly associated with ESCCs in non-autoimmune human patients. Therefore, autoreactive T cells and chronic fungal infection, fostered by inflammation and epithelial injury, promote ESCC development.

On the Selective Packaging of Genomic RNA by HIV-1.

Like other retroviruses, human immunodeficiency virus type 1 (HIV-1) selectively packages genomic RNA (gRNA) during virus assembly. However, in the absence of the gRNA, cellular messenger RNAs (mRNAs) are packaged. While the gRNA is selected because of its cis-acting packaging signal, the mechanism of this selection is not understood. The affinity of Gag (the viral structural protein) for cellular RNAs at physiological ionic strength is not much higher than that for the gRNA. However, binding to the gRNA is more salt-resistant, implying that it has a higher non-electrostatic component. We have previously studied the spacer 1 (SP1) region of Gag and showed that it can undergo a concentration-dependent conformational transition. We proposed that this transition represents the first step in assembly, i.e., the conversion of Gag to an assembly-ready state. To explain selective packaging of gRNA, we suggest here that binding of Gag to gRNA, with its high non-electrostatic component, triggers this conversion more readily than binding to other RNAs; thus we predict that a Gag-gRNA complex will nucleate particle assembly more efficiently than other Gag-RNA complexes. New data shows that among cellular mRNAs, those with long 3'-untranslated regions (UTR) are selectively packaged. It seems plausible that the 3'-UTR, a stretch of RNA not occupied by ribosomes, offers a favorable binding site for Gag.

Point Mutations in Exon 1B of APC Reveal Gastric Adenocarcinoma and Proximal Polyposis of the Stomach as a Familial Adenomatous Polyposis Variant.

Gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS) is an autosomal-dominant cancer-predisposition syndrome with a significant risk of gastric, but not colorectal, adenocarcinoma. We mapped the gene to 5q22 and found loss of the wild-type allele on 5q in fundic gland polyps from affected individuals. Whole-exome and -genome sequencing failed to find causal mutations but, through Sanger sequencing, we identified point mutations in APC promoter 1B that co-segregated with disease in all six families. The mutations reduced binding of the YY1 transcription factor and impaired activity of the APC promoter 1B in luciferase assays. Analysis of blood and saliva from carriers showed allelic imbalance of APC, suggesting that these mutations lead to decreased allele-specific expression in vivo. Similar mutations in APC promoter 1B occur in rare families with familial adenomatous polyposis (FAP). Promoter 1A is methylated in GAPPS and sporadic FGPs and in normal stomach, which suggests that 1B transcripts are more important than 1A in gastric mucosa. This might explain why all known GAPPS-affected families carry promoter 1B point mutations but only rare FAP-affected families carry similar mutations, the colonic cells usually being protected by the expression of the 1A isoform. Gastric polyposis and cancer have been previously described in some FAP-affected individuals with large deletions around promoter 1B. Our finding that GAPPS is caused by point mutations in the same promoter suggests that families with mutations affecting the promoter 1B are at risk of gastric adenocarcinoma, regardless of whether or not colorectal polyps are present.

caOmicsV: an R package for visualizing multidimensional cancer genomic data.

BACKGROUND: Translational genomics research in cancers, e.g., International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), has generated large multidimensional datasets from high-throughput technologies. Data analysis at multidimensional level will greatly benefit clinical applications of genomic information in diagnosis, prognosis and therapeutics of cancers. To help, tools to effectively visualize integrated multidimensional data are important for understanding and describing the relationship between genomic variations and cancers. RESULTS: We implemented the R package, caOmicsV, to provide methods under R environment to visualize multidimensional cancer genomic data in two layouts: matrix layout and combined biological network and circular layout. Both layouts support to display sample information, gene expression (e.g., RNA and miRNA), DNA methylation, DNA copy number variations, and summarized data. A set of supplemental functions are included in the caOmicsV package to help users in generation of plot data sets from multiple genomic datasets with given gene names and sample names. Default plot methods for both layouts for easy use are also implemented. CONCLUSION: caOmicsV package provides an easy and flexible way to visualize integrated multidimensional cancer genomic data under R environment.

Characterization of genomic alterations in radiation-associated breast cancer among childhood cancer survivors, using comparative genomic hybridization (CGH) arrays.

Ionizing radiation is an established risk factor for breast cancer. Epidemiologic studies of radiation-exposed cohorts have been primarily descriptive; molecular events responsible for the development of radiation-associated breast cancer have not been elucidated. In this study, we used array comparative genomic hybridization (array-CGH) to characterize genome-wide copy number changes in breast tumors collected in the Childhood Cancer Survivor Study (CCSS). Array-CGH data were obtained from 32 cases who developed a second primary breast cancer following chest irradiation at early ages for the treatment of their first cancers, mostly Hodgkin lymphoma. The majority of these cases developed breast cancer before age 45 (91%, n = 29), had invasive ductal tumors (81%, n = 26), estrogen receptor (ER)-positive staining (68%, n = 19 out of 28), and high proliferation as indicated by high Ki-67 staining (77%, n = 17 out of 22). Genomic regions with low-copy number gains and losses and high-level amplifications were similar to what has been reported in sporadic breast tumors, however, the frequency of amplifications of the 17q12 region containing human epidermal growth factor receptor 2 (HER2) was much higher among CCSS cases (38%, n = 12). Our findings suggest that second primary breast cancers in CCSS were enriched for an "amplifier" genomic subgroup with highly proliferative breast tumors. Future investigation in a larger irradiated cohort will be needed to confirm our findings.

Super-enhancers delineate disease-associated regulatory nodes in T cells.

Enhancers regulate spatiotemporal gene expression and impart cell-specific transcriptional outputs that drive cell identity. Super-enhancers (SEs), also known as stretch-enhancers, are a subset of enhancers especially important for genes associated with cell identity and genetic risk of disease. CD4(+) T cells are critical for host defence and autoimmunity. Here we analysed maps of mouse T-cell SEs as a non-biased means of identifying key regulatory nodes involved in cell specification. We found that cytokines and cytokine receptors were the dominant class of genes exhibiting SE architecture in T cells. Nonetheless, the locus encoding Bach2, a key negative regulator of effector differentiation, emerged as the most prominent T-cell SE, revealing a network in which SE-associated genes critical for T-cell biology are repressed by BACH2. Disease-associated single-nucleotide polymorphisms for immune-mediated disorders, including rheumatoid arthritis, were highly enriched for T-cell SEs versus typical enhancers or SEs in other cell lineages. Intriguingly, treatment of T cells with the Janus kinase (JAK) inhibitor tofacitinib disproportionately altered the expression of rheumatoid arthritis risk genes with SE structures. Together, these results indicate that genes with SE architecture in T cells encompass a variety of cytokines and cytokine receptors but are controlled by a 'guardian' transcription factor, itself endowed with an SE. Thus, enumeration of SEs allows the unbiased determination of key regulatory nodes in T cells, which are preferentially modulated by pharmacological intervention.

NCI-60 whole exome sequencing and pharmacological CellMiner analyses.

Exome sequencing provides unprecedented insights into cancer biology and pharmacological response. Here we assess these two parameters for the NCI-60, which is among the richest genomic and pharmacological publicly available cancer cell line databases. Homozygous genetic variants that putatively affect protein function were identified in 1,199 genes (approximately 6% of all genes). Variants that are either enriched or depleted compared to non-cancerous genomes, and thus may be influential in cancer progression and differential drug response were identified for 2,546 genes. Potential gene knockouts are made available. Assessment of cell line response to 19,940 compounds, including 110 FDA-approved drugs, reveals ≈80-fold range in resistance versus sensitivity response across cell lines. 103,422 gene variants were significantly correlated with at least one compound (at p<0.0002). These include genes of known pharmacological importance such as IGF1R, BRAF, RAD52, MTOR, STAT2 and TSC2 as well as a large number of candidate genes such as NOM1, TLL2, and XDH. We introduce two new web-based CellMiner applications that enable exploration of variant-to-compound relationships for a broad range of researchers, especially those without bioinformatics support. The first tool, "Genetic variant versus drug visualization", provides a visualization of significant correlations between drug activity-gene variant combinations. Examples are given for the known vemurafenib-BRAF, and novel ifosfamide-RAD52 pairings. The second, "Genetic variant summation" allows an assessment of cumulative genetic variations for up to 150 combined genes together; and is designed to identify the variant burden for molecular pathways or functional grouping of genes. An example of its use is provided for the EGFR-ERBB2 pathway gene variant data and the identification of correlated EGFR, ERBB2, MTOR, BRAF, MEK and ERK inhibitors. The new tools are implemented as an updated web-based CellMiner version, for which the present publication serves as a compendium.

High prevalence of MAP2K1 mutations in variant and IGHV4-34-expressing hairy-cell leukemias.

To understand the genetic mechanisms driving variant and IGHV4-34-expressing hairy-cell leukemias, we performed whole-exome sequencing of leukemia samples from ten affected individuals, including six with matched normal samples. We identified activating mutations in the MAP2K1 gene (encoding MEK1) in 5 of these 10 samples and in 10 of 21 samples in a validation set (overall frequency of 15/31), suggesting potential new strategies for treating individuals with these diseases.

A polymorphism in IRF4 affects human pigmentation through a tyrosinase-dependent MITF/TFAP2A pathway.

Sequence polymorphisms linked to human diseases and phenotypes in genome-wide association studies often affect noncoding regions. A SNP within an intron of the gene encoding Interferon Regulatory Factor 4 (IRF4), a transcription factor with no known role in melanocyte biology, is strongly associated with sensitivity of skin to sun exposure, freckles, blue eyes, and brown hair color. Here, we demonstrate that this SNP lies within an enhancer of IRF4 transcription in melanocytes. The allele associated with this pigmentation phenotype impairs binding of the TFAP2A transcription factor that, together with the melanocyte master regulator MITF, regulates activity of the enhancer. Assays in zebrafish and mice reveal that IRF4 cooperates with MITF to activate expression of Tyrosinase (TYR), an essential enzyme in melanin synthesis. Our findings provide a clear example of a noncoding polymorphism that affects a phenotype by modulating a developmental gene regulatory network.

The exomes of the NCI-60 panel: a genomic resource for cancer biology and systems pharmacology.

The NCI-60 cell lines are the most frequently studied human tumor cell lines in cancer research. This panel has generated the most extensive cancer pharmacology database worldwide. In addition, these cell lines have been intensely investigated, providing a unique platform for hypothesis-driven research focused on enhancing our understanding of tumor biology. Here, we report a comprehensive analysis of coding variants in the NCI-60 panel of cell lines identified by whole exome sequencing, providing a list of possible cancer specific variants for the community. Furthermore, we identify pharmacogenomic correlations between specific variants in genes such as TP53, BRAF, ERBBs, and ATAD5 and anticancer agents such as nutlin, vemurafenib, erlotinib, and bleomycin showing one of many ways the data could be used to validate and generate novel hypotheses for further investigation. As new cancer genes are identified through large-scale sequencing studies, the data presented here for the NCI-60 will be an invaluable resource for identifying cell lines with mutations in such genes for hypothesis-driven research. To enhance the utility of the data for the greater research community, the genomic variants are freely available in different formats and from multiple sources including the CellMiner and Ingenuity websites.

SRAdb: query and use public next-generation sequencing data from within R.

BACKGROUND: The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Illumina (Genome Analyzer, HiSeq, MiSeq, .etc), Roche 454 GS System, Applied Biosystems SOLiD System, Helicos Heliscope, PacBio RS, and others. RESULTS: SRAdb is an attempt to make queries of the metadata associated with SRA submission, study, sample, experiment and run more robust and precise, and make access to sequencing data in the SRA easier. We have parsed all the SRA metadata into a SQLite database that is routinely updated and can be easily distributed. The SRAdb R/Bioconductor package then utilizes this SQLite database for querying and accessing metadata. Full text search functionality makes querying metadata very flexible and powerful. Fastq files associated with query results can be downloaded easily for local analysis. The package also includes an interface from R to a popular genome browser, the Integrated Genomics Viewer. CONCLUSIONS: SRAdb Bioconductor package provides a convenient and integrated framework to query and access SRA metadata quickly and powerfully from within R.

Harnessing genomics to identify environmental determinants of heritable disease.

Next-generation sequencing technologies can now be used to directly measure heritable de novo DNA sequence mutations in humans. However, these techniques have not been used to examine environmental factors that induce such mutations and their associated diseases. To address this issue, a working group on environmentally induced germline mutation analysis (ENIGMA) met in October 2011 to propose the necessary foundational studies, which include sequencing of parent-offspring trios from highly exposed human populations, and controlled dose-response experiments in animals. These studies will establish background levels of variability in germline mutation rates and identify environmental agents that influence these rates and heritable disease. Guidance for the types of exposures to examine come from rodent studies that have identified agents such as cancer chemotherapeutic drugs, ionizing radiation, cigarette smoke, and air pollution as germ-cell mutagens. Research is urgently needed to establish the health consequences of parental exposures on subsequent generations.

Genome-wide depletion of replication initiation events in highly transcribed regions.

This report investigates the mechanisms by which mammalian cells coordinate DNA replication with transcription and chromatin assembly. In yeast, DNA replication initiates within nucleosome-free regions, but studies in mammalian cells have not revealed a similar relationship. Here, we have used genome-wide massively parallel sequencing to map replication initiation events, thereby creating a database of all replication initiation sites within nonrepetitive DNA in two human cell lines. Mining this database revealed that genomic regions transcribed at moderate levels were generally associated with high replication initiation frequency. In genomic regions with high rates of transcription, very few replication initiation events were detected. High-resolution mapping of replication initiation sites showed that replication initiation events were absent from transcription start sites but were highly enriched in adjacent, downstream sequences. Methylation of CpG sequences strongly affected the location of replication initiation events, whereas histone modifications had minimal effects. These observations suggest that high levels of transcription interfere with formation of pre-replication protein complexes. Data presented here identify replication initiation sites throughout the genome, providing a foundation for further analyses of DNA-replication dynamics and cell-cycle progression.

Kinetic complexity of the global response to glucocorticoid receptor action.

We have characterized the kinetic response of gene targets throughout the murine genome to transcriptional modulation by the glucocorticoid receptor (GR). In contrast to a model in which multiple genes are either repressed or activated during the GR response, the vast majority of responsive genes are subject to complex regulation profiles, frequently with alternate activation and repression phases. We also observe that GR binding at response elements does not always correlate with the target gene response profile. Thus, the cellular response to GR stimulation involves a highly orchestrated series of regulatory actions and not simply a binary response to hormone.

TRAIL induces apoptosis in triple-negative breast cancer cells with a mesenchymal phenotype.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) induces apoptosis in some but not all breast cancer cell lines. Breast cancers can be divided into those which express the estrogen (ER) and progesterone (PR) receptors, those with HER-2 amplification, and those without expression of ER, PR, or HER-2 amplification (referred to as basal or triple-negative breast cancer). We tested a panel of 20 breast cancer cell lines representing the different types of breast cancer to evaluate if the molecular phenotype of the breast cancer cells determined their response to TRAIL. The most striking finding was that eight of eleven triple-negative cell lines are sensitive to TRAIL-mediated apoptosis. The eight TRAIL-sensitive triple-negative cell lines have a mesenchymal phenotype while the three TRAIL-resistant triple-negative cell lines have an epithelial phenotype. Two of five cell lines with HER-2 amplification were sensitive to TRAIL and none of the five ER positive cell lines were sensitive. RNAi-mediated knockdown of TRAIL receptor expression demonstrated that TRAIL Receptor 2 (TRAIL-R2) mediates the effects of TRAIL, even when both TRAIL-R1 and TRAIL-R2 are expressed. Finally, inhibition of EGFR, expressed in both TRAIL-sensitive and TRAIL-resistant triple-negative breast cancer cell lines, using a small molecule tyrosine kinase inhibitor (AG1478), enhanced TRAIL-induced apoptosis in TRAIL-sensitive cell lines but did not convert resistant cells into TRAIL-sensitive cells. Together, these findings suggest that a subset of triple-negative breast cancer, those with mesenchymal features, may be the most likely to benefit from TRAIL targeted therapy. These findings could form the basis to select breast cancer patients for clinical trials of TRAIL-R2 ligands.

Interaction of the glucocorticoid receptor with the chromatin landscape.

The generality and spectrum of chromatin-remodeling requirements for nuclear receptor function are unknown. We have characterized glucocorticoid receptor (GR) binding events and chromatin structural transitions across GR-induced or -repressed genes. This analysis reveals that GR binding invariably occurs at nuclease-accessible sites (DHS). A remarkable diversity of mechanisms, however, render these sites available for GR binding. Accessibility of the GR binding sites is either constitutive or hormone inducible. Within each category, some DHS sites require the Brg1-containing Swi/Snf complex, but others are Brg1 independent, implicating a different remodeling complex. The H2A.Z histone variant is highly enriched at both inducible and constitutive DHS sites and is subject to exchange during hormone activation. The DHS profile is highly cell specific, implicating cell-selective organization of the chromatin landscape as a critical determinant of tissue-selective receptor function. Furthermore, the widespread requirement for chromatin remodeling supports the recent hypothesis that the rapid exchange of receptor proteins occurs during nucleosome reorganization.

Modeling synovial sarcoma: timing is everything.

Synovial sarcoma is characterized by the presence of a fusion protein involving SYT and SSX2. In this issue of Cancer Cell, Haldar et al. have genetically engineered a mouse model of this disease. They show that expression of the SYT-SSX2 fusion gene yields a highly penetrant and representative model of human synovial sarcoma, but only if expression occurs in a particular biologic context. The mouse model will be a valuable resource for studying tumor biology but is also a striking example of how important understanding of normal tissue and developmental biology is to our understanding of cancer.