Based on clinical outcomes in colorectal cancer, high microsatellite instability (MSI-H) has recently been approved by the Food and Drug Administration (FDA) as a genetic test to select patients for immunotherapy targeting PD-1 and/or CTLA-4 without limitation to cancer type. However, it is unclear whether the MSI-H would broadly alter the tumor microenvironment to confer the therapeutic response of different cancer types to immunotherapy. To fill in this gap, we performed an in silico analysis of tumor immunity among different MSI statuses in five cancer types. We found that consistent with clinical responses to immunotherapy, MSI-H and non-MSI-H samples from colorectal cancer (COAD-READ) exhibited distinct infiltration levels and immune phenotypes. Surprisingly, the immunological difference between MSI-H and non-MSI-H samples was diminished in stomach adenocarcinoma and esophageal carcinoma (STAD-ESCA) and completely disappeared in uterine corpus endometrial carcinoma (UCEC). Regardless of cancer types, the abundance of tumor-infiltrating immune cells, rather than MSI status, strongly associated with the clinical outcome. Since preexisting antitumor immune response in the tumor (hot cancer) is accepted as a prerequisite to the therapeutic response to anti-PD-1/CTLA-4 immunotherapy, our data demonstrate that the impact of MSI varied on immune contexture will lead to the further evaluation of predictive immunotherapy responsiveness based on the universal biomarker of MSI status.

SUMMARY: JavaScript-based Circos libraries have been widely implemented to generate interactive Circos plots in web applications. However, these libraries require either local installation, which requires the compilation of extra libraries, or extra data processing procedures to prepare input and configuration for each track of plot, which limits the utility and capability of integration with powerful R packages. In this report, we present interacCircos, an R package for creating interactive Circos plots through the integration of JavaScript-based libraries. interacCircos can simply and flexibly implement 14 track-plot functions and 7 auxiliary functions for presenting large-scale genomic data in interactive Circos plots. AVAILABILITY AND IMPLEMENTATION: InteracCircos and its manual are freely available at https://github.com/mrcuizhe/interacCircos under the GPL license. The online documentation is available at https://mrcuizhe.github.io/interacCircos_documentation/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Long non-coding RNAs (lncRNAs) are essential in many molecular pathways, and are frequently associated with disease but the mechanisms of most lncRNAs have not yet been characterized. Genetic variations, including single nucleotide polymorphisms (SNPs) and structural variations, are widely distributed in the genome, including lncRNA gene regions. As the number of studies on lncRNAs grows rapidly, it is necessary to evaluate the effects of genetic variations on lncRNAs. RESULTS: A modification sites of lncRNAs and provided comprehensive effects of SNPs on transcription and modification of lncRNAs. We collected putatively translated open reading frames (ORFs) in lncRNAs, and identified both synonymous and non-synonymous SNPs in ORFs. We also collected expression quantitative trait loci of lncRNAs from the literature. Furthermore, we identified lncRNAs in CNV regions as prognostic biomarker candidates of cancers and predicted lncRNA gene fusion events from RNA-seq data from cell lines. The LncVar database can be used as a resource to evaluate the effects of the variations on the biological function of lncRNAs. AVAILABILITY AND IMPLEMENTATION: LncVar is available at http://bioinfo.ibp.ac.cn/LncVar CONTACT: [email protected] information: Supplementary materials are available at Bioinformatics online.

UNLABELLED: We here present BioCircos.js, an interactive and lightweight JavaScript library especially for biological data interactive visualization. BioCircos.js facilitates the development of web-based applications for circular visualization of various biological data, such as genomic features, genetic variations, gene expression and biomolecular interactions. AVAILABILITY AND IMPLEMENTATION: BioCircos.js and its manual are freely available online at http://bioinfo.ibp.ac.cn/biocircos/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: PIWI-interacting RNAs (piRNAs) are a class of small non-coding RNAs that are highly abundant in the germline. One important role of piRNAs is to defend genome integrity by guiding PIWI proteins to silence transposable elements (TEs), which have a high potential to cause deleterious effects on their host. The mechanism of piRNA-mediated post-transcriptional silencing was also observed to affect mRNAs, suggesting that piRNAs might play a broad role in gene expression regulation. However, there has been no systematic report with regard to how many protein-coding genes might be targeted and regulated by piRNAs. RESULTS: We trained a support vector machine classifier based on a combination of Miwi CLIP-Seq-derived features and position-derived features to predict the potential targets of piRNAs on mRNAs in the mouse. Reanalysis of a published microarray dataset suggested that the expression level of the 2587 protein-coding genes predicted as piRNA targets showed significant upregulation as a whole after abolishing the slicer activity of Miwi, supporting the conclusion that they are subject to piRNA-mediated regulation. AVAILABILITY AND IMPLEMENTATION: A web version of the method called pirnaPre as well as our results for browse is available at http://www.regulatoryrna.org/software/piRNA/piRNA_target_mRNA/index.php CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Protein domains are fundamental units of protein structure, function and evolution; thus, it is critical to gain a deep understanding of protein domain organization. Previous works have attempted to identify key residues involved in organization of domain architecture. Because one of the most important characteristics of domain architecture is the arrangement of secondary structure elements (SSEs), here we present a picture of domain organization through an integrated consideration of SSE arrangements and residue contact networks. RESULTS: In this work, by representing SSEs as main-chain scaffolds and side-chain interfaces and through construction of residue contact networks, we have identified the SSE interfaces well packed within protein domains as SSE packing clusters. In total, 17 334 SSE packing clusters were recognized from 9015 Structural Classification of Proteins domains of <40% sequence identity. The similar SSE packing clusters were observed not only among domains of the same folds, but also among domains of different folds, indicating their roles as common scaffolds for organization of protein domains. Further analysis of 14 small single-domain proteins reveals a high correlation between the SSE packing clusters and the folding nuclei. Consistent with their important roles in domain organization, SSE packing clusters were found to be more conserved than other regions within the same proteins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.