INTEGRATE-Neo: A pipeline for personalized gene fusion neoantigen discovery

Abstract Motivation While high-throughput sequencing (HTS) has been used successfully to discover tumor-specific mutant peptides (neoantigens) from somatic missense mutations, the field currently lacks a method for identifying which gene fusions may generate neoantigens. Results We demonstrate the application of our gene fusion neoantigen discovery pipeline, called INTEGRATE-Neo, by identifying gene fusions in prostate cancers that may produce neoantigens. Availability and Implementation INTEGRATE-Neo is implemented in C ++ and Python. Full source code and installation instructions are freely available from https://github.com/ChrisMaherLab/INTEGRATE-Neo. Supplementary information Supplementary data are available at Bioinformatics online. </jats:sec

The 5-hydroxymethylcytosine landscape of prostate cancer

UNLABELLED: Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease. SIGNIFICANCE: In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880

End Zone Reinforcement for Pretensioned Concrete Girders

In this study, a literature review was conducted to establish the background of current specifications and to evaluate the applicability of various theories and methods for design of end zone reinforcement. Analytical methods reviewed in this paper include finite element analysis, strut-and-tie modeling, and the Gergely-Sozen equivalent beam method. Previous experimental work combined with work conducted as part of this study was used to correlate between various theoretical and experimental results. This paper illustrates that no single theoretical method adequately represents the complex behavior at the end of a pretensioned concrete member. A general semi-empirical design procedure is proposed here. It is based on theoretical behavior and experimental observation. Standard reinforcement details are given. The proposed procedure could result in significant reduction in the amount of reinforcement while maintaining acceptable crack control at the member end. Application of the proposed procedure to highly pretensioned bridge girders is demonstrated

Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer

BACKGROUND: Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue- and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive. RESULTS: Here we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation. CONCLUSIONS: Our systematic characterization of publicly available transcriptome data provides the foundation for future efforts to understand the role of LCALs, develop novel biomarkers, and improve knowledge of lung tumor biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0429-8) contains supplementary material, which is available to authorized users

Long, noncoding RNA dysregulation in glioblastoma

Transcription occurs across more than 70% of the human genome and more than half of currently annotated genes produce functional noncoding RNAs. Of these transcripts, the majority-long, noncoding RNAs (lncRNAs)-are greater than 200 nucleotides in length and are necessary for various roles in the cell. It is increasingly appreciated that these lncRNAs are relevant in both health and disease states, with the brain expressing the largest number of lncRNAs compared to other organs. Glioblastoma (GBM) is an aggressive, fatal brain tumor that demonstrates remarkable intratumoral heterogeneity, which has made the development of effective therapies challenging. The cooperation between genetic and epigenetic alterations drives rapid adaptation that allows therapeutic evasion and recurrence. Given the large repertoire of lncRNAs in normal brain tissue and the well-described roles of lncRNAs in molecular and cellular processes, these transcripts are important to consider in the context of GBM heterogeneity and treatment resistance. Herein, we review the general mechanisms and biological roles of lncRNAs, with a focus on GBM, as well as RNA-based therapeutics currently in development

Visualizing tumor evolution with the fishplot package for R

BACKGROUND: Massively-parallel sequencing at depth is now enabling tumor heterogeneity and evolution to be characterized in unprecedented detail. Tracking these changes in clonal architecture often provides insight into therapeutic response and resistance. In complex cases involving multiple timepoints, standard visualizations, such as scatterplots, can be difficult to interpret. Current data visualization methods are also typically manual and laborious, and often only approximate subclonal fractions. RESULTS: We have developed an R package that accurately and intuitively displays changes in clonal structure over time. It requires simple input data and produces illustrative and easy-to-interpret graphs suitable for diagnosis, presentation, and publication. CONCLUSIONS: The simplicity, power, and flexibility of this tool make it valuable for visualizing tumor evolution, and it has potential utility in both research and clinical settings. The fishplot package is available at https://github.com/chrisamiller/fishplot. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3195-z) contains supplementary material, which is available to authorized users

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies