Ha X. Dang

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

BackgroundLong 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.ResultsHere 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.ConclusionsOur 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.

Genomic characterization of the conditionally dispensable chromosome in Alternaria arborescens provides evidence for horizontal gene transfer

BackgroundFungal plant pathogens cause serious agricultural losses worldwide. Alternaria arborescens is a major pathogen of tomato, with its virulence determined by the presence of a conditionally dispensable chromosome (CDC) carrying host-specific toxin genes. Genes encoding these toxins are well-studied, however the genomic content and organization of the CDC is not known.ResultsTo gain a richer understanding of the molecular determinants of virulence and the evolution of pathogenicity, we performed whole genome sequencing of A. arborescens. Here we present the de-novo assembly of the CDC and its predicted gene content. Also presented is hybridization data validating the CDC assembly. Predicted genes were functionally annotated through BLAST. Gene ontology terms were assigned, and conserved domains were identified. Differences in nucleotide usage were found between CDC genes and those on the essential chromosome (EC), including GC3-content, codon usage bias, and repeat region load. Genes carrying PKS and NRPS domains were identified in clusters on the CDC and evidence supporting the origin of the CDC through horizontal transfer from an unrelated fungus was found.ConclusionsWe provide evidence supporting the hypothesis that the CDC in A. arborescens was acquired through horizontal transfer, likely from an unrelated fungus. We also identified several predicted CDC genes under positive selection that may serve as candidate virulence factors.

Identification of a polyketide synthase required for alternariol (AOH) and alternariol-9-methyl ether (AME) formation in Alternaria alternata.

Alternaria alternata produces more than 60 secondary metabolites, among which alternariol (AOH) and alternariol-9-methyl ether (AME) are important mycotoxins. Whereas the toxicology of these two polyketide-based compounds has been studied, nothing is known about the genetics of their biosynthesis. One of the postulated core enzymes in the biosynthesis of AOH and AME is polyketide synthase (PKS). In a draft genome sequence of A. alternata we identified 10 putative PKS-encoding genes. The timing of the expression of two PKS genes, pksJ and pksH, correlated with the production of AOH and AME. The PksJ and PksH proteins are predicted to be 2222 and 2821 amino acids in length, respectively. They are both iterative type I reducing polyketide synthases. PksJ harbors a peroxisomal targeting sequence at the C-terminus, suggesting that the biosynthesis occurs at least partly in these organelles. In the vicinity of pksJ we found a transcriptional regulator, altR, involved in pksJ induction and a putative methyl transferase, possibly responsible for AME formation. Downregulation of pksJ and altR caused a large decrease of alternariol formation, suggesting that PksJ is the polyketide synthase required for the postulated Claisen condensations during the biosynthesis. No other enzymes appeared to be required. PksH downregulation affected pksJ expression and thus caused an indirect effect on AOH production.

The Alternaria genomes database: a comprehensive resource for a fungal genus comprised of saprophytes, plant pathogens, and allergenic species

BackgroundAlternaria is considered one of the most common saprophytic fungal genera on the planet. It is comprised of many species that exhibit a necrotrophic phytopathogenic lifestyle. Several species are clinically associated with allergic respiratory disorders although rarely found to cause invasive infections in humans. Finally, Alternaria spp. are among the most well known producers of diverse fungal secondary metabolites, especially toxins.DescriptionWe have recently sequenced and annotated the genomes of 25 Alternaria spp. including but not limited to many necrotrophic plant pathogens such as A. brassicicola (a pathogen of Brassicaceous crops like cabbage and canola) and A. solani (a major pathogen of Solanaceous plants like potato and tomato), and several saprophytes that cause allergy in human such as A. alternata isolates. These genomes were annotated and compared. Multiple genetic differences were found in the context of plant and human pathogenicity, notably the pro-inflammatory potential of A. alternata. The Alternaria genomes database was built to provide a public platform to access the whole genome sequences, genome annotations, and comparative genomics data of these species. Genome annotation and comparison were performed using a pipeline that integrated multiple computational and comparative genomics tools. Alternaria genome sequences together with their annotation and comparison data were ported to Ensembl database schemas using a self-developed tool (EnsImport). Collectively, data are currently hosted using a customized installation of the Ensembl genome browser platform.ConclusionRecent efforts in fungal genome sequencing have facilitated the studies of the molecular basis of fungal pathogenicity as a whole system. The Alternaria genomes database provides a comprehensive resource of genomics and comparative data of an important saprophytic and plant/human pathogenic fungal genus. The database will be updated regularly with new genomes when they become available. The Alternaria genomes database is freely available for non-profit use at http://alternaria.vbi.vt.edu.

Allerdictor: fast allergen prediction using text classification techniques.

MOTIVATION Accurately identifying and eliminating allergens from biotechnology-derived products are important for human health. From a biomedical research perspective, it is also important to identify allergens in sequenced genomes. Many allergen prediction tools have been developed during the past years. Although these tools have achieved certain levels of specificity, when applied to large-scale allergen discovery (e.g. at a whole-genome scale), they still yield many false positives and thus low precision (even at low recall) due to the extreme skewness of the data (allergens are rare). Moreover, the most accurate tools are relatively slow because they use protein sequence alignment to build feature vectors for allergen classifiers. Additionally, only web server implementations of the current allergen prediction tools are publicly available and are without the capability of large batch submission. These weaknesses make large-scale allergen discovery ineffective and inefficient in the public domain. RESULTS We developed Allerdictor, a fast and accurate sequence-based allergen prediction tool that models protein sequences as text documents and uses support vector machine in text classification for allergen prediction. Test results on multiple highly skewed datasets demonstrated that Allerdictor predicted allergens with high precision over high recall at fast speed. For example, Allerdictor only took ∼6 min on a single core PC to scan a whole Swiss-Prot database of ∼540 000 sequences and identified <1% of them as allergens. AVAILABILITY AND IMPLEMENTATION Allerdictor is implemented in Python and available as standalone and web server versions at http://allerdictor.vbi.vt.edu CONTACT: lawrence@vbi.vt.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Signatures of recombination in clonal lineages of the citrus brown spot pathogen, Alternaria alternata sensu lato.

Most Alternaria spp. are considered asexual but recent molecular evolution analyses of Alternaria mating-type genes show that the mating locus is under strong purifying selection, indicating a possible role in sexual reproduction. The objective of this study was to determine the mode of reproduction of an Alternaria alternata sensu lato population causing citrus brown spot in central Florida. Mating type of each isolate was determined, and isolates were sequenced at six putatively unlinked loci. Three genetically distinct subpopulations (SH1, SH4A, and SH4B) were identified using network and Bayesian population structure analyses. Results demonstrate that most subpopulations of A. alternata associated with citrus are clonal but some have the ability to extensively recombine through a cryptic sexual cycle or parasexual cycle. Although isolates were sampled in close physical proximity (≈2,500-m² area), we were able to reject a random mating model using multilocus gametic disequilibrium tests for two subpopulations, SH1 and SH4B, suggesting that these subpopulations were predominantly asexual. However, three recombination events were identified in SH1 and SH4B and localized to individuals of opposite mating type, possibly indicating meiotic recombination. In contrast, in the third subpopulation (SH4A), where only one mating type was present, extensive reticulation was evident in network analyses, and multilocus gametic disequilibrium tests were consistent with recombination. Recombination among isolates of the same mating type suggests that a nonmeiotic mechanism of recombination such as the parasexual cycle may be operating in this subpopulation. The level of gene flow detected among subpopulations does not appear to be sufficient to prevent differentiation, and perhaps future speciation, of these A. alternata subpopulations.

Visualizing tumor evolution with the fishplot package for R

BackgroundMassively-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.ResultsWe 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.ConclusionsThe 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.

Multi-institutional Analysis Shows that Low PCAT-14 Expression Associates with Poor Outcomes in Prostate Cancer

BACKGROUND Long noncoding RNAs (lncRNAs) are an emerging class of relatively underexplored oncogenic molecules with biological and clinical significance. Current inadequacies for stratifying patients with aggressive disease presents a strong rationale to systematically identify lncRNAs as clinical predictors in localized prostate cancer. OBJECTIVE To identify RNA biomarkers associated with aggressive prostate cancer. DESIGN, SETTING, AND PARTICIPANTS Radical prostatectomy microarray and clinical data was obtained from 910 patients in three published institutional cohorts: Mayo Clinic I (N=545, median follow-up 13.8 yr), Mayo Clinic II (N=235, median follow-up 6.7 yr), and Thomas Jefferson University (N=130, median follow-up 9.6 yr). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The primary clinical endpoint was distant metastasis-free survival. Secondary endpoints include prostate cancer-specific survival and overall survival. Univariate and multivariate Cox regression were used to evaluate the association of lncRNA expression and these endpoints. RESULTS AND LIMITATIONS An integrative analysis revealed Prostate Cancer Associated Transcript-14 (PCAT-14) as the most prevalent lncRNA that is aberrantly expressed in prostate cancer patients. Down-regulation of PCAT-14 expression significantly associated with Gleason score and a greater probability of metastatic progression, overall survival, and prostate cancer-specific mortality across multiple independent datasets and ethnicities. Low PCAT-14 expression was implicated with genes involved in biological processes promoting aggressive disease. In-vitro analysis confirmed that low PCAT-14 expression increased migration while overexpressing PCAT-14 reduced cellular growth, migration, and invasion. CONCLUSIONS We discovered that androgen-regulated PCAT-14 is overexpressed in prostate cancer, suppresses invasive phenotypes, and lower expression is significantly prognostic for multiple clinical endpoints supporting its significance for predicting metastatic disease that could be used to improve patient management. PATIENT SUMMARY We discovered that aberrant prostate cancer associated transcript-14 expression during prostate cancer progression is prevalent across cancer patients. Prostate cancer associated transcript-14 is also prognostic for metastatic disease and survival highlighting its importance for stratifying patients that could benefit from treatment intensification.

Increased breast tissue receptor activator of nuclear factor- κB ligand (RANKL) gene expression is associated with higher mammographic density in premenopausal women

Increased mammographic breast density is associated with a 4-6-fold increased risk of breast cancer, yet lifestyle factors that can reduce dense breasts are yet to be identified, and viable prevention strategies to reduce breast density-associated breast cancer development are yet to be developed. We investigated the associations of breast tissue receptor activator of nuclear factor-κB (RANK) pathway gene expression with mammographic density in 48 premenopausal women, with no previous history of cancer. Gene expression levels were measured in total RNA isolated from formalin-fixed paraffin-embedded breast tissue samples, using the NanoString nCounter platform. Mammographic density was classified based on the American College of Radiology Breast Imaging Reporting and Data (BI-RADS). Linear regression was used to evaluate associations between gene expression and mammographic density. The mean age of participants was 44.4 years. Women with higher breast tissue RANKL (TNFSF11) (p-value = 0.0076), and TNF (p-value = 0.007) gene expression had higher mammographic density. Our finding provides mechanistic support for a breast cancer chemoprevention trial with a RANKL inhibitor among high-risk premenopausal women with dense breasts.Increased mammographic breast density is associated with a 4–6-fold increased risk of breast cancer, yet lifestyle factors that can reduce dense breasts are yet to be identified, and viable prevention strategies to reduce breast density-associated breast cancer development are yet to be developed. We investigated the associations of breast tissue receptor activator of nuclear factor-κB (RANK) pathway gene expression with mammographic density in 48 premenopausal women, with no previous history of cancer. Gene expression levels were measured in total RNA isolated from formalin-fixed paraffin-embedded breast tissue samples, using the NanoString nCounter platform. Mammographic density was classified based on the American College of Radiology Breast Imaging Reporting and Data (BI-RADS). Linear regression was used to evaluate associations between gene expression and mammographic density. The mean age of participants was 44.4 years. Women with higher breast tissue RANKL (TNFSF11) (p-value = 0.0076), and TNF (p-value = 0.007) gene expression had higher mammographic density. Our finding provides mechanistic support for a breast cancer chemoprevention trial with a RANKL inhibitor among high-risk premenopausal women with dense breasts.

Clonotyping for precision oncology.

Advances in identifying subpopulations of cancer cells and reconstructing the clonal evolution of tumors greatly enhance our understanding of the molecular events within a patient and their context relative to one another. In the rapidly unfolding era of personalized medicine, the ability to monitor clonal dynamics throughout patient care has significant clinical implications for the appropriate development or application of targeted therapies as well as understanding the potential mechanisms driving resistance. In this review, we discuss advances in biotechnology and bioinformatics that improve precision treatment by dissecting clonal evolution, focusing first on the initial discoveries in lymphomas and leukemias followed by the more recent applications to advance our understanding of prostate cancer (PCa).