Citations

Abstract Motivation The significance of long non-coding RNAs (lncRNAs) in many biological processes and diseases has gained intense interests over the past several years. However, computational identification of lncRNAs in a wide range of species remains challenging; it requires prior knowledge of well-established sequences and annotations or species-specific training data, but the reality is that only a limited number of species have high-quality sequences and annotations. Results Here we first characterize lncRNAs in contrast to protein-coding RNAs based on feature relationship and find that the feature relationship between open reading frame length and guanine-cytosine (GC) content presents universally substantial divergence in lncRNAs and protein-coding RNAs, as observed in a broad variety of species. Based on the feature relationship, accordingly, we further present LGC, a novel algorithm for identifying lncRNAs that is able to accurately distinguish lncRNAs from protein-coding RNAs in a cross-species manner without any prior knowledge. As validated on large-scale empirical datasets, comparative results show that LGC outperforms existing algorithms by achieving higher accuracy, well-balanced sensitivity and specificity, and is robustly effective (>90% accuracy) in discriminating lncRNAs from protein-coding RNAs across diverse species that range from plants to mammals. To our knowledge, this study, for the first time, differentially characterizes lncRNAs and protein-coding RNAs based on feature relationship, which is further applied in computational identification of lncRNAs. Taken together, our study represents a significant advance in characterization and identification of lncRNAs and LGC thus bears broad potential utility for computational analysis of lncRNAs in a wide range of species. Availability and implementation LGC web server is publicly available at http://bigd.big.ac.cn/lgc/calculator. The scripts and data can be downloaded at http://bigd.big.ac.cn/biocode/tools/BT000004. Supplementary information Supplementary data are available at Bioinformatics online.

The many existing hierarchical classifications present opportunities for computer-aided classification of medical data. The authors evaluate lexical term mapping followed by hierarchical node activation to determine the semantic locality of diagnoses in the American College of Radiology (ACR) classification. The activated hierarchy exposes conceptual structures behind lexically matched categories and markedly narrows the alternatives for human review. Several distribution analyses are evaluated for narrowing the candidate search space, to reduce ambiguity. The methods were tested on a prototype system, using a set of 78 samples of Mayo radiology diagnoses; their relative effectiveness is illustrated.

Abstract Oncogenic role of p21-activated protein 4 (PAK4) in relation to cell growth and migration through various signalling cascades has been well studied in multiple cancer types. Such role might be contributed largely by cytoplasmic PAK4 as most of the known PAK4 signalling events occur in the cytoplasm. However, recent studies have demonstrated that PAK4 is capable of shuttling between nucleus and cytoplasm. The precise function of nuclear PAK4 (nPAK4) remains substantially unexplored. We have previously shown that PAK4 can act as a transcription factor. Herein, we aim to identify nPAK4-regulated genes by delineating the PAK4-binding landscape in ovarian cancer genome and mapping the PAK4 transcriptome in ovarian cancer cells. PAK4-enriched genomic regions were identified by chromatin immunoprecipitation with a PAK4 antibody followed by next-generation sequencing (ChIP-seq) in OVCAR3 cells. PAK4 transcriptome data was generated using RNA extracted from SKOV3 cells stably expressing PAK4 in the Affymetrix GeneChIP® Human Transcriptome Array 2.0 system. Gene lists generated from both ChIP-seq and microarray dataset were subjected to pathway enrichment analysis by Partek® PathwayTM. Among the 20 most significantly enriched pathways from microarray studies, several pathways in which PAK4 has no known reported function by far have been identified. Notably, DNA repair pathways that are known to influence drug chemosensitivity in ovarian cancer, such as the nucleotide excision repair (p=0.008), homologous recombination (p=0.012), mismatch repair (p=0.018) and DNA replication (p=0.018) pathways were significantly enriched. In concordance with the findings, the nucleotide excision repair pathway was also significantly enriched (p<0.006) in the gene list derived from promoter-restricted PAK4 binding sites in the ovarian cancer genome. Among the many candidates that were deregulated by PAK4, cyclin-dependent kinase 7 (CDK7), a core component in the CAK subcomplex crucial to nucleotide excision repair pathway, was further validated. The transcription start site (TSS) of cyclin-dependent kinase 7 (CDK7) was bound by PAK4. CDK7 mRNA expression was upregulated upon PAK4 overexpression. Quantitative-PCR showed downregulated CDK7 mRNA expression upon siRNA-mediated knockdown of PAK4 in OVCAR3 and TUOS3. This study points to the possible role of PAK4 in regulating gene transcription as PAK4 is mapped to several core promoter/TSS regions in the ovarian cancer genome. Our findings also shed light into the potential role of PAK4 in regulating drug chemosensitivity via its transcriptional control on genes implicated in DNA repair pathways. We postulate CDK7 as a direct transcriptional target of PAK4 and thereby contributes to chemoresistance in ovarian cancer cells. Citation Format: Ivy Tsz-Lo Wong, Oscar Gee-Wan Wong, Yiming Qin, Junwen Wang, Annie Nga-Yin Cheung. Genome-wide profiling of PAK4 DNA-binding sites and transcriptome reveals its potential transcriptional control on DNA repair-related genes in ovarian cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2419. doi:10.1158/1538-7445.AM2017-2419

AbstractPituitary stalk interruption syndrome (PSIS) is a rare type of hypopituitarism manifesting various degrees of pituitary hormone deficiency. Although mutations have been identified in some familial cases, the underpinning mechanisms of sporadic patients with PSIS who are in a vast majority remain elusive, necessitating a comprehensive study using systemic approaches. We postulate that other genetic mechanisms may be responsible for the sporadic PSIS. To test this hypothesis, we conducted a study in 24 patients with PSIS of Han Chinese with no family history using whole‐exome sequencing (WES) and bioinformatic analysis. We identified a group of heterozygous mutations in 92% (22 of 24) of the patients, and these genes are mostly associated with Notch, Shh, Wnt signalling pathways. Importantly, 83% (20 of 24) of the patients had more than one mutation in those pathways suggesting synergy of compound mutations underpin the pathogenesis of sporadic PSIS.

The mononegaviral family Filoviridae has eight members assigned to three genera and seven species. Until now, genus and species demarcation were based on arbitrarily chosen filovirus genome sequence divergence values (≈50% for genera, ≈30% for species) and arbitrarily chosen phenotypic virus or virion characteristics. Here we report filovirus genome sequence-based taxon demarcation criteria using the publicly accessible PAirwise Sequencing Comparison (PASC) tool of the US National Center for Biotechnology Information (Bethesda, MD, USA). Comparison of all available filovirus genomes in GenBank using PASC revealed optimal genus demarcation at the 55–58% sequence diversity threshold range for genera and at the 23–36% sequence diversity threshold range for species. Because these thresholds do not change the current official filovirus classification, these values are now implemented as filovirus taxon demarcation criteria that may solely be used for filovirus classification in case additional data are absent. A near-complete, coding-complete, or complete filovirus genome sequence will now be required to allow official classification of any novel “filovirus.” Classification of filoviruses into existing taxa or determining the need for novel taxa is now straightforward and could even become automated using a presented algorithm/flowchart rooted in RefSeq (type) sequences.

494 Background: Renal cell carcinoma (RCC) with rhabdoid differentiation is thought to portend a poor prognosis, similar to RCC with sarcomatoid differentiation. Both rhabdoid and sarcomatoid differentiation are classified as grade 4 RCC based on the most recent International Society of Urological Pathology (ISUP) grading system. We sought to determine the prognostic value of rhabdoid differentiation in comparison to RCC with sarcomatoid differentiation, grade 4 RCC without rhabdoid or sarcomatoid differentiation, and grade 3 RCC. Methods: Using the Mayo Clinic Nephrectomy Registry, we identified 406 patients with ISUP grade 4 RCC and 1,758 patients with grade 3 RCC. A urologic pathologist reviewed all specimens to determine the presence of both rhabdoid and sarcomatoid differentiation. Associations of clinical and pathologic features with death from RCC were evaluated using Cox models. Results: Among the 406 grade 4 RCC tumors, 111 (27%) had rhabdoid differentiation and 189 (47%) had sarcomatoid differentiation, although only 28 (7%) demonstrated both rhabdoid and sarcomatoid differentiation. In multivariable analysis of grade 4 RCC tumors, the presence of rhabdoid differentiation was not associated with death from RCC (HR 0.95, p=0.75); in contrast, sarcomatoid differentiation was significantly associated with death from RCC (HR 1.63, p<0.001). Patients with RCC with rhabdoid differentiation were significantly more likely to die of RCC than patients with grade 3 RCC (HR 2.45, p<0.001) and grade 3 RCC with necrosis (HR 1.62; p<0.001). Conclusions: This study confirms that RCC with rhabdoid differentiation is appropriately classified as grade 4. However, unlike sarcomatoid differentiation, the presence of rhabdoid differentiation in grade 4 RCC is not associated with an increased risk of death from RCC. Therefore, rhabdoid and sarcomatoid differentiation should not be grouped together when assessing risk in a patient with grade 4 RCC.