The mammalian Janus kinase (JAK) family consists of four members, namely JAK1, JAK2, JAK3 and TYK2, which play a critical role in cytokine/growth factor signaling and is increasingly associated with human cancers. Aberrant activation of these non-receptor tyrosine kinases may contribute to carcinogenesis. Herein, we focused on exploring the potential role of p-JAK1 in breast cancer. The expression profiles of p-JAK1 were analyzed in 68 pairs of cancer and non-cancer breast tissues from the same infiltrating ductal carcinoma case by using immunoblotting technique. The results obtained were further correlated with clinicopathological characteristics. Intriguingly, p-JAK1 expression was decreased in 55.9% of breast cancer tissues as compared to the matched noncancer tissues. Further immunohistochemistry study showed an intense p-JAK1 staining predominantly in adjacent normal breast tissues but not the matched cancer lesions. Decreased p-JAK1 expression in breast cancer tissues was significantly correlated with positive estrogen receptor (ER) status and increased tumor size (p=0.010 and 0.009). We also found that p-JAK1 expression was high in ER•-negative breast cancer cell lines but was low in ER•-positive breast cell lines. Transfection of ER•-positive MCF-7 cells with an ER•-specific siRNA upregulated the expression of p-JAK1. In summary, our results indicated that an altered p-JAK1 expression might be involved in the development of breast infiltrating ductal carcinoma in an ER•-related manner.

Objectives The United States transitioned to the tenth version of the International Classification of Diseases (ICD) system (ICD-10) for mortality coding in 1999 and to the International Classification of Diseases, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS) on October 1, 2015. The purpose of this study was to conduct a narrative literature review to better understand the impact of the implementation of ICD-10/ICD-10-CM/PCS. Materials and Methods We searched English-language articles in PubMed, Web of Science, and Business Source Complete and reviewed websites of relevant professional associations, government agencies, research groups, and ICD-10 news aggregators to identify literature on the impact of the ICD-10/ICD-10-CM/PCS transition. We used Google to search for additional gray literature and used handsearching of the references of the most on-target articles to help ensure comprehensiveness. Results Impact areas reported in the literature include: productivity and staffing, costs, reimbursement, coding accuracy, mapping between ICD versions, morbidity and mortality surveillance, and patient care. With the exception of morbidity and mortality surveillance, quantitative studies describing the actual impact of the ICD-10/ICD-10-CM/PCS implementation were limited and much of the literature was based on the ICD-10-CM/PCS transition rather than the earlier conversion to ICD-10 for mortality coding. Discussion This study revealed several gaps in the literature that limit the ability to draw reliable conclusions about the overall impact, positive or negative, of moving to ICD-10/ICD-10-CM/PCS in the United States. Conclusion These knowledge gaps present an opportunity for future research and knowledge sharing and will be important to consider when planning for ICD-11.

Human aspartyl-(asparaginyl)-β-hydroxylase (HAAH) is a type 2 transmembrane protein and an α-ketoglutarate-dependent dioxygenase that can stereospecifically catalyze the post-translational hydroxylation reaction of β-carbon atoms of aspartic acid and asparagine residues present in epidermal growth factor-like domains of certain specific proteins. Humbug is a truncated isoform of aspartyl (asparaginyl) β-hydroxylase that lacks the catalytic domain. A series of reports demonstrated that overexpression of HAAH/humbug was identified in hepatocellular carcinoma (HCC) and various tumor tissues. However, the prognostic value of HAAH/humbug expression in HCC remains unclear. The purpose of this study was to investigate the expression of the HAAH/humbug gene at the mRNA and protein levels in HCC and to assess the overexpression of HAAH/humbug as a diagnostic and prognostic marker in HCC. HAAH/humbug mRNA levels were measured in 120 HCCs and 40 paired non-tumor liver tissues by molecular beacon (MB) quantitative RT-PCR. Immunohistochemical staining was used to detect the protein level of the HAAH/humbug in the same specimens. ROC analysis was performed based on the expression levels of the HAAH/humbug gene in 120 cases of HCC tissues and 40 cases of adjacent non-tumor liver tissues. The results showed that 117 (97.5%) of the 120 frozen sections of patients with HCCs had HAAH/humbug-positive immunoreactivity, whereas the 40 adjacent non-tumor liver tissues exhibited no staining. Higher levels of HAAH/humbug mRNA were found in 114 (95%) of the 120 HCC tissues relative to the adjacent cancer‑free tissue. ROC curve analysis exhibited that the sensitivity was 90.1%, specificity was 97.6% and ROC AUC was 0.986. The specific value of HAAH/β-actin abundance used as a cut‑off point was 0.315, while the gene copy number (7.35 copies/µl) was used a as cut‑off point, with sensitivity being 99.2%, specificity 96.7% and the ROC AUC used 0.990. No statistically significant difference was observed for these two factors. HAAH/humbug expression levels were upregulated in almost all the HCC tissues when compared to the adjacent cancer-free tissue, irrespective of the cut‑off point used. Results of the present study suggested that HAAH/humbug is a potential diagnostic and prognostic biomarker for the treatment of HCC.

Background: Advances in the health sciences rely on sharing research and data through publication. As information professionals are often asked to contribute their knowledge to assist clinicians and researchers in selecting journals for publication, the authors recognized an opportunity to build a decision support tool, SPI-Hub: Scholarly Publishing Information Hub™, to capture the team’s collective publishing industry knowledge, while carefully retaining the quality of service.Case Presentation: SPI-Hub’s decision support functionality relies on a data framework that describes journal publication policies and practices through a newly designed metadata structure, the Knowledge Management Journal Record™. Metadata fields are populated through a semi-automated process that uses custom programming to access content from multiple sources. Each record includes 25 metadata fields representing best publishing practices. Currently, the database includes more than 24,000 health sciences journal records. To correctly capture the resources needed for both completion and future maintenance of the project, the team conducted an internal study to assess time requirements for completing records through different stages of automation.Conclusions: The journal decision support tool, SPI-Hub, provides an opportunity to assess publication practices by compiling data from a variety of sources in a single location. Automated and semi-automated approaches have effectively reduced the time needed for data collection. Through a comprehensive knowledge management framework and the incorporation of multiple quality points specific to each journal, SPI-Hub provides prospective users with both recommendations for publication and holistic assessment of the trustworthiness of journals in which to publish research and acquire trusted knowledge.

The cBioPortal for Cancer Genomics is an open source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets. It integrates genomic and clinical data, and provides a suite of visualization and analysis options, including cohort and patient-level visualization, mutation visualization, survival analysis, alteration enrichment analysis, and network analysis. The user interface is user-friendly, responsive, and makes genomic data easily accessible to scientists and clinicians. The public site (http://www.cbioportal.org) hosts data from more than 165 studies, including data from large consortia (TCGA and ICGC) and individual labs. With newly released functionality, users can now explore and query these studies individually or can combine multiple studies into new “virtual studies”. The main features of the portal include OncoPrints, a compact graphical representation of alterations in multiple genes across a cohort, mutational diagrams that show locations and frequencies of mutations in a single gene, Kaplan-Meier survival curves, plots that allow the visualization of correlation between different data types for a single or multiple genes (e.g. the correlation between DNA copy number and mRNA expression), among others. To facilitate interpretation of genomic data, the cBioPortal also now integrates annotations from several leading knowledgebases (OncoKB, CIViC, MyCancerGenome and COSMIC), as well as other resources that can guide variant interpretation (CancerHotspots, MutationAssessor, SIFT and PolyPhen). The cBioPortal has been widely adopted by the cancer community, with dozens of private instances at academic institutions and pharmaceutical/biotechnology companies. The public portal is currently accessed by approximately 25K unique visitors per month. Another notable instance is the cBioPortal for AACR GENIE (http://www.cbioportal.org/genie/), which hosts 31,706 samples from AACR Project GENIE. The cBioPortal is fully open source and all code is available on GitHub (https://github.com/cBioPortal/) under a GNU Affero GPL license. Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children's Hospital of Philadelphia, Princess Margaret Cancer Centre, and The Hyve, an open source bioinformatics company based in the Netherlands. Ongoing development efforts are focused on (1) building the open source community; (2) implementing architectural and performance improvements; (3) expanding user support, documentation and training resources; (4) developing novel features to support immunogenomics and immunotherapy; (5) enhancing visualization of patient timelines, multiple tumor profiles, and cohort response; and (6) releasing a new public Application Programming Interface (API). Citation Format: Jianjiong Gao, Tali Mazor, Ersin Ciftci, Pichai Raman, Pieter Lukasse, Istemi Bahceci, Alexandros Sigaras, Adam Abeshouse, Ino de Bruijn, Benjamin Gross, Ritika Kundra, Aaron Lisman, Angelica Ochoa, Robert Sheridan, Jing Su, Selcuk O. Sumer, Yichao Sun, Avery Wang, Jiaojiao Wang, Manda Wilson, Hongxin Zhang, Priti Kumari, James Lindsay, Karthik Kalletla, Kelsey Zhu, Oleguer Plantalech, Fedde Schaeffer, Sander Tan, Dionne Zaal, Sjoerd van Hagen, Kees van Bochove, Ugur Dogrusoz, Trevor J. Pugh, Adam Resnick, Chris Sander, Nikolaus Schultz, Ethan Cerami. The cBioPortal for Cancer Genomics: An intuitive open-source platform for exploration, analysis and visualization of cancer genomics data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 923.