Overexpression of the Lung Cancer-Prognostic miR-146b MicroRNAs Has a Minimal and Negative Effect on the Malignant Phenotype of A549 Lung Cancer Cells

INTRODUCTION:Expression levels of miR-146b-5p and -3p microRNAs in human non-small cell lung cancer (NSCLC) are associated with recurrence of the disease after surgery. To understand this, the effect of miR-146b overexpression was studied in A549 human lung cancer cells. METHODS:A549 cells, engineered with lentiviruses to overexpress the human pre-miR-146b precursor microRNA, were examined for proliferation, colony formation on plastic surface and in soft agar, migration and invasiveness in cell culture and in vivo in mice, chemosensitivity to cisplatin and doxorubicin, and global gene expression. miR-146b expressions were assessed in microdissected stroma and epithelia of human NSCLC tumors. Association of miR-146b-5p and -3p expression in early stage NSCLC with recurrence was analyzed. PRINCIPAL FINDINGS:A549 pre-miR-146b-overexpressors had 3-8-fold higher levels of both miR-146b microRNAs than control cells. Overexpression did not alter cellular proliferation, chemosensitivity, migration, or invasiveness; affected only 0.3% of the mRNA transcriptome; and, reduced the ability to form colonies in vitro by 25%. In human NSCLC tumors, expression of both miR-146b microRNAs was 7-10-fold higher in stroma than in cancerous epithelia, and higher miR-146b-5p but lower -3p levels were predictive of recurrence. CONCLUSIONS:Only a minimal effect of pre-miR-146b overexpression on the malignant phenotype was seen in A549 cells. This could be because of opposing effects of miR-146b-5p and -3p overexpression as suggested by the conflicting recurrence-predictive values of the two microRNAs, or because miR-146b expression changes in non-cancerous stroma and not cancerous epithelia of tumors are responsible for the prognostic value of miR-146b

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Locus-Specific DNA Methylation Editing in Melanoma Cell Lines Using a CRISPR-Based System

DNA methylation is a key epigenetic modification implicated in the pathogenesis of numerous human diseases, including cancer development and metastasis. Gene promoter methylation changes are widely associated with transcriptional deregulation and disease progression. The advent of CRISPR-based technologies has provided a powerful toolkit for locus-specific manipulation of the epigenome. Here, we describe a comprehensive global workflow for the design and application of a dCas9-SunTag-based tool for editing the DNA methylation locus in human melanoma cells alongside protocols for downstream techniques used to evaluate subsequent methylation and gene expression changes in methylation-edited cells. Using transient system delivery, we demonstrate both highly efficacious methylation and demethylation of the EBF3 promoter, which is a putative epigenetic driver of melanoma metastasis, achieving up to a 304.00% gain of methylation and 99.99% relative demethylation, respectively. Furthermore, we employ a novel, targeted screening approach to confirm the minimal off-target activity and high on-target specificity of our designed guide RNA within our target locus

Reactivity of polyaminocarboxylatoruthenium(III) complexes with serine and their protease inhibition

Reaction of [Ru(edta)(H2O)]� (edta4�¼ethylenediaminetetraacetate), [Ru(pdta)(H2O)]� (pdta4�¼propylenediaminetetraacetate) and [Ru(hedtra)(H2O)] (hedtra3�¼N-hydroxyethylethylenediaminetriacetate) with S-serine (Ser) was studied spectrophotometrically and kinetically. Serine protease inhibition studies were performed with the three complexes using the serine protease enzymes chymotrypsin and subtilisin with azoalbumin as substrate. Results are discussed in terms of the reactivity of the Ru-pac (pac¼polyaminopolycarboxylates) complexes with serine. The order of protease inhibition efficacy of the Ru-pac complexes is [Ru(pdta)(H2O)]�>[Ru(edta)(H2O)]��[Ru(hedtra)(H2O)], in good agreement with the observed reactivity of Ru-pac complexes with serin

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press