Blocking Tumor-Educated MSC Paracrine Activity Halts Osteosarcoma Progression

Purpose: Human osteosarcoma is a genetically heterogeneous bone malignancy with poor prognosis despite the employment of aggressive chemotherapy regimens. Because druggable driver mutations have not been established, dissecting the interactions between osteosarcoma cells and supporting stroma may provide insights into novel therapeutic targets.Experimental Design: By using a bioluminescent orthotopic xenograft mouse model of osteosarcoma, we evaluated the effect of tumor extracellular vesicle (EV)-educated mesenchymal stem cells (TEMSC) on osteosarcoma progression. Characterization and functional studies were designed to assess the mechanisms underlying MSC education. Independent series of tissue specimens were analyzed to corroborate the preclinical findings, and the composition of patient serum EVs was analyzed after isolation with size-exclusion chromatography.Results: We show that EVs secreted by highly malignant osteosarcoma cells selectively incorporate a membrane-associated form of TGF\u3b2, which induces proinflammatory IL6 production by MSCs. TEMSCs promote tumor growth, accompanied with intratumor STAT3 activation and lung metastasis formation, which was not observed with control MSCs. Importantly, intravenous administration of the anti-IL6 receptor antibody tocilizumab abrogated the tumor-promoting effects of TEMSCs. RNA-seq analysis of human osteosarcoma tissues revealed a distinct TGF\u3b2-induced prometastatic gene signature. Tissue microarray immunostaining indicated active STAT3 signaling in human osteosarcoma, consistent with the observations in TEMSC-treated mice. Finally, we isolated pure populations of EVs from serum and demonstrated that circulating levels of EV-associated TGF\u3b2 are increased in osteosarcoma patients.Conclusions: Collectively, our findings suggest that TEMSCs promote osteosarcoma progression and provide the basis for testing IL6- and TGF\u3b2-blocking agents as new therapeutic options for osteosarcoma patients. Clin Cancer Res; 23(14); 3721-33. \ua92017 AACR

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

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements