Intestinal BMP-9 locally upregulates FGF19 and is down-regulated in obese patients with diabetes

believed to be mainly produced in the liver. The serum levels of BMP-9 were reported to be reduced in newly diagnosed diabetic patients and BMP-9 overexpression ameliorated steatosis in the high fat diet-induced obesity mouse model. Furthermore, injection of BMP-9 in mice enhanced expression of fibroblast growth factor (FGF)21. However, whether BMP-9 also regulates the expression of the related FGF19 is not clear. Because both FGF21 and 19 were described to protect the liver from steatosis, we have further investigated the role of BMP-9 in this context. We first analyzed BMP-9 levels in the serum of streptozotocin (STZ)-induced diabetic rats (a model of type I diabetes) and confirmed that BMP-9 serum levels decrease during diabetes. Microarray analyses of RNA samples from hepatic and intestinal tissue from BMP-9 KO- and wild-type mice (C57/Bl6 background) pointed to basal expression of BMP-9 in both organs and revealed a down-regulation of hepatic Fgf21 and intestinal Fgf19 in the KO mice. Next, we analyzed BMP-9 levels in a cohort of obese patients with or without diabetes. Serum BMP-9 levels did not correlate with diabetes, but hepatic BMP-9 mRNA expression negatively correlated with steatosis in those patients that did not yet develop diabetes. Likewise, hepatic BMP-9 expression also negatively correlated with serum LPS levels. In situ hybridization analyses confirmed intestinal BMP-9 expression. Intestinal (but not hepatic) BMP-9 mRNA levels were decreased with diabetes and positively correlated with intestinal E-Cadherin expression. In vitro studies using organoids demonstrated that BMP-9 directly induces FGF19 in gut but not hepatocyte organoids, whereas no evidence of a direct induction of hepatic FGF21 by BMP-9 was found. Consistent with the in vitro data, a correlation between intestinal BMP-9 and FGF19 mRNA expression was seen in the patients’ samples. In summary, our data confirm that BMP-9 is involved in diabetes development in humans and in the control of the FGF-axis. More importantly, our data imply that not only hepatic but also intestinal BMP-9 associates with diabetes and steatosis development and controls FGF19 expression. The data support the conclusion that increased levels of BMP-9 would most likely be beneficial under pre-steatotic conditions, making supplementation of BMP-9 an interesting new approach for future therapies aiming at prevention of the development of a metabolic syndrome and liver steatosis

NY-BR-1 is a differentiation antigen of the mammary gland

NY-BR-1 was recently identified by autologous serological typing of the recombinant expression library in a breast cancer patient. Extensive reverse transcriptase-polymerase chain reaction analysis revealed the presence of NY-BR-1 in normal breast tissue and tumors derived thereof. Except normal testis, no other normal tissue or tumors showed NY-BR-1 expression. However, nothing is known about the expression of its actual antigen. In the present study, we describe the generation of 2 new monoclonal antibodies, NY-BR-1#2 and NY-BR-1#3, to NY-BR-1 for the analysis of its expression on a protein level employing recombinant NY-BR-1 protein for the immunization of BALB/c mice. In normal tissues, immunohistochemical testing demonstrates NY-BR-1 in a mostly focal fashion in the epithelia of ducts and acini of the mammary gland. No other tissue was immunopositive including testis. In tumors, homogenous staining can be seen in almost all ductal carcinomas in situ and/or the intraductal component of invasive carcinomas. Invasive carcinomas show a lower number of NY-BR-1-positive tumors. Initial higher numbers of NY-BR-1 mRNA-positive invasive carcinomas are most likely based on sample error owing to the contamination of tumor tissue with remnants of normal breast epithelium. Sweat gland carcinomas, which are related to breast cancer, are also positive in about one-third of the cases. These data indicate that NY-BR-1 is a differentiation antigen of the mammary gland that could be useful for diagnosis and/or immunotherapy of breast carcinomas

Author Correction: The landscape of viral associations in human cancers

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The landscape of viral associations in human cancers

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, for which whole-genome and-for a subset-whole-transcriptome sequencing data from 2,658 cancers across 38 tumor types was aggregated, we systematically investigated potential viral pathogens using a consensus approach that integrated three independent pipelines. Viruses were detected in 382 genome and 68 transcriptome datasets. We found a high prevalence of known tumor-associated viruses such as Epstein-Barr virus (EBV), hepatitis B virus (HBV) and human papilloma virus (HPV; for example, HPV16 or HPV18). The study revealed significant exclusivity of HPV and driver mutations in head-and-neck cancer and the association of HPV with APOBEC mutational signatures, which suggests that impaired antiviral defense is a driving force in cervical, bladder and head-and-neck carcinoma. For HBV, HPV16, HPV18 and adeno-associated virus-2 (AAV2), viral integration was associated with local variations in genomic copy numbers. Integrations at the TERT promoter were associated with high telomerase expression evidently activating this tumor-driving process. High levels of endogenous retrovirus (ERV1) expression were linked to a worse survival outcome in patients with kidney cancer

Measurement of the top quark pole mass using tt‾ \textrm{t}\overline{\textrm{t}} +jet events in the dilepton final state in proton-proton collisions at s \sqrt{s} = 13 TeV

A measurement of the top quark pole mass ${{m_{\mathrm{t}}} ^{\text{pole}}}$ in events where a top quark-antiquark pair ($\mathrm{t\bar{t}}$) is produced in association with at least one additional jet ($\mathrm{t\bar{t}}$+jet) is presented. This analysis is performed using proton-proton collision data at $\sqrt{s} =$ 13 TeV collected by the CMS experiment at the CERN LHC, corresponding to a total integrated luminosity of 36.3 fb$^{-1}$. Events with two opposite-sign leptons in the final state (e$^{+}$e$^{-}$, $\mu^{+}\mu^{-}$, e$^{\pm}\mu^{\mp}$) are analyzed. The reconstruction of the main observable and the event classification are optimized using multivariate analysis techniques based on machine learning. The production cross section is measured as a function of the inverse of the invariant mass of the $\mathrm{t\bar{t}}$+jet system at the parton level using a maximum likelihood unfolding. Given a reference parton distribution function (PDF), the top quark pole mass is extracted using the theoretical predictions at next-to-leading order. For the ABMP16NLO PDF, this results in ${{m_{\mathrm{t}}} ^{\text{pole}}} =$ 172.94 $\pm$ 1.37 GeV.A measurement of the top quark pole mass ${m}_{\textrm{t}}^{\textrm{pole}}$ in events where a top quark-antiquark pair ($\textrm{t}\overline{\textrm{t}}$) is produced in association with at least one additional jet ($\textrm{t}\overline{\textrm{t}}$+jet) is presented. This analysis is performed using proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the CMS experiment at the CERN LHC, corresponding to a total integrated luminosity of 36.3 fb$^{−1}$. Events with two opposite-sign leptons in the final state (e$^{+}$e$^{−}$, μ$^{+}$μ$^{−}$, e$^{±}$μ$^{∓}$) are analyzed. The reconstruction of the main observable and the event classification are optimized using multivariate analysis techniques based on machine learning. The production cross section is measured as a function of the inverse of the invariant mass of the $\textrm{t}\overline{\textrm{t}}$+jet system at the parton level using a maximum likelihood unfolding. Given a reference parton distribution function (PDF), the top quark pole mass is extracted using the theoretical predictions at next-to-leading order. For the ABMP16NLO PDF, this results in ${m}_{\textrm{t}}^{\textrm{pole}}$ = 172.93 ± 1.36 GeV.[graphic not available: see fulltext]A measurement of the top quark pole mass $m_\mathrm{t}^\text{pole}$ in events where a top quark-antiquark pair ($\mathrm{t\bar{t}}$) is produced in association with at least one additional jet ($\mathrm{t\bar{t}}$+jet) is presented. This analysis is performed using proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the CMS experiment at the CERN LHC, corresponding to a total integrated luminosity of 36.3 fb$^{-1}$. Events with two opposite-sign leptons in the final state (e$^+$e$^-$, $\mu^+\mu^-$, e$^\pm\mu^\mp$) are analyzed. The reconstruction of the main observable and the event classification are optimized using multivariate analysis techniques based on machine learning. The production cross section is measured as a function of the inverse of the invariant mass of the $\mathrm{t\bar{t}}$+jet system at the parton level using a maximum likelihood unfolding. Given a reference parton distribution function (PDF), the top quark pole mass is extracted using the theoretical predictions at next-to-leading order. For the ABMP16NLO PDF, this results in $m_\mathrm{t}^\text{pole}$ = 172.93 $\pm$ 1.36 GeV