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Species

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Gene

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Platform

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Channel

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HiPlex Channel

  • T1 (85058) Apply T1 filter
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  • T11 (85039) Apply T11 filter
  • T9 (82563) Apply T9 filter
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  • S1 (32) Apply S1 filter
  • 8 (17) Apply 8 filter
  • 1 (1) Apply 1 filter
  • 10 (1) Apply 10 filter
  • 6 (1) Apply 6 filter

Product

  • RNAscope Multiplex Fluorescent Assay (1035) Apply RNAscope Multiplex Fluorescent Assay filter
  • RNAscope (998) Apply RNAscope filter
  • RNAscope Fluorescent Multiplex Assay (732) Apply RNAscope Fluorescent Multiplex Assay filter
  • RNAscope 2.5 HD Red assay (704) Apply RNAscope 2.5 HD Red assay filter
  • RNAscope 2.0 Assay (497) Apply RNAscope 2.0 Assay filter
  • RNAscope 2.5 HD Brown Assay (293) Apply RNAscope 2.5 HD Brown Assay filter
  • TBD (193) Apply TBD filter
  • RNAscope 2.5 LS Assay (191) Apply RNAscope 2.5 LS Assay filter
  • RNAscope 2.5 HD Duplex (160) Apply RNAscope 2.5 HD Duplex filter
  • RNAscope 2.5 HD Reagent Kit - BROWN (108) Apply RNAscope 2.5 HD Reagent Kit - BROWN filter
  • RNAscope Multiplex Fluorescent v2 (97) Apply RNAscope Multiplex Fluorescent v2 filter
  • BASEscope Assay RED (91) Apply BASEscope Assay RED filter
  • RNAscope 2.5 VS Assay (85) Apply RNAscope 2.5 VS Assay filter
  • Basescope (53) Apply Basescope filter
  • RNAscope HiPlex v2 assay (30) Apply RNAscope HiPlex v2 assay filter
  • miRNAscope (26) Apply miRNAscope filter
  • DNAscope HD Duplex Reagent Kit (15) Apply DNAscope HD Duplex Reagent Kit filter
  • RNAscope 2.5 HD duplex reagent kit (13) Apply RNAscope 2.5 HD duplex reagent kit filter
  • BaseScope Duplex Assay (12) Apply BaseScope Duplex Assay filter
  • RNAscope Multiplex fluorescent reagent kit v2 (6) Apply RNAscope Multiplex fluorescent reagent kit v2 filter
  • RNAscope Fluorescent Multiplex Reagent kit (5) Apply RNAscope Fluorescent Multiplex Reagent kit filter
  • RNAscope ISH Probe High Risk HPV (5) Apply RNAscope ISH Probe High Risk HPV filter
  • CTCscope (4) Apply CTCscope filter
  • RNAscope 2.5 HD Reagent Kit (4) Apply RNAscope 2.5 HD Reagent Kit filter
  • RNAscope HiPlex12 Reagents Kit (3) Apply RNAscope HiPlex12 Reagents Kit filter
  • DNAscope Duplex Assay (2) Apply DNAscope Duplex Assay filter
  • RNAscope 2.5 HD Assay (2) Apply RNAscope 2.5 HD Assay filter
  • RNAscope 2.5 LS Assay - RED (2) Apply RNAscope 2.5 LS Assay - RED filter
  • RNAscope Multiplex Fluorescent Assay v2 (2) Apply RNAscope Multiplex Fluorescent Assay v2 filter
  • BOND RNAscope Brown Detection (1) Apply BOND RNAscope Brown Detection filter
  • HybEZ Hybridization System (1) Apply HybEZ Hybridization System filter
  • miRNAscope Assay Red (1) Apply miRNAscope Assay Red filter
  • RNA-Protein CO-Detection Ancillary Kit (1) Apply RNA-Protein CO-Detection Ancillary Kit filter
  • RNAscope 2.0 HD Assay - Chromogenic (1) Apply RNAscope 2.0 HD Assay - Chromogenic filter
  • RNAscope 2.5 HD- Red (1) Apply RNAscope 2.5 HD- Red filter
  • RNAscope 2.5 LS Reagent Kits (1) Apply RNAscope 2.5 LS Reagent Kits filter
  • RNAScope HiPlex assay (1) Apply RNAScope HiPlex assay filter
  • RNAscope HiPlex Image Registration Software (1) Apply RNAscope HiPlex Image Registration Software filter
  • RNAscope LS Multiplex Fluorescent Assay (1) Apply RNAscope LS Multiplex Fluorescent Assay filter
  • RNAscope Multiplex Fluorescent Reagent Kit V3 (1) Apply RNAscope Multiplex Fluorescent Reagent Kit V3 filter
  • RNAscope Multiplex Fluorescent Reagent Kit v4 (1) Apply RNAscope Multiplex Fluorescent Reagent Kit v4 filter
  • RNAscope Multiplex Fluorescent v1 (1) Apply RNAscope Multiplex Fluorescent v1 filter
  • RNAscope Target Retrieval Reagents (1) Apply RNAscope Target Retrieval Reagents filter

Research area

  • Neuroscience (1849) Apply Neuroscience filter
  • Cancer (1385) Apply Cancer filter
  • Development (509) Apply Development filter
  • Inflammation (472) Apply Inflammation filter
  • Infectious Disease (410) Apply Infectious Disease filter
  • Other (406) Apply Other filter
  • Stem Cells (258) Apply Stem Cells filter
  • Covid (237) Apply Covid filter
  • Infectious (220) Apply Infectious filter
  • HPV (187) Apply HPV filter
  • lncRNA (135) Apply lncRNA filter
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  • Immunotherapy (72) Apply Immunotherapy filter
  • Other: Methods (67) Apply Other: Methods filter
  • HIV (64) Apply HIV filter
  • CGT (62) Apply CGT filter
  • Pain (62) Apply Pain filter
  • diabetes (57) Apply diabetes filter
  • LncRNAs (46) Apply LncRNAs filter
  • Aging (43) Apply Aging filter
  • Other: Heart (40) Apply Other: Heart filter
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  • Obesity (29) Apply Obesity filter
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  • Behavior (27) Apply Behavior filter
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  • Other: Kidney (27) Apply Other: Kidney filter
  • Alzheimer's Disease (26) Apply Alzheimer's Disease filter
  • Bone (24) Apply Bone filter
  • Stress (21) Apply Stress filter
  • Other: Zoological Disease (20) Apply Other: Zoological Disease filter
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  • Fibrosis (17) Apply Fibrosis filter
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  • Other: Endocrinology (16) Apply Other: Endocrinology filter
  • Other: Skin (16) Apply Other: Skin filter
  • Injury (15) Apply Injury filter
  • Anxiety (14) Apply Anxiety filter
  • Memory (14) Apply Memory filter
  • Reproductive Biology (14) Apply Reproductive Biology filter

Product sub type

  • Target Probes (256568) Apply Target Probes filter
  • Control Probe - Automated Leica (409) Apply Control Probe - Automated Leica filter
  • Control Probe - Automated Leica Multiplex (284) Apply Control Probe - Automated Leica Multiplex filter
  • Control Probe - Automated Leica Duplex (168) Apply Control Probe - Automated Leica Duplex filter
  • Control Probe- Manual RNAscope Multiplex (148) Apply Control Probe- Manual RNAscope Multiplex filter
  • Control Probe - Automated Ventana (143) Apply Control Probe - Automated Ventana filter
  • Control Probe - Manual RNAscope Singleplex (142) Apply Control Probe - Manual RNAscope Singleplex filter
  • Control Probe - Manual RNAscope Duplex (137) Apply Control Probe - Manual RNAscope Duplex filter
  • Control Probe (73) Apply Control Probe filter
  • Control Probe - Manual BaseScope Singleplex (51) Apply Control Probe - Manual BaseScope Singleplex filter
  • Control Probe - VS BaseScope Singleplex (41) Apply Control Probe - VS BaseScope Singleplex filter
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  • L-HBsAG (15) Apply L-HBsAG filter
  • Cancer (13) Apply Cancer filter
  • Automated Assay 2.5: Leica System (8) Apply Automated Assay 2.5: Leica System filter
  • Control Probe- Manual BaseScope Duplex (8) Apply Control Probe- Manual BaseScope Duplex filter
  • 1765 (8) Apply 1765 filter
  • 1379 (8) Apply 1379 filter
  • 2184 (8) Apply 2184 filter
  • 38322 (8) Apply 38322 filter
  • Manual Assay 2.5: Pretreatment Reagents (5) Apply Manual Assay 2.5: Pretreatment Reagents filter
  • Controls: Manual Probes (5) Apply Controls: Manual Probes filter
  • Control Probe- Manual RNAscope HiPlex (5) Apply Control Probe- Manual RNAscope HiPlex filter
  • Manual Assay RNAscope Brown (4) Apply Manual Assay RNAscope Brown filter
  • Manual Assay RNAscope Duplex (4) Apply Manual Assay RNAscope Duplex filter
  • Manual Assay RNAscope Multiplex (4) Apply Manual Assay RNAscope Multiplex filter
  • Manual Assay BaseScope Red (4) Apply Manual Assay BaseScope Red filter
  • IA: Other (4) Apply IA: Other filter
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  • Manual Assay miRNAscope Red (4) Apply Manual Assay miRNAscope Red filter
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  • Control Probe - Automated Ventana Duplex (3) Apply Control Probe - Automated Ventana Duplex filter
  • Manual Assay BaseScope Duplex (3) Apply Manual Assay BaseScope Duplex filter
  • Manual Assay RNAscope Red (2) Apply Manual Assay RNAscope Red filter
  • Controls: Control Slides (2) Apply Controls: Control Slides filter
  • Control Probe- Manual BaseScope Singleplex (2) Apply Control Probe- Manual BaseScope Singleplex filter
  • Control Probe - Manual BaseScope™Singleplex (2) Apply Control Probe - Manual BaseScope™Singleplex filter
  • Manual Assay: Accessory Reagent (1) Apply Manual Assay: Accessory Reagent filter
  • Accessory Reagent (1) Apply Accessory Reagent filter
  • Controls: Manual RNAscope Multiplex (1) Apply Controls: Manual RNAscope Multiplex filter
  • IA: HybEZ (1) Apply IA: HybEZ filter
  • Automated Assay BaseScope: LS (1) Apply Automated Assay BaseScope: LS filter
  • Automated Assay BaseScope: VS (1) Apply Automated Assay BaseScope: VS filter
  • Software: RNAscope HiPlex Image Registration (1) Apply Software: RNAscope HiPlex Image Registration filter
  • miRNAscope Automated Assay: Leica System (1) Apply miRNAscope Automated Assay: Leica System filter
  • Automated Assay: VS (1) Apply Automated Assay: VS filter
  • Control Probe - VS BaseScope™Singleplex (1) Apply Control Probe - VS BaseScope™Singleplex filter
  • Controls:2.5VS Probes (1) Apply Controls:2.5VS Probes filter
  • Control Probe - Manual RNAscope Multiplex (1) Apply Control Probe - Manual RNAscope Multiplex filter

Sample Compatibility

  • Cell pellets (49) Apply Cell pellets filter
  • FFPE (41) Apply FFPE filter
  • Fixed frozen tissue (31) Apply Fixed frozen tissue filter
  • TMA (31) Apply TMA filter
  • Adherent cells (26) Apply Adherent cells filter
  • Freshfrozen tissue (18) Apply Freshfrozen tissue filter
  • Fresh frozen tissue (13) Apply Fresh frozen tissue filter
  • Cell Cultures (12) Apply Cell Cultures filter
  • TMA(Tissue Microarray) (9) Apply TMA(Tissue Microarray) filter
  • FFPE,Freshfrozen tissue,Fixed frozen tissue,TMA,Cell pellets,Adherent cells (7) Apply FFPE,Freshfrozen tissue,Fixed frozen tissue,TMA,Cell pellets,Adherent cells filter
  • CTC (4) Apply CTC filter
  • PBMC's (4) Apply PBMC's filter
  • Adherent or Cultured Cells (1) Apply Adherent or Cultured Cells filter
  • Fixed frozen (1) Apply Fixed frozen filter
  • FFPE,TMA (1) Apply FFPE,TMA filter
  • Fixed frozen tissues (for chromogenic assays) (1) Apply Fixed frozen tissues (for chromogenic assays) filter

Category

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Application

  • Cancer (139875) Apply Cancer filter
  • Neuroscience (51010) Apply Neuroscience filter
  • Cancer, Neuroscience (32227) Apply Cancer, Neuroscience filter
  • Non-coding RNA (24365) Apply Non-coding RNA filter
  • Cancer, Inflammation (16436) Apply Cancer, Inflammation filter
  • Cancer, Inflammation, Neuroscience (12591) Apply Cancer, Inflammation, Neuroscience filter
  • Inflammation (9879) Apply Inflammation filter
  • Cancer, Stem Cell (7932) Apply Cancer, Stem Cell filter
  • Cancer, Neuroscience, Stem Cell (7028) Apply Cancer, Neuroscience, Stem Cell filter
  • Cancer, Immunotherapy, Inflammation, Neuroscience, Stem Cell (6854) Apply Cancer, Immunotherapy, Inflammation, Neuroscience, Stem Cell filter
  • Cancer, Inflammation, Neuroscience, Stem Cell (5424) Apply Cancer, Inflammation, Neuroscience, Stem Cell filter
  • Immunotherapy (5368) Apply Immunotherapy filter
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  • Cancer, Immunotherapy, Inflammation (2844) Apply Cancer, Immunotherapy, Inflammation filter
  • Cancer, Immunotherapy, Inflammation, Neuroscience (1878) Apply Cancer, Immunotherapy, Inflammation, Neuroscience filter
  • Cancer, Immunotherapy, Neuroscience (1786) Apply Cancer, Immunotherapy, Neuroscience filter
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Ubiquitin ligase RNF146 coordinates bone dynamics and energy metabolism.

J Clin Invest.

2017 Jun 05

Matsumoto Y, La Rose J, Lim M, Adissu HA, Law N, Mao X, Cong F, Mera P, Karsenty G, Goltzman D, Changoor A, Zhang L, Stajkowski M, Grynpas MD, Bergmann C, Rottapel R.
PMID: 28581440 | DOI: 10.1172/JCI92233

Cleidocranial dysplasia (CCD) is an autosomal dominant human disorder characterized by abnormal bone development that is mainly due to defective intramembranous bone formation by osteoblasts. Here, we describe a mouse strain lacking the E3 ubiquitin ligase RNF146 that shows phenotypic similarities to CCD. Loss of RNF146 stabilized its substrate AXIN1, leading to impairment of WNT3a-induced β-catenin activation and reduced Fgf18 expression in osteoblasts. We show that FGF18 induces transcriptional coactivator with PDZ-binding motif (TAZ) expression, which is required for osteoblast proliferation and differentiation through transcriptional enhancer associate domain (TEAD) and runt-related transcription factor 2 (RUNX2) transcription factors, respectively. Finally, we demonstrate that adipogenesis is enhanced in Rnf146-/- mouse embryonic fibroblasts. Moreover, mice with loss of RNF146 within the osteoblast lineage had increased fat stores and were glucose intolerant with severe osteopenia because of defective osteoblastogenesis and subsequent impaired osteocalcin production. These findings indicate that RNF146 is required to coordinate β-catenin signaling within the osteoblast lineage during embryonic and postnatal bone development.

Changes in serum interleukin-8 (IL-8) levels reflect and predict response to anti-PD-1 treatment in melanoma and non-small cell lung cancer patients.

Ann Oncol.

2017 Jun 08

Sanmamed MF, Perez-Gracia JL, Schalper KA, Fusco JP, Gonzalez A, Rodriguez-Ruiz ME, Oñate C, Perez G, Alfaro C, Martín-Algarra S, Andueza MP, Gurpide A, Morgado M, Wang J, Bacchiocchi A, Halaban R, Kluger H, Chen L, Sznol M, Melero I.
PMID: 28595336 | DOI: 10.1093/annonc/mdx190

Abstract

Background

Surrogate biomarkers of efficacy are needed for anti-PD1/PD-L1 therapy, given the existence of delayed responses and pseudo-progressions. We evaluated changes in serum IL-8 levels as a biomarker of response to anti-PD-1 blockade in melanoma and non-small cell lung cancer (NSCLC) patients.

Patients and methods

Metastatic melanoma and NSCLC patients treated with nivolumab or pembrolizumab alone or nivolumab plus ipilimumab, were studied. Serum was collected at baseline; at 2-4 weeks after the first dose; and at the time-points of response evaluation. Serum IL-8 levels were determined by sandwich ELISA. Changes in serum IL-8 levels were compared with the Wilcoxon test and their strength of association with response was assessed with the Mann-Whitney test. Accuracy of changes in IL-8 levels to predict response was estimated using receiver operation characteristics (ROC) curves.

Results

Twenty-nine melanoma patients treated with nivolumab or pembrolizumab were studied. In responding patients, serum IL-8 levels significantly decreased between baseline and best response (P < .001), and significantly increased upon progression (P = .004). In non-responders, IL-8 levels significantly increased between baseline and progression (P = .013). Early changes in serum IL-8 levels (2-4 weeks after treatment initiation) were strongly associated with response (P < .001). These observations were validated in 19 NSCLC patients treated with nivolumab or pembrolizumab (P = .001), and in 15 melanoma patients treated with nivolumab plus ipilimumab (P < .001). Early decreases in serum IL-8 levels were associated with longer overall survival in melanoma (P = .001) and NSCLC (P = .015) patients. Serum IL-8 levels also correctly reflected true response in 3 cancer patients presenting pseudoprogression.

Conclusions

Changes in serum IL-8 levels could be used to monitor and predict clinical benefit from immune checkpoint blockade in melanoma and NSCLC patients.

Age and gender associations of virus positivity in Merkel cell carcinoma characterized using a novel RNA in situ hybridization assay

Clin Cancer Res.

2017 Jun 12

Wang L, Harms PW, Palanisamy N, Carskadon S, Cao , Siddiqui J, Patel RM, Zelenka-Wang S, Durham AB, Fullen DR, Harms K, Su F, Shukla S, Mehra R, Chinnaiyan AM.
PMID: 28606924 | DOI: 10.1158/1078-0432.CCR-17-0299

Abstract

Purpose: Merkel cell carcinoma (MCC) is a highly aggressive neuroendocrine tumor of the skin. Merkel cell polyomavirus (MCPyV) plays an oncogenic role in the majority of MCCs. Detection of MCPyV in MCCs has diagnostic utility and prognostic potential. We investigated whether RNAscope, an RNA in situ hybridization (ISH) assay for detection of RNA transcripts in tissues, is useful for MCPyV detection. <p>Experimental Design: We applied an RNAscope probe targeting MCPyV T antigen transcripts on tissue microarrays (TMAs) and whole tissue sections encompassing 87 MCCs from 75 patients, 14 carcinomas of other types, and benign tissues. For comparison, quantitative PCR (qPCR) was performed on 57 cases of MCC from 52 patients.   </p> <p>Results: RNA-ISH demonstrated the presence of MCPyV in 37/75 (49.3%) cases. Notably, tumors from younger patients (< 73 years) had a significantly higher virus positivity than those from elderly patients (≥ 73 years) (64.9% vs. 34.2%, P =0.011). Female patients had a higher positive rate of MCPyV than male patients (66.7% vs. 39.6%, P =0.032). Data from both RNA-ISH and qPCR were available for 57 samples. Considering MCPyV qPCR as the gold standard for determining MCPyV status, RNAscope had 100% sensitivity and 100% specificity. There was a strong correlation between qPCR copy number and RNA-ISH product score (Spearman's correlation coefficient R2 = 0.932, P < 0.0001).  </p> <p>Conclusions: RNA-ISH is comparably sensitive to qPCR for detection of MCPyV and allows for correlation with tissue morphology. This study also reveals a significant association between age, gender, and MCPyV positivity.

Kupffer Cell-Derived Tnf Triggers Cholangiocellular Tumorigenesis through JNK due to Chronic Mitochondrial Dysfunction and ROS

Cancer Cell.

2017 Jun 12

Yuan D, Huang S, Berger E, Liu L, Gross N, Heinzmann F, Ringelhan M, Connor TO, Stadler M, Meister M, Weber J, Öllinger R, Simonavicius N, Reisinger F, Hartmann D, Meyer R, Reich M, Seehawer M, Leone V, Höchst B, Wohlleber D, Jörs S, Prinz M, Spalding D,
PMID: 28609656 | DOI: 10.1016/j.ccell.2017.05.006

Intrahepatic cholangiocarcinoma (ICC) is a highly malignant, heterogeneous cancer with poor treatment options. We found that mitochondrial dysfunction and oxidative stress trigger a niche favoring cholangiocellular overgrowth and tumorigenesis. Liver damage, reactive oxygen species (ROS) and paracrine tumor necrosis factor (Tnf) from Kupffer cells caused JNK-mediated cholangiocellular proliferation and oncogenic transformation. Anti-oxidant treatment, Kupffer cell depletion, Tnfr1 deletion, or JNK inhibition reduced cholangiocellular pre-neoplastic lesions. Liver-specific JNK1/2 deletion led to tumor reduction and enhanced survival in Akt/Notch- or p53/Kras-induced ICC models. In human ICC, high Tnf expression near ICC lesions, cholangiocellular JNK-phosphorylation, and ROS accumulation in surrounding hepatocytes are present. Thus, Kupffer cell-derived Tnf favors cholangiocellular proliferation/differentiation and carcinogenesis. Targeting the ROS/Tnf/JNK axis may provide opportunities for ICC therapy.

Sexual dimorphism in the inflammatory response to traumatic brain injury

Glia.

2017 Jun 13

Villapol S, Loane DJ, Burns MP.
PMID: 28608978 | DOI: 10.1002/glia.23171

The activation of resident microglial cells, alongside the infiltration of peripheral macrophages, are key neuroinflammatory responses to traumatic brain injury (TBI) that are directly associated with neuronal death. Sexual disparities in response to TBI have been previously reported; however it is unclear whether a sex difference exists in neuroinflammatory progression after TBI. We exposed male and female mice to moderate-to-severe controlled cortical impact injury and studied glial cell activation in the acute and chronic stages of TBI using immunofluorescence and in situ hybridization analysis. We found that the sex response was completely divergent up to 7 days postinjury. TBI caused a rapid and pronounced cortical microglia/macrophage activation in male mice with a prominent activated phenotype that produced both pro- (IL-1β and TNFα) and anti-inflammatory (Arg1 and TGFβ) cytokines with a single-phase, sustained peak from 1 to 7 days. In contrast, TBI caused a less robust microglia/macrophage phenotype in females with biphasic pro-inflammatory response peaks at 4 h and 7 days, and a delayed anti-inflammatory mRNA peak at 30 days. We further report that female mice were protected against acute cell loss after TBI, with male mice demonstrating enhanced astrogliosis, neuronal death, and increased lesion volume through 7 days post-TBI. Collectively, these findings indicate that TBI leads to a more aggressive neuroinflammatory profile in male compared with female mice during the acute and subacute phases postinjury. Understanding how sex affects the course of neuroinflammation following brain injury is a vital step toward developing personalized and effective treatments for TBI.

Cellular senescence drives age-dependent hepatic steatosis.

Nat Commun.

2017 Jun 13

Ogrodnik M, Miwa S, Tchkonia T, Tiniakos D, Wilson CL, Lahat A, Day CP, Burt A, Palmer A, Anstee QM, Grellscheid SN, Hoeijmakers JHJ, Barnhoorn S, Mann DA, Bird TG, Vermeij WP, Kirkland JL, Passos JF, von Zglinicki T, Jurk D.
PMID: 28608850 | DOI: 10.1038/ncomms15691

The incidence of non-alcoholic fatty liver disease (NAFLD) increases with age. Cellular senescence refers to a state of irreversible cell-cycle arrest combined with the secretion of proinflammatory cytokines and mitochondrial dysfunction. Senescent cells contribute to age-related tissue degeneration. Here we show that the accumulation of senescent cells promotes hepatic fat accumulation and steatosis. We report a close correlation between hepatic fat accumulation and markers of hepatocyte senescence. The elimination of senescent cells by suicide gene-meditated ablation of p16Ink4a-expressing senescent cells in INK-ATTAC mice or by treatment with a combination of the senolytic drugs dasatinib and quercetin (D+Q) reduces overall hepatic steatosis. Conversely, inducing hepatocyte senescence promotes fat accumulation in vitro and in vivo. Mechanistically, we show that mitochondria in senescent cells lose the ability to metabolize fatty acids efficiently. Our study demonstrates that cellular senescence drives hepatic steatosis and elimination of senescent cells may be a novel therapeutic strategy to reduce steatosis.

PD-L2 Expression in Human Tumors: Relevance to Anti-PD-1 Therapy in Cancer

Clin Cancer Res.

2017 Jun 15

Yearley JH, Gibson C, Yu N, Moon C, Murphy E, Juco J, Lunceford J, Cheng J, Chow LQM, Seiwert TY, Handa M, Tomassini JE, McClanahan T.
PMID: 28619999 | DOI: 10.1158/1078-0432.CCR-16-1761

Abstract

Purpose: Tumor-associated PD-L1 expression is predictive of clinical response to PD-1-directed immunotherapy. However, PD-L1-negative patients may also respond to PD-1 checkpoint blockade, suggesting that other PD-1 ligands may be relevant to the clinical activity of these therapies. The prevalence of PD-L2, the other known ligand of PD-1, and its relationship to response to anti-PD-1 therapy were evaluated.Experimental Design: PD-L2 expression was assessed in archival tumor tissue from seven indications using a novel immunohistochemical assay. In addition, relationships between clinical response and PD-L2 status were evaluated in tumor tissues from patients with head and neck squamous cell carcinoma (HNSCC) with recurrent or metastatic disease, treated with pembrolizumab.Results: PD-L2 expression was observed in all tumor types and present in stromal, tumor, and endothelial cells. The prevalence and distribution of PD-L2 correlated significantly with PD-L1 (P = 0.0012-<0.0001); however, PD-L2 was detected in the absence of PD-L1 in some tumor types. Both PD-L1 and PD-L2 positivity significantly predicted clinical response to pembrolizumab on combined tumor, stromal and immune cells, with PD-L2 predictive independent of PD-L1. Response was greater in patients positive for both PD-L1 and PD-L2 (27.5%) than those positive only for PD-L1 (11.4%). PD-L2 status was also a significant predictor of progression-free survival (PFS) with pembrolizumab independent of PD-L1 status. Longer median times for PFS and overall survival were observed for PD-L2-positive than PD-L2-negative patients.Conclusions: Clinical response to pembrolizumab in patients with HNSCC may be related partly to blockade of PD-1/PD-L2 interactions. Therapy targeting both PD-1 ligands may provide clinical benefit in these patients.

Cisplatin Increases Sensitivity to FGFR Inhibition in Patient-Derived Xenograft Models of Lung Squamous Cell Carcinoma.

Mol Cancer Ther.

2017 Jun 13

Weeden CE, Holik AZ, Young RJ, Ma SB, Garnier JM, Fox SB, Antippa P, Irving LB, Steinfort DP, Wright GM, Russell PA, Ritchie ME, Burns CJ, Solomon B, Asselin-Labat ML.
PMID: 28611104 | DOI: 10.1158/1535-7163.MCT-17-0174

Lung squamous cell carcinoma (SqCC) is a molecularly complex and genomically unstable disease. No targeted therapy is currently approved for lung SqCC, although potential oncogenic drivers of SqCC have been identified, including amplification of the fibroblast growth factor receptor 1 (FGFR1). Reports from a recently completed clinical trial indicate low response rates in patients treated with FGFR tyrosine kinase inhibitors, suggesting inadequacy of FGFR1 amplification as a biomarker of response, or the need for combination treatment. We aimed to develop accurate models of lung SqCC and determine improved targeted therapies for these tumors. We show that detection of FGFR1 mRNA by RNA in situ hybridization is a better predictor of response to FGFR inhibition than FGFR1 gene amplification using clinically relevant patient-derived xenograft (PDX) models of lung SqCC. FGFR1-overexpressing tumors were observed in all histologic subtypes of non-small cell lung cancers (NSCLC) as assessed on a tissue microarray, indicating a broader range of tumors that may respond to FGFR inhibitors. In FGFR1-overexpressing PDX tumors, we observed increased differentiation and reduced proliferation following FGFR inhibition. Combination therapy with cisplatin was able to increase tumor cell death, and dramatically prolonged animal survival compared to single-agent treatment. Our data suggest that FGFR tyrosine kinase inhibitors can benefit NSCLC patients with FGFR1-overexpressing tumors and provides a rationale for clinical trials combining cisplatin with FGFR inhibitors.

Both interferon alpha and lambda can reduce all intrahepatic HDV infection markers in HBV/HDV infected humanized mice

Sci Rep.

2017 Jun 16

Giersch K, Homs M, Volz T, Helbig M, Allweiss L, Lohse AW, Petersen J, Buti M, Pollicino T, Sureau C, Dandri M, Lütgehetmann M.
PMID: 28623307 | DOI: 10.1038/s41598-017-03946-9

Co-infection with hepatitis B (HBV) and D virus (HDV) is associated with the most severe course of liver disease. Interferon represents the only treatment currently approved. However, knowledge about the impact of interferons on HDV in human hepatocytes is scant. Aim was to assess the effect of pegylated interferon alpha (peg-IFNα) and lambda (peg-IFNλ), compared to the HBV-polymerase inhibitor entecavir (ETV) on all HDV infection markers using human liver chimeric mice and novel HDV strand-specific qRT-PCR and RNA in situ hybridization assays, which enable intrahepatic detection of HDV RNA species. Peg-IFNα and peg-IFNλ reduced HDV viremia (1.4 log and 1.2 log, respectively) and serum HBsAg levels (0.9-log and 0.4-log, respectively). Intrahepatic quantification of genomic and antigenomic HDV RNAs revealed a median ratio of 22:1 in untreated mice, resembling levels determined in HBV/HDV infected patients. Both IFNs greatly reduced intrahepatic levels of genomic and antigenomic HDV RNA, increasing the amounts of HDAg- and antigenomic RNA-negative hepatocytes. ETV-mediated suppression of HBV replication (2.1-log) did not significantly affect HBsAg levels, HDV productivity and/or release. In humanized mice lacking adaptive immunity, IFNs but not ETV suppressed HDV. Viremia decrease reflected the intrahepatic reduction of all HDV markers, including the antigenomic template, suggesting that intracellular HDV clearance is achievable.

TGFβ pathway limits dedifferentiation following WNT and MAPK pathway activation to suppress intestinal tumourigenesis

Cell Death Differ.

2017 Jun 16

Cammareri P, Vincent DF, Hodder MC, Ridgway RA, Murgia C, Nobis M, Campbell AD, Varga J, Huels DJ, Subramani C, Prescott KLH, Nixon C, Hedley A, Barry ST, Greten FR, Inman GJ, Sansom OJ.
PMID: 28622298 | DOI: 10.1038/cdd.2017.92

Recent studies have suggested increased plasticity of differentiated cells within the intestine to act both as intestinal stem cells (ISCs) and tumour-initiating cells. However, little is known of the processes that regulate this plasticity. Our previous work has shown that activating mutations of Kras or the NF-κB pathway can drive dedifferentiation of intestinal cells lacking Apc. To investigate this process further, we profiled both cells undergoing dedifferentiation in vitro and tumours generated from these cells in vivo by gene expression analysis. Remarkably, no clear differences were observed in the tumours; however, during dedifferentiation in vitro we found a marked upregulation of TGFβ signalling, a pathway commonly mutated in colorectal cancer (CRC). Genetic inactivation of TGFβ type 1 receptor (Tgfbr1/Alk5) enhanced the ability of KrasG12D/+ mutation to drive dedifferentiation and markedly accelerated tumourigenesis. Mechanistically this is associated with a marked activation of MAPK signalling. Tumourigenesis from differentiated compartments is potently inhibited by MEK inhibition. Taken together, we show that tumours arising in differentiated compartments will be exposed to different suppressive signals, for example, TGFβ and blockade of these makes tumourigenesis more efficient from this compartment.

p16 immunohistochemistry in oropharyngeal squamous cell carcinoma: a comparison of antibody clones using patient outcomes and high-risk human papillomavirus RNA status.

Mod Pathol.

2017 Jun 16

Shelton J, Purgina BM, Cipriani NA, Dupont WD, Plummer D, Lewis JS Jr.
PMID: 28621317 | DOI: 10.1038/modpathol.2017.31

High-risk human papillomavirus (HPV)-related oropharyngeal squamous cell carcinomas have a more favorable prognosis than HPV-negative ones. p16 immunohistochemistry has been recommended as a prognostic test in clinical practice. Several p16 antibodies are available, and their performance has not been directly compared. We evaluated three commercially available p16 antibody clones (E6H4, JC8 and G175-405) utilizing 199 cases of oropharyngeal squamous cell carcinoma from a tissue microarray, read by three pathologists with three different cutoffs for positivity: any staining, >50% and >75%. Positive predictive values for high-risk HPV status by RNA in situ hybridization for the E6H4, JC8 and G175-405 clones were 98%, 100% and 99% at the 75% cutoff, but negative predictive values were much more variable at 86%, 69% and 56%, respectively. These improved using the 50% cutoff, becoming similar for all three antibodies. Intensity varied substantially, with 85% of E6H4, 72% of JC8 and 67% of G175-405 showing strong (3+) intensity. With Kaplan-Meier survival plots at the 75% cutoff, the E6H4 clone showed the largest differential in disease specific and overall survival between p16-positive and -negative results. Decreasing the cutoff to 50% increased correlation with HPV in situ hybridization and improved the survival differential for the JC8 and G175-405 clones without worsening of performance for the E6H4 clone. Interobserver agreement was also assessed by kappa scores and was highest for the E6H4 clone. Overall, these study results show modest but important performance differences between the three different p16 antibody clones, suggesting that the E6H4 clone performs best because of strongest staining intensity, greatest differential in outcomes between positive and negative results, lowest interobserver variability, and lowest background, nonspecific staining. The results also suggest that a 75% cutoff is very functional but that, in this patient population with high HPV incidence, 50% and any staining cutoffs may be more effective, particularly for the non-E6H4 clones.

Pro-inflammatory cytokine responses in extra-respiratory tissues during severe influenza

Short KR, Veeris R, Leijten LM, van den Brand JM, Jong VL, Stittelaar K, Osterhaus ADME, Andeweg A, van Riel D.

2017 Jun 16

Short KR, Veeris R, Leijten LM, van den Brand JM, Jong VL, Stittelaar K, Osterhaus ADME, Andeweg A, van Riel D.
PMID: - | DOI: 10.1093/infdis/jix281

Severe influenza is often associated with disease manifestations outside the respiratory tract. Whilst pro-inflammatory cytokines can be detected in the lungs and blood of infected patients, the role of extra-respiratory organs in the production of pro-inflammatory cytokines is unknown. Here, we show that both pandemic H1N1 and highly pathogenic H5N1 virus induce expression of TNFα, IL-6 and IL-8 in the respiratory tract and central nervous system. In addition, H5N1 virus induced cytokines in the heart, pancreas, spleen, liver and jejunum. Together, these data suggest that extra-respiratory tissues contribute to systemic cytokine responses which may increase the severity of influenza.

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Description
sense
Example: Hs-LAG3-sense
Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe.
Intron#
Example: Mm-Htt-intron2
Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection
Pool/Pan
Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G)
A mixture of multiple probe sets targeting multiple genes or transcripts
No-XSp
Example: Hs-PDGFB-No-XMm
Does not cross detect with the species (Sp)
XSp
Example: Rn-Pde9a-XMm
designed to cross detect with the species (Sp)
O#
Example: Mm-Islr-O1
Alternative design targeting different regions of the same transcript or isoforms
CDS
Example: Hs-SLC31A-CDS
Probe targets the protein-coding sequence only
EnEmProbe targets exons n and m
En-EmProbe targets region from exon n to exon m
Retired Nomenclature
tvn
Example: Hs-LEPR-tv1
Designed to target transcript variant n
ORF
Example: Hs-ACVRL1-ORF
Probe targets open reading frame
UTR
Example: Hs-HTT-UTR-C3
Probe targets the untranslated region (non-protein-coding region) only
5UTR
Example: Hs-GNRHR-5UTR
Probe targets the 5' untranslated region only
3UTR
Example: Rn-Npy1r-3UTR
Probe targets the 3' untranslated region only
Pan
Example: Pool
A mixture of multiple probe sets targeting multiple genes or transcripts

Enabling research, drug development (CDx) and diagnostics

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