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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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Smad4 controls signaling robustness and morphogenesis by differentially contributing to the Nodal and BMP pathways

Nature communications

2021 Nov 04

Guglielmi, L;Heliot, C;Kumar, S;Alexandrov, Y;Gori, I;Papaleonidopoulou, F;Barrington, C;East, P;Economou, AD;French, PMW;McGinty, J;Hill, CS;
PMID: 34737283 | DOI: 10.1038/s41467-021-26486-3

The transcriptional effector SMAD4 is a core component of the TGF-β family signaling pathways. However, its role in vertebrate embryo development remains unresolved. To address this, we deleted Smad4 in zebrafish and investigated the consequences of this on signaling by the TGF-β family morphogens, BMPs and Nodal. We demonstrate that in the absence of Smad4, dorsal/ventral embryo patterning is disrupted due to the loss of BMP signaling. However, unexpectedly, Nodal signaling is maintained, but lacks robustness. This Smad4-independent Nodal signaling is sufficient for mesoderm specification, but not for optimal endoderm specification. Furthermore, using Optical Projection Tomography in combination with 3D embryo morphometry, we have generated a BMP morphospace and demonstrate that Smad4 mutants are morphologically indistinguishable from embryos in which BMP signaling has been genetically/pharmacologically perturbed. Smad4 is thus differentially required for signaling by different TGF-β family ligands, which has implications for diseases where Smad4 is mutated or deleted.
Progenitor translatome changes coordinated by Tsc1 increase perception of Wnt signals to end nephrogenesis

Nature communications

2021 Nov 03

Jarmas, AE;Brunskill, EW;Chaturvedi, P;Salomonis, N;Kopan, R;
PMID: 34732708 | DOI: 10.1038/s41467-021-26626-9

Mammalian nephron endowment is determined by the coordinated cessation of nephrogenesis in independent niches. Here we report that translatome analysis in Tsc1+/- nephron progenitor cells from mice with elevated nephron numbers reveals how differential translation of Wnt antagonists over agonists tips the balance between self-renewal and differentiation. Wnt agonists are poorly translated in young niches, resulting in an environment with low R-spondin and high Fgf20 promoting self-renewal. In older niches we find increased translation of Wnt agonists, including R-spondin and the signalosome-promoting Tmem59, and low Fgf20, promoting differentiation. This suggests that the tipping point for nephron progenitor exit from the niche is controlled by the gradual increase in stability and possibly clustering of Wnt/Fzd complexes in individual cells, enhancing the response to ureteric bud-derived Wnt9b inputs and driving synchronized differentiation. As predicted by these findings, removing one Rspo3 allele in nephron progenitors delays cessation and increases nephron numbers in vivo.
The serine proteases dipeptidyl-peptidase 4 and urokinase are key molecules in human and mouse scar formation

Nature communications

2021 Oct 29

Vorstandlechner, V;Laggner, M;Copic, D;Klas, K;Direder, M;Chen, Y;Golabi, B;Haslik, W;Radtke, C;Tschachler, E;Hötzenecker, K;Ankersmit, HJ;Mildner, M;
PMID: 34716325 | DOI: 10.1038/s41467-021-26495-2

Despite recent advances in understanding skin scarring, mechanisms triggering hypertrophic scar formation are still poorly understood. In the present study, we investigate mature human hypertrophic scars and developing scars in mice at single cell resolution. Compared to normal skin, we find significant differences in gene expression in most cell types present in scar tissue. Fibroblasts show the most prominent alterations in gene expression, displaying a distinct fibrotic signature. By comparing genes upregulated in murine fibroblasts during scar development with genes highly expressed in mature human hypertrophic scars, we identify a group of serine proteases, tentatively involved in scar formation. Two of them, dipeptidyl-peptidase 4 (DPP4) and urokinase (PLAU), are further analyzed in functional assays, revealing a role in TGFβ1-mediated myofibroblast differentiation and over-production of components of the extracellular matrix in vitro. Topical treatment with inhibitors of DPP4 and PLAU during scar formation in vivo shows anti-fibrotic activity and improvement of scar quality, most prominently after application of the PLAU inhibitor BC-11. In this study, we delineate the genetic landscape of hypertrophic scars and present insights into mechanisms involved in hypertrophic scar formation. Our data suggest the use of serine protease inhibitors for the treatment of skin fibrosis.
Skin inflammation activates intestinal stromal fibroblasts and promotes colitis

The Journal of clinical investigation

2021 Nov 01

Dokoshi, T;Seidman, JS;Cavagnero, KJ;Li, F;Liggins, MC;Taylor, BC;Olvera, J;Knight, R;Chang, JT;Salzman, NH;Gallo, RL;
PMID: 34720087 | DOI: 10.1172/JCI147614

Inflammatory disorders of the skin are frequently associated with inflammatory bowel diseases (IBDs). To explore mechanisms by which these organs communicate, we performed single-cell RNA-Seq analysis on fibroblasts from humans and mice with IBD. This analysis revealed that intestinal inflammation promoted differentiation of a subset of intestinal stromal fibroblasts into preadipocytes with innate antimicrobial host defense activity. Furthermore, this process of reactive adipogenesis was exacerbated if mouse skin was inflamed as a result of skin wounding or infection. Since hyaluronan (HA) catabolism is activated during skin injury and fibroblast-to-adipocyte differentiation is dependent on HA, we tested the hypothesis that HA fragments could alter colon fibroblast function by targeted expression of human hyaluronidase-1 in basal keratinocytes from mouse skin. Hyaluronidase expression in the skin activated intestinal stromal fibroblasts, altered the fecal microbiome, and promoted excessive reactive adipogenesis and increased inflammation in the colon after challenge with dextran sodium sulfate. The response to digested HA was dependent on expression of TLR4 by preadipocytes. Collectively, these results suggest that the association between skin inflammation and IBD may be due to recognition by mesenchymal fibroblasts in the colon of HA released during inflammation of the skin.
CCR5 antagonist reduces HIV-induced amyloidogenesis, tau pathology, neurodegeneration, and blood-brain barrier alterations in HIV-infected hu-PBL-NSG mice

Molecular neurodegeneration

2021 Nov 22

Bhargavan, B;Woollard, SM;McMillan, JE;Kanmogne, GD;
PMID: 34809709 | DOI: 10.1186/s13024-021-00500-0

Neurocognitive impairment is present in 50% of HIV-infected individuals and is often associated with Alzheimer's Disease (AD)-like brain pathologies, including increased amyloid-beta (Aβ) and Tau hyperphosphorylation. Here, we aimed to determine whether HIV-1 infection causes AD-like pathologies in an HIV/AIDS humanized mouse model, and whether the CCR5 antagonist maraviroc alters HIV-induced pathologies.NOD/scid-IL-2Rγcnull mice engrafted with human blood leukocytes were infected with HIV-1, left untreated or treated with maraviroc (120 mg/kg twice/day). Human cells in animal's blood were quantified weekly by flow cytometry. Animals were sacrificed at week-3 post-infection; blood and tissues viral loads were quantified using p24 antigen ELISA, RNAscope, and qPCR. Human (HLA-DR+) cells, Aβ-42, phospho-Tau, neuronal markers (MAP 2, NeuN, neurofilament-L), gamma-secretase activating protein (GSAP), and blood-brain barrier (BBB) tight junction (TJ) proteins expression and transcription were quantified in brain tissues by immunohistochemistry, immunofluorescence, immunoblotting, and qPCR. Plasma Aβ-42, Aβ-42 cellular uptake, release and transendothelial transport were quantified by ELISA.HIV-1 significantly decreased human (h)CD4+ T-cells and hCD4/hCD8 ratios; decreased the expression of BBB TJ proteins claudin-5, ZO-1, ZO-2; and increased HLA-DR+ cells in brain tissues. Significantly, HIV-infected animals showed increased plasma and brain Aβ-42 and phospho-Tau (threonine181, threonine231, serine396, serine199), associated with transcriptional upregulation of GSAP, an enzyme that catalyzes Aβ formation, and loss of MAP 2, NeuN, and neurofilament-L. Maraviroc treatment significantly reduced blood and brain viral loads, prevented HIV-induced loss of neuronal markers and TJ proteins; decreased HLA-DR+ cells infiltration in brain tissues, significantly reduced HIV-induced increase in Aβ-42, GSAP, and phospho-Tau. Maraviroc also reduced Aβ retention and increased Aβ release in human macrophages; decreased the receptor for advanced glycation end products (RAGE) and increased low-density lipoprotein receptor-related protein-1 (LRP1) expression in human brain endothelial cells. Maraviroc induced Aβ transendothelial transport, which was blocked by LRP1 antagonist but not RAGE antagonist.Maraviroc significantly reduced HIV-induced amyloidogenesis, GSAP, phospho-Tau, neurodegeneration, BBB alterations, and leukocytes infiltration into the CNS. Maraviroc increased cellular Aβ efflux and transendothelial Aβ transport via LRP1 pathways. Thus, therapeutically targeting CCR5 could reduce viremia, preserve the BBB and neurons, increased brain Aβ efflux, and reduce AD-like neuropathologies.
Psilocybin targets a common molecular mechanism for cognitive impairment and increased craving in alcoholism

Science advances

2021 Nov 19

Meinhardt, MW;Pfarr, S;Fouquet, G;Rohleder, C;Meinhardt, ML;Barroso-Flores, J;Hoffmann, R;Jeanblanc, J;Paul, E;Wagner, K;Hansson, AC;Köhr, G;Meier, N;von Bohlen Und Halbach, O;Bell, RL;Endepols, H;Neumaier, B;Schönig, K;Bartsch, D;Naassila, M;Spanagel, R;Sommer, WH;
PMID: 34788104 | DOI: 10.1126/sciadv.abh2399

[Figure: see text].
Lef1 restricts ectopic crypt formation and tumor cell growth in intestinal adenomas

Science advances

2021 Nov 19

Heino, S;Fang, S;Lähde, M;Högström, J;Nassiri, S;Campbell, A;Flanagan, D;Raven, A;Hodder, M;Nasreddin, N;Xue, HH;Delorenzi, M;Leedham, S;Petrova, TV;Sansom, O;Alitalo, K;
PMID: 34788095 | DOI: 10.1126/sciadv.abj0512

[Figure: see text].
REV-ERB nuclear receptors in the suprachiasmatic nucleus control circadian period and restrict diet-induced obesity

Science advances

2021 Oct 29

Adlanmerini, M;Krusen, BM;Nguyen, HCB;Teng, CW;Woodie, LN;Tackenberg, MC;Geisler, CE;Gaisinsky, J;Peed, LC;Carpenter, BJ;Hayes, MR;Lazar, MA;
PMID: 34705514 | DOI: 10.1126/sciadv.abh2007

[Figure: see text].
928 A translational approach to catalog pancreatic cancer heterogeneity using spatial genomics in large patient cohorts for target validation and rational combination selection

Journal for ImmunoTherapy of Cancer

2021 Nov 01

Jabado, O;Fan, L;Souza, P;Harris, A;Chaparro, A;Qutaish, M;Si, H;Dannenberg, J;Sasser, K;Couto, S;Fereshteh, M;
| DOI: 10.1136/jitc-2021-sitc2021.928

BackgroundPancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with short overall survival; the standard of care (SoC) is chemotherapy. Immunotherapies in development aim to remodel the stroma by depleting immunosuppressive cell types or using T-cell redirection to kill tumor cells. To date, none of these methods have improved overall survival beyond SoC. Next generation immunotherapies that employ histopathology and molecular subtyping1 for target and patient selection may succeed. Here we leverage a spatial transcriptomics platform (Nanostring Digital Spatial Profiling, DSP) to reveal molecular signaling in tumoral and stromal cells in 57 PDAC patients using tumor microarrays (TMAs). This approach is rapid and clinically relevant as molecular and histology data can be easily bridged.MethodsTMAs generated from surgical resection tissue were commercially sourced. DSP was performed using the CTA RNA panel (1,800 target genes) using PanCK fluorescence for tumor/stroma segmentation. In parallel, slides were chromogenically stained for T-cells (CD3) and macrophages (CD68/CD163). Differential gene expression, gene signature and gene co-expression network analysis was performed using linear models in R.2 3ResultsDifferential gene expression analysis and correlation to IHC confirmed the DSP platform successfully profiled tumor and stromal compartments (figure 1). Immune cell signatures4 and pathway analysis revealed a heterogenous stromal environment. Using a fibroblast gene signature derived from single-cell RNAseq5 we found fibroblast density was positively correlated to PDGFR signaling and MHC-II expression but negatively correlated to B, CD4+ T and neutrophil cell levels (figure 2a). This finding supports the idea that atypical antigen presentation in cancer associated fibroblasts (CAFs) may be exploitable for immunotherapies.6 We constructed a co-expression network from in-situ stromal gene expression and used it to identify receptors coordinately expressed with the immunosuppressive macrophage marker CSF1R as a bispecific antibody partner (figure 2b).7 Classical macrophage markers were identified but also receptors with lesser-known functions in macrophages (TIM3/HAVCR2, FPR3, MS4A6A, LILRB4). Surveying target pairs in this method allows rapid, patient-specific confirmation in serial TMA sections with singleplex IHC or RNAscope.Abstact 928 Figure 1Segmentation strategy and validation of DSP (A) PanCK, CD68 and CD3 staining from two representative tumor cores; (B, C) correlation of gene transcripts in stroma to cell counts from chromogenic staining; (D) heatmap of selected genes differentially expressed in tumor and stroma (n=57 patients).Abstract 928 Figure 2Exploration of the stromal compartment in PDAC TMAs. (A) Heatmap of selected cell type and gene signatures from gene expression in the stroma, color represents single sample enrichment score using GSVA method; (B) a gene co-expression subnetwork in the stroma centered on CSF1R, edge thickness represents strength of correlation, green nodes have evidence for cell surface expression based on proteomic profiling.7ConclusionsIn this study we were able to recapitulate known PDAC biology using very small samples of primary tumors. The combination of TMAs and DSP enables a rapid validation of targets and hypothesis generation for bispecific parings. Further analysis of untreated (n=14) and post-adjuvant chemotherapy (n=26) patients using RNA DSP, IHC and bulk RNAseq is under way. Results from this cohort will enable an integrated histopathology and molecular approach to developing next-generation immunotherapies.ReferencesCollisson EA, Bailey P, Chang DK, Biankin AV. Molecular subtypes of pancreatic cancer. Nat Rev Gastroenterol Hepatol 2019 April;16(4):207-220.Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015). “limma powers differential expression analyses for RNA-sequencing and microarray studies.” Nucleic Acids Research 43(7):e47.Hänzelmann S, Castelo R, Guinney J (2013). “GSVA: gene set variation analysis for microarray and RNA-Seq data.” BMC Bioinformatics 14,7.Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, Hackl H, Trajanoski Z. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep 2017 January 3;18(1):248-262.Tirosh I, Izar B, Prakadan SM, Wadsworth MH 2nd, Treacy D, Trombetta JJ, Rotem A, Rodman C, Lian C, Murphy G, Fallahi-Sichani M, Dutton-Regester K, Lin JR, Cohen O, Shah P, Lu D, Genshaft AS, Hughes TK, Ziegler CG, Kazer SW, Gaillard A, Kolb KE, Villani AC, Johannessen CM, Andreev AY, Van Allen EM, Bertagnolli M, Sorger PK, Sullivan RJ, Flaherty KT, Frederick DT, Jané-Valbuena J, Yoon CH, Rozenblatt-Rosen O, Shalek AK, Regev A, Garraway LA. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 2016 April 8;352(6282):189-96.Elyada E, Bolisetty M, Laise P, Flynn WF, Courtois ET, Burkhart RA, Teinor JA, Belleau P, Biffi G, Lucito MS, Sivajothi S, Armstrong TD, Engle DD, Yu KH, Hao Y, Wolfgang CL, Park Y, Preall J, Jaffee EM, Califano A, Robson P, Tuveson DA. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. Cancer Discov 2019 August;9(8):1102-1123. Bausch-Fluck D, Hofmann A, Bock T, Frei AP, Cerciello F, Jacobs A, Moest H, Omasits U, Gundry RL, Yoon C, Schiess R, Schmidt A, Mirkowska P, Härtlová A, Van Eyk JE, Bourquin JP, Aebersold R, Boheler KR, Zandstra P, Wollscheid B. A mass spectrometric-derived cell surface protein atlas. PLoS One 2015 April 20;10(3):e0121314.Ethics ApprovalSpecimens were harvested from unused tissue after a surgical tumor resection procedure. A discrete legal consent form from both hospital and individuals was obtained by the commercial tissue vendor BioMax US for all samples analyzed in this abstract. All human tissues are collected under HIPPA approved protocols.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.
93 Computational biology and tissue-based approaches to inform indication selection for a novel AHR inhibitor

Journal for ImmunoTherapy of Cancer

2021 Nov 01

Sanchez-Martin, M;Wang, L;Ecsedy, J;Mcgovern, K;Zhang, M;
| DOI: 10.1136/jitc-2021-sitc2021.093

BackgroundAryl Hydrocarbon Receptor (AHR) is a ligand-activated transcription factor that regulates the activities of multiple innate and adaptive immune cell types. Multiple ligands such as kynurenine bind to AHR driving its nuclear translocation and transcriptional activation, leading to an immunosuppressive tumor microenvironment.1 2 AHR activation is implicated in tumor development in multiple cancer types. In addition, high levels of serum kynurenine are associated with resistance to checkpoint inhibitors.3 To overcome AHR-mediated immunosuppression in cancers, we developed a selective oral AHR inhibitor IK-175 and took a combined computational and tissue-based approach to select cancer indications for its clinical development.MethodsThe aim of this work is to identify tumor indications dependent on AHR signaling and design patient selection strategies based on a proprietary transcriptional signature, mRNA and protein detection assays to evaluate AHR pathway activation in tumors.ResultsGenomic profiling of solid and hematological cancers from TCGA and Project GENIE databases identified bladder and esophageal tumors among others, as frequently harboring AHR gene amplifications.A proprietary gene signature of AHR activation was developed integrating literature, pathway analysis, RNAseq and nanostring data from PBMC, T-cells and cell lines upon AHR inhibition. Transcriptional analysis of the TCGA data using this signature demonstrated bladder cancer has the highest expressions of AHR and AHR signature genes, suggesting increased pathway activity in bladder cancer relative to other cancer types. Increased AHR signature gene expression was associated with worse overall survival in the TCGA bladder cancer cohort. Furthermore, RNAscope analysis of a tissue microarray containing 10 different tumor types revealed bladder cancer had one of the highest AHR transcript expression in the tumor compartment.Finally, nuclear localization of AHR protein was assessed as an indicator of pathway activation through the development of a novel IHC method. Extensive TMA screening of AHR protein in 15 different indications demonstrated bladder cancer as the tumor type with the highest prevalence of AHR nuclear expression.ConclusionsIn summary, we demonstrated high prevalence of nuclear AHR protein expression, AHR gene amplification and target gene expression in bladder cancer, suggesting aberrant AHR activation may play an important role in the progression of this tumor type. This study provides rationale for therapeutic targeting of AHR in bladder cancer patients. Ikena is currently evaluating the anti-tumor activity of IK-175 as a single agent and in combination with nivolumab in bladder cancer in a Phase 1a/1b clinical study (NCT04200963).ReferencesQuintana FJ, Sherr DH. Aryl hydrocarbon receptor control of adaptive immunity. Pharmacol Rev 2013 Aug 1;65(4):1148-61.Murray IA, Patterson AD, Perdew GH. Aryl hydrocarbon receptor ligands in cancer: friend and foe. Nat Rev Cancer 2014 Dec;14(12):801-14.Li, Haoxin et al. ‘Metabolomic adaptations and correlates of survival to immune checkpoint blockade.’ Nature Communications 2019 Sep 25;10:1-4346.
92 Single cell and spatial multiplex profiling of immune cell markers in FFPE tumor tissues using the novel RNAscope HiPlex v2 in situ hybridization assay

Journal for ImmunoTherapy of Cancer

2021 Nov 01

Basak, S;Dikshit, A;Yu, M;Ji, H;Chang, C;Zhang, B;
| DOI: 10.1136/jitc-2021-sitc2021.092

BackgroundThe tumor microenvironment (TME) is highly complex, comprised of tumor cells, immune cells, stromal cells, and extracellular matrix. Understanding spatial interactions between various cell types and their activation states in the TME is crucial for implementing successful immunotherapy strategies against various types of cancer. This study demonstrates a highly sensitive and specific multiplexed technique, the RNAscope HiPlex v2 in situ hybridization (ISH) assay for spatial and transcriptomic profiling of target genes to assess immune regulation in human lung, breast, cervical and ovarian FFPE tumor tissues.MethodsWe have expanded our current RNAscope HiPlex assay capability of iteratively multiplexing up to 12 targets in fixed and fresh frozen samples to include formalin fixed paraffin embedded (FFPE) tissues. The novel FFPE reagent effectively reduces background autofluorescence, improving the signal to noise ratio. We have leveraged this technology to investigate spatial expression of 12 oncology and immuno-oncology target genes, including tumor markers, immune checkpoint markers, immunosuppression markers, immune cell markers and secreted chemokine RNA expression profile within the TME. The targets were simultaneously registered using HiPlex image registration software v2 that enables background subtraction.ResultsWe visualized T cell infiltration and identified T cell subsets within tumors using CD3and CD8 expression and activated T cells by IFNG expression. We further identified subsets of pro- and anti-inflammatory macrophages by CD68 and CD163 expression as well effector cells which secrete chemokines and cytokine. We also detected the hypoxia markers HIF1A and VEGF to elucidate the immunosuppressive state of tumor cells. Preliminary analysis and quantification of the HIF1A expression using HALO image analysis software showed higher copy numbers in the lung tumor as compared to the other tumors, demonstrating the sensitivity of the assay through differential expression. We additionally showed the differential expression of immune checkpoint markers PDCD1, and CD274 within the TME.ConclusionsUsing a highly sensitive multiplexed RNAscope HiPlex v2 ISH assay, we have demonstrated the capability of this technique to spatially resolve 12 targets in four different tumor types. The FFPE reagent efficiently quenched background autofluorescence in the tissues and identified immune cell signatures within the TME. Quantification of immunosuppressive markers further depicted a differential expression among various tumors. This technology is highly beneficial for investigating complex and spatial tumor-stroma interactions in basic science and translational research. The assay can also provide valuable understanding of the biological crosstalk among various cell types in complex and heterogeneous tissues.
Dopamine neurons exhibit emergent glutamatergic identity in Parkinson's disease

Brain

2021 Sep 30

Steinkellner, T;Conrad, WS;Kovacs, I;Rissman, RA;
| DOI: 10.1093/brain/awab373

Loss of midbrain dopamine neurons causes the cardinal symptoms of Parkinson’s disease. However, not all dopamine neurons are equally vulnerable and a better understanding of the cell-type specific properties relating to selective dopamine neuron degeneration is needed. Most midbrain dopamine neurons express the vesicular glutamate transporter VGLUT2 during development and a subset continue to express low levels of VGLUT2 in adulthood, enabling the co-release of glutamate. Moreover, VGLUT2 expression in dopamine neurons can be neuroprotective since its genetic disruption was shown to sensitize dopamine neurons to neurotoxins. Here, we show that in response to toxic insult, and in two distinct models of alpha-synuclein stress, VGLUT2 dopamine neurons were resilient to degeneration. Dopamine neurons expressing VGLUT2 were enriched whether or not insult induced dopamine neuron loss, suggesting that while VGLUT2 dopamine neurons are more resilient, VGLUT2 expression can also be transcriptionally upregulated by injury. Finally, we observed that VGLUT2 expression was enhanced in surviving DA neurons from postmortem Parkinson’s disease subjects. These data indicate that emergence of a glutamatergic identity in dopamine neurons may be part of a neuroprotective response in Parkinson’s disease.

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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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For career opportunities: hr.ACD@bio-techne.com

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