ACD can configure probes for the various manual and automated assays for INS for RNAscope Assay, or for Basescope Assay compatible for your species of interest.
The Journal of clinical investigation
2021 Dec 14
Yadav, VK;Berger, JM;Singh, P;Nagarajan, P;Karsenty, G;
PMID: 34905510 | DOI: 10.1172/JCI153752
Molecular metabolism
2022 Jun 09
Zhang, L;Koller, J;Gopalasingam, G;Qi, Y;Herzog, H;
PMID: 35691527 | DOI: 10.1016/j.molmet.2022.101525
Molecular Metabolism
2018 Apr 03
Egerod KL, Petersen N ,Timshel PN, Rekling JC, Wang Y, Liu Q, Schwartz TW, Gautron L.
PMID: - | DOI: 10.1016/j.molmet.2018.03.016
Abstract
Objectives
G protein-coupled receptors (GPCRs) act as transmembrane molecular sensors of neurotransmitters, hormones, nutrients, and metabolites. Because unmyelinated vagalafferents richly innervate the gastrointestinal mucosa, gut-derived molecules may directly modulate the activity of vagal afferents through GPCRs. However, the types of GPCRs expressed in vagal afferents are largely unknown. Here, we determined the expression profile of all GPCRs expressed in vagal afferents of the mouse, with a special emphasis on those innervating the gastrointestinal tract.
Methods
Using a combination of high-throughput quantitative PCR, RNA sequencing, and in situhybridization, we systematically quantified GPCRs expressed in vagal unmyelinated Nav1.8-expressing afferents.
Results
GPCRs for gut hormones that were the most enriched in Nav1.8-expressing vagal unmyelinated afferents included NTSR1, NPY2R, CCK1R, and to a lesser extent, GLP1R, but not GHSR and GIPR. Interestingly, both GLP1R and NPY2R were coexpressed with CCK1R. In contrast, NTSR1 was coexpressed with GPR65, a marker preferentially enriched in intestinal mucosal afferents. Only few microbiome-derived metabolite sensors such as GPR35 and, to a lesser extent, GPR119 and CaSR were identified in the Nav1.8-expressing vagal afferents. GPCRs involved in lipid sensing and inflammation (e.g. CB1R, CYSLTR2, PTGER4), and neurotransmitters signaling (CHRM4, DRD2, CRHR2) were also highly enriched in Nav1.8-expressing neurons. Finally, we identified 21 orphan GPCRs with unknown functions in vagal afferents.
Conclusion
Overall, this study provides a comprehensive description of GPCR-dependent sensing mechanisms in vagal afferents, including novel coexpression patterns, and conceivably coaction of key receptors for gut-derived molecules involved in gut-brain communication.
Human molecular genetics
2022 Aug 11
Bando, H;Brinkmeier, ML;Castinetti, F;Fang, Q;Lee, MS;Saveanu, A;Albarel, F;Dupuis, C;Brue, T;Camper, SA;
PMID: 35951005 | DOI: 10.1093/hmg/ddac192
Nature communications
2021 Nov 03
Jarmas, AE;Brunskill, EW;Chaturvedi, P;Salomonis, N;Kopan, R;
PMID: 34732708 | DOI: 10.1038/s41467-021-26626-9
Cellular and molecular gastroenterology and hepatology
2021 Dec 29
Kim, TY;Kim, S;Kim, Y;Lee, YS;Lee, S;Lee, SH;Kweon, MN;
PMID: 34971821 | DOI: 10.1016/j.jcmgh.2021.12.015
Clin Cancer Res.
2019 Apr 19
Piskol R, Huw LY, Sergin I, Klijn C, Modrusan Z, Kim D, Kljavin NM, Tam R, Patel R, Burton J, Penuel E, Qu X, Koeppen H, Sumiyoshi T, de Sauvage FJ, Lackner MR, de Sousa E Melo F, Kabbarah O.
PMID: 31004000 | DOI: 10.1158/1078-0432.CCR-18-3032
Abstract
PURPOSE:
Four consensus molecular subtypes (CMS1-4) of colorectal cancer (CRC) were identified in primary tumors and found to be associated with distinctive biological features and clinical outcomes. Given that distant metastasis largely accounts for CRC-related mortality, we examined the molecular and clinical attributes of CMS in metastatic CRC (mCRC).
EXPERIMENTAL DESIGN:
We developed a CRC-focused Nanostring based CMS classifier that is ideally suited to interrogate archival tissues. We successfully employ this panel in the CMS classification of FFPE tissues from mCRC cohorts, one of which is comprised of paired primary tumors and metastases. Finally, we developed novel mouse implantation models to enable modelling of CRC in vivo at relevant sites.
RESULTS:
Using our classifier we find that the biological hallmarks of mCRC, including CMS, are in general highly similar to those observed in non-metastatic early stage disease. Importantly, our data demonstrate that CMS1 has the worst outcome in relapsed disease, compared to other CMS. Assigning CMS to primary tumors and their matched metastases revealed mostly concordant subtypes between primary and metastasis. Molecular analysis of matched discordant pairs revealed differences in stromal composition at each site. The development of two novel in vivo orthotopic implantation models further reinforces the notion that extrinsic factors may impact on CMS identification in matched primary and metastatic CRC.
CONCLUSION:
We describe the utility of a Nanostring panel for CMS classification of FFPE clinical samples. Our work reveals the impact of intrinsic and extrinsic factors on CRC heterogeneity during disease progression.
Cell.
2017 Jul 27
Nectow AR, Schneeberger M, Zhang H, Field BC, Renier N, Azevedo E, Patel B, Liang Y, Mitra S, Tessier-Lavigne M, Han MH, Friedman JM.
PMID: 28753423 | DOI: 10.1016/j.cell.2017.06.045
Hunger, driven by negative energy balance, elicits the search for and consumption of food. While this response is in part mediated by neurons in the hypothalamus, the role of specific cell types in other brain regions is less well defined. Here, we show that neurons in the dorsal raphe nucleus, expressing vesicular transporters for GABA or glutamate (hereafter, DRNVgat and DRNVGLUT3 neurons), are reciprocally activated by changes in energy balance and that modulating their activity has opposite effects on feeding-DRNVgat neurons increase, whereas DRNVGLUT3 neurons suppress, food intake. Furthermore, modulation of these neurons in obese (ob/ob) mice suppresses food intake and body weight and normalizes locomotor activity. Finally, using molecular profiling, we identify druggable targets in these neurons and show that local infusion of agonists for specific receptors on these neurons has potent effects on feeding. These data establish the DRN as an important node controlling energy balance. PAPERCLIP.
Development (Cambridge, England)
2021 May 15
Kaiser, K;Jang, A;Kompanikova, P;Lun, MP;Prochazka, J;Machon, O;Dani, N;Prochazkova, M;Laurent, B;Gyllborg, D;van Amerongen, R;Fame, RM;Gupta, S;Wu, F;Barker, RA;Bukova, I;Sedlacek, R;Kozmik, Z;Arenas, E;Lehtinen, MK;Bryja, V;
PMID: 34032267 | DOI: 10.1242/dev.192054
Developmental biology
2021 Nov 06
Bertozzi, A;Wu, CC;Hans, S;Brand, M;Weidinger, G;
PMID: 34748730 | DOI: 10.1016/j.ydbio.2021.11.001
Nature (2015)
Wang B, Zhao L, Fish M, Logan CY, Nusse R.
PMID: 26245375 | DOI: 10.1038/nature14863
Cancer Res.
2019 Mar 01
El Ayachi I, Fatima I, Wend P, Alva-Ornelas JA, Runke S, Kuenzinger WL, Silva J, Silva W, Gray JK, Lehr S, Barch HC, Krutilina RI, White AC, Cardiff R, Yee LD, Yang L, O'Regan RM, Lowry WE, Seagroves TN, Seewaldt V, Krum SA, Miranda-Carboni GA.
PMID: 30563890 | DOI: 10.1158/0008-5472.CAN-18-1069
Triple-negative breast cancer (TNBC) commonly develops resistance to chemotherapy, yet markers predictive of chemoresistance in this disease are lacking. Here, we define WNT10B-dependent biomarkers for β-CATENIN/HMGA2/EZH2 signaling predictive of reduced relapse-free survival. Concordant expression of HMGA2 and EZH2 proteins is observed in MMTV-Wnt10bLacZ transgenic mice during metastasis, and Hmga2 haploinsufficiency decreased EZH2 protein expression, repressing lung metastasis. A novel autoregulatory loop interdependent on HMGA2 and EZH2 expression is essential for β-CATENIN/TCF-4/LEF-1 transcription. Mechanistically, both HMGA2 and EZH2 displaced Groucho/TLE1 from TCF-4 and served as gatekeepers for K49 acetylation on β-CATENIN, which is essential for transcription. In addition, we discovered that HMGA2-EZH2 interacts with the PRC2 complex. Absence of HMGA2 or EZH2 expression or chemical inhibition of Wnt signaling in a chemoresistant patient-derived xenograft (PDX) model of TNBC abolished visceral metastasis, repressing AXIN2, MYC, EZH2, and HMGA2 expression in vivo. Combinatorial therapy of a WNT inhibitor with doxorubicin synergistically activated apoptosis in vitro, resensitized PDX-derived cells to doxorubicin, and repressed lung metastasis in vivo. We propose that targeting the WNT10B biomarker network will provide improved outcomes for TNBC. SIGNIFICANCE: These findings reveal targeting the WNT signaling pathway as a potential therapeutic strategy in triple-negative breast cancer.
Description | ||
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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 | |
EnEm | Probe targets exons n and m | |
En-Em | Probe 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 |
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