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
J Clin Invest. 2019 Jan 7.
2019 Jan 07
MacFarlane EG, Parker SJ, Shin JY, Ziegler SG, Creamer TJ, Bagirzadeh R, Bedja D, Chen Y, Calderon JF, Weissler K, Frischmeyer-Guerrerio PA, Lindsay ME, Habashi JP, Dietz HC.
PMID: 30614814 | DOI: 10.1172/JCI123547
Nat Commun. 2018 Nov 30;9(1):5083.
2018 Nov 30
Pinho AV, Van Bulck M, Chantrill L, Arshi M, Sklyarova T, Herrmann D, Vennin C, Gallego-Ortega D, Mawson A, Giry-Laterriere M, Magenau A, Leuckx G, Baeyens L, Gill AJ, Phillips P, Timpson P, Biankin AV, Wu J, Rooman I.
PMID: 30504844 | DOI: 10.1038/s41467-018-07497-z
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.
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
J Am Coll Cardiol. 2015 Apr 7;65(13):1324-36.
Bertoli-Avella AM, Gillis E, Morisaki H, Verhagen JM, de Graaf BM, van de Beek G, Gallo E, Kruithof BP, Venselaar H, Myers LA, Laga S, Doyle AJ, Oswald G, van Cappellen GW, Yamanaka I, van der Helm RM, Beverloo B, de Klein A, Pardo L, Lammens M, Evers C,
PMID: 25835445 | DOI: 10.1016/j.jacc.2015.01.040.
BACKGROUND: Aneurysms affecting the aorta are a common condition associated with high mortality as a result of aortic dissection or rupture. Investigations of the pathogenic mechanisms involved in syndromic types of thoracic aortic aneurysms, such as Marfan and Loeys-Dietz syndromes, have revealed an important contribution of disturbed transforming growth factor (TGF)-β signaling. OBJECTIVES: This study sought to discover a novel gene causing syndromic aortic aneurysms in order to unravel the underlying pathogenesis. METHODS: We combined genome-wide linkage analysis, exome sequencing, and candidate gene Sanger sequencing in a total of 470 index cases with thoracic aortic aneurysms. Extensive cardiological examination, including physical examination, electrocardiography, and transthoracic echocardiography was performed. In adults, imaging of the entire aorta using computed tomography or magnetic resonance imaging was done. RESULTS: Here, we report on 43 patients from 11 families with syndromic presentations of aortic aneurysms caused by TGFB3 mutations. We demonstrate that TGFB3 mutations are associated with significant cardiovascular involvement, including thoracic/abdominal aortic aneurysm and dissection, and mitral valve disease. Other systemic features overlap clinically with Loeys-Dietz, Shprintzen-Goldberg, and Marfan syndromes, including cleft palate, bifid uvula, skeletal overgrowth, cervical spine instability and clubfoot deformity. In line with previous observations in aortic wall tissues of patients with mutations in effectors of TGF-β signaling (TGFBR1/2, SMAD3, and TGFB2), we confirm a paradoxical up-regulation of both canonical and noncanonical TGF-β signaling in association with up-regulation of the expression of TGF-β ligands. CONCLUSIONS: Our findings emphasize the broad clinical variability associated with TGFB3 mutations and highlight the importance of early recognition of the disease because of high cardiovascular risk.
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.
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
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 | |
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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