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.
Appl Immunohistochem Mol Morphol.
2017 Sep 29
Gafeer MM, Hosny Mohammed K, Ormenisan-Gherasim C, Choudhary F, Siddiqui MT, Cohen C.
PMID: 28968265 | DOI: 10.1097/PAI.0000000000000595
Abstract
BACKGROUND:
Programmed death receptor and programmed death ligand (PD-L1) are immunoregulatory proteins. Nonsmall cell lung cancer bypasses the immune system through the induction of protumorigenic immunosuppressive changes. The better understanding of immunology and antitumor immune responses has brought the promising development of novel immunotherapy agents like programmed death receptor checkpoint inhibitors. The aim of this study was to investigate the expression of PD-L1 in lung adenocarcinoma (ADC), comparing 2 different technologies: immunohistochemistry (IHC) by 2 methods versus RNA in situ hybridization (RISH).
METHODOLOGY:
In total, 20 cases of ADC of the lung and 4 samples of metastatic colon ADC were selected. Evaluation of PD-L1 expression was performed by IHC and RISH. RISH was performed using RNAscope. Both methods were scored in tumor cells and quantified using combined intensity and proportion scores.
RESULTS:
Eight of 20 (40%) lung ADC and 2 of 4 (50%) colon ADC were positive for PD-L1 with Cell Signaling IHC, and 65% lung ADC were positive by Dako IHC (13/20). All 4 cases of colon ADC were negative. When evaluated by RISH, 12 lung ADC (60%) and 1 colon ADC (25%) were PD-L1 positive.
CONCLUSIONS:
RNAscope probes provide sensitive and specific detection of PD-L1 in lung ADC. Both IHC methods (Cell Signaling and Dako) show PD-L1 expression, with the Dako method more sensitive (40% vs. 65%). This study illustrates the utility of RISH and Cell Signaling IHC as complementary diagnostic tests, and Food and Drug Administration approved Dako IHC as a companion diagnostic test.
Cell Rep
2020 Apr 28
Erwin SR, Sun W, Copeland M, Lindo S, Spruston N, Cembrowski MS
PMID: 32348756 | DOI: 10.1016/j.celrep.2020.107551
bioRxiv : the preprint server for biology
2023 Feb 08
Hughes, AC;Pollard, BG;Xu, B;Gammons, JW;Chapman, P;Bikoff, JB;Schwarz, LA;
PMID: 36798174 | DOI: 10.1101/2023.02.07.527312
Nature communications
2023 Jan 03
Liau, ES;Jin, S;Chen, YC;Liu, WS;Calon, M;Nedelec, S;Nie, Q;Chen, JA;
PMID: 36596814 | DOI: 10.1038/s41467-022-35574-x
Neuron
2022 Mar 10
Ayloo, S;Lazo, CG;Sun, S;Zhang, W;Cui, B;Gu, C;
PMID: 35294899 | DOI: 10.1016/j.neuron.2022.02.017
Cell research
2021 Nov 30
Liu, Z;Le, Q;Lv, Y;Chen, X;Cui, J;Zhou, Y;Cheng, D;Ma, C;Su, X;Xiao, L;Yang, R;Zhang, J;Ma, L;Liu, X;
PMID: 34848869 | DOI: 10.1038/s41422-021-00588-5
Neuron.
2017 Jan 31
François A, Low SA, Sypek EI, Christensen AJ, Sotoudeh C, Beier KT, Ramakrishnan C, Ritola KD, Sharif-Naeini R, Deisseroth K, Delp SL, Malenka RC, Luo L, Hantman AW, Scherrer G.
PMID: 28162807 | DOI: 10.1016/j.neuron.2017.01.008
Pain thresholds are, in part, set as a function of emotional and internal states by descending modulation of nociceptive transmission in the spinal cord. Neurons of the rostral ventromedial medulla (RVM) are thought to critically contribute to this process; however, the neural circuits and synaptic mechanisms by which distinct populations of RVM neurons facilitate or diminish pain remain elusive. Here we used in vivo opto/chemogenetic manipulations and trans-synaptic tracing of genetically identified dorsal horn and RVM neurons to uncover an RVM-spinal cord-primary afferent circuit controlling pain thresholds. Unexpectedly, we found that RVM GABAergic neurons facilitate mechanical pain by inhibiting dorsal horn enkephalinergic/GABAergic interneurons. We further demonstrate that these interneurons gate sensory inputs and control pain through temporally coordinated enkephalin- and GABA-mediated presynaptic inhibition of somatosensory neurons. Our results uncover a descending disynaptic inhibitory circuit that facilitates mechanical pain, is engaged during stress, and could be targeted to establish higher pain thresholds.
Neuron.
2017 Mar 22
Kim J, Zhang X, Muralidhar S, LeBlanc SA, Tonegawa S.
PMID: 28334609 | DOI: 10.1016/j.neuron.2017.02.034
Basolateral amygdala (BLA) principal cells are capable of driving and antagonizing behaviors of opposing valence. BLA neurons project to the central amygdala (CeA), which also participates in negative and positive behaviors. However, the CeA has primarily been studied as the site for negative behaviors, and the causal role for CeA circuits underlying appetitive behaviors is poorly understood. Here, we identify several genetically distinct populations of CeA neurons that mediate appetitive behaviors and dissect the BLA-to-CeA circuit for appetitive behaviors. Protein phosphatase 1 regulatory subunit 1B+ BLA pyramidal neurons to dopamine receptor 1+ CeA neurons define a pathway for promoting appetitive behaviors, while R-spondin 2+ BLA pyramidal neurons to dopamine receptor 2+ CeA neurons define a pathway for suppressing appetitive behaviors. These data reveal genetically defined neural circuits in the amygdala that promote and suppress appetitive behaviors analogous to the direct and indirect pathways of the basal ganglia.
JCI Insight
2020 Feb 27
Celik M�, Labuz D, Keye J, Glauben R, Machelska H
PMID: 32102987 | DOI: 10.1172/jci.insight.133093
Nature genetics
2021 Apr 08
Kameneva, P;Artemov, AV;Kastriti, ME;Faure, L;Olsen, TK;Otte, J;Erickson, A;Semsch, B;Andersson, ER;Ratz, M;Frisén, J;Tischler, AS;de Krijger, RR;Bouderlique, T;Akkuratova, N;Vorontsova, M;Gusev, O;Fried, K;Sundström, E;Mei, S;Kogner, P;Baryawno, N;Kharchenko, PV;Adameyko, I;
PMID: 33833454 | DOI: 10.1038/s41588-021-00818-x
Developmental cell
2023 Jan 19
Rodrigo Albors, A;Singer, GA;Llorens-Bobadilla, E;Frisén, J;May, AP;Ponting, CP;Storey, KG;
PMID: 36706756 | DOI: 10.1016/j.devcel.2023.01.003
Oncotarget.
2018 Jan 02
Soo RA, Lim JSY, Asuncion BR, Fazreen Z, Herrera MC, Omar MFM, Phuong NHD, Seet JE, Amanuel B, Iacopetta B, Byrne D, Hendry S, Fox S, Soong R.
PMID: - | DOI: 10.18632/oncotarget.23827
Programmed death ligand-1 (PD-L1) expression as determined by immunohistochemistry (IHC) is potentially predictive of clinical outcome. The aim of this study was to assess the concordance of reported PD-L1 IHC assays and investigate factors influencing variability. Consecutive sections from 20 non-small cell lung cancers (NSCLCs) comprising resection, core biopsy, cytology and pleural fluid samples underwent IHC with 5 different antibody/autostainer combinations: 22C3/Link48, 28-8/BOND-MAX, E1L3N/BOND-MAX, SP142/BenchMark and SP263/BenchMark. PD-L1 RNA levels were assessed using RNAscope. The frequency of positive cases using scoring thresholds from clinical trials was 72%, 33%, 61%, 56%, and 33% for the 5 IHC protocols respectively, and 33% for RNAscope. Pairwise agreement on the classification of cases as positive or negative for PD-L1 expression ranged from 61%-94%. On a continuous scale, the lowest correlation was between 28-8/BOND-MAX and SP142/BenchMark (R2=0.25) and highest was between 22C3/Link48 and E1L3N/BOND-MAX (R2=0.71). When cases were ordered according to tumor cell (TC)%, a similar ranking of cases across IHC protocols could be observed, albeit with different quanta and limits of detection. Single-slide OPAL 7-color fluorescence IHC analysis revealed a high degree of co-localization of staining from the 5 PD-L1 antibodies. Using SP142 antibody in a BOND-MAX protocol led to increased TC% quanta, while retaining a similar ranking of samples according to TC%. The results of this study highlight tumor PD-L1 status can vary significantly according to IHC protocol. Protocol-dependent staining intensities and nominated thresholds for positivity contribute to this variability, while the antibody used appears to be less of a factor.
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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