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.
Anticancer Res.
2017 Mar 01
Ahn SY, Kim J, Kim MA, Choi J, Kim WH.
PMID: 28314274 | DOI: -
Cell discovery
2023 Feb 14
Yu, B;Zhang, Q;Lin, L;Zhou, X;Ma, W;Wen, S;Li, C;Wang, W;Wu, Q;Wang, X;Li, XM;
PMID: 36788214 | DOI: 10.1038/s41421-022-00506-y
Cell Metabolism
2018 Aug 30
Apicella M, Giannoni E, Fiore S, Ferrari KJ, Fernández-Pérez D, Isella C, Granchi C, Minutolo F, Sottile A, Comoglio PM, Medico E, Pietrantonio F, Volante M, Pasini D, Chiarugi P, Giordano S, Corso S.
PMID: - | DOI: 10.1016/j.cmet.2018.08.006
The microenvironment influences cancer drug response and sustains resistance to therapies targeting receptor-tyrosine kinases. However, if and how the tumor microenvironment can be altered during treatment, contributing to resistance onset, is not known. We show that, under prolonged treatment with tyrosine kinase inhibitors (TKIs), EGFR- or MET-addicted cancer cells displayed a metabolic shift toward increased glycolysis and lactate production. We identified secreted lactate as the key molecule instructing cancer-associated fibroblasts to produce hepatocyte growth factor (HGF) in a nuclear factor κB-dependent manner. Increased HGF, activating MET-dependent signaling in cancer cells, sustained resistance to TKIs. Functional or pharmacological targeting of molecules involved in the lactate axis abrogated in vivo resistance, demonstrating the crucial role of this metabolite in the adaptive process. This adaptive resistance mechanism was observed in lung cancer patients progressed on EGFR TKIs, demonstrating the clinical relevance of our findings and opening novel scenarios in the challenge to drug resistance.
J Clin Invest.
2018 Jul 12
Wang C, Reyes de Mochel NS, Christenson SA, Cassandras M, Moon R, Brumwell AN, Byrnes LE, Li A, Yokosaki Y, Shan P, Sneddon JB, Jablons D, Lee PJ, Matthay MA, Chapman HA, Peng T.
PMID: 29999500 | DOI: 10.1172/JCI99435
Genome-wide association studies have repeatedly mapped susceptibility loci for emphysema to genes that modify hedgehog signaling, but the functional relevance of hedgehog signaling to this morbid disease remains unclear. In the current study, we identified a broad population of mesenchymal cells in the adult murine lung receptive to hedgehog signaling, characterized by higher activation of hedgehog surrounding the proximal airway relative to the distal alveoli. Single cell RNA-sequencing showed that the hedgehog-receptive mesenchyme is composed of mostly fibroblasts with distinct proximal and distal subsets with discrete identities. Ectopic hedgehog activation in the distal fibroblasts promoted expression of proximal fibroblast markers, and promoted loss of distal alveoli and airspace enlargement of over twenty percent compared to controls. We found that hedgehog suppressed mesenchymal-derived mitogens enriched in distal fibroblasts that regulate alveolar stem cell regeneration and airspace size. Finally, single cell analysis of the human lung mesenchyme showed that segregated proximal-distal identity with preferential hedgehog activation in the proximal fibroblasts is conserved between mice and humans. In conclusion, we showed that differential hedgehog activation segregates mesenchymal identities of distinct fibroblast subsets, and disruption of fibroblast identity can alter the alveolar stem cell niche leading to emphysematous changes in the murine lung.
J Clin Oncol.
2016 Dec 05
Cloughesy T, Finocchiaro G, Belda-Iniesta C, Recht L, Brandes AA, Pineda E, Mikkelsen T, Chinot OL, Balana C, Macdonald DR, Westphal M, Hopkins K, Weller M, Bais C, Sandmann T, Bruey JM, Koeppen H, Liu B, Verret W, Phan SC, Shames DS.
PMID: 27918718 | DOI: -
Purpose Bevacizumab regimens are approved for the treatment of recurrent glioblastoma in many countries. Aberrant mesenchymal-epithelial transition factor (MET) expression has been reported in glioblastoma and may contribute to bevacizumab resistance. The phase II study GO27819 investigated the monovalent MET inhibitor onartuzumab plus bevacizumab (Ona + Bev) versus placebo plus bevacizumab (Pla + Bev) in recurrent glioblastoma. Methods At first recurrence after chemoradiation, bevacizumab-naïve patients with glioblastoma were randomly assigned 1:1 to receive Ona (15 mg/kg, once every 3 weeks) + Bev (15 mg/kg, once every 3 weeks) or Pla + Bev until disease progression. The primary end point was progression-free survival by response assessment in neuro-oncology criteria. Secondary end points were overall survival, objective response rate, duration of response, and safety. Exploratory biomarker analyses correlated efficacy with expression levels of MET ligand hepatocyte growth factor, O6-methylguanine-DNA methyltransferase promoter methylation, and glioblastoma subtype. Results Among 129 patients enrolled (Ona + Bev, n = 64; Pla + Bev, n = 65), baseline characteristics were balanced. The median progression-free survival was 3.9 months for Ona + Bev versus 2.9 months for Pla + Bev (hazard ratio, 1.06; 95% CI, 0.72 to 1.56; P = .7444). The median overall survival was 8.8 months for Ona + Bev and 12.6 months for Pla + Bev (hazard ratio, 1.45; 95% CI, 0.88 to 2.37; P = .1389). Grade ≥ 3 adverse events were reported in 38.5% of patients who received Ona + Bev and 35.9% of patients who received Pla + Bev. Exploratory biomarker analyses suggested that patients with high expression of hepatocyte growth factor or unmethylated O6-methylguanine-DNA methyltransferase may benefit from Ona + Bev. Conclusion There was no evidence of further clinical benefit with the addition of onartuzumab to bevacizumab compared with bevacizumab plus placebo in unselected patients with recurrent glioblastoma in this phase II study; however, further investigation into biomarker subgroups is warranted.
Nature communications
2022 Jul 18
Igarashi, N;Miyata, K;Loo, TM;Chiba, M;Hanyu, A;Nishio, M;Kawasaki, H;Zheng, H;Toyokuni, S;Kon, S;Moriyama, K;Fujita, Y;Takahashi, A;
PMID: 35851277 | DOI: 10.1038/s41467-022-31642-4
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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