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.
Human Pathology
2016 Apr 08
Gupta M, Babic A, Beck AH, Terry K.
PMID: - | DOI: 10.1016/j.humpath.2016.03.006
Inflammatory cytokines, like tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6), are elevated in ovarian cancer. Differences in cytokine expression by histologic subytpe or ovarian cancer risk factors can provide useful insight into ovarian cancer risk and etiology. We used ribonucleic acid (RNA) in-situ hybridization to assess TNF-α and IL-6 expression on tissue microarray slides from 78 epithelial ovarian carcinomas (51 serous, 12 endometrioid, 7 clear cell, 2 mucinous, 6 other) from a population-based case control study. Cytokine expression was scored semi-quantitatively and odds ratios (OR) and 95% confidence intervals (CI) were calculated using polytomous logistic regression. TNF-α was expressed in 46% of the tumors while sparse IL-6 expression was seen only 18% of the tumors. For both markers, expression was most common in high grade serous carcinomas followed by endometrioid carcinomas. Parity was associated with a reduced risk of TNF-α positive (OR = 0.3, 95% CI: 0.1-0.7 for 3 or more children versus none) but not TNF-α negative tumors (p-heterogeneity = 0.02). In contrast, current smoking was associated with a nearly three fold increase in risk of TNF-α negative (OR = 2.8, 95% CI: 1.2, 6.6) but not TNF-α positive tumors (p-heterogeneity = 0.06). Our data suggests that TNF-α expression in ovarian carcinoma varies by histologic subtype and provides some support for the role of inflammation in ovarian carcinogenesis. The novel associations detected in our study need to be validated in a larger cohort of patients in future studies.
Sci Transl Med.
2016 Apr 13
Balko JM, Schwarz LJ, Luo N, Estrada MV, Giltnane JM, Dávila-González D, Wang K, Sánchez V, Dean PT, Combs SE, Hicks D, Pinto JA, Landis MD, Doimi FD, Yelensky R, Miller VA, Stephens PJ, Rimm DL, Gómez H, Chang JC, Sanders ME, Cook RS, Arteaga CL.
PMID: 27075627 | DOI: 10.1126/scitranslmed.aad3001
Amplifications at 9p24 have been identified in breast cancer and other malignancies, but the genes within this locus causally associated with oncogenicity or tumor progression remain unclear. Targeted next-generation sequencing of postchemotherapy triple-negative breast cancers (TNBCs) identified a group of 9p24-amplified tumors, which contained focal amplification of the Janus kinase 2 (JAK2) gene. These patients had markedly inferior recurrence-free and overall survival compared to patients with TNBC withoutJAK2amplification. Detection ofJAK2/9p24 amplifications was more common in chemotherapy-treated TNBCs than in untreated TNBCs or basal-like cancers, or in other breast cancer subtypes. Similar rates ofJAK2amplification were confirmed in patient-derived TNBC xenografts. In patients for whom longitudinal specimens were available,JAK2amplification was selected for during neoadjuvant chemotherapy and eventual metastatic spread, suggesting a role in tumorigenicity and chemoresistance, phenotypes often attributed to a cancer stem cell-like cell population. In TNBC cell lines withJAK2copy gains or amplification, specific inhibition of JAK2 signaling reduced mammosphere formation and cooperated with chemotherapy in reducing tumor growth in vivo. In these cells, inhibition of JAK1-signal transducer and activator of transcription 3 (STAT3) signaling had little effect or, in some cases, counteracted JAK2-specific inhibition. Collectively, these results suggest that JAK2-specific inhibitors are more efficacious than dual JAK1/2 inhibitors against JAK2-amplified TNBCs. Furthermore,JAK2amplification is a potential biomarker for JAK2 dependence, which, in turn, can be used to select patients for clinical trials with JAK2 inhibitors.
Nature communications
2022 Sep 17
Lee, SH;Kim, N;Kim, M;Woo, SH;Han, I;Park, J;Kim, K;Park, KS;Kim, K;Shim, D;Park, SE;Zhang, JY;Go, DM;Kim, DY;Yoon, WK;Lee, SP;Chung, J;Kim, KW;Park, JH;Lee, SH;Lee, S;Ann, SJ;Lee, SH;Ahn, HS;Jeong, SC;Kim, TK;Oh, GT;Park, WY;Lee, HO;Choi, JH;
PMID: 36115863 | DOI: 10.1038/s41467-022-33202-2
Nat Med.
2018 Sep 17
Zanconato F, Battilana G, Forcato M, Filippi L, Azzolin L, Manfrin A, Quaranta E, Di Biagio D, Sigismondo G, Guzzardo V, Lejeune P, Haendler B, Krijgsveld J, Fassan M, Bicciato S, Cordenonsi M, Piccolo S.
PMID: 30224758 | DOI: 10.1038/s41591-018-0158-8
Cancer cells rely on dysregulated gene expression. This establishes specific transcriptional addictions that may be therapeutically exploited. Yet, the mechanisms that are ultimately responsible for these addictions are poorly understood. Here, we investigated the transcriptional dependencies of transformed cells to the transcription factors YAP and TAZ. YAP/TAZ physically engage the general coactivator bromodomain-containing protein 4 (BRD4), dictating the genome-wide association of BRD4 to chromatin. YAP/TAZ flag a large set of enhancers with super-enhancer-like functional properties. YAP/TAZ-bound enhancers mediate the recruitment of BRD4 and RNA polymerase II at YAP/TAZ-regulated promoters, boosting the expression of a host of growth-regulating genes. Treatment with small-molecule inhibitors of BRD4 blunts YAP/TAZ pro-tumorigenic activity in several cell or tissue contexts, causes the regression of pre-established, YAP/TAZ-addicted neoplastic lesions and reverts drug resistance. This work sheds light on essential mediators, mechanisms and genome-wide regulatory elements that are responsible for transcriptional addiction in cancer and lays the groundwork for a rational use of BET inhibitors according to YAP/TAZ biology.
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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