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Probes for INS

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.

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TNF-α expression, risk factors, and inflammatory exposures in ovarian cancer: evidence for an inflammatory pathway of ovarian carcinogenesis?

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.

Co-Detection of miR-21 and TNF-α mRNA in Budding Cancer Cells in Colorectal Cancer.

Int J Mol Sci.

2019 Apr 17

Møller T, James JP, Holmstrøm K, Sørensen FB, Lindebjerg J, Nielsen BS.
PMID: 30999696 | DOI: 10.3390/ijms20081907

MicroRNA-21 (miR-21) is upregulated in many cancers including colon cancers and is a prognostic indicator of recurrence and poor prognosis. In colon cancers, miR-21 is highly expressed in stromal fibroblastic cells and more weakly in a subset of cancer cells, particularly budding cancer cells. Exploration of the expression of inflammatory markers in colon cancers revealed tumor necrosis factor alpha (TNF-α) mRNA expression at the invasive front of colon cancers. Surprisingly, a majority of the TNF-α mRNA expressing cells were found to be cancer cells and not inflammatory cells. Because miR-21 is positively involved in cell survival and TNF-α promotes necrosis, we found it interesting to analyze the presence of miR-21 in areas of TNF-α mRNA expression at the invasive front of colon cancers. For this purpose, we developed an automated procedure for the co-staining of miR-21, TNF-α mRNA and the cancer cell marker cytokeratin based on analysis of frozen colon cancer tissue samples (n = 4) with evident cancer cell budding. In all four cases, TNF-α mRNA was seen in a small subset of cancer cells at the invasive front. Evaluation of miR-21 and TNF-α mRNA expression was performed on digital slides obtained by confocal slide scanning microscopy. Both co-expression and lack of co-expression with miR-21 in the budding cancer cells was noted, suggesting non-correlated expression. miR-21 was more often seen in cancer cells than TNF-α mRNA. In conclusion, we report that miR-21 is not linked to expression of the pro-inflammatory cytokine TNF-α mRNA, but that miR-21 and TNF-α both take part in the cancer expansion at the invasive front of colon cancers. We hypothesize that miR-21 may protect both fibroblasts and cancer cells from cell death directed by TNF-α paracrine and autocrine activity.

Tissue-resident memory T cells in immune-related adverse events: friend or foe?

Oncoimmunology

2023 Apr 04

Reschke, R;Gajewski, TF;
PMID: 37035636 | DOI: 10.1080/2162402X.2023.2197358

Many cancer patients experience toxicity during checkpoint blockade immunotherapy, which often leads to treatment discontinuation. To this end, understanding the mechanisms mediating immune-related adverse events (irAE) should ultimately enable improvement in clinical outcomes. Recent work has revealed that tissue-resident memory T (TRM) cells are locally expanded in irAE-dermatitis and -colitis.
TNF-α-producing macrophages determine subtype identity and prognosis via AP1 enhancer reprogramming in pancreatic cancer

Nature Cancer

2021 Nov 01

Tu, M;Klein, L;Espinet, E;Georgomanolis, T;Wegwitz, F;Li, X;Urbach, L;Danieli-Mackay, A;Küffer, S;Bojarczuk, K;Mizi, A;Günesdogan, U;Chapuy, B;Gu, Z;Neesse, A;Kishore, U;Ströbel, P;Hessmann, E;Hahn, S;Trumpp, A;Papantonis, A;Ellenrieder, V;Singh, S;
| DOI: 10.1038/s43018-021-00258-w

A,B, Expression correlation analysis in 78 PDAC patient tumors12 [/articles/s43018-021-00258-w#ref-CR12] (E-MTAB-6134 [http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-6134/]) with high tumor cellularity between cJUN and VIM (A) as well as GATA6 and VIM (B). RMA-normalized probe intensity values were plotted. A linear regression with 95% CI is shown in orange. Pearson’s correlation (_R_) and corresponding two-tailed _P_ value are indicated. C, Representative bright-field images of GCDX62 cells transduced with empty vector (EV) or cJUN overexpression (cJUN-OE) constructs. Morphology was monitored over several passages. D-F, RNA-seq analysis was performed on GCDX62 cells transduced with EV or cJUN-OE. n = 3 independent cultures. D, PCA plot. E,F, Enrichment plots for gene set enrichment analysis between cJUN-OE and EV samples for ‘classical’ and ‘quasi-mesenchymal’ PDAC13 [/articles/s43018-021-00258-w#ref-CR13] (E), as well as the top genes up- and downregulated following TNFα treatment in CLA (CAPAN1) cells (F). G, WB for indicated targets in CAPAN1 cells transduced with EV or cJUN-OE. Representative of n = 3 independent experiments. H, Representative bright-field images of CAPAN1 cells transduced with EV or cJUN-OE. Morphology was monitored over several passages. C,H, Scale bar: 200 µm. I,J, Trans-well invasion assay of CAPAN1 cells transduced with EV or cJUN-OE, showing representative DAPI staining of invaded cells (I) as well as quantification thereof (J). I, Scale bar: 100 µm. J, Data given as average counts per F.o.V., with means ± s.d. Unpaired, two-tailed Student’s t-test. n = 3 independent experiments. K-M, Mean cell viability ± s.d. at different concentrations of gemcitabine (K), oxaliplatin (L) and SN38 (M) in CAPAN1 cells transduced with EV or cJUN-OE. IC50 values for each drug are indicated. n = 3 independent experiments.
Two FOXP3+CD4+ T cell subpopulations distinctly control the prognosis of colorectal cancers

Nat Med.

2016 May 25

Saito T, Nishikawa H, Wada H, Nagano Y, Sugiyama D, Atarashi K, Maeda Y, Hamaguchi M, Ohkura N, Sato E, Nagase H, Nishimura J, Yamamoto H, Takiguchi S, Tanoue T, Suda W, Morita H, Hattori M, Honda K, Mori M, Doki Y, Sakaguchi S.
PMID: 27111280 | DOI: 10.1038/nm.4086

CD4+ T cells that express the forkhead box P3 (FOXP3) transcription factor function as regulatory T (Treg) cells and hinder effective immune responses against cancer cells. Abundant Treg cell infiltration into tumors is associated with poor clinical outcomes in various types of cancers. However, the role of Treg cells is controversial in colorectal cancers (CRCs), in which FOXP3+ T cell infiltration indicated better prognosis in some studies. Here we show that CRCs, which are commonly infiltrated by suppression-competent FOXP3hi Treg cells, can be classified into two types by the degree of additional infiltration of FOXP3lo nonsuppressive T cells. The latter, which are distinguished from FOXP3+ Treg cells by non-expression of the naive T cell marker CD45RA and instability of FOXP3, secreted inflammatory cytokines. Indeed, CRCs with abundant infiltration of FOXP3lo T cells showed significantly better prognosis than those with predominantly FOXP3hi Treg cell infiltration. Development of such inflammatory FOXP3lonon-Treg cells may depend on secretion of interleukin (IL)-12 and transforming growth factor (TGF)-β by tissues and their presence was correlated with tumor invasion by intestinal bacteria, especially Fusobacterium nucleatum. Thus, functionally distinct subpopulations of tumor-infiltrating FOXP3+ T cells contribute in opposing ways to determining CRC prognosis. Depletion of FOXP3hi Treg cells from tumor tissues, which would augment antitumor immunity, could thus be used as an effective treatment strategy for CRCs and other cancers, whereas strategies that locally increase the population of FOXP3lo non-Treg cells could be used to suppress or prevent tumor formation.

X
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
EnEmProbe targets exons n and m
En-EmProbe 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

Enabling research, drug development (CDx) and diagnostics

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