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Cancer Inflammation & Immunity Crosstalk PCR Array人癌症炎症反应和免疫交互作用PCR芯片 The Human Cancer Inflammation & Immunity Crosstalk RT² Profiler PCR Array profiles the expression of 84 key genes involved in mediating communication between tumor cells and the cellular mediators of inflammation and immunity. In addition to epithelial and stromal compartments, the tumor microenvironment contains several cell types of the innate and adaptive immune systems including B and T lymphocytes, dendritic cells, and macrophages. In response to tumor-associated antigens presented via MHC Class I molecules, or to abnormal molecular patterns recognized by Toll-like receptors, the immune system eliminates target cells using a variety of effector enzymes and the engagement of pro-apoptotic signals including TRAIL and FAS ligand. If normal homeostasis is not resolved quickly, a state of chronic inflammation can ensue, including locally increased levels of reactive oxygen and nitrogen species that promote genomic instability. Immune cells produce a variety of cytokines that coordinate the inflammatory response, which is fueled by positive feedback loops commonly involving the STAT and NFκB signaling pathways in tumor cells. The resulting upregulation of antiapoptotic and immunosuppressive factors enables transformed cells to proliferate unchecked by the immune system. During cancer progression, the repertoire of chemokines, cytokines, and growth factors that orchestrates normal immune responses can be commandeered to create an immunosuppressive state that facilitates invasion and metastasis. The genes profiled with this array include mediators and effectors of the cross-talk between tumors and the immune system that influences the course of cancer progression. A set of controls present on each array enables data analysis using the ΔΔCT method of relative quantification as well as assessment of reverse transcription performance, genomic DNA contamination, and PCR performance. Using real-time PCR, researchers can easily and reliably analyze the expression of a focused panel of genes involved in cancer inflammation and immune crosstalk with this array.
人癌症炎症反应和免疫交互作用PCR芯片研究参与调节炎症反应和免疫过程中肿瘤细胞和细胞介质之间的通讯的84关键基因的表达。除了上皮和基质隔间，肿瘤微环境包含几个先天和适应性免疫系统的细胞类型包括B和T淋巴细胞、树突状细胞和巨噬细胞。通过MHC I型分子应答肿瘤相关抗原呈现或toll样受体识别异常分子模式中,免疫系统使用各种效应酶和参与促凋亡信号的衔接包括TRAIL和FAS配体消除靶细胞。如果不迅速解决正常的体内平衡，慢性炎症状态就会接踵而至,包括原地提高活性氧水平和氮种类促进基因组不稳定。免疫细胞产生多种细胞因子协调炎性反应 ,被正反馈循环刺激通常涉及在肿瘤细胞中的STAT和NFκB信号通路。上调抗凋亡和免疫抑制因子结果使转化细胞增殖不被免疫系统检测。癌症恶化期,趋化因子组分,细胞因子和协调正常免疫反应的生长因子,可被招募来创建一个免疫抑制状态,促进入侵和转移。这个芯片的基因包括肿瘤和影响癌症恶化进程的免疫系统之间交互作用的介质和效应器。每张芯片含一个对照组使得分析数据时可以用相对定量ΔΔCT方法评估逆转录效率,基因组DNA污染,和PCR效率。利用这张芯片，通过实时定量PCR，可以简易且可靠地分析癌症炎症和免疫反应交互作用的关键基因的表达。
PCR芯片仅用于分子生物学应用。本产品不用于疾病的诊断、预防和治疗。
提供96孔板——384 -(4 x 96)板,和100孔板
Immune & Inflammatory Responses:
Immunostimulatory Factors:IFNG, IL2, IL12A, IL12B, IL15, TNF.
Immunosuppressive Factors:CD274 (PD-L1), CSF2 (GM-CSF), CTLA4, CXCL12 (SDF1), CXCL5, IDO1 (IDO), IL10, IL13, IL4, IL8, MIF, NOS2 (iNOS), PDCD1 (PD1), PTGS2 (COX2), TGFB1, VEGFA.
Pro-Inflammatory Genes:CCL2 (MCP-1), CCL20 (MIP-3A), IFNG, IL1A, IL1B, IL2, IL6, IL12A, IL12B, IL17A, IL23A, PTGS2 (COX2), TLR4, TNF, VEGFA.
Anti-Inflammatory Genes:IL4, IL10, IL13, TGFB1.
Enzymatic Modulators of Inflammation & Immunity:AICDA (AID), GZMA, GZMB, IDO1 (IDO), NOS2 (iNOS), PTGS2 (COX2).
Antigen Presentation:HLA-A, HLA-B, HLA-C, MICA, MICB.
Chemokines:CCL2 (MCP-1), CCL4 (MIP-1B), CCL5 (RANTES), CCL18 (PARC), CCL20 (MIP-3A), CCL21, CCL22 (MDC), CCL28, CXCL1, CXCL2, CXCL5, CXCL9 (MIG), CXCL10 (IP-10), CXCL11 (I-TAC, IP-9), CXCL12 (SDF1).
Chemokine Receptors:ACKR3 (CXCR7), CCR1, CCR2, CCR4, CCR7, CCR9, CCR10, CXCR1 (IL8RA), CXCR2 (IL8RB), CXCR3, CXCR4, CXCR5.
Interleukins:IL1A, IL1B, IL2, IL4, IL6, IL8, IL10, IL12A, IL12B, IL13, IL15, IL17A, IL23A.
Other Cytokines:KITLG (SCF), MIF, SPP1, TNF, TNFSF10 (TRAIL).
Growth Factors & Receptors:CSF1 (MCSF), CSF2 (GM-CSF), CSF3 (GCSF), EGF, EGFR, IGF1, TGFB1, VEGFA.
Signal Transduction:
Interferon Signaling:GBP1, IFNG, IL6, IRF1.
Interferon-Responsive Genes:CCL2 (MCP-1), CCL5 (RANTES), CXCL9 (MIG), CXCL10 (IP-10), GBP1, IRF1, MYD88, STAT1, TLR3, TNFSF10 (TRAIL).
NFκB Targets:BCL2L1 (BCL-XL), CCL2 (MCP-1), CCL5 (RANTES), CSF1 (MCSF), CSF2 (GM-CSF), CSF3 (GCSF), IFNG, IL8, TNF.
STAT Targets:CCL2 (MCP-1), CCL4 (MIP-1B), CCL5 (RANTES), CSF1 (MCSF), CSF2 (GM-CSF), CSF3 (GCSF), CXCL9 (MIG), CXCL10 (IP-10), CXCL11 (I-TAC, IP-9), CXCL12 (SDF1), IL1B, IL6, IL8, IL10, IL17A, IL23A, MYC.
Toll-Like Receptor Signaling:TLR2, TLR3, TLR4, MYD88.
Transcription Factors:FOXP3, HIF1A, IRF1, MYC, NFKB1, STAT1, STAT3, TP53 (p53).Apoptosis:
Pro-Apoptotic: FASLG (TNFSF6), TNF, TNFSF10 (TRAIL), TP53 (p53).
Anti-Apoptotic: BCL2, BCL2L1 (BCL-XL), MYC, STAT3.
How it Works The PCR array is a set of optimized real-time PCR primer assays on 96-well or 384-well plates for pathway or disease focused genes as well as appropriate RNA quality controls. The PCR array performs gene expression analysis with real-time PCR sensitivity and the multi-gene profiling capability of a microarray. Simply mix your cDNA template with the appropriate ready-to-use PCR master mix, aliquot equal volumes to each well of the same plate, and then run the real-time PCR cycling program. (Download user manual) 
| Figure 1: | How PCR Arrays Work - Protocol Chart |
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What it offers?
Guaranteed Performance* - ready-to-use for gene expression analysis
Time and cost saving - less than 30 min hands-on time for analyzing 84 genes
Ease of data analysis using our easy-to-use Excel-based data analysis template or web-based analysis tool Layout and Controls: The PCR Arrays are available in both 96- and 384-well plates and are used to monitor the expression of 84 genes related to a disease state or pathway plus five housekeeping genes. Controls are also included on each array for genomic DNA contamination, RNA quality, and general PCR performance You can easily perform a PCR Array experiment in your own laboratory, or send your samples to us and take advantage of our PCR Array Services. *: when using complete PCR array system. Performance Data Sensitivity:
The complete PCR Array System yields a greater-than 85 percent present call with as little as 25 ng as much as 5 µg of total RNA from a pathway representing genes expressed at a lower level (inflammatory cytokines and receptors). 
| Figure 2: | PCR Arrays Let You See More Genes with Less RNA
Different amounts of universal total RNA were characterized using the Human Inflammatory Cytokines and Receptors PCR Array, and the percentage of detectable genes was calculated for each RNA amount.
As little as 25 ng total RNA yields greater than an 80% positive call, even for cytokines expressed at very low levels. |
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Reproducibility
The complete PCR Array System demonstrates strong correlations across technical replicates, lots, and instruments with average correlation coefficients > 0.99 insuring reliable detection of differences in expression between biological samples. 
| 050825_1 | 050825_2 | 050825_3 | 050825_4 | | 060111_1 | 0.993 | 0.989 | 0.995 | 0.992 | | 060111_2 | 0.994 | 0.990 | 0.995 | 0.992 | | 060111_3 | 0.992 | 0.990 | 0.993 | 0.992 | | 060111_4 | 0.993 | 0.992 | 0.994 | 0.992 |
| Figure 3: | PCR Arrays Yield Highly Reproducible Results
Four replicate sets of raw threshold data (1-4) obtained by two different scientists (A & B) at two different times (050825 & 060111) on Human Drug Metabolism RT² Profiler PCR Arrays are directly compared. The results demonstrate a high degree of correlation (R2 > 0.990). |
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Specificity
The complete PCR Array System, with high quality input RNA, is guaranteed to yield single bands of the predicted size without primer dimers or other secondary products thus providing the most accurate real-time PCR results possible. 
| Figure 4: | PCR Arrays Amplify A Single Gene-Specific Product in Every Reaction.
Universal total RNA was characterized on the TGFβ / BMP Signaling Pathway PCR Array, followed by dissociation (melt) curve analysis. PCR Arrays specifically detect individual genes despite the expression of related gene family members in the same RNA sample. |
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Application Data Cancer Research:
To ascertain the oncogenic route that two different human breast tumors have taken, the relative expression level of cancer- and adhesion-related genes in normal and two different cancerous tissues were compared.Template cDNAs prepared from total RNA of normal human breast and two human breast tumors (BioChain Institute, Inc., 5.0 µg) were characterized in technical triplicates using the Human Cancer PathwayFinder™ PCR Array and the Human Extracellular Matrix & Adhesion Molecule PCR Array with the RT² SYBR Green / Fluorescein PCR master mix on the Bio-Rad iCycler®. 
| Figure 5: | ECM & Adhesion PCR Arrays Revealed Up- and Down-Regulated Genes in Breast Cancer
Total RNA from normal human breast and a human breast tumor were characterized in technical triplicates, and the relative expression levels for each gene in the two samples are plotted against each other in the Scatter Plot. Genes encoding the matrix metallopeptidases (MMP3 & MMP9) and their inhibitors (TIMP3) are up-regulated, while genes encoding integrins (ITGB3 & ITGB4) are down-regulated, by at least three-fold (outside the silver field) in breast tumors relative to normal tissue. |
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Toxicology Research:
Rezulin (Troglitazone or "Tro" or "T"), a glitazone PPAR-gamma agonist, was approved for treatment of type 2 diabetes mellitus, but was withdrawn from the market due to idiosyncratic liver toxicity. Two similar drugs, Avandia (Rosiglitazone or "Rosi" or "R") and Actos (Pioglitazone or "Pio" or "P"), are considered to be safe treatments for the same condition. The expression profile of key drug metabolism genes should be different in cells treated with Rezulin versus those treated with Avandia and Actos. Hepatocellular carcinoma HepG2 cells were treated at 80% cell confluence with these three drugs (100 µM, Cayman Chemical) or a DMSO vehicle control for 24 h. RNA isolated using the ArrayGrade™ Total RNA Isolation Kit was used to characterize gene expression with the Human Drug Metabolism and Stress & Toxicity PathwayFinder™ RT² Profiler™ PCR Arrays and RT² SYBR Green / Fluorescein PCR master mix on the Bio-Rad iCycler®. 
| Figure 6: | Stress & Toxicity PathwayFinder™ PCR Array Uncovered Idiosyncratic Mechanisms of Action for Liver Toxicity Caused by 3 PPARγ Agonists.
RNA from HepG2 cells treated with three different glitazone PPARγ agonists for type 2 diabetes mellitus was characterized, and the results were compared to that of a vehicle (DMSO) control. A withdrawn drug with idiosyncratic liver toxicity (Rezulin) induces very different changes in the expression of stress-related genes than two safer drugs still on the market (Avandia and Actos). |
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