Immune monitoring of tumor micro-environment,
blood immune cell phenotyping, circulation cytokine analysis.
Development of immune monitoring platform and kit.
Development of early diagnosis kit for Alzheimer's, prostate cancer and cardiovascular diseases.
Development of multiplex cytokines detection kit.
Development of companion diagnosis kit for personalized medical treatment, biomarker diagnostics and immunotherapy.
Laboratories used for scientific research take many forms because of the differing requirements of specialists.
prismCDX, based on its innovative technology and scientific expertise, aims to provide solutions for the appropriate immunotherapy for individual patients. Recently, anticancer immunotherapy has helped to cure cancer successfully. However, anticancer immunotherapy requires analytical methods to comprehensively understand the complexity of the cellular level in the tumor microenvironment because treatment prognosis may vary depending on cancer, immune cells, biomarkers, and biological environment. prismCDX’s immune monitoring technology will help you fully understand the patient’s immune status and apply the right medication to the individual patient. prismCDX is committed to the growth of global healthcare by developing technologies for diagnosis and companion diagnosis with unique technology.
Our approach is to allow different phenotypes to be visualized and quantified simultaneously in the same tissue section, enabling researchers to study the relationships and distribution of these cells within tumors and within the tumor micro-environment.
Using standard FFPE (Formalin-fixed, Paraffin-embedded) biopsies.
CD3, CD4, CD8, CD11b, CD11c, CD14, CD15, CD16, CD20, CD31, CD33, CD39, CD44, CD45, CD45RO, CD56, CD57, CD66b, CD66c, CD68, CD69, CD73, CD103, CD115, CD133, CD137, CD155, CD163, CD195, CD206, CD326, AFP, ALDH1/2, Alpha SMA, Bax, Bcl2, BDNF, Beta-actin, CA9, CCR7, cGAS, CK, CSF1R, CXCL10, CXCR5, DOG1, E-cadherin, EGLN1, Estrogen receptor alpha, FGB(fibrinogen), Fibrin, FOXP3, Glut1, Granzyme B, HePTP, Her2, HLA Class I, HLA Class II, IDO, IL15, IL17A, Ki67, LAG3, LRRC15, MAGEA1, Mannose receptor, M-CST, MPO, N-cadherin, NDRG1, NELFA, Oct4, Pan-keratin, PD-1, PD-L1, Phospho-AKT, Phospho-Stat1, Phospho-Stat3, Phospho-Smad2, Phospho-Smad3, PSMB10, PVR, ROR gamma T, SLAMF6, Snail, SOX2, SOX10, SP-B, T-bet, TBR2, TCF1, TCF8, TERT, TGF-bata, TGF-beta1, TGFBI(BIGH3), TIGHT, TIM3, TrkB, Vimentin, WT1, Xct, and etc.
Inquiry for other antibody settings
CD3, CD4, CD8, CD11b, CD11c, CD19, CD20, CD25, CD31, CD45, CD56, CD68, CD73, CD80, CD86, CD161c, CD163, CD206, AFP, Active caspase3, alpha-SMA, Arginase2, cGAS, CXCL9, CXCL10, E2F8, EGFP, FAM20c, FOXP3, GIP, GLP1, GPC3, Gr1 (Ly6G+Ly6C), Granzyme B, IBA1, IFN-gamma, IL-1beta, IL-6, Ki67, Ly6G, LYVE1, MAGE1, MCP1, PD-1, PD-L1, PDPN, Xcr1, and etc.
Inquiry for other antibody settings
Digital vs. Analog Detection
Human PBMC / Using 30 Biomarkers
t-SNE gating analysis of immune cell subsets. Immune cell subsets were identified and manually gated in the t-SNE space according to the signal strength of the phenotypic marker.
t-SNE gating analysis of T lymphocyte subsets. T lymphocyte subsets were identified and manually gated in the t-SNE space according to the signal strength of the phenotypic marker.
Expression of biomarker displayed on t-SNE plot.
SPADE presents a spanning tree analysis of density normalization events. Through a combination of downsampling, clustering and minimal spanning tree, it provides intuitive visualization of high-dimensional single cell data to support data-driven cellular heterogeneity analysis.
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