Cell Signaling Technology

Product Pathways - Translational Research

PD-L1, CD3ε, CD8α Multiplex IHC Antibody Panel #65713

B7-H1   B7H1   CD274   CD3   CD3e   CD3epsilon   CD8   CD8a   mIHC   multiplexIHC   PD-L1   PD1L1   PDCD1   PDL1  

REACTIVITY
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No. Size Price
65713T 1 Kit ( 50 sections ) ¥6,000.00 现货查询 购买询价
Kit Includes Quantity Applications Reactivity Homology† MW (kDa) Isotype
CD8α (C8/144B) Mouse mAb (IHC Specific) 20 µl 29 Mouse IgG1
PD-L1 (E1L3N®) XP® Rabbit mAb 20 µl 40-50 Rabbit IgG
CD3ε (D7A6E™) XP® Rabbit mAb 20 µl 23 Rabbit IgG

Specificity / Sensitivity

Each antibody in this panel recognizes endogenous levels of its specific target protein.

Source / Purification

Monoclonal antibodies are produced by immunizing animals with a synthetic peptide corresponding to residues near the carboxy terminus of human PD-L1 protein, residues surrounding Glu178 of human CD3ε protein, or residues near the carboxy terminus of human CD8α protein.

Description

The PD-L1, CD3ε, CD8α Multiplex IHC Antibody Panel enables researchers to simultaneously detect these targets in paraffin-embedded tissues using tyramide signal amplification. Each antibody in the panel has been validated for this approach. For recommended staining conditions optimized specifically for this antibody panel please refer to Table 1.

Fluorescent multiplex immunohistochemical analysis of paraffin-embedded human breast cancer using PD-L1 (E1L3N®) XP® Rabbit mAb (green), CD3ε (D7A6E™) XP® Rabbit mAb (yellow), and CD8α (C8/144B) Mouse mAb (IHC Specific) (Red). Blue pseudocolor = DAPI #8961 (fluorescent DNA dye). Image acquisition was performed with a multispectral camera.

Fluorescent multiplex immunohistochemical analysis of paraffin-embedded human tonsil using PD-L1 (E1L3N®) XP® Rabbit mAb (green), CD3ε (D7A6E™) XP® Rabbit mAb (yellow), and CD8α (C8/144B) Mouse mAb (IHC Specific) (Red). Blue pseudocolor = DAPI #8961 (fluorescent DNA dye). Image acquisition was performed with a multispectral camera.

Background

The field of cancer immunotherapy is focused on empowering the immune system to fight cancer. This approach has seen recent success in the clinic with targeting immune checkpoint control proteins, such as PD-1 (1,2). Despite this success, clinical biomarkers that predict response to therapeutic strategies involving PD-1 receptor blockade are still under investigation (3-5). While PD-L1 expression has been linked with an increased likelihood of response to anti-PD-1 therapy, research studies have shown that additional factors, such as tumor-immune infiltration and the ratio of effector to regulatory T cells within the tumor, could play a significant role in predicting treatment outcome (6-9).

Programmed cell death 1 ligand 1 (PD-L1) is a member of the B7 family of cell surface ligands that regulate T cell activation and immune responses. The PD-L1 ligand binds the PD-1 transmembrane receptor and inhibits T cell activation. PD-L1 is expressed in several tumor types, including melanoma, ovary, colon, lung, breast, and renal cell carcinomas (10-12).

CD3 (Cluster of Differentiation 3) is a multiunit protein complex that directly associates with the T cell receptor (TCR). CD3 is composed of four polypeptides (ζ, γ, ε and δ), each of which contains at least one immunoreceptor tyrosine-based activation motif (ITAM) (13). Engagement of TCR complex with foreign antigens induces tyrosine phosphorylation in the ITAM motifs and phosphorylated ITAMs function as docking sites for signaling molecules such as ZAP-70 and p85 subunit of PI-3 kinase (14,15).

CD8 (Cluster of Differentiation 8) is a disulphide-linked heterodimer consisting of α and β subunits. On T cells, CD8 is the coreceptor for the TCR, and these two distinct structures recognize the Antigen–Major Histocompatibility Complex (MHC). CD8 ensures specificity of the TCR–antigen interaction, prolongs the contact between the T cell and the antigen presenting cell, and the α chain recruits the tyrosine kinase Lck, which is essential for T cell activation (16).

  1. Topalian, S.L. et al. (2012) N Engl J Med 366, 2443-54.
  2. Piccinini, M. et al. (2014) Comput Methods Biomech Biomed Engin 17, 1403-17.
  3. Chakravarti, N. and Prieto, V.G. (2015) Transl Lung Cancer Res 4, 743-51.
  4. Sholl, L.M. et al. (2016) Arch Pathol Lab Med , .
  5. Carbognin, L. et al. (2015) PLoS One 10, e0130142.
  6. Tokito, T. et al. (2016) Eur J Cancer 55, 7-14.
  7. Tumeh, P.C. et al. (2014) Nature 515, 568-71.
  8. Feng, Z. et al. (2015) J Immunother Cancer 3, 47.
  9. Baine, M.K. et al. (2015) Oncotarget 6, 24990-5002.
  10. Dong, H. et al. (2002) Nat Med 8, 793-800.
  11. Thompson, R.H. et al. (2006) Cancer Res 66, 3381-5.
  12. Pardoll, D.M. (2012) Nat Rev Cancer 12, 252-64.
  13. Pitcher, L.A. and van Oers, N.S. (2003) Trends Immunol 24, 554-60.
  14. Osman, N. et al. (1996) Eur J Immunol 26, 1063-8.
  15. Hatada, M.H. et al. (1995) Nature 377, 32-8.
  16. Zamoyska, R. (1994) Immunity 1, 243-6.

Application References

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For Research Use Only. Not For Use In Diagnostic Procedures.

Cell Signaling Technology is a trademark of Cell Signaling Technology, Inc.

XP is a registered trademark of Cell Signaling Technology, Inc.

E1L3N is a registered trademark of Cell Signaling Technology, Inc.

D7A6E is a trademark of Cell Signaling Technology. Inc.

Cy3 is a registered trademark of GE Healthcare.

Cy5 is a registered trademark of GE Healthcare.

Cell Signaling Technology® is a trademark of Cell Signaling Technology, Inc.

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