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Inflamed Tumor Markers

Inflamed tumors show evidence of immune-cell infiltration and activation in the tumor microenvironment.1,2 Several Immuno-Oncology (I-O) biomarkers exist that are reflective of an inflamed tumor microenvironment:



Programmed death ligand 1 (PD-L1), a ligand for the immune checkpoint receptor called programmed death receptor-1 (PD-1), is expressed on various cells, including tumor and immune cells. PD-L1 expression on tumor and immune cells depends on many variables and can change over time, and vary by tumor type, histology, location and line of therapy.

Click below to learn more about the role of PD-L1 as an I-O biomarker.
  • PD-L1 is a ligand for the immune checkpoint receptor called programmed death receptor-1 (PD-1), which is expressed on the surface of cytotoxic T cells1-3
  • PD-L1 is expressed on several cell types, including tumor cells and immune cells

Research is ongoing to better understand the role of PD-L1 as an I-O biomarker, both alone and in combination with other I-O biomarkers.



Tumor infiltrating lymphocytes (TILs) are recruited into the tumor microenvironment and may correlate with inflammation, and include cytotoxic T cells and natural killer cells.

Click below to learn more about the role of TILS in I-O.

Inflammation Gene Signatures

Inflammation gene signatures are a specific type of gene expression profile (GEP) and can be used to assess inflammation signatures of a tumor microenvironment. They vary across tumor types and may be a powerful diagnostic tool.

Click below to learn more about inflammation gene signatures as a potential predictive I-O biomarker.

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References–Inflamed tumor markers

1. Masucci GV, Cesano A, Hawtin R, et al. Validation of biomarkers to predict response to immunotherapy in cancer: Volume I — pre-analytical and analytical validation. J Immunother Cancer. 2016;4:76. 2. Hegde PS, Karanikas V, Evers S. The where, the when, and the how of immune monitoring for cancer immunotherapies in the era of checkpoint inhibition. Clin Cancer Res. 2016;22(8):1865-1874.


1. Freeman GJ, Long AJ, Iwai Y, et al. Engagement of the PD-1 immunoinhibitory receptor by a novel B7 family member leads to negative regulation of lymphocyte activation. J Exp Med. 2000;192(7):1027-1034. 2. Latchman Y, Wood CR, Chernova T, et al. PD-L2 is a second ligand for PD-1 and inhibits T cell activation. Nat Immunol. 2001;2(3):261-268. 3. Gatalica Z, Snyder C, Maney T, et al. Programmed cell death 1 (PD-1) and its ligand (PD-L1) in common cancers and their correlation with molecular cancer type. Cancer Epidemiol Biomarkers Prev. 2014;23(12):2965-2970. 4. Taube JM, Klein A, Brahmer JR, et al. Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti–PD-1 therapy. Clin Cancer Res. 2014;20(19):5064-5074. 5. Kerr KM, Tsao M-S, Nicholson AG, Yatabe Y, Wistuba II, Hirsch FR. Programmed death-ligand 1 immunohistochemistry in lung cancer: in what state is this art? J Thorac Oncol. 2015;10(7):985-989. 6. PD-L1 IHC 22C3 pharmDx [package insert]. Carpinteria, CA: Dako North America, Inc.; 2018. 7. Krigsfeld G et al. Poster presentation at AACR 2017. Abstract CT143. 8. Brown JA, Dorfman DM, Ma F-R, et al. Blockade of programmed death-1 ligands on dendritic cells enhances T cell activation and cytokine production. J Immunol. 2003;170(3):1257-1266.9. Wang X, Teng F, Kong L, Yu J. PD-L1 expression in human cancers and its association with clinical outcomes. Onco Targets Ther. 2016;9:5023-5039. 10. Hirsch FR, McElhinny A, Stanforth D, et al. PD-L1 immunohistochemistry assays for lung cancer: results from phase 1 of the Blueprint PD-L1 IHC assay comparison project. J Thorac Oncol. 2017;12(2):208-222. 11. Scheel AH, Dietel M, Heukamp LC, et al. Harmonized PD-L1 immunohistochemistry for pulmonary squamous-cell and adenocarcinomas. Mod Pathol. 2016;29(10):1165-1172.


1. Wein L, Savas P, Luen SJ, Virassamy B, Salgado R, Loi S. Clinical validity and utility of tumor-infiltrating lymphocytes in routine clinical practice for breast cancer patients: current and future directions. Front Oncol. 2017. doi:10.3389/fonc.2017.00156. 2. Melero I, Rouzaut A, Motz GT, Coukos G. T-cell and NK-cell infiltration into solid tumors: a key limiting factor for efficacious cancer immunotherapy. Cancer Discov. 2014;4(5):522-526. 3. Hegde PS, Karanikas V, Evers S, et al. The where, the when, and the how of immune monitoring for cancer immunotherapies in the era of checkpoint inhibition. Clin Cancer Res. 2016;22(8):1865-1874. 4. Masucci GV, Cesano A, Hawtin R, et al. Validation of biomarkers to predict response to immunotherapy in cancer: Volume I—pre-analytical and analytical validation. J Immunother Cancer. 2016;4:76. 5. Ma W, Gilligan BM, Yuan J, Li T. Current status and perspectives in translational biomarker research for PD-1/PD-L1 immune checkpoint blockade therapy. J Hematol Oncol. 2016;9(1):47.

References–Inflammation gene signatures

1. Torri A, Beretta O, Ranghetti A, et al. Gene expression profiles identify inflammatory signatures in dendritic cells. PLoS One. 2010. doi:10.1371/journal.pone.0009404. 2. Walker MS, Hughes TA. Messenger RNA expression profiling using DNA microarray technology: diagnostic tool, scientific analysis or un-interpretable data? (review). Int J Mol Med. 2008;21(1):13-17. 3. Linsley PS, Chaussabel D, Speake C. The relationship of immune cell signatures to patient survival varies within and between tumor types. PLoS One. 2015. doi:10.1371/journal.pone.0138726. 4. Galon J, Angell HK, Bedognetti D, Marincola FM. The continuum of cancer immunosurveillance: prognostic, predictive, and mechanistic signatures. Immunity. 2013;39(1):11-26. 5. Gibney GT, Weiner LM, Atkins MB. Predictive biomarkers for checkpoint inhibitor-based immunotherapy. Lancet Oncol. 2016;17(12):e542-e551. 6. Cesano A, Warren S. Bringing the next generation of immune-oncology biomarkers to the clinic. Biomedicines. 2018. doi:10.3390/biomedicines6010014. 7. Ikeda H, Old LJ, Schreiber RD. The roles of IFNγ in protection against tumor development and cancer immunoediting. Cytokine Growth Factor Rev. 2002;13(2):95-109. 8. Abiko K, Matsumura N, Hamanishi J, et al. IFN-γ from lymphocytes induces PD-L1 expression and promotes progression of ovarian cancer. Br J Cancer. 2015;112(9):1501-1509. 9. Fumagalli D, Blanchet-Cohen A, Brown D, et al. Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology. BMC Genomics. 2014. doi:10.1186/1471-2164-15-1008. 10. Cesano A. nCounter® PanCancer Immune Profiling Panel (NanoString Technologies, Inc., Seattle, WA). J Immunother Cancer. 2015. doi:10.1186/s40425-015-0088-7. 11. Finotello F, Di Camillo B. Measuring differential gene expression with RNA-seq: challenges and strategies for data analysis. Brief Funct Genomics. 2015;14(2):130-142. 12.Sharma P, Retz M, Siefker-Radtke A, et al. Nivolumab in metastatic urothelial carcinoma after platinum therapy (CheckMate 275): a multicentre, single-arm, phase 2 trial. Lancet Oncology. 2017;18(3):312-322.