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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:

PD-L1

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.

Relevance as a cancer biomarker

PD-L1 pathway expressed on a T cell and tumor cell diagram

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 cells^1-3
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.

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Prevalence across tumors

PD-L1 may be expressed on tumor and/or immune cells at any point along a continuum of expression from 0% to 100%^3-6
PD-L1 expression may vary by tumor type, histology, location, and line of therapy^3,5,6,8,9
The cutoff points for defining high PD-L1 expression differ among tumor types and lines of therapy, and thus the potential for PD-L1 to predict responders for I-O therapy response may also differ across tumors^6,9

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Assessment

Assessment of PD-L1 expression can include looking for expression on tumor cells, select immune cells, or a combination of both⁴
PD-L1 expression is determined by IHC and can be detected on tumor and immune cells⁶

As multiple IHC assays are available, many studies have compared their analytical performance^9,10

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PD-L1: Exploration as an I-O biomarker

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TILs

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.

Relevance as a cancer biomarker

Cytotoxic T cells and NK cells pathways expressed on a Tumor cell diagram

TILs are immune cells that enter the tumor and its microenvironment to mediate an antitumor immune response

TILs include cytotoxic T cells and natural killer cells¹

Expression of key secreted factors in the tumor microenvironment, such as chemokines and proinflammatory cytokines, can recruit these immune cells to the tumor²
Tumors can be characterized by the extent of immune-cell infiltration
The level of TILs correlates with the degree of inflammation^3,4

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Assessment

The number, type, and activation state of TILs found within a tumor can be identified using techniques such as IHC and cell-sorting technology such as flow cytometry⁵

Establishing the role of TILs in the tumor microenvironment

Learn about our research into TILs as a potential I-O biomarker

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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.

Relevance as a cancer biomarker

Inflammation gene signatures, a specific type of gene expression profile (GEP), can be used to assess inflammation signatures of a tumor microenvironment¹

GEP measures the expression of mRNA across huge sets of genes²
This can create a distinct molecular profile (or gene signature), providing a holistic view of cellular function^2,3
Reflecting the combined expression of certain genes involved in the process of inflammation, inflammation gene signatures may indicate the presence of immune cells in the tumor microenvironment^1,3

Inflammation gene signatures vary across tumor types and may be a powerful diagnostic tool^3-6

These gene signatures may be used as surrogates for immune activity in the tumor microenvironment⁴

The interferon gamma (IFN-γ) gene plays a major role in the activation of the immune response⁷

Inflammation gene signatures, such as IFN-y, can be used to assess the level of inflammation within the tumor microenvironment⁸

Inflammation gene signatures are being investigated as a potential predictive I-O biomarker.

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Assessment

To assess gene signatures, mRNA expression is used as an intermediary to determine the expression levels of multiple genes²
NGS can be used to assess GEP via RNA-seq, and gene expression panels (see hypothetical example of gene expression profile below)^9,10

Gene Expression Panel

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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.

References–PD-L1

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.

References–TILs

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.