Immune-Biomarkers and Immuno-Oncology Research
Immune-biomarkers are indicators of immune activity
Interactions between immune cells and tumor cells shape the tumor microenvironment.1 Here, the immune system seeks to detect and destroy tumor cells, while the tumor attempts to escape the immune response and continue to grow. The field of immune-biomarkers aims to characterize this ongoing interaction between the immune system and cancer.2 The interplay of these individual elements determines the balance of immune activation versus suppression.3,4
Immune-biomarkers are a unique and emerging subset of biomarkers
As immune-biomarkers are measures of activity within the tumor microenvironment, they differ from established gene mutation biomarkers.
Established gene mutation biomarkers have binary expression patterns. They are either present or absent.5,6 BRAF and EGFR are examples of gene mutation biomarkers.7-9
In contrast, as components and regulators of the immune response, immune-biomarkers include cell surface proteins, secreted proteins or peptides, and tumor-infiltrating immune cells.2 PD-L1 is the most widely explored immune-biomarker to date.10
There are specific features of PD-L1 expression under investigation to evaluate its use as an immune-biomarker:
- PD-L1 may present at any point along a continuum of expression. Between 0% and 100% of cells within a tumor sample may express PD-L1.10
- Assessment of PD-L1 expression is determined by immunohistochemical (IHC) assay10
- IHC assays may have varying levels of concordance, in part because staining intensity may differ between diagnostics10
- PD-L1 expression can vary within and across tumor types or histologies.11-14 It can also change by line of therapy as well as by cell type.10,15,16 For example, PD-L1 can be found on tumor cells and immune cells.15
- The clinical relevance of PD-L1 as a biomarker may vary by tumor type and histology17
- Cutoff points for defining high PD-L1 expression may differ among tumor types17
Multiple immune-biomarkers may provide a more realistic representation of the tumor microenvironment
These hallmarks suggest that—similar to the immune response they seek to measure—immune-biomarkers are diverse and inducible. Numerous factors are simultaneously engaged within the tumor microenvironment.4 Therefore, the presence or absence of any single immune-biomarker, including PD-L1, does not fully define immune status.9 Evaluating multiple immune-biomarkers in combination may provide a more accurate and comprehensive assessment.
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(Pt 23):5591-5596. 2. Yuan J, Hegde PS, Clynes R, et al. Novel technologies and emerging biomarkers for personalized cancer immunotherapy. J ImmunoTher Cancer. 2016;4:3. doi:10.1186/s40425-016-0107-3. 3. Gkretsi V, Stylianou A, Papageorgis P, Polydorou C, Stylianopoulos T. Remodeling components of the tumor microenvironment to enhance cancer therapy. Front Oncol. 2015;5:214. doi:10.3389/fonc.2015.00214. 4. Nelson D, Fisher S, Robinson B. The ‘‘Trojan Horse’’ Approach to Tumor Immunotherapy: Targeting the Tumor Microenvironment. J Immunol Res. 2014; 2014:789069.doi: 10.1155/2014/789069. 5. Merid SK, Goranskaya D, Alexeyenko A. Distinguishing between driver and passenger mutations in individual cancer genomes by network enrichment analysis. BMC Bioinformatics. 2014;15:308. 6. Van Allen EM, Wagle N, Levy MA. Clinical Analysis and Interpretation of Cancer Genome Data. J Clin Oncol. 2013;31(15):1825-1833. 7. Davies H, Bignell GR, Cox C, et al. Mutations of the BRAF gene in human cancer. Nature. 2002;417(6892):949-954. 8. Mok TS. Personalized medicine in lung cancer: what we need to know. Nat Rev Clin Oncol. 2011;8(11):661-668. 9. Sharma P, Allison JP. The future of immune checkpoint therapy. Science. 2015;348(6230):56-64. 10. Kerr KM, Tsao MS, 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. 11. Brown JA, Dorfman DM, Ma FR, 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. 12. Callea M, Albiges L, Gupta M, et al. Differential expression of PD-L1 between primary and metastatic sites in clear cell Renal Cell Carcinoma. Cancer Immunol Res. 2014;3(10):1158-1164. 13. Calles A, Liao X, Sholl LM, et al. Expression of PD-1 and Its Ligands, PD-L1 and PD-L2, in Smokers and Never Smokers with KRAS-Mutant Lung Cancer. J Thorac Oncol. 2015;10(12):1726-1735. 14. Dong H, Strome SE, Salomao DR, et al. Tumor-associated B7-H1 promotes T-cell apoptosis: A potential mechanism of immune evasion. Nat Med. 2002;8(8):793-800. 15. 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. 16. Sharpe K, Stewart GD, Mackay A, et al. The Effect of VEGF-Targeted Therapy on Biomarker Expression in Sequential Tissue from Patients with Metastatic Clear Cell Renal Cancer. Clin Cancer Res. 2013;19(24):6924-6934. 17. 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.