Examples of cancer biomarker assays predictive of response to immunotherapy with different levels of evidence for clinical validity/utility
| Biomarker Assay | Biomarker | Clinical Use | Study Type/Level of Evidence | References/ Regulatory Clearance |
|---|---|---|---|---|
| IHC, PD-L1 22C3 pharmDx,Companion Diagnostic | PD-L1 | Predicting response to anti-PD-1 therapy (pembrolizumab) in NSCLC50 % cut-off | Prospective, Phase III clinical trial KEYNOTE-001 | FDA approval [32] |
| IHC, PD-L1 28-8 pharmDx,Complementary Test | PD-L1 | Informs about risk vs. benefit of anti-PD-1 therapy (nivolumab) in non-squamous NSCLC and melanoma- continuous correlation of PD-1 expression with magnitude of treatment effect | Prospective-retrospective, Phase III clinical trial CheckMate-057 | FDA approval [33] |
| IHC, PD-L1 SP142, Complementary Test | PD-L1 | Informs about the risk vs. benefit of anti-PD-L1 therapy (atezolizumab) for metastatic urothelial bladder cancer | Prospective-retrospective, Phase II clinical trial IMvigor-210 | FDA approval [34] |
| IHC | Tumor T cell Infiltrate, PD-L1 with spatial resolution | Predictive to anti-PD-1 therapy in melanoma and NSCLC | Retrospective, Exploratory analysis | Tumeh et al., 2014 [6]; Teng et al. 2015 [35]; Herbst et al., 2014 [36] |
| Enzyme Linked Immunospot (ELISpot) | IFNγ release | Post-treatment/monitoring, cancer vaccines | Retrospective,Exploratory analysis | Kenter et al., 2009 [21]; Sheikh et al., 2009 [24] |
| Multi-parametric Flow Cytometry | MDSC, Tregs, ICOS+ CD4 T cells | Post-treatment/monitoring, cancer vaccines, Predictive of anti-CTLA-4 therapy in RCC and melanoma | Retrospective, Exploratory analysis, Phase I,II trial | Walter et al., 2012 [22]; Tarhini et al., 2014 [171]; Di Giacomo et al., 2013 [172]; Hodi et al., 2014 [173]; Martens et al., 2016 [20] |
| Multi-parametric Flow Cytometry | Absolute lymphocyte count (ALC) | Predictive of response to anti-CTLA-4 therapy | Retrospective, Small cohort, Significant variability among institutions | Ku et al., 2010 [174] |
| Single Cell Network Profiling (SCNP) | AraC → cPARPAraC → CD34 | Predictive of response to induction therapy in elderly patients with de novo acute myeloid leukemia | Retrospective, Training and validation study establishing clinical utility | Cesano et al., 2015 [29] |
| TCR Sequencing | Limited clonality | Clonality assessments of tumor-infiltrating lymphocytes,Predictive to response with anti-CTLA-4 and anti-PD-1 in melanoma | Retrospective,Small cohort | Tumeh et al., 2014 [6]; Cha et al., 2014 [59] |
| nCounter Gene Expression, NanoString Technologies, Inc. | Gene expression profile | Predictive of response to anti-PD-1 therapy in melanoma and multiple solid tumors | Retrospective, Training and test sets – prospective validation ongoing on different tumor types | Ribas et al., 2015 [61]; Wallden et al., 2016 [175]; Piha-Paul et al., 2016 [176]; Man Chow et al., 2016 [177] |
| Next Generation Sequencing (NGS) | Mutational load | Predictive of response to anti-CTLA-4 therapy in melanoma and anti-PD-1 in NSCLC | Retrospective,Small cohort,Training and test sets | Snyder et al., 2014 [46]; Rizvi et al., 2015 [47] |
| NGS/in silico Epitope Prediction | MHC class I epitope frequency/specificity | Predictive of response to anti-CTLA-4 and anti-PD-1 in melanoma, NSCLC, and CRC | Retrospective,Small cohorts | Snyder et al., 2014 [46]; Rizvi et al., 2015 [47]; Van Allen et al., 2015 [52]; Van Rooij et al., 2013 [48] |
| IHC or PCR, Microsatellite Instability Analysis | Mismatch-repair status | Predictive of response to anti-PD-1 therapy in CRC | Phase II study, small cohort | Le et al., 2015 [53] |