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. 2021 Apr 6;113(12):1634–1647. doi: 10.1093/jnci/djab067

Table 1.

Genomic biomarkers for response or resistance to checkpoint blockadea

Genomic biomarker Cancer type Role Predictive value and comments Selected references
FDA-approved biomarkers associated with response
Deficient mismatch repair/microsatellite instability Across solid tumor types, adult and pediatric

  • MSH2, MSH5, MLH1, PMS2, and EPCAM

  • Repairs mismatches in microsatellites

  • Predicts response

  • FDA approved for pembrolizumab

  • Le, et al. 2020 (10)

  • Marabelle, et al. 2019 (6)

  • Overman, et al. 2018 (11)

  • Lenz, et al. 2020 (12)
TMB (>10 mutations/mb) regardless of microsatellite status Across solid tumor types, adult and pediatric Increased mutations/neo-antigens

  • Predicts response

  • FDA-approved: pembrolizumab and TMB >10 mutations/mb

  • Goodman, et al. 2017 (8)

  • Hellman, et al. 2018 (13)

  • Gandara, et al. 2018 (14)
Reported/Investigational response alterations
Chromatin remodeling (SWI/SNF complex)
ARID1A Across solid tumors (eg, ovarian clear cell, endometrial, and gastric) SWI/SNF chromatin remodeling ARID1A deficiency leads to impaired MMR function

  • Shen, et al. 2018 (15)

  • Okamura, et al. 2020 (16)

  • Kim, et al. 2019 (17)
PBRM1 Clear cell renal cancer SWI/SNF chromatin remodeling Contradictory data; some papers suggest that PBRM1 alterations predict response to immunotherapy, others do not

  • Miao, et al. 2018 (18)

  • Braun, et al. 2019 (19)

  • Liu, et al. 2020 (20)
SMARCA4 Driver in small cell ovarian cancer with hypercalcemia (found in uterine and thoracic sarcomas [undifferentiated], NSCLC, bladder, colorectal) SWI/SNF chromatin remodeling

  • SMARC4-deficient tumors have immunogenic microenvironment

  • May predict immunotherapy response

  • Requires validation

  • Jelinic, et al. 2018 (21)

  • Naito, et al. 2019 (22)

  • Iijima, et al. 2020 (23)
SMARCB1 Rhabdoid tumors SWI/SNF chromatin remodeling Preliminary: SMARCB1 loss in rhabdoid tumors may correlate with immunotherapy response Bakouny, et al. 2020 (24)
Other alterations
BAP1 alterations Mesothelioma Promotes immune inflammatory environment in mesothelioma

  • Predicts response

  • Requires validation

  • Alley, et al. 2017 (25)

  • Scherperel, et al. 2019 (26)

  • Shrestha, et al. 2019 (27)
Major histocompatibility complex class-I (MHC-I) genotype Across solid tumors Efficient presentation of driver neoantigens to CD8+ T cells

  • Predicts response in patients with high TMB

  • Requires validation

 Goodman, et al. 2020 (28)
Mutational signatures APOBEC-related ultraviolet-related Across solid tumors Associated with high immunogenicity

  • Predicts response independently of TMB

  • Requires validation

  • Boichard, et al. 2020 (29)

  • Pham, et al. 2019 (30)
Mutational signatures ultraviolet-related Across solid tumors Associated with high immunogenicity Predicts response in patients with low TMB
Requires validation		 Pham, et al. 2019 (30)
PD-L1 amplification Across solid tumors (and in Hodgkin lymphoma) PD-L1 ligand is important in the immune checkpoint machinery

  • Predicts response

  • Requires validation

 Goodman, et al. 2018 (31)
POLE/POLD1 Across solid tumors High tumor mutational rates, high TIL rates, and increased expression of cytotoxic T-cell markers Predicts response

  • Wang, et al. 2019 (32)

  • Yao, et al. 2019 (33)
Biomarkers associated with resistance/Hyperprogression
Beta-2 microglobulin mutations Melanoma Defects in antigen presentation, escape of immune recognition

  • Predicts resistance

  • Requires validation

  • Zaretsky, et al. 2016 (34)

  • Sade-Feldman, et al. 2017 (35)

  • Rodig, et al. 2018 (36)
EGFR alterations Across tumor types Unclear

  • Predicts resistance and hyperprogression

  • Requires validation

  • Kato, et al. 2017 (3)

  • Ferrara, et al. 2018 (37)
KEAP1 mutations NSCLC Associated with “cold” tumor microenvironment Not clear if KEAP1 alterations are predictive or prognostic

  • Chen, et al. 2020 (38)

  • Arbour, et al. 2018 (39)

  • Rizvi, et al. 2019 (40)

  • Papillon-Cavanagh, et al. 2020 (41)
JAK1/2 loss Across tumor types (melanoma, colorectal) Defects in interferon-receptor signaling pathways

  • Predicts resistance

  • Requires validation

  • Zaretsky, et al. 2016 (34)

  • Shin, et al. 2017 (42)

  • Horn, et al. 2018 (43)
MDM2 amplification Melanoma Unclear

  • Predicts hyperprogression

  • Requires validation

  • Kato, et al. 2017 (3)

  • Kato, et al. 2018 (44)
PTEN loss Melanoma Upregulation of immunosuppressive cytokines; may decrease CD8+ T cell infiltration

  • Predicts resistance

  • Requires validation

  • Peng, et al. 2016 (45)

  • Zhao, et al. 2019 (46)
STK11 mutations with KRAS alterations Lung Altered cytokines/chemokines, metabolic restriction of T cells, impaired antigenicity Not clear if STK11 alterations are predictive or prognostic

  • Skoulidis, et al. 2018 (47)

  • Papillon-Cavanagh, et al. 2020 (41)
Wnt/Beta-catenin pathway alterations Melanoma, colon cancer Decreases T-cell infiltration

  • Predicts resistance

  • Requires validation

  • Spranger, et al. 2015 (48)

  • Abril-Rodriguez, et al. 2020 (49)
a

BAP1 = BRCA1-associated protein 1; EGFR = epidermal growth factor receptor; FDA = US Food and Drug Administration; JAK = Janus kinase; KEAP1 = Kelch-like ECH associated protein 1; mb = megabase; MDM2 = murine double minute 2; MHC-I = major histocompatibility complex class-I; MMR = mismatch repair; NSCLC = non-small cell lung cancer; PBRM1 = polybromo-1; PD-1 = programmed cell death-1; PD-L1 = programmed cell death-ligand 1; POLE = DNA polymerase epsilon; PTEN = phosphatase and TENsin homolog deleted on chromosome 10; SMARCB = SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily B; STK11 = serine/threonine kinase 11; TIL = tumor infiltrative lymphocyte; TMB = tumor mutational burden.