Table 3 –
Examples of biomarkers/genomic changes other than TMB that may influence the response to checkpoint blockade
| Gene/Protein | Comments | References |
|---|---|---|
| Possible association with increased benefit | ||
| APOBEC-related mutagenesis | APOBEC-related mutagenesis increases neo-peptide hydrophobicity, and, thus immunogenicity. APOBEC signature correlated with responses to immunotherapy independently of TMB. | (Boichard et al., 2019) |
| ARID1A | ARID1A alterations (part of the SWI/SNF chromatin remodeling complex) function as a biomarker for longer progression-free survival after anti-PD-1/PD-L1 immunotherapy | (Okamura et al., 2020) |
| CDK12 | CDK12 biallelic inactivating mutations is associated with genomic instability, including increased gene fusions. Most of the genomic alterations in these tumors are not captured by current TMB estimation, but lead to increased neo-antigen burden and T cell infiltration, suggesting benefit from check-point inhibition. | (Wu et al., 2018) |
| DDR genes* | Alterations in DDR genes are associated with increased TMB and tumor infiltration by T cells. Some series demonstrated higher response rate and longer survival during therapy with PD-1/PD-L1 in the presence of DDR alterations. DNA damage is also associated with cellular stress that may trigger immune innate mechanisms. | (Teo et al., 2018) (Chae et al., 2019) |
| KRAS | In NSCLC the presence of KRAS mutations correlates with an inflammatory microenvironment, and may indicate patients that will benefit from checkpoint-inhibitors in monotherapy. | (Liu et al., 2020a). |
| MHC1 presentation | Poor presentation of driver mutation neoantigens by MHC-I may explain why some tumors (even with a high TMB) do not respond to checkpoint blockade. | (Goodman et al., 2020) |
| MLH1, MSH2, MSH6, PMS2 | Loss of function of mismatch repair genes leads to microsatellite instability and a higher number of somatic mutations. These alterations were predictive of higher responses to checkpoint inhibitors.(Le et al., 2017) | (Le et al., 2017) |
| PBRM1 loss | PBRM1 (part of the SWI/SNF chromatin remodeling complex) loss is associated with T-cell mediated tumor killing; series of patients with renal cell carcinoma showed higher benefit from ICIs in the presence of PBRM1 loss | (Miao et al., 2018) |
| PD-1 expression | Frequency of PD-1+CD8+ T cells relative to that of PD-1+ regulatory T (Treg) cells in the tumor microenvironment can predict the clinical efficacy of anti-PD1 therapies | (Kumagai et al., 2020) |
| PD-L1 amplification | PD-L1 (CD274) amplification may be present ~0.7% of solid tumors; most PD-L1 amplified tumors demonstrated low to intermediate TMB. Clinical responses to checkpoint ICIs are frequent (66.7%) and independent of TMB in solid tumors; however, only a small number of such patients have been treated. PD-L1 amplification is also a hallmark of Hodgkin disease, which is highly responsive to checkpoint blockade. | (Goodman et al., 2018) |
| PD-L1 expression by immunohistochemistry | PD-L1 overexpression is an indicator of intra-tumoral inflammatory environment. Expression levels are independent of TMB. PD-L1 expression on tumor or immune cells may be important. | (Ott et al., 2019) (Patel and Kurzrock, 2015) (Liu et al., 2020b) (Gonzalez-Ericsson et al., 2020) |
| POLD1, POLE | Loss-of-function mutations in POLD1 and POLE correlate with increased immune infiltration and a hyper-mutated phenotype, and predict responses to anti-PD-L1 therapy. | (Budczies et al., 2018) (Wang et al., 2018) |
| SERPINB3, SERPINB4 mutations | Serpin mutations were associated with higher clinical benefit rates and longer survival in melanoma patients treated with anti-CTLA4 therapy. This possible positive predictive effect was independent of TMB. | (Riaz et al., 2016) |
| SMARCA4 | SMARCA4 (part of the SWI/SNF chromatin remodeling complex) alterations are correlated with ICI response in small cell ovarian cancer hypercalcemic type and anecdotally in other tumors | (Tischkowitz et al., 2020) |
| Tumor infiltrating lymphocytes | High tumor infiltrating lymphocytes have been associated with checkpoint inhibitor responsiveness | (Gonzalez-Ericsson et al., 2020) |
| Possible association with resistance | ||
| B2M inactivating mutations | B2M truncating mutations lead to loss of surface expression of MHC I and resistance to PD-1 blockade. | (Zaretsky et al., 2016) |
| JAK1/2 mutations | JAK1/2 loss of function mutations can lead to acquired and primary resistance to anti-PD-1 therapy, even in the setting of high TMB. | (Shin et al., 2017) |
| KEAP1 alterations | Associated with worse outcome after ICI. Not clear if these alterations are prognostic or predictive | (Chen et al., 2020; Skoulidis and Heymach, 2019) |
| STK11/LKB1 | Associated with worse outcome after ICI. Not clear if these alterations are prognostic or predictive | (Skoulidis et al., 2018) |
| Possible association with hyper-progression | ||
| MDM2/MDM4 and EGFR | MDM2/MDM4 amplifications and EGFR aberrations were associated with hyperprogression in patients treated with checkpoint inhibitors. This association was independent of TMB. | (Kato et al., 2017) (Singavi et al., 2017) |
*
DDR genes definitions are variable and commonly includes BRCA1, BRCA2, ATM, CHECK2, PALBB2, ATM, ERCC2, FANCA
Abbreviations: B2M: Beta-2-microglobulin, DDR: DNA damage repair; ICI= immune checkpoint inhibitor; MHC: major histocompatibility complex