Tumor mutational burden for the prediction of PD-(L)1 blockade efficacy in cancer: challenges and opportunities.

Tumor mutational burden (TMB) is a biomarker that measures the number of somatic mutations in a tumor's genome. TMB has emerged as a predictor of response to immune checkpoint inhibitors (ICIs) in various cancer types, and several studies have shown that patients with high TMB have better outcomes when treated with programmed death-ligand 1-based therapies. Recently, the Food and Drug Administration has approved TMB as a companion diagnostic for the use of pembrolizumab in solid tumors. However, despite its potential, the use of TMB as a biomarker for immunotherapy efficacy is limited by several factors. Here we review the limitations of TMB in predicting immunotherapy outcomes in patients with cancer and discuss potential strategies to optimize its use in the clinic.

Clonal KEAP1 mutations with loss of heterozygosity share reduced immunotherapy efficacy and low immune cell infiltration in lung adenocarcinoma.

BACKGROUND: KEAP1 mutations have been associated with reduced survival in lung adenocarcinoma (LUAD) patients treated with immune checkpoint inhibitors (ICIs), particularly in the presence of STK11/KRAS alterations. We hypothesized that, beyond co-occurring genomic events, clonality prediction may help identify deleterious KEAP1 mutations and their counterparts with retained sensitivity to ICIs. PATIENTS AND METHODS: Beta-binomial modelling of sequencing read counts was used to infer KEAP1 clonal inactivation by combined somatic mutation and loss of heterozygosity (KEAP1 C-LOH) versus partial inactivation [KEAP1 clonal diploid-subclonal (KEAP1 CD-SC)] in the Memorial Sloan Kettering Cancer Center (MSK) MetTropism cohort (N = 2550). Clonality/LOH prediction was compared to a streamlined clinical classifier that relies on variant allele frequencies (VAFs) and tumor purity (TP) (VAF/TP ratio). The impact of this classification on survival outcomes was tested in two independent cohorts of LUAD patients treated with immunotherapy (MSK/Rome N = 237; DFCI N = 461). Immune-related features were studied by exploiting RNA-sequencing data (TCGA) and multiplexed immunofluorescence (DFCI mIF cohort). RESULTS: Clonality/LOH inference in the MSK MetTropism cohort overlapped with a clinical classification model defined by the VAF/TP ratio. In the ICI-treated MSK/Rome discovery cohort, predicted KEAP1 C-LOH mutations were associated with shorter progression-free survival (PFS) and overall survival (OS) compared to KEAP1 wild-type cases (PFS log-rank P = 0.001; OS log-rank P < 0.001). Similar results were obtained in the DFCI validation cohort (PFS log-rank P = 0.006; OS log-rank P = 0.014). In both cohorts, we did not observe any significant difference in survival outcomes when comparing KEAP1 CD-SC and wild-type tumors. Immune deconvolution and multiplexed immunofluorescence revealed that KEAP1 C-LOH and KEAP1 CD-SC differed for immune-related features. CONCLUSIONS: KEAP1 C-LOH mutations are associated with an immune-excluded phenotype and worse clinical outcomes among advanced LUAD patients treated with ICIs. By contrast, survival outcomes of patients whose tumors harbored KEAP1 CD-SC mutations were similar to those with KEAP1 wild-type LUADs.