Background: The effects of non-amplification short variant (SV) mutations in (programmed death-ligand 1 (PD-L1)) on PD-L1 protein expression and immune checkpoint inhibitors (ICPIs) therapy are unknown. Here, we present a retrospective analysis of mutations detected by comprehensive genomic profiling (CGP) and correlate these results with tumor-cell PD-L1 immunohistochemistry (IHC)-based expression assessment to better understand the relationship between mutations and protein expression of PD-L1.

Methods: CGP was performed on hybridization-captured, adaptor ligation-based libraries using DNA and/or RNA extracted from 314,631 tumor samples that were sequenced for up to 406 cancer-related genes and select gene rearrangements. PD-L1 IHC was performed on a subset of cases (n=58,341) using the DAKO 22C3 PD-L1 IHC assay and scored with the tumor proportion score (TPS).

Results: Overall, the prevalence of SV mutations was low (0.3%, 1081/314,631) with 577 unique variants. The most common SV mutations were R260H (n=51), R260C (n=18), R125Q (n=12), C272fs*13 (n=11), R86W (n=10), and R113H (n=10). The prevalence of mutations varied depending on tumor type with diffuse large B-cell lymphoma (1.9%, 19/997), cutaneous squamous cell carcinoma (1.6%, 14/868), endometrial adenocarcinoma (1.0%, 36/3740), unknown primary melanoma (0.9%, 33/3679), and cutaneous melanoma (0.8%, 32/3874) having the highest frequency of mutations. Of the R260H cases concurrently tested with PD-L1 IHC, most (81.8%, 9/11) had no PD-L1 expression, which contrasts to the five E237K cases where most (80%, 4/5) had PD-L1 expression. In addition, we saw a significantly lower level of PD-L1 expression in samples with a clonal truncating variant (nonsense or frameshift indel) when compared with samples with a subclonal truncating variants (mean: TPS=1 vs TPS=38; p<0.001), and also in clonal versus subclonal missense mutations (mean: TPS=11 vs TPS=22, respectively; p=0.049) CONCLUSIONS: We defined the landscape of mutations in a large cohort of tumor types that can be used as a reference for examining mutations as potential resistance biomarkers for ICPI. Furthermore, we presented novel data on the correlation of mutations and PD-L1 protein expression, providing important new information on the potential functionality of these mutations and can serve as a basis for future research.

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http://dx.doi.org/10.1136/jitc-2021-002558DOI Listing

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