Karlijn Hummelink

A PD-1T signature as clinical applicable biomarker in NSCLC 147 4 Discussion In spite of the success of PD-(L)1 blockade therapies, the majority of patients do not benefit from these agents. Therefore, biomarkers that reliably allow to identify patients without clinical response are urgently needed to guide alternative treatment decisions beyond PD-1 blockade. In addition, such biomarkers should be developed using robust clinical grade platforms that can easily be implemented in a clinical setting. We previously established PD-1T TILs, a functionally and transcriptionally distinct intratumoral T cell population with enriched tumor reactivity, as a novel predictive biomarker for long-term benefit to PD-1 blockade7,8. However, the measurement of PD-1T TIL status using advanced digital image analysis-based quantification of IHC stainings is complex, and multiple – predominantly technical – sources of potential bias are challenging to cope with in a routine diagnostic setting. Therefore, we here developed a clinically applicable mRNA signature reflecting the presence of PD-1T TILs by using the Nanostring nCounter platform. This study shows that the PD-1T TIL IHC biomarker could successfully be translated into a gene expression signature, as the latter had a similar predictive performance to the digital IHC quantification approach7. Importantly, a high sensitivity and NPV (100%) was reached, which should allow to reliably identify patients without clinical benefit to PD-1 blockade alone. In this relatively small number of patients, the PD-1T signature performed superior to PD-L1 TPS which is similar to previous work7. The clinical applicability of the Nanostring nCounter platform has been demonstrated previously16 and this platform has been shown to have a high analytical sensitivity, technical reproducibility, and to generate robust data from routine FFPE samples10. Therefore, we expect that by using this approach the PD-1T signature can now easily be applied in a clinical setting, and that a similar approach can be exploited for other promising biomarker candidates. Genes in the PD-1T signature are related to, for instance, co-inhibitory signaling (CD274, CTLA4, LAG3), cytokines and chemokines (CXCL13, IL6), interferon signaling (IFIT2, OAS1, STAT1), antigen presentation (TAP1) and angiogenesis (HEY1). This is in line with features of a tumor microenvironment with a pre-existing adaptive immune response as well as with ongoing immunosuppressive stimuli associated with T cell dysfunction17,18. Of note, LAG3, CTLA4 and CXCL13 correspond to the dysfunctional phenotype that characterizes PD-1T TILs8, indicating that the gene signature captures the presence of PD-1T TILs in the TME. Intriguingly, the PDCD1 gene was not among the signature genes, probably due to a partial overlap in expression levels between PD-1T TIL high and low tumors. Notably, the predictive performance of the PD-1T signature was better than PDCD1 gene expression alone.

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