Appendix 282 The study of Hummelink and colleagues, emphasizes that a nuanced spatially informed quantitative analysis, that captures T-cell populations with unique functional properties and tumor recognition capacities, may more accurately identify individuals more likely to respond to immune checkpoint blockade compared with conventionally used biomarkers. Currently established predictive biomarkers of ICI response include microsatellite instability5 (MSI), which is detected in <5% of human cancers, as well as PD-L1 expression and tumor mutation burden (TMB), that both suffer from technical and biological limitations. The clinical utility of PD-L1 testing varies on the basis of the cancer type evaluated and the ICI therapy considered6, with several phase III trials failing to reproduce the association between PD-L1 expression and ICI response7,8. Similarly, with the exception of MSI-high tumors, the predictive value of TMB is cancer-lineage dependent9 and not consistently predictive of ICI response10,11. In contrast to PD-L1 expression or TMB that serve as surrogates of an antitumor immune response, PD-1T TILs are an indicator that an effective tumor-specific T-cell response has occurred and can therefore serve as a biologically relevant measure of clinical outcomes. Furthermore, as PD-1T TIL density was largely independent from PD-L1 TPS in the study by Hummelink and colleagues; it is conceivable that PD-1T TIL density may be informative for PD-L1 negative tumors as well as tumors with PD-L1 TPS in the gray zone of 1% to 50% (Figure 1). Conceptually, PD-1T TILs can be used as a footprint for active tumor-specific adaptive immune responses and therefore might enable patient selection for ICIs in cancers with marginal anti–PD-1 response rates, for example ovarian and breast cancer. The value of TILs in reflecting adaptive antitumor immune responses and ultimately clinical responses with ICI therapy has been previously demonstrated12, with emerging studies supporting the additive benefit of considering TIL functional profiles and their spatial localization within the tumor microenvironment (TME). To this end, spatially resolved multiplex immunofluorescence analyses have uniquely enabled spatial mapping of immune cells and assessment of their heterogeneity in the TME13-15, revealing relationships among TIL subpopulations that are linked with differential ICI clinical outcomes16. Furthermore, evaluation of PD-1/PD-L1 proximity rather than PD-L1 expression alone may more optimally distinguish tumors more likely to regress with ICI therapy17. In addition to evaluation of the PD-1/PD-L1 axis, spatially resolved quantitative immunofluorescence approaches have the potential to interrogate interactions and localization of immunoregulatory molecules such as IDO-1, LAG-3, TIGIT, TIM-3, and VISTA, providing a unique opportunity to understand mechanisms of response and resistance to novel checkpoint inhibitors currently tested in clinical trials. Overall, these approaches have been shown to more accurately predict ICI response compared with PD-L1 expression and TMB18.
RkJQdWJsaXNoZXIy MTk4NDMw