Abstract B096: Dissecting the flames from the fire: Distribution of immune checkpoints in hot and cold tumors

Abstract

Introduction: Numerous immune checkpoint inhibitors are being developed for the clinic, but identifying the population of patients most likely to respond remains a significant challenge. PD-(L)1 blocking antibodies have been approved for multiple indications, but even in those indications the majority of patients fail to respond to PD-(L)1 monotherapy. Consequently, diagnostic assays have been developed to identify patients with a higher likelihood of response. PD-L1 immunohistochemistry is the platform for multiple assays currently being used in the clinical as companion and complementary diagnostics for the PD-(L)1 checkpoint inhibitors, but those assays have limited sensitivity and selectivity and have inherent risk of subjective interpretation bias. Tumor mutation burden is in development as a proxy readout for a tumor’s potential to prime immune responses, but it does not measure the actual presence of an immune response, and it is not able to inform treatment decisions if there is the option of more than one immunomodulatory intervention. Gene expression assays have the advantage of being a sensitive, selective, and quantitative assay which can directly measure immune biology, and may overcome many of the limitations of the other assay platforms. The Tumor Inflammation Signature (TIS) has been developed on the NanoString® platform as an 18-gene signature of a suppressed immune response within the tumor and has been developed as a clinically validated assay which enriches for response to anti-PD-1 (Ayers, JCI 2017). We have recently evaluated the distribution of TIS in The Cancer Genome Atlas (TCGA) database to understand the prevalence and distribution of immune “hot” vs “cold” tumors by indication (Danaher, JITC 2018). We now extend that work to evaluate the expression of individual immune checkpoint molecules after segregating tumors by TIS to understand the distribution of immune checkpoints across indications and within the context of a preexisting immune response. Methods: We leverage biostatistical analysis of the RNA-seq data in the TCGA database to evaluate the expression of the TIS signature and individual immune checkpoints. Results: We observe that the expression of many immune checkpoint molecules is directly proportional to the degree of immune infiltrate within the tumor as measured by TIS. As such, there is a distribution of IO targets across indications, with inflamed tumors expressing greater median levels of immune checkpoints vs noninflamed tumors. Within individual indication, we also see a distribution of hot and cold tumors, and a corresponding distribution of checkpoint molecules, indicating that there may be some subpopulations of patients with the potential to respond to immune checkpoint blockade even in an indication that is nonresponsive in an unselected population. Furthermore, we also observe increased expression of particular immune checkpoints in subpopulations of certain tumors. For example, certain bladder cancers express PD-L1 at higher levels than would be predicted by TIS alone, despite the fact that CD274, the gene that encodes for PD-L1, is one of the genes which is in the TIS. Likewise, we see elevated LAG3 expression in a fraction of sarcomas above the expected level based on TIS. Conclusions: Close evaluation of the expression levels of immune checkpoints may guide clinical development of combination immunotherapies. Furthermore, these findings could lead to the development of novel diagnostic assays based on gene signatures that could be used in combination with TIS to segregate patients who would benefit from monotherapy alone versus those who need combination strategies. Citation Format: Sarah Warren, Tressa Hood, Patrick Danaher, Alessandra Cesano. Dissecting the flames from the fire: Distribution of immune checkpoints in hot and cold tumors [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B096.