Homogeneous, Low‐volume, Efficient, and Sensitive Quantitation of Circulating Exosomal PD‐L1 for Cancer Diagnosis and Immunotherapy Response Prediction

Cancer treatment by immune checkpoint blockade (ICB) can bring long-lasting clinical benefits, but only a fraction of patients respond to treatment. To predict ICB response, we developed TIDE, a computational method to model two primary mechanisms of tumor immune evasion: the induction of T cell dysfunction in tumors with high infiltration of cytotoxic T lymphocytes (CTL) and the prevention of T cell infiltration in tumors with low CTL level. We identified signatures of T cell dysfunction from large tumor cohorts by testing how the expression of each gene in tumors interacts with the CTL infiltration level to influence patient survival. We also modeled factors that exclude T cell infiltration into tumors using expression signatures from immunosuppressive cells. Using this framework and pre-treatment RNA-Seq or NanoString tumor expression profiles, TIDE predicted the outcome of melanoma patients treated with first-line anti-PD1 or anti-CTLA4 more accurately than other biomarkers such as PD-L1 level and mutation load. TIDE also revealed new candidate ICB resistance regulators, such as SERPINB9 , demonstrating utility for immunotherapy research.

Immune checkpoint therapy, which targets regulatory pathways in T cells to enhance antitumor immune responses, has led to important clinical advances and provided a new weapon against cancer. This therapy has elicited durable clinical responses and, in a fraction of patients, long-term remissions where patients exhibit no clinical signs of cancer for many years. The way forward for this class of novel agents lies in our ability to understand human immune responses in the tumor microenvironment. This will provide valuable information regarding the dynamic nature of the immune response and regulation of additional pathways that will need to be targeted through combination therapies to provide survival benefit for greater numbers of patients.

Tumor cells evade the immune surveillance by up-regulating surface expression of PD-L1, which interacts with PD-1 on T cells to elicit the immune checkpoint response 1,2 . Anti-PD-1 antibodies have shown remarkable promise in treating tumors, including metastatic melanoma 2–4 . However, patient response rate is low 4,5 . A better understanding of PD-L1-mediated immune evasion is needed to predict patient response and improve treatment efficacy. Here we report that metastatic melanoma releases a high level of extracellular vesicles (EVs), mostly in the form of exosomes, that carry PD-L1 on their surface. Interferon-γ (IFN-γ) up-regulates PD-L1 on these vesicles, which suppresses the function of CD8 T cells and facilitates tumor growth. In patients with metastatic melanoma, the level of circulating exosomal PD-L1 positively correlates with that of IFN-γ, and changes during the course of anti-PD-1 therapy. The magnitudes of the early on-treatment increase in circulating exosomal PD-L1, as an indicator of the adaptive response of the tumor cells to T cell re-invigoration, stratifies clinical responders from non-responders. Our study unveils a mechanism by which tumor cells systemically suppress the immune system, and provides a rationale for the application of exosomal PD-L1 as a predictor for anti-PD-1 therapy.