Abstract Background: Despite recent successes with immune checkpoint blockade (ICB) in melanoma, the prognosis for most patients remains dire. Whereas a small fraction of patients are able to achieve disease control, most do not respond or are limited by immune-related adverse events. Robust non-invasive predictors of ICB response have the potential to guide clinical decision making and alter management of patients, however, no such predictors currently exist. Methods: We applied a highly-multiplex proximity extension assay (Olink Proteomics) to simultaneously detect >1000 proteins in the plasma of metastatic melanoma patients treated with anti-PD-1 antibodies. Our training cohort comprised of 116 patients, 66 of whom were classified as having treatment benefit (responders, R) and 50 having no benefit (non-responders, NR). An additional 58 patients comprised a validation cohort, including 44 R and 14 NR. Plasma samples were collected at baseline, and at 6-weeks and 6-months after starting treatment. A subset of patients additionally had single-cell RNA-seq performed on tumor tissue. Group differences and treatment effects were evaluated using a linear model with maximum likelihood estimation for model parameters and Benjamini and Hochberg multiple hypothesis correction. Results: At the baseline, 6 significantly differentially expressed (DE) proteins were identified between R and NR. In particular, we found elevated expression of ST2 and IL-6, two key immunoregulatory proteins, in NR. At the 6-week on-treatment time point, more dynamic changes occurred and 79 significantly DE proteins were identified between R and NR, including proteins implicated in primary or acquired resistance, such as IL-8, MIA, TNFR1 and potential novel targets as MCP-4/CCL13, ICOSLG and VEGF. Proteomic changes identified at baseline and 6-weeks were more profound at 6-months post-treatment, and moreover 238 DE proteins were confirmed significant between R and NR at this later time-point. Importantly, we were able to leverage these differences to build classifiers of R and NR subsets. We next looked at the mRNA expression of DE proteins within the tumor microenvironment by leveraging scRNAseq data from a subset of these patients. We uncovered enriched expression of these genes in certain myeloid and exhausted T cell subsets, thus shedding insight into the potential role of these cell subsets in ICB response. Conclusions: Whole plasma proteomic profiling of anti-PD1 treated patients identified important tumor and immune changes associated with R and NR. Advanced proteomic technologies enabling an easy and non-invasive means for the discovery of circulatory protein biomarkers may predict sensitivity to immunotherapy and uncover biological insights underlying primary resistance. Citation Format: Arnav Mehta, Marijana Rucevic, Emmett Sprecher, Lina H. Rosenberg, David Lieb, Gyulnara Kasumova, Michelle S. Kim, Xue Bai, Dennie T. Frederick, Keith Flaherty, Ryan J. Sullivan, Nir Hacohen, Genevieve Boland. The use of blood-based protein biomarkers to uncover determinants of immunotherapy response in melanoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-260.