Abstract LB404: A new biomarker measuring signal of immune activation (SIA) can improve prediction of response to immune checkpoint inhibitor (ICI) regimens in malignant melanoma

Abstract Background: ICI therapy have improved outcome in different tumor types, including melanoma, but in general, ∼50% of patients respond. Hence, many patients do not benefit from treatment and face immune-related adverse effects due to autoimmune toxicities and many patients eventually acquire resistance to ICI. Several biomarkers for predicting response to ICI have been suggested, but so far none sufficiently sensitive for clinical use. Therefore, improved predictive biomarkers to better select patients suitable for ICI are warranted. Immune cells are embedded in the tumor microenvironment and are believed to play an important role in tumor progression. Immune cells can either support or suppress the tumor cells. For tumors to be able to grow, tumor cells need to be able to avoid the immune system. ICIs take advantage of this opportunity by blocking interactions between immune- and tumor cells in order to suppress the tumor growth. Through a multiplex in situ analysis evaluating 15 immune cell classes, anti-tumoral CD8+ lymphocytes and tumor supportive CD68+CD163+ macrophages were combined into a Signature of Immune Activation (SIA), which captures the interplay between tumor supportive and suppressing immune cells. Furthermore, CD68+CD163+ macrophages was identified as the major producers of complement C1q. Hence, in bulk RNA sequencing, C1q could serve as a surrogate marker for CD68+CD163+ macrophages resulting in the ratio of CD8A to C1QA, B or C. Methods: Publicly available RNA sequencing data from pre-treatment tumor tissue samples of 77 melanoma patients were normalized and combined into a meta cohort. A majority of the patients had metastasized disease (n=69), and eight patients had unknown stage at study entry. All patients received anti-PD1, including 49 patients who received treatment with nivolumab, and 28 patients who received treatment with pembrolizumab. Responders included complete and partial responders (n=25), and non-responders included stable and progressive disease (n=52). Mann Whitney U test was used for comparing responders and non-responders. Cox proportional hazards ratio and log rank p values were used to evaluate statistical significance for the survival analysis. The patients were divided into SIA high or low based on the optimal cut point using maximally selected rank statistics. Results: RNA-based version of SIA was predictive of response to anti-PD1 (p=0.034) and a higher SIA ratio was associated with longer overall survival (OS) (HR: 2.575, 95% CI [1.324, 5.008], p=0.003). Median OS for SIA high (n=30) was 22.2 months, whereas median OS for SIA low (n=47) was 12.4 months. The cut point for SIA high versus low was at 0.21. Conclusions: SIA have potential to inform selection on which patients will benefit from ICI regimens, a quality which would be of high clinical value and merits further investigation. Citation Format: Emma Sandberg, Artur Mezheyeuski, Chatarina Larsson, Tobias Sjöblom. A new biomarker measuring signal of immune activation (SIA) can improve prediction of response to immune checkpoint inhibitor (ICI) regimens in malignant melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB404.