Abstract 5571: FoxP3 absolute quantification to build an effective risk model for cancer patient survival

Abstract

Abstract Background: Forkhead box protein P3 (FOXP3), belonging to the forkhead/winged-helix family, is of great importance in modulating the differentiation and development of T-regulatory cells (Tregs). The numbers of FOXP3+ Tregs as well as exhaustive subsets of CD4+ and CD8+ T cells have been observed increased in solid tumor tissues of patients with colorectal and breast cancers, which helps to create an immunosuppressive environment and promotes tumor progression. However, the correlation between the presence of FOXP3+ Tregs and patients’ survival has been extensively studied in many cancer types, which remains conflicting. The approach presented here aims to absolutely quantify the level of FOXP3 in single cells and constructed effective immune risk models to predict tumor prognosis. Method: Imaging mass cytometry (IMC) was used to quantify FOXP3 inside each single cell. The indirect quantification used a free-metal titration curve in order to match the level of intensity of the metal-tagged antibodies to the level of expression of the antigen. Deep learning (StarDist QuPath extension) was used for cell segmentation and expression quantification. FOXP3 quantification in tissue or at the single cell level was validated against ELISA assay that measure FOXP3 in tissue lysate. Results: Linearity of the metal signals with an average %CV of 17% was observed emphasizing the linear correlation between free metal concentration and intensity. With the IMC technique, the minimum amount of FoxP3 detectable is 0.09 femtogram and its absolute quantification in the different cells in tumor tissues was confronted to disease prognosis in order to start building an effective immune risk model. Conclusion: With the introduction of new biologics in cancer therapy, it is imperative to follow real quantitative change in the expression of biological marker that are indicator of tumor prognosis. Indeed, although the FOXP3 distribution was already seen to be heterogenous in tumors, its absolute level of expression indicative of disease progression can be directly correlated to gain better understanding of the patient response stratification to biologics. Citation Format: Adele Ponzoni, Sandra Delebecq, Melodie Boute, Corinne Ramos, Jonathan Stauber. FoxP3 absolute quantification to build an effective risk model for cancer patient survival. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5571.