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Abstract 1665: QuPath versus InForm: Digital image analysis of multiplex immunofluorescence (mIF) tumor-infiltrating lymphocyte (TIL) outcomes in an immunotherapy clinical trial

Background: mIF has emerged as a biomarker platform for characterizing TILs in breast cancer. One pitfall limiting wider application is the complex, proprietary nature of image analysis software. QuPath is an alternative, open-source platform recognized for its processing speed and ease of use. Here, we compare TIL analysis using QuPath version 0.2.3 versus InForm version 2.4, using specimens from a completed pre-operative phase Ib trial of locoregional cytokine therapy (IRX-2 regimen, Brooklyn ImmunoTherapeutics). Methods: 15 paired pre-/post-immunotherapy stage I-III early stage breast cancer specimens were analyzed using the PerkinElmer Vectra platform with a 6-plex panel: cytokeratin (CK, tumor marker), CD3 (T cells), CD8 (cytotoxic T cells), CD163 (macrophages), FoxP3 (regulatory T cells, Treg), programmed death ligand 1 (PD-L1), and DAPI nuclear counterstain. Four high-power fields (HPF) were randomly selected to represent each specimen. Images were analyzed per manufacturer instructions with InForm, and corresponding data were compared with QuPath analysis. Unmixed images were imported into QuPath and cells were segmented using a confidence threshold of DAPI stain. Cells were phenotyped using basic thresholding and random trees machine learning. Tissue was segmented using machine learning. We hypothesized that QuPath and InForm would generate correlating TIL counts data and similar cohort-level estimates of immunotherapy treatment effect. Results: We found a strong correlation in total cell count between QuPath v. InForm (R2 = 0.73, p Conclusion: Exploratory mIF biomarker outcomes in clinical trials may depend on the method of image analysis. Further work is ongoing to evaluate and improve upon discordant results using QuPath v. InForm. These data also highlight the importance of collaborative efforts via the NIH Cancer Immune Monitoring and Analysis Centers to standardize and validate mIF methodologies across institutions. Citation Format: Benjamin M. Nikitin, Brie Chun, Isaac Kim, William L. Redmond, Katherine Sanchez, Zhaoyu Sun, Yaping Wu, David B. Page. QuPath versus InForm: Digital image analysis of multiplex immunofluorescence (mIF) tumor-infiltrating lymphocyte (TIL) outcomes in an immunotherapy clinical trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1665.