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Abstract 491: Tumor heterogeneity and its impact on immunoprofiling data: Whole tumor vs regions of interest (ROI) analysis of multiplex immunofluorescence in four carcinoma types

2019; American Association for Cancer Research; Volume: 79; Issue: 13_Supplement Linguagem: Inglês

10.1158/1538-7445.am2019-491

1538-7445

Jaime Rodriguez‐Canales, Michael Surace, Jennifer Cann,

Cancer Immunotherapy and Biomarkers

Abstract Background: Multiplex immunofluorescence (mIF) is a key tool for cancer immunoprofiling in tissue samples. These techniques typically require an investigator to select regions of interest (ROI) within the tumor for digital image analysis. However, tumor heterogeneity and sampling bias may result in data that may not be representative of the whole tumor. Our goal was to compare immunoprofiling data from ROI analysis versus whole tumor in lung, colorectal, and bladder carcinomas using mIF and multispectral image analysis. Methods: 9 lung adenocarcinomas, 11 lung squamous cell carcinomas, 10 colorectal adenocarcinomas (CRC), and 10 bladder urothelial carcinomas (BC) were stained with a 6-marker mIF panel (PDL1, CD8, Ki67, CD68, AE1/AE3, PD1) using the Opal technique, and imaged using a Polaris multispectral scanner. Two pathologists independently selected 5 ROI (0.64 mm2) within the tumor for each case. To address the possibility of human sampling bias, 2 additional sets of 5 ROI were randomly generated in the tumor by a computer. HALO software was used to analyze the ROIs and the whole tumor area. The data was compared using Spearman’s ranked correlation coefficients. Results: 6 cell populations were assessed in the tumor epithelium and stroma: cytotoxic T-lymphocytes (CTL, CD8+), antigen-experienced CTL (CD8+/PD1+), proliferating CTL (CD8+/Ki67+), macrophages (CD68+), PDL1+ tumor cells (AE1AE3+/PDL1+), and proliferating tumor cells (AE1AE3+/Ki67+). These immunophenotypes were assessed in each set of 5 ROI and compared with data from the whole tumor. Spearman’s correlation coefficients (r) ranged from -0.25 to 1.00 depending on markers and tumor type. The best correlations across all tumor types were percentage of PDL1+ tumor cells (r=0.82 to 0.89), while cell densities of CTL and PD1+CTL showed the lowest correlations (r=0.35). Among tumor types, lung tumors and BC showed overall good correlation (r=0.82 to 0.83), depending on the marker. CRC showed the highest variability (average r=0.68), with correlation coefficients as low as 0.35 (PD1+CTL) and 0.46 (PDL1+macrophages). Computer selected ROI were not significantly more or less concordant with whole tumor analysis as compared to ROI selected by pathologists. Conclusion: Our results suggest that for immunoprofiling data, particularly proportion-based endpoints such as percent of PDL1+ tumor cells in lung and BC, ROI analysis has acceptable correlation with data from the whole tumor. However, CRC showed high variability, particularly in PD1+CTL, Ki67+CTL, and PDL1+macrophages, suggesting that CRC has higher tumor immunological heterogeneity compared with lung cancer and BC. These results suggest that investigators should analyze the whole tumor areas, otherwise, special attention should be paid to the image analysis strategy and its validation. Citation Format: Jaime Rodriguez-Canales, Michael Surace, Jennifer Cann. Tumor heterogeneity and its impact on immunoprofiling data: Whole tumor vs regions of interest (ROI) analysis of multiplex immunofluorescence in four carcinoma types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 491.