Digital quantitative tissue image analysis of hypoxia in resected pancreatic ductal adenocarcinomas

Iram Siddiqui; Jade Bilkey; Trevor D McKee; Stefano Serra; Melania Pintilie; Trevor Do; Jing Xu; Ming-Sound Tsao; Steve Gallinger; Richard P Hill; David W Hedley; Neesha C Dhani

doi:10.3389/fonc.2022.926497

Digital quantitative tissue image analysis of hypoxia in resected pancreatic ductal adenocarcinomas

Front Oncol. 2022 Aug 1:12:926497. doi: 10.3389/fonc.2022.926497. eCollection 2022.

Authors

Iram Siddiqui¹, Jade Bilkey², Trevor D McKee², Stefano Serra³, Melania Pintilie⁴, Trevor Do², Jing Xu⁵, Ming-Sound Tsao³, Steve Gallinger^{6

7}, Richard P Hill⁸, David W Hedley⁵, Neesha C Dhani⁵

Affiliations

¹ Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada.
² Spatio-temporal Targeting and Amplification of Radiation Response (STTARR), University Health Network, Toronto, ON, Canada.
³ Department of Pathology, Toronto General Hospital, Toronto, ON, Canada.
⁴ Department of Biostatistics, The Princess Margaret Cancer Centre, Toronto, ON, Canada.
⁵ Department of Medical Oncology, The Princess Margaret Cancer Centre, Toronto, ON, Canada.
⁶ PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, ON, Canada.
⁷ Hepato-Pancreatico-Biliary Surgical Oncology Program, University Health Network, Toronto, ON, Canada.
⁸ Medicine Program, The Princess Margaret Cancer Centre/Ontario Cancer Institute, Radiation Toronto, ON, Canada.

Abstract

Background: Tumor hypoxia is theorized to contribute to the aggressive biology of pancreatic ductal adenocarcinoma (PDAC). We previously reported that hypoxia correlated with rapid tumor growth and metastasis in patient-derived xenografts. Anticipating a prognostic relevance of hypoxia in patient tumors, we developed protocols for automated semi-quantitative image analysis to provide an objective, observer-independent measure of hypoxia. We further validated this method which can reproducibly estimate pimonidazole-detectable hypoxia in a high-through put manner.

Methods: We studied the performance of three automated image analysis platforms in scoring pimonidazole-detectable hypoxia in resected PDAC (n = 10) in a cohort of patients enrolled in PIMO-PANC. Multiple stained tumor sections were analyzed on three independent image-analysis platforms, Aperio Genie (AG), Definiens Tissue Studio (TS), and Definiens Developer (DD), which comprised of a customized rule set.

Results: The output from Aperio Genie (AG) had good concordance with manual scoring, but the workflow was resource-intensive and not suited for high-throughput analysis. TS analysis had high levels of variability related to misclassification of cells class, while the customized rule set of DD had a high level of reliability with an intraclass coefficient of more than 85%.

Discussion: This work demonstrates the feasibility of developing a robust, high-performance pipeline for an automated, quantitative scoring of pimonidazole-detectable hypoxia in patient tumors.

Keywords: ductal adenocarcinoma (PDAC); hypoxia; image analysis; tumor heterogeneity; tumor microenvironment.