Spa-RQ: an Image Analysis Tool to Visualise and Quantify Spatial Phenotypes Applied to Non-Small Cell Lung Cancer

Jie Bao, Margarita Walliander, Ferenc Kovács, Ashwini S. Nagaraj, Annabrita Hemmes, Virinder Kaur Sarhadi, Sakari Knuutila, Johan Lundin, Peter Horvath, Emmy W. Verschuren

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Abstract

To facilitate analysis of spatial tissue phenotypes, we created an open-source tool package named ‘Spa-RQ’ for ‘Spatial tissue analysis: image Registration & Quantification’. Spa-RQ contains software for image registration (Spa-R) and quantitative analysis of DAB staining overlap (Spa-Q). It provides an easy-to-implement workflow for serial sectioning and staining as an alternative to multiplexed techniques. To demonstrate Spa-RQ’s applicability, we analysed the spatial aspects of oncogenic KRAS-related signalling activities in non-small cell lung cancer (NSCLC). Using Spa-R in conjunction with ImageJ/Fiji, we first performed annotation-guided tumour-by-tumour phenotyping using multiple signalling markers. This analysis showed histopathology-selective activation of PI3K/AKT and MAPK signalling in Kras mutant murine tumours, as well as high p38MAPK stress signalling in p53 null murine NSCLC. Subsequently, Spa-RQ was applied to measure the co-activation of MAPK, AKT, and their mutual effector mTOR pathway in individual tumours. Both murine and clinical NSCLC samples could be stratified into ‘MAPK/mTOR’, ‘AKT/mTOR’, and ‘Null’ signature subclasses, suggesting mutually exclusive MAPK and AKT signalling activities. Spa-RQ thus provides a robust and easy to use tool that can be employed to identify spatially-distributed tissue phenotypes.

Original languageEnglish
Article number17613
JournalScientific reports
Volume9
Issue number1
DOIs
Publication statusPublished - Dec 1 2019

ASJC Scopus subject areas

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    Bao, J., Walliander, M., Kovács, F., Nagaraj, A. S., Hemmes, A., Sarhadi, V. K., Knuutila, S., Lundin, J., Horvath, P., & Verschuren, E. W. (2019). Spa-RQ: an Image Analysis Tool to Visualise and Quantify Spatial Phenotypes Applied to Non-Small Cell Lung Cancer. Scientific reports, 9(1), [17613]. https://doi.org/10.1038/s41598-019-54038-9