#EXCEL 3013 QUICK ANALYSIS BUTTON SERIAL#
#EXCEL 3013 QUICK ANALYSIS BUTTON REGISTRATION#
#EXCEL 3013 QUICK ANALYSIS BUTTON SOFTWARE#

#EXCEL 3013 QUICK ANALYSIS BUTTON REGISTRATION#

Hence, we created a Spatial tissue analysis tool package for image Registration and Quantification, called ‘Spa-RQ’, to enable image alignment and quantitative examination of spatial tissue phenotypes detected by standard histochemical 3,3’-diaminobenzidine (DAB) staining of adjacent tissue sections. This highlights that baseline oncogenic signalling phenotypes in tumour tissues may inform on drug sensitivity. We further showed that an increased spatial overlap of phosphorylated ERK and 4EBP1, respectively marking MAPK and mTOR pathway activities, was associated with increased cytotoxic response towards co-inhibition of these pathways in murine tumour slice explants 15. By using NSCLC tumours from genetically engineered mouse models (GEMMs) driven by Kras G12D expression together with loss of Lkb1 ( Kras G12D Lkb1 fl/fl, hereafter called KL) or p53 ( Kras G12D p53 fl/fl, hereafter called KP), we previously demonstrated that NSCLC histopathologies exhibit differences in oncogenic signalling activities 15. The PI3K/AKT and MAPK pathways are frequently activated in cancers, including KRAS mutant NSCLCs, and around 30% of adenocarcinomas (ACs) and 3% of squamous cell carcinomas (SCCs) contain KRAS mutations 14. Furthermore, the oncogenic signalling landscapes of tumours or cancer cell lines are typically characterised by genetic profiling 12 or mass spectrometry-based multi-omics analysis 13, while the spatial aspects of networked oncogenic activities in native tumour tissues remain understudied. However, drug-response studies are mostly done in vitro using biochemical means following extrinsic modulation, despite the knowledge that oncogenic functions are dynamically and spatially regulated within tumours. Personalised medicine efforts currently focus on the identification of sample-specific drug sensitivities, or synergistic combinatorial strategies. Therapies targeting mutations in the EGFR and ALK proteins are available, but these mutations are only detected in a small portion of NSCLCs 11.

NSCLC accounts for 85% of all lung cancers and constitutes a heterogeneous set of diseases with complex genomic landscapes 9, 10.

#EXCEL 3013 QUICK ANALYSIS BUTTON SOFTWARE#

However, this requires image analysis software that integrates image registration, annotation, and spatial signal quantification.

#EXCEL 3013 QUICK ANALYSIS BUTTON SERIAL#

No such issues exist for the staining of serial sections using standard IHC. Although powerful in principle, practical factors limit flexible implementation of multiplexed strategies, including availability of specific antibodies of varying host species or signal unmixing accuracy. Recent advances in multiplexed staining techniques have deepened our understanding of spatial phenotypes at tissue levels and yielded data with clinical relevance 6, 7, 8.

Tumour heterogeneity can be interrogated by gene-centric methods, such as multi-regional or single cell spatial sequencing, or by phenotypic assays, such as high-content in vitro imaging or tissue profiling using immunohistochemistry (IHC) analyses. During carcinoma progression, such factors contribute to microenvironmental heterogeneity which, in conjunction with tumour cell-intrinsic genetic and molecular heterogeneity, fosters tumour evolution and compromises treatment success 3, 4, 5. Spa-RQ thus provides a robust and easy to use tool that can be employed to identify spatially-distributed tissue phenotypes.Įpithelial cells are locally influenced by neighbouring stromal cells and secreted molecules, as well as tissue gradients in oxygenation and mechanical forces 1, 2. 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. Subsequently, Spa-RQ was applied to measure the co-activation of MAPK, AKT, and their mutual effector mTOR pathway in individual tumours. 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.

Using Spa-R in conjunction with ImageJ/Fiji, we first performed annotation-guided tumour-by-tumour phenotyping using multiple signalling markers. To demonstrate Spa-RQ’s applicability, we analysed the spatial aspects of oncogenic KRAS-related signalling activities in non-small cell lung cancer (NSCLC). It provides an easy-to-implement workflow for serial sectioning and staining as an alternative to multiplexed techniques. Spa-RQ contains software for image registration (Spa-R) and quantitative analysis of DAB staining overlap (Spa-Q). To facilitate analysis of spatial tissue phenotypes, we created an open-source tool package named ‘Spa-RQ’ for ‘Spatial tissue analysis: image Registration & Quantification’.

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