Abstract 979: Analysis of metabolic and genetic changes in human colorectal cancer and colorectal metastatic tissue by combined NanoString technology and mass spectrometry imaging (MSI)

Abstract

Abstract Introduction: The development of normal colon tissue to carcinoma can progress through several pathways, which exhibit different clinical, pathological and genetic features. Increasing evidence indicates that tumor development and metastases are not solely driven by genetic alterations but also the tumor microenvironment which is associated with changes in metabolic processes. While many studies show the importance of gene expression profiling in cancer progression, little is known about how this correlates with altered lipid metabolism at metastatic sites within the peritoneal cavity. NanoString nCounter provides specific and sensitive genetic profiling data identifying up to 800 genes simultaneously from small amounts of RNA. For biomolecule analysis, MSI is a powerful tool as it enables the rapid identification of phenotype-dependent MS signatures from tissues with little sample preparation. The aim of this study was to investigate the characteristics of secondary tumors at different metastatic sites compared to the primary tumors using a combination of immunohistochemistry, NanoString analysis and Desorption Electrospray Ionization (DESI) MSI. Methods: 12 fresh-frozen human colorectal adenocarcinoma and metastases samples were cut into 12μm sections. DESI-MSI (Xevo G2-XS, Waters) was performed in both polarities with 50μm spatial resolution. SCiLS Lab (Bruker) software were used for data analysis. Histologically-stained (H&E) adjacent sections were used for microscopy. For genomic analysis, RNA was extracted using AllPrep DNA/RNA micro kit from 20μm sections. Following this, RNA abundance was measured using Qubit fluorimeter. Lastly, mRNA hybridisation, detection and scanning was performed on a NanoString nCounter mRNA Gene Expression system and analysed using nSolver 4.0 software. Results: H&E staining allowed the visualisation of different tissue histopathologies. These differences are echoed in selected DESI-MSI ion images. DESI spectra from distinct regions of the tissue show differences in biomolecule expression especially for phospholipids (m/z 600-900). Ions such as m/z 812 correlated with the non-cancerous region whereas others such as m/z 861 were only observed in the cancerous regions of the tissue. Gene expression analysis showed concordance between primary and metastatic tumors such as in RAS/RAF genes. Others, such as IL-6 expression was seen to upregulated in the metastatic sites compared to the primary tumor. Multivariate analysis enabled identification of biomolecules representative of different tissue phenotypes, with the data showing putative MS biomarkers associated with genetic mutations. Conclusion: Results confirmed the advantage of the combined techniques to reveal spatial correlations between changes in lipid metabolism, tumor heterogeneity and gene expression. Citation Format: Yasmin Shanneik, Emrys Jones, Michal Smiga, Bipasha Chakrabarty, Omer Aziz, Steven Pringle, Kaye Williams, Adam McMahon. Analysis of metabolic and genetic changes in human colorectal cancer and colorectal metastatic tissue by combined NanoString technology and mass spectrometry imaging (MSI) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 979.