6-Aza-2-Thiothymine as a Novel Matrix for MALDI-MSI-Based Lipid Profiling in FFPE Samples

Historically, research on human disease mechanisms has primarily focused on proteins and nucleic acids. However, growing evidence has underscored the critical role of lipids as key regulators in various pathological processes, including cancer [1]. This recognition has contributed to the rapid expansion of spatial lipidomics as an emerging research field. Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) has become a powerful technique for spatially resolving the distribution and relative abundance of biomolecules, including lipids, within tissue sections, particularly in solid tumors [2]. While formalin-fixed paraffin-embedded (FFPE) tissue preservation is the gold standard for maintaining histological architecture, it is known to cause the loss of several lipid species, posing challenges for lipidomic analyses [3]. Nevertheless, recent advances in MALDI-MSI technique have enabled the detection and spatial mapping of solvent-resistant lipids, especially phospholipids, which continue to offer valuable biomedical insights [4]. A critical factor influencing the success of lipid imaging with MALDI-MSI is the choice of matrix, which directly affects lipid extraction efficiency, ionization, and sensitivity. Traditional matrices such as 2',5'-dihydroxybenzoic acid (DHB) and Norharmane (NOR) are frequently used in lipidomic workflows, although matrix selection should ultimately align with specific research objectives [5]. In this study, we explore the potential of 6-aza-2-thiothymine (ATT) as a novel MALDI matrix for lipid imaging. Previously validated for peptide analysis [6], ATT is here evaluated for its capacity to map lipid species in FFPE tissue. As a proof-of-concept, we assessed its performance on FFPE mouse brain sections in both positive and negative ionization modes, comparing the results with those obtained from other widely used dual-polarity matrices. Our data suggest that ATT represents a viable alternative for lipidomic MALDI-MSI analysis. To further investigate its applicability, ATT was applied to tissue microarrays (TMAs) representing multiple cancer types, including colorectal cancer (CRC), breast cancer (BRCA), clear cell renal cell carcinoma (ccRCC), and glioblastoma (GB). These analyses aimed to evaluate ATT’s ability to ionize lipids across different pathological tissue contexts, supporting its broader use in cancer spatial lipidomics.