Exploring 6-Aza-2-Thiothymine as a MALDI-MSI Matrix for Lipid Mapping in FFPE Samples

Proteins and nucleic acids have historically been the primary research focus on human pathology mechanisms. However, recent studies have highlighted the critical role of lipids as regulators in various disease processes, including cancer. While lipids are well-known for their function as components of cell membranes and energy sources, their involvement in cancer pathogenesis, progression, and outcomes has become increasingly recognized [1]. This has led to the emergence of cancer spatial lipidomics as a rapidly growing research field. Matrix-Assisted Laser Desorption/Ionisation- Mass Spectrometry Imaging (MALDI-MSI) has further expanded, enabling the mapping of spatial distribution and relative abundance of analytes within tissues, including lipids in solid tumours [2]. Formalin fixation and paraffin embedding (FFPE) is the standard method for preserving tissue samples, enhancing histological quality. However, this process results in the depletion of several lipid species, complicating lipid analysis [3]. Nevertheless, recent advancements in the MALDI-MSI technique hinted the possibility to still extract and map solvent-resistant lipids, mainly represented by phospholipids, which still hold biomedically relevant information [4]. The choice of MALDI matrix plays a crucial role in lipid extraction and ionization, influencing molecular coverage and sensitivity. While matrices like 2',5'-dihydroxybenzoic acid (DHB) and Norharmane (NOR) are commonly used for lipidomic analysis, the optimal matrix depends on the specific research objectives [5]. In this study, we aim to investigate the potential of using 6-aza-2-thiothymine (ATT) as the matrix for mapping lipid species with MALDI-MSI, given that ATT has already proven to be an optimal matrix for peptide analysis [6]. As a proof-of-concept, we evaluated ATT's performance in lipid analysis on FFPE mouse brain sections using both positive and negative ion modes, comparing the results with those obtained from other widely used dual-polarity matrices. These analyses demonstrate that ATT matrix could be a possible alternative to traditional matrix employed for lipidomics MALDI- MSI analysis. Moreover, we applied ATT on tissue microarrays of various cancer types, including colorectal cancer (CRC), breast cancer (BRCA), clear cell Renal Cell Carcinoma (ccRCC), and glioblastoma (GB), to assess the capability of ATT to ionise lipids in different pathological tissue types.