MALDI-MSI emerges as spatial molecular adjudicator for clinical oncopathology, refining diagnosis, margins, and therapy.

Clinical oncology increasingly relies on molecular insights, yet traditional assays often sacrifice the crucial spatial context inherent to diagnostic decisions. This disconnect means that while molecular markers are identified, their precise location within the tissue, relative to tumor cells or the tumor microenvironment (TME), is lost. Understanding this spatial relationship is vital for accurate tumor histology, assessing surgical margins, and predicting therapeutic response. MALDI-MSI offers a unique solution by directly measuring a wide array of molecules, including lipids, metabolites, and peptides, from tissue sections, preserving their original histological coordinates. This technique aims to bridge the gap between molecular detail and spatial information in cancer diagnostics.

This comprehensive review evaluates the current and prospective applications of Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in clinical oncopathology. Researchers systematically analyzed literature focusing on how spatial molecular evidence from MALDI-MSI can enhance, rather than replace, conventional hematoxylin and eosin (H&E) morphology. The review specifically examined applications across molecularly resolved tumor histology, margin and adjacent-tissue assessment, tumor microenvironment interpretation, and therapeutic-response prediction. It also critically assessed the requirements for clinical translation, including quality control, molecular identification confidence, and patient-level validation, while identifying key challenges hindering routine adoption.

The literature reveals significant progress in MALDI-MSI applications, moving beyond simple visual ion-map comparisons towards sophisticated multimodal registration techniques. Advances include the integration of machine-learning classification for automated interpretation and the development of spatial proteomics and spatial pharmacology approaches. For clinical value, the review emphasizes that MALDI-MSI findings must align with H&E morphology, be supported by expert annotation, adhere to stringent quality control, ensure high molecular-identification confidence, and undergo robust patient-level validation. > MALDI-MSI is identified as a realistic near-term solution for "spatial molecular adjudication" in specific, decision-relevant problems, such as difficult tumor classification, uncertain surgical margins, understanding field effects, assessing microenvironment-associated risk, and characterizing heterogeneous drug exposure. Despite these advancements, the review highlights persistent challenges, including pre-analytical variability, incomplete metabolite annotation, batch effects, and validation leakage in pixel-level models, which currently limit routine clinical adoption.