Due to limited biopsy samples, ~20% of
DCIS lesions confirmed by biopsy are upgraded to invasive
ductal carcinoma (IDC) upon surgical resection. Avoiding underestimation of IDC when diagnosing
DCIS has become an urgent challenge in an era discouraging overtreatment of
DCIS. In this study, the metabolic profiles of 284 fresh frozen breast samples, including
tumor tissues and adjacent benign tissues (
ABTs) and distant surrounding tissues (DSTs), were analyzed using desorption electrospray ionization-mass spectrometry (DESI-MS) imaging. Metabolomics analysis using DESI-MS data revealed significant differences in metabolite levels, including small-molecule
antioxidants, long-chain
polyunsaturated fatty acids (PUFAs) and
phospholipids between pure
DCIS and IDC. However, the metabolic profile in
DCIS with invasive
carcinoma components clearly shifts to be closer to adjacent IDC components. For instance,
DCIS with invasive
carcinoma components showed lower levels of
antioxidants and higher levels of
free fatty acids compared to pure
DCIS. Furthermore, the accumulation of long-chain PUFAs and the
phosphatidylinositols (PIs) containing PUFA residues may also be associated with the progression of
DCIS. These distinctive metabolic characteristics may offer valuable indications for investigating the malignant potential of
DCIS. By combining DESI-MS data with machine learning (ML) methods, various breast lesions were discriminated. Importantly, the pure
DCIS components were successfully distinguished from the
DCIS components in samples with invasion in postoperative specimens by a Lasso prediction model, achieving an AUC value of 0.851. In addition, pixel-level prediction based on DESI-MS data enabled automatic visualization of tissue properties across whole tissue sections. Summarily, DESI-MS imaging on histopathological sections can provide abundant metabolic information about breast lesions. By analyzing the spatial metabolic characteristics in tissue sections, this technology has the potential to facilitate accurate diagnosis and individualized treatment of
DCIS by inferring the presence of IDC components surrounding
DCIS lesions. © 2023 The Pathological Society of Great Britain and Ireland.