Table S3. List of Hyper-fucosylated glycans for prostate cancer analysis

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables spatially resolved detection of diverse biomolecules directly from tissues, supporting pathology-guided and unbiased biomarker discovery. By maintaining spatial context, MALDI-MSI overcomes key limitations of bulk omics approaches, which obscure the cellular origins of analytes, particularly in heterogeneous tumors containing abundant normal tissue or extracellular matrix. Complementary biofluids such as serum, urine, saliva, or cerebrospinal fluid are valuable for biomarker validation yet similarly lack spatial information when used as primary discovery materials. Integrating spatially defined diseased tissues with matched proximal biofluids therefore represents a powerful strategy for biomarker development. N-glycan mass spectrometry imaging (N-glycan MSI) has emerged as a versatile platform for characterizing N-glycan distributions in tissues and for quantifying glycan compositions in cells, antibodies, and biofluids. This method relies on on-tissue application of peptide N-glycosidase F (PNGase F) to liberate N-linked glycans, which are subsequently detected by MALDI-MSI to generate micron-scale, two-dimensional glycan maps. The workflow is highly modular, accommodating tissues, cultured cells, arrays, membranes, and isotopic or label-free quantification approaches. Recent advances also include the use of specialized glycosidases to resolve glycan isomers. This review highlights established and emerging N-glycan MSI strategies for biomarker discovery and validation, with applications in liver, brain, breast, and other clinically relevant tissues.

Figure S3. Ley expression in small cell prostate cancer.

Figure S5. Heat map of selected glycans of a metastatic small cell carcinoma to a lymph node.

Spatial omics has transformed biomedical research by uncovering the molecular characterization of biological systems while preserving spatial context. Among these approaches, mass spectrometry imaging (MSI) provides a label-free, in situ visualization of diverse molecular classes, including metabolites, lipids, proteins, and glycans. Recent advances in instrumentation, sample preparation, and data acquisition have pushed MSI into the field of single-cell analysis, providing unprecedented access to cellular heterogeneity and molecular states across biological contexts. Here, we review current single-cell MSI platforms and highlight key innovations that have improved spatial resolution, sensitivity, and throughput. Presented examples from published workflows highlight the variability in strategies for cell isolation, capture, and data acquisition. The three main ionization techniques of desorption electrospray ionization (DESI), secondary ion mass spectrometry (SIMS), and matrix-assisted laser desorption ionization (MALDI) are highlighted for their capabilities to generate robust single-cell multi-omics profiling. We outline future directions for the field and the potential of single-cell MSI to impact translational spatial omic research and precision medicine.

Figure S8. Fucosylated glycan expression in tumors from prostatectomy specimens do not associate with PSA, grade, or stage.

Table S2. Patient data from the University of Texas Health San Antonio Tissue Microarray.

H&E and MALDI-MSI images of N-glycans of full tissue samples

Collagen breast stroma can become a breast cancer risk factor, yet proteomic regulation of normal breast stroma remains poorly defined. This study evaluates the spatial regulation of the collagen proteome from normal breast tissue. Normal breast tissue sections from the Susan G. Komen tissue bank were used (n = 40), with data including genetic ancestry (n = 20 African ancestry; n = 20 European ancestry), body-mass-index (BMI), age, and mammogram density by the Breast Imaging Reporting and Data System (BI-RADS). 10-plex cell marker staining showed CD44 and COL1A1 markers modulated with BMI. Collagen fiber widths by second harmonic generation microscopy contrasted in BMI categories by genetic ancestry. Targeted extracellular matrix proteomics mass spectrometry imaging showed the collagen alpha-1(I) chain proteome was spatially heterogeneous across the normal breast microenvironment with site-specific post-translational modification of proline hydroxylation. Signatures computationally extracted from stroma-rich regions reported that 47 collagen peptides distinguished BI-RADS categories (area under the receiver operating curve >0.7; p-value >0.05). Multivariate modeling of collagen peptides, fiber metrics, and clinical features supported a strong positive association with BMI as a determinant of collagen alterations in the normal breast. This study provides a foundation for larger studies investigating the clinical value of spatial collagen proteome alterations in human breast.

Table S1. Patient data from the Washington University cohort.

Figure S1. Schematic of fucosylated glycan architecture.

It is now apparent that cardiac form and function are governed at a system level by an integrated collective of heterogeneous single-cell programs that together regulate tissue homeostasis, drive disease emergence, and shape individualized responses to therapy. Current advances in single-cell proteomics and spatial multiomics by mass spectrometry imaging allow systematic dissection of clinically defined cardiovascular tissues with an unprecedented molecular resolving power, yet remain relatively underutilized in cardiovascular research. This compendium review works to stimulate new research into spatial regulation of the heart, emphasizing integration of single-cell proteomic regulation with comprehensive multiomic mass spectrometry imaging studies. In this context, we outline conceptual foundations, technological innovations, and biological insights that have resulted in the current success of single-cell proteomic and spatial multiomic analyses in cardiovascular disease. We provide an experimental design knowledge base of critical components in single-cell proteomics and spatial workflows by mass spectrometry imaging, essential for generating robust and reproducible data sets that are interpretable by advanced computational methods. Key cardiovascular discoveries by single-cell proteomics and multiomic mass spectrometry imaging are reviewed, highlighting how these approaches have provided new molecular insights into cardiac cell programming.

Introduction Diabetic kidney disease (DKD) is characterized by impairment of renal glomerular and tubular cells. Low plasma levels of ceramides and lactosylceramides containing very long-chain (VLC) fatty acid were found to be predictive of DKD development. Elongase 1 (Elovl1) is a ubiquitous elongase that elongates C20-C22 fatty acids to generate very long-chain C24 fatty acids. Using a novel transgenic mouse overexpressing Elovl1, we investigated whether modification to sphingolipid fatty acid composition averts DKD development. Methods A transgenic (TG) mouse overexpressing Elovl1 was created at the Medical University of South Carolina/Transgenic Core. Elovl1 TG and wild type (WT) mice were rendered diabetic using serial streptozotocin injections. Plasma, kidney, liver, and urine sphingolipidomics of diabetic and non-diabetic TG and WT mice were analyzed using mass spectroscopy and Matrix-Assisted Laser Desorption/Ionization-Imaging Mass Spectrometry. Sphingolipid metabolizing enzymes were analyzed using immunohistochemical & multispectral imaging coupled with digital analysis. Results Plasma sphingomyelins were higher, but lactosylceramides were lower in diabetic TG than in diabetic WT mice. Kidney lactosylceramides were also lower in diabetic TG mice. In urine, diabetic TG mice excreted more VLC lactosylceramides than diabetic WT mice, but less VLC sphingomyelins, VLC ceramides, sphingosine and sphingosine 1-phosphate. There was extensive damage to proximal tubules in kidneys of diabetic WT mice compared to diabetic TG mice. Glomeruli in diabetic WT kidneys appeared also abnormal, whereas no obvious abnormality of glomeruli in diabetic TG was observed. In diabetic TG, Elovl1 overexpression resulted in decreased kidneys levels of both ceramide synthase and acid sphingomyelinase, but increased acid ceramidase levels compared to non-diabetic TG mice. Conclusion The diabetic Elovl1 TG mouse revealed interaction between Elovl1 overexpression and DKD development, and showed that distinct VLC sphingolipids could be involved in maintaining cell membrane integrity of renal cells.

Figure S7. Example of adenocarcinoma with NE features.

Segmentation Analysis of tissues according to N-glycan analysis

Recent advances in spatially resolved molecular profiling have positioned matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) as a powerful platform for multiomic tissue analyses. However, conventional workflows that sequentially target distinct molecular classes are time- and resource-intensive, requiring repeated sequential sample preparation, imaging, and data integration. Here, we evaluate streamlined strategies for simultaneous or combined acquisition of N-glycan and collagen-derived peptide information using PNGase F and collagenase. In-solution studies demonstrate that simultaneous enzymatic digestion yields comparable peptide identifications and glycan profiles relative to traditional sequential workflows, with minimal impact on enzymatic specificity. On the basis of these findings, we developed and optimized MALDI-MSI protocols enabling either simultaneous enzyme application or sequential enzyme treatment with unified matrix deposition and single-pass imaging. While direct coapplication reduced image uniformity, a hybrid approach that used sequential enzyme deposition with combined imaging preserved spatial fidelity and spectral quality while significantly reducing processing and computational demands. Application to human tissues, including vertebral bone and ocular samples, highlights the utility of this workflow for fragile specimens and exploratory multiomic surveys. Collectively, these results establish a framework for integrated glycomic and proteomic imaging targeting the extracellular microenvironment, expanding multiomic MALDI-MSI analyses.

Figure S2. Enrichment of glycans in specimens with small cell versus adenocarcinoma histology.

Background:Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with variable risk of progression to invasive breast cancer (IBC). Current transcription and cell marker investigations suggest ECM decreases in later events but are limited in details of ECM proteomic composition, including post-translational modifications. We investigated whether the extracellular matrix (ECM) proteome alters with later breast events of DCIS or IBC. Methods:ECM-targeted mass spectrometry imaging and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were applied to ten tissue microarrays from the Resource of Archival Human Breast Tissue cohort (RAHBT). Primary DCIS specimens (n=136) were analyzed in relation to later events of DCIS (n=40) or IBC(n=30), with a mean follow-up of 192.1 months 95% CI [179.1,205.1]. Statistical modeling, survival analyses, and exploratory machine learning approaches were used to identify ECM peptide signatures associated with later events. Results:Distinct ECM peptide profiles were associated with later events of DCIS or IBC. Fifteen peptides derived from fibrillar collagens (COL1A1, COL1A2, COL3A1) and elastin, showed significantly reduced abundance in patients who developed IBC. Lower expression of specific collagen peptides associated with overall 19.9% 95% CI [17.92, 21.81] decreased disease-free survival for IBC. Lower expression of these peptides was significantly associated with reduced disease-free survival (age-adjusted hazard ratio [HR] = 2.45, 95% CI: 2.33-2.57; P < 0.05). Patient-matched samples of primary DCIS, later DCIS, and later invasive breast cancer further demonstrated reduction in ECM peptide detection. Exploratory predictive modeling from patient-matched samples achieved high performance (AUROC >0.98, accuracy >93%) in distinguishing primary from later events. Following prior work in the RAHBT cohort, reduction of certain collagen peptides was also observed in primary DCIS samples from higher risk patient groups. Conclusions:ECM proteomic remodeling, particularly decreases of specific collagen domains, is strongly associated with later events of DCIS and IBC. These findings highlight ECM proteome as a critical regulator of breast cancer emergence with potential as a prognosticator of risk stratification to guide clinical management of DCIS.