Blood serves as the primary global biological matrix for health surveillance, disease diagnosis, and response to drug treatment, holding significant promise for personalized medicine. The diverse array of lipids and metabolites in the blood provides a snapshot of both physiological and pathological processes, with many routinely monitored during conventional wellness checks. The conventional method involves intravenous blood collection, extracting a few milliliters via venipuncture, a technique limited to clinical settings due to its dependence on trained personnel. Microsampling methods have evolved to be less invasive (collecting ≤150 µL of capillary blood), user-friendly (enabling self-collection), and suitable for remote collection in longitudinal studies. Dried blood spot (DBS), a pioneering microsampling technique, dominates clinical and research domains. Recent advancements in device technology address critical limitations of classical DBS, specifically variations in hematocrit and volume. This review presents a comprehensive overview of state-of-the-art microsampling devices, emphasizing their applications and potential for monitoring metabolites and lipids in blood. The scope extends to diverse areas, encompassing population studies, nutritional investigations, drug discovery, sports medicine, and multi-omics research.

Purpose: The identification of novel molecular biomarkers may assist in the characterization of indeterminate thyroid nodules, which pose significant diagnostic challenges. Here, we aimed to explore the potential of proteomic analyses to support biomarker discovery in challenging thyroid lesions. Methods: Linear Discriminant Analysis (LDA) was applied to Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) data from 44 thyroid neoplasms to select the most impactful molecular features for the classification of different tumor histologies, as well as for the distinction between NRAS-mutant (mNRAS) and NRAS-wild-type (wtNRAS) tumors. Relevant peaks were subsequently identified through nanoscale liquid chromatography electrospray ionization tandem mass spectrometry (nLC–ESI-MS/MS). Results: The LDA selected nine relevant molecular markers distinguishing noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTPs) from other tumor histologies (balanced accuracy = 73%), as well as 19 relevant markers able to identify mNRAS cases (balanced accuracy = 84%). Nine differentially expressed proteins were putatively identified: among them, ATP-dependent RNA helicase DDX42 showed a similar distribution between NIFTPs and papillary thyroid carcinomas (PTCs) / follicular variant PTCs (FVPTCs), while the distribution of the Histone H4 signal was similar between NIFTPs and follicular adenomas (FAs). In addition, Protein disulfide-isomerase A1 and Complement C4-B were overexpressed in wtNRAS compared to mNRAS cases, regardless of histology. Conclusion: The LDA-selected features enable to distinguish NIFTPs from morphologically similar lesions and to discriminate between mNRAS and wtNRAS cases. The identified markers might complement genetic analyses and provide insights into the distinct pathogenic drivers behind the development of mNRAS compared to wtNRAS lesions.

Follicular-patterned thyroid neoplasms comprise a diverse group of lesions that pose significant challenges in terms of differential diagnosis based solely on morphologic and genetic features. Thus, the identification of easily testable biomarkers complementing microscopic and genetic analyses is a highly anticipated advancement that could improve diagnostic accuracy, particularly for noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTPs). These tumors exhibit considerable morphological and molecular heterogeneity, which may complicate their distinction from structurally similar neoplasms, especially when genetic analyses reveal shared genomic alterations (e.g., RAS mutations). Here, we integrated next-generation sequencing (NGS) with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to perform a proteogenomic analysis on 85 NIFTPs (n = 30 RAS-mutant [RAS-mut] and n = 55 RAS-wild type [RAS-wt]), with the aim to detect putative biomarkers of RAS-mut lesions. Through this combined approach, we identified four proteins that were significantly underexpressed in RAS-mut as compared to RAS-wt NIFTPs. These proteins could serve as readily accessible markers in morphologically borderline cases showing RAS mutations. Additionally, our findings may provide insights into the distinct pathogenic pathways through which RAS-mut and RAS-wt NIFTPs arise, highlighting the pivotal role of constitutive RAS–mitogen-activated protein kinase (MAPK) pathway activation in the development and progression of RAS-mut tumors.

In contemporary medical practice, human thyroglobulin (Tg) stands out as the primary serum biomarker for detecting recurrence or persistence (presence of residual tumor) of differentiated thyroid carcinoma (DTC) in patients post-thyroidectomy. Immunoassays (IMAs) and radioimmunoassays (RIAs) have been implemented in clinical settings to gauge Tg levels. However, these methods can be unreliable because anti-thyroglobulin antibodies (Tg-Abs) and heterophile antibodies (HAs) interfere with assay binding, leading to either under- or overestimation of true Tg concentrations. Liquid chromatography tandem mass spectrometry (LC-MS/MS) has emerged as a distinctive alternative tool for Tg measurements. Despite its potential, the effectiveness of LC-MS/MS is under ongoing investigation. This review aims to provide a clear overview of existing follow-up procedures for Tg quantification and evaluate the potential of mass spectrometry (MS) in Tg analysis. The distinctive contribution of this review is the introduction of an emerging approach combining dried blood spots (DBSs) with LC-MS/MS for Tg measurement, emphasizing their translational potential for clinical follow-up of DTC patients.

Background/Objectives: In recent years, lipids have emerged as critical regulators of different disease processes, being involved in cancer pathogenesis, progression, and outcome. Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) has significantly expanded the technology’s reach, enabling spatially resolved profiling of lipids directly from tissue, including formalin-fixed paraffin-embedded (FFPE) specimens. In this context, MALDI matrix selection is crucial for lipid extraction and ionization, influencing key aspects such as molecular coverage and sensitivity, especially in such specimens with already depleted lipid content. Thus, in this work, we aim to explore the feasibility of mapping lipid species in FFPE clinical samples with MALDI-MSI using 6-aza-2-thiothymine (ATT) as a matrix of choice. Methods: To do so, ATT performances were first compared to those two other matrices commonly used for lipidomic analyses, 2′,5′-dihydroxybenzoic acid (DHB) and Norharmane (NOR), on lipid standards. Results: As a proof-of-concept, we then assessed ATT’s performance for the MALDI-MSI analysis of lipids in FFPE brain sections, both in positive and negative ion modes, comparing results with those obtained from other commonly used dual-polarity matrices. In this context, ATT enabled the putative annotation of 98 lipids while maintaining a well-balanced detection of glycerophospholipids (60.2%) and sphingolipids (32.7%) in positive ion mode. It outperformed both DHB and NOR in the identification of glycolipids (3%) and fatty acids (4%). Additionally, ATT exceeded DHB in terms of total lipid count (62 vs. 21) and class diversity and demonstrated performance comparable to NOR in negative ion mode. Moreover, ATT was applied to a FFPE glioblastoma tissue microarray (TMA) evaluating the ability of this matrix to reveal biologically relevant lipid features capable of distinguishing normal brain tissue from glioblastoma regions. Conclusions: Altogether, the results presented in this work suggest that ATT is a suitable matrix for pathology imaging applications, even at higher lateral resolutions of 20 μm, not only for proteomic but also for lipidomic analysis. This could enable the use of the same matrix type for the analysis of both lipids and peptides on the same tissue section, offering a unique strategic advantage for multi-omics studies, while also supporting acquisition in both positive and negative ionization modes.

The high molecular heterogeneity of breast cancer (BC) poses a significant challenge for its classification and biological characterization. Despite numerous efforts, conventional immunohistochemical techniques and traditional mass spectrometry (MS) have failed to provide an exhaustive characterization of tumor subtypes. This limitation is likely due to the loss of spatial information, which significantly impacts the interpretation of the results. In this study, we present a matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) approach that spatially integrates three multiomics layers, including lipids, N-glycans, and tryptic peptides, on the same tissue microarray (TMA) section with BC and normal tissue cores. The analysis of individual layers and their integration demonstrates the potential of multiomics MALDI-MSI in discriminating between healthy and tumor tissues and in capturing molecular differences associated with different subtypes of BC. Specifically, the approach adopted highlighted the significant contribution of lipids and glycans to characterizing breast tumor subtypes. The proteomic layer provides complementary information on the proliferative state and biological heterogeneity of the tumors, clearly distinguishing between the healthy and neoplastic conditions. Overall, this proof-of-concept study demonstrates the potential of spatial multiomics MALDI-MSI as a tool for a more in-depth characterization of BC subtypes, laying the groundwork for future applications on larger sample cohorts.