In situ probing changes in fatty-acyl chain length and desaturation of lipids in cancerous areas using mass spectrometry imaging

Mass spectrometry imaging in pulmonary disorders

Mass Spectrometry Imaging (MSI) represents a novel and advancing technology that offers unparalleled in situ characterization of tissues. It provides comprehensive insights into the chemical structures, relative abundances, and spatial distributions of a vast array of both identified and unidentified endogenous and exogenous compounds, a capability not paralleled by existing analytical methodologies. Recent scholarly endeavors have increasingly explored the utility of MSI in the adjunct diagnosis and biomarker research of pulmonary disorders, including but not limited to lung cancer. Concurrently, MSI has proven instrumental in elucidating the spatiotemporal dynamics of various pharmacological agents. This review concisely delineates the fundamental principles underpinning MSI, its applications in pulmonary disease diagnosis, biomarker discovery, and drug distribution investigations. Additionally, it presents a forward-looking perspective on the prospective trajectories of MSI technological advancements.

On-Tissue Spatial Proteomics Integrating MALDI-MS Imaging with Shotgun Proteomics Reveals Soy Consumption-Induced Protein Changes in a Fragile X Syndrome Mouse Model

Fragile X syndrome (FXS), the leading cause of inherited intellectual disability and autism, is caused by the transcriptional silencing of the FMR1 gene, which encodes the fragile X messenger ribonucleoprotein (FMRP). FMRP interacts with numerous brain mRNAs that are involved in synaptic plasticity and implicated in autism spectrum disorders. Our published studies indicate that single-source, soy-based diets are associated with increased seizures and autism. Thus, there is an acute need for an unbiased protein marker identification in FXS in response to soy consumption. Herein, we present a spatial proteomics approach integrating mass spectrometry imaging with label-free proteomics in the FXS mouse model to map the spatial distribution and quantify levels of proteins in the hippocampus and hypothalamus brain regions. In total, 1250 unique peptides were spatially resolved, demonstrating the diverse array of peptidomes present in the tissue slices and the broad coverage of the strategy. A group of proteins that are known to be involved in glycolysis, synaptic transmission, and coexpression network analysis suggest a significant association between soy proteins and metabolic and synaptic processes in the Fmr1KO brain. Ultimately, this spatial proteomics work represents a crucial step toward identifying potential candidate protein markers and novel therapeutic targets for FXS.

Extracellular stimulation of lung fibroblasts with arachidonic acid increases interleukin 11 expression through p38 and ERK signaling

Interleukin-11 (IL-11) is a pleiotropic cytokine that regulates proliferation and motility of cancer cells. Fibroblasts reside in the cancer microenvironment and are the primary source of IL-11. Activated fibroblasts, including cancer-associated fibroblasts that produce IL-11, contribute to the development and progression of cancer, and induce fibrosis associated with cancer. Changes in fatty acid composition or its metabolites, and an increase in free fatty acids have been observed in cancer. The effect of deregulated fatty acids on the development and progression of cancer is not fully understood yet. In the present study, we investigated the effects of fatty acids on mRNA expression and secretion of IL-11 in lung fibroblasts. Among the eight fatty acids added exogenously, arachidonic acid (AA) increased mRNA expression and secretion of IL-11 in lung fibroblasts in a dose-dependent manner. AA-induced upregulation of IL-11 was dependent on the activation of the p38 or ERK MAPK signaling pathways. Furthermore, prostaglandin E2, associated with elevated cyclooxygenase-2 expression, participated in the upregulation of IL-11 via its specific receptor in an autocrine/paracrine manner. These results suggest that AA may mediate IL-11 upregulation in lung fibroblasts in the cancer microenvironment, accompanied by unbalanced fatty acid composition.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Small molecules as potential biomarkers of early gastric cancer: A mass spectrometry imaging approach

BACKGROUND AND AIMS

Early detection of gastric cancer is an effective way to decrease the associated mortality. Efficient methods are needed to provide more sensitive biomarkers for detection of early gastric cancer (EGC).

MATERIALS AND METHODS

We performed liquid extraction-electrosonic spray ionization mass spectrometry imaging and immunofluorescent staining of enzymes related to lipid synthesis on cancerous and paracancerous tissues obtained from six EGC patients and investigated the serum lipid profiles. Areas under the receiver operating characteristic curves were used to determine the diagnostic accuracy of putative biomarkers.

RESULTS

Five lipids detected in the positive ion mode and seven in negative ion mode displayed higher relative intensities in the cancerous than the paracancerous tissues. Seven lipids detected in the positive ion mode and seven in the negative ion mode displayed lower relative intensities in the cancerous than the paracancerous regions. Phosphatidylcholine (34:3) and phosphatidylcholine (36:1) showed higher relative intensities in the cancerous than in the paracancerous tissues and showed higher relative intensities in the serum of EGC patients than healthy controls. Phosphatidylcholine (32:0) showed lower relative intensities in the cancerous than in the paracancerous tissues and lower relative intensities in the serum of EGC patients than healthy controls. The areas under the receiver operating characteristic curves of serum phosphatidylcholine (32:0) and phosphatidylcholine (34:3) for identifying EGC patients were 1.000 and 0.978, respectively.

CONCLUSIONS

Regions associated with EGC showed different lipid distributions and enzyme expression from the paracancerous regions. Serum Phosphatidylcholine (32:0) and phosphatidylcholine (34:3) are potential biomarkers for discriminating between EGC patients and healthy controls.

Roles of Lipid Profiles in Human Non-Small Cell Lung Cancer

Aims: This review aims to identify lipid biomarkers of non-small cell lung cancer (NSCLC) in human tissue samples and discuss the roles of lipids in tissue molecular identification, the discovery of potential biomarkers, and surgical margin assessment. Methods: A review of the literature focused on lipid-related research using mass spectrometry (MS) techniques in human NSCLC tissues from January 1, 2015, to November 20, 2020, was conducted. The quality of included studies was assessed using the QUADAS-2 tool. Results: Twelve studies met the inclusion criteria and were included in the review. The risk of bias was unclear in the majority of the studies. The contents of lipids including fatty acids, phosphatidyl choline, phosphatidyl ethanolamine, phosphatidyl inositol, cardiolipin, phosphatidyl serine, phosphatidyl glycerol, ceramide, lysophosphatidylethanolamine, lysophosphatidylcholine, and lysophosphatidylglycerol differed significantly between cancer and healthy tissues. The sensitivity or specificity of the discrimination model was reported in 8 studies, and the sensitivity and specificity varied among the reported methods. The lipid profiles differed between adenocarcinoma and squamous cell carcinoma NSCLC subtypes. Conclusion: In preclinical studies, MS analysis and multiple discrimination models can be combined to distinguish NSCLC tissues from healthy tissues based on lipid profiles, which provides a new opportunity to evaluate the surgical margin and cancer subtype intraoperatively. Future studies should provide guidance for selecting patients and discrimination models to develop an improved method for clinical application.