Paraffin-Embedded Tissue as a Novel Matrix in Metabolomics Study: Optimization of Metabolite Extraction Method

Development of metabolome extraction strategy for metabolite profiling of skin tissue

INTRODUCTION

Changes in skin phenotypic characteristics are based on skin tissue. The study of the metabolic changes in skin tissue can help understand the causes of skin diseases and identify effective therapeutic interventions.

OBJECTIVES

We aimed to establish and optimize a non-targeted skin metabolome extraction system for skin tissue metabolomics with high metabolite coverage, recovery, and reproducibility using gas chromatography/mass spectrometry.

METHODS

The metabolites in skin tissues were extracted using eleven different extraction systems, which were designed using reagents with different polarities based on sequential solid-liquid extraction employing a two-step strategy and analyzed using gas chromatograph/mass spectrometry. The extraction efficiency of diverse solvents was evaluated by coefficient of variation (CV), multivariate analysis, metabolites coverage, and relative peak area analysis.

RESULTS

We identified 119 metabolites and the metabolite profiles differed significantly between the eleven extraction systems. Metabolites with high abundances in the organic extraction systems, followed by aqueous extraction, were involved in the biosynthesis of unsaturated fatty acids, while metabolites with high abundances in the aqueous extraction systems, followed by organic extraction, were involved in amino sugar and nucleotide sugar metabolism, and glycerolipid metabolism. MeOH/chloroform-H2O and MeOH/H2O-chloroform were the extraction systems that yielded the highest number of metabolites, while MeOH/acetonitrile (ACN)-H2O and ACN/H2O-IPA exhibited superior metabolite recoveries.

CONCLUSION

Our results demonstrated that our research facilitates the selection of an appropriate metabolite extraction approach based on the experimental purpose for the metabolomics study of skin tissue.

Unravel the Local Complexity of Biological Environments by MALDI Mass Spectrometry Imaging

Classic metabolomic methods have proven to be very useful to study functional biology and variation in the chemical composition of different tissues. However, they do not provide any information in terms of spatial localization within fine structures. Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) does and reaches at best a spatial resolution of 0.25 μm depending on the laser setup, making it a very powerful tool to analyze the local complexity of biological samples at the cellular level. Here, we intend to give an overview of the diversity of the molecules and localizations analyzed using this method as well as to update on the latest adaptations made to circumvent the complexity of samples. MALDI MSI has been widely used in medical sciences and is now developing in research areas as diverse as entomology, microbiology, plant biology, and plant–microbe interactions, the rhizobia symbiosis being the most exhaustively described so far. Those are the fields of interest on which we will focus to demonstrate MALDI MSI strengths in characterizing the spatial distributions of metabolites, lipids, and peptides in relation to biological questions.

Reproducible Lipid Alterations in Patient-Derived Breast Cancer Xenograft FFPE Tissue Identified with MALDI MSI for Pre-Clinical and Clinical Application

The association between lipid metabolism and long-term outcomes is relevant for tumor diagnosis and therapy. Archival material such as formalin-fixed and paraffin embedded (FFPE) tissues is a highly valuable resource for this aim as it is linked to long-term clinical follow-up. Therefore, there is a need to develop robust methodologies able to detect lipids in FFPE material and correlate them with clinical outcomes. In this work, lipidic alterations were investigated in patient-derived xenograft of breast cancer by using a matrix-assisted laser desorption ionization mass spectrometry (MALDI MSI) based workflow that included antigen retrieval as a sample preparation step. We evaluated technical reproducibility, spatial metabolic differentiation within tissue compartments, and treatment response induced by a glutaminase inhibitor (CB-839). This protocol shows a good inter-day robustness (CV = 26 ± 12%). Several lipids could reliably distinguish necrotic and tumor regions across the technical replicates. Moreover, this protocol identified distinct alterations in the tissue lipidome of xenograft treated with glutaminase inhibitors. In conclusion, lipidic alterations in FFPE tissue of breast cancer xenograft observed in this study are a step-forward to a robust and reproducible MALDI-MSI based workflow for pre-clinical and clinical applications.

The potential role of fatty acids in prostate cancer determined by GC-MS analysis of formalin-fixed paraffin-embedded tissue samples

Prostate cancer (PCa) is one of the leading types of cancer in men. Although the diagnosis of this disease is currently quite effective, there is still a need to search for noninvasive diagnostic and monitoring methods. Consequently, identifying the mechanisms underlying the development and progression of PCa is crucial. It has been confirmed that the hallmarks of PCa include changes in metabolism, particularly that of fatty acids. Therefore, the application of lipidomics with an accurate histopathological assessment can provide the necessary information and reveal the metabolites that are characteristic of the disease. The use of formalin-fixed, paraffin-embedded (FFPE) tissue samples as an alternative matrix in retrospective research makes this approach highly innovative. The main goal of this study was to perform an untargeted lipidomic analysis of FFPE PCa tissue samples (n = 52) using gas chromatography coupled with mass spectrometry (GC-MS), in comparison to controls (n = 50). To our knowledge, this study is the first to simultaneously conduct a metabolic analysis and histopathological assessment. In the latter, the samples were evaluated based on Gleason grading score and pTNM stage. The obtained results were evaluated by univariate (Student's t-test or Mann-Whitney U-test) as well as multivariate statistical analysis (principal component analysis, partial least squares-discriminant analysis, variable importance into projection, and selectivity ratio) in order to select the metabolites with the most discriminative power. Additionally, the correlation between the level of metabolites and pathological characteristics was determined. The results of the analyses confirmed the changes in the lipid metabolism pathway in PCa. It can be assumed that PCa is linked with elevated de novo biosynthesis of steroid hormone-related fatty acids and beta-oxidation of fatty acids. An increased level of three fatty acids, namely 9-octadecanoic acid, 9,12-octadecadienoic acid, and 5, 8, 1,14-eicosatetraenoic acid, was observed in the PCa samples. These fatty acids were assigned as metabolites with the best discriminative power for the two tested groups. In practice, these compounds could be considered as specific biochemical factors that may be implemented in the diagnosis of PCa, but their significance should be validated on a more extensive set of samples. Undoubtedly, these results are valuable as they provide important information on prostate cancerogenesis in the context of a metabolic switch.

Targeted metabolomics in formalin-fixed paraffin-embedded tissue specimens: Liquid chromatography-tandem mass spectrometry determination of acidic metabolites in cancer research

Formalin-fixed paraffin-embedded (FFPE) tissues play an irreplaceable role in cancer research. Although extensive research has been conducted for the detection of DNA, RNA and proteins in FFPE samples, literature dealing with the FFPE determination of small molecules is scarce. In this study, we aimed to explore the potential of targeted metabolomics in FFPE specimens. For that purpose, we developed a LC-MS/MS method for the quantification of acidic metabolites in FFPE samples. The method involves trimming tissue slices from FFPE blocks, deparaffinization, lysis of the tissue, o-benzyl hydroxylamine derivatization and LC-MS/MS detection. Deparaffinization and lysis steps were optimized to maximize the analytes extraction and to minimize the effect of the ubiquitous presence of some metabolites in the paraffin. Two validation approaches were applied: (i) using blank paraffin as matrix and (ii) using actual human FFPE tissue samples by standard additions. The method quantified 40 metabolites with appropriate accuracy (commonly 80-120%) and precision (CV 2-19%) in both validation approaches. LLOQs ranging 0.88-2001 pg mg^-1 with low-moderate matrix effects (commonly 85-115%) were obtained. FFPE samples from 15 patients with colorectal cancer were analyzed and metabolites concentrations in tumor vs matched normal FFPE tissues were compared. Results show that tumor tissues have a well-established fingerprint including an increase in ketogenesis, a decrease in lipogenesis and an imbalance in the tricarboxylic acid cycle.

OMICS insights into cancer histology; Metabolomics and proteomics approach

Metabolomics as a post-genomic research area comprising different analytical methods for small molecules analysis. One of the underlying applications of metabolomics technology for better disease diagnosis and prognosis is discovering the metabolic pathway differences between healthy individuals and patients. On the other hand, the other noteworthy applications of metabolomics include its effective role in biomarker screening for cancer detection, monitoring, and prediction. In other words, emerging of the metabolomics field can be hopeful to provide a suitable alternative for the common current cancer diagnostic methods especially histopathological tests. Indeed, cancer as a major global issue places a substantial burden on the health care system. Hence, proper management can be beneficial. In this respect, formalin-fixed paraffin-embedded tissue specimens (in histopathological tests) are considered as a valuable source for metabolomics investigations. Interestingly, formalin-fixed paraffin-embedded tissue specimens can provide informative data for cancer management. In general, using these specimens, determining the cancer stage, individual response to the different therapies, personalized risk prediction are possible and high-quality clinical services are the promise of OMICS technologies for cancer disease. However, considering all of these beneficial characteristics, there are still some limitations in this area that need to be addressed in order to optimize the metabolomics utilizations and advancement.