Ex vivo HR-MAS Magnetic Resonance Spectroscopy of human gastric adenocarcinomas: a comparison with healthy gastric mucosa

Characterization of lipomatous tumors with high-resolution 1H MRS at 17.6T: Do benign lipomas, atypical lipomatous tumors and liposarcomas have a distinct metabolic signature?

Background

Distinguishing between some benign lipomas (BLs), atypical lipomatous tumors (ALTs), and dedifferentiated liposarcomas (DDLs) can be challenging due to overlapping magnetic resonance imaging characteristics, and poorly understood molecular mechanisms underlying the malignant transformation of liposarcomas.

Purpose

To identify metabolic biomarkers of the lipomatous tumor spectrum by examining human tissue specimens using high-resolution ¹H magnetic resonance spectroscopy (MRS).

Materials and methods

In this prospective study, human tissue specimens were obtained from participants who underwent surgical resection for radiologically-indeterminate lipomatous tumors between November 2016 and May 2019. Tissue specimens were obtained from normal subcutaneous fat (n=9), BLs (n=10), ALTs (n=7) and DDLs (n=8). Extracts from specimens were examined with high-resolution MRS at 17.6T. Computational modeling of pattern recognition-based cluster analysis was utilized to identify significant differences in metabolic signatures between the lipomatous tumor types.

Results

Significant differences between BLs and ALTs were observed for multiple metabolites, including leucine, valine, branched chain amino acids, alanine, acetate, glutamine, and formate. DDLs were distinguished from ALTs by increased glucose and lactate, and increased phosphatidylcholine. Multivariate principal component analysis showed clear clustering identifying distinct metabolic signatures of the tissue types.

Conclusion

Metabolic signatures identified in ¹H MR spectra of lipomatous tumors provide new insights into malignant progression and metabolic targeting. The metabolic patterns identified provide the foundation of developing noninvasive MRS or PET imaging biomarkers to distinguish between BLs, ALTs, and DDLs.

Identification of 14 Differentially-Expressed Metabolism-Related Genes as Potential Targets of Gastric Cancer by Integrated Proteomics and Transcriptomics

Although research on the metabolism related to gastric cancer (GC) is gradually gaining increasing interest, there are few studies regarding metabolism-related genes in GC. Understanding the characteristic changes of metabolism-related genes at the transcriptional and protein levels in GC will help us to identify new biomarkers and novel therapeutic targets. We harvested six pairs of samples from GC patients and evaluated the differentially expressed proteins using mass spectrometry-based proteomics. RNA sequencing was conducted simultaneously to detect the corresponding expression of mRNAs, and bioinformatics analysis was used to reveal the correlation of significant differentially expressed genes. A total of 57 genes were observed to be dysregulated both in proteomics and transcriptomics. Bioinformatics analysis showed that these differentially expressed genes were significantly associated with regulating metabolic activity. Further, 14 metabolic genes were identified as potential targets for GC patients and were related to immune cell infiltration. Moreover, we found that dysregulation of branched-chain amino acid transaminase 2 (BCAT2), one of the 14 differentially expressed metabolism-related genes, was associated with the overall survival time in GC patients. We believe that this study provides comprehensive information to better understand the mechanism underlying the progression of GC metastasis and explores the potential therapeutic and prognostic metabolism-related targets for GC.

A systematic review of metabolomic profiling of gastric cancer and esophageal cancer

Objective: Upper gastrointestinal (UGI) cancers, predominantly gastric cancer (GC) and esophageal cancer (EC), are malignant tumor types with high morbidity and mortality rates. Accumulating studies have focused on metabolomic profiling of UGI cancers in recent years. In this systematic review, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with GC and EC.

Methods: A systematic search of three databases (Embase, PubMed, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of GC and EC was conducted. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included articles.

Results: A total of 52 original studies were included for review. A number of metabolites were differentially distributed between GC and EC cases and non-cases, including those involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and protein and lipid metabolism. Lactic acid, glucose, citrate, and fumaric acid were among the most frequently reported metabolites of cellular respiration while glutamine, glutamate, and valine were among the most commonly reported amino acids. The lipid metabolites identified previously included saturated and unsaturated free fatty acids, aldehydes, and ketones. However, the key findings across studies to date have been inconsistent, potentially due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group.

Conclusions: Studies on metabolomics have thus far provided insights into etiological factors and biomarkers for UGI cancers, supporting the potential of applying metabolomic profiling in cancer prevention and management efforts.

Shared and unique metabolic features of the malignant and benign thyroid lesions determined with use of 1H HR MAS NMR spectroscopy

The purpose of this work was to investigate the distinct and common metabolic features of the malignant and benign thyroid lesions in reference to the non-transformed tissue from the contralateral gland (chronic thyroiditis and colloid goiter). 1H HR MAS NMR spectra of 38 malignant lesions, 32 benign lesions and 112 samples from the non-tumoral tissue (32 from chronic thyroiditis and 80 samples from colloid goiter) were subjected both to multivariate and univariate analysis. The increased succinate, glutamine, glutathione, serine/cysteine, ascorbate, lactate, taurine, threonine, glycine, phosphocholine/glycerophosphocholine and decreased lipids were found in both lesion types in comparison to either colloid goiter or chronic thyroiditis. The elevated glutamate and choline, and reduced citrate and glucose were additionally evident in these lesions in reference to goiter, while the increased myo-inositol-in comparison to thyroiditis. The malignant lesions were characterized by the higher alanine and lysine levels than colloid goiter and thyroiditis, while scyllo-inositol was uniquely increased in the benign lesions (not in cancer) in comparison to both non-tumoral tissue types. Moreover, the benign lesions presented with the unique increase of choline in reference to thyroiditis (not observed in the cancerous tissue). The metabolic heterogeneity of the non-tumoral tissue should be considered in the analysis of metabolic reprogramming in the thyroid lesions.

Metabolic reprogramming results in abnormal glycolysis in gastric cancer: a review

The Warburg effect in tumor cells involves the uptake of high levels of glucose, enhanced glycolysis, and the metabolism of pyruvate to lactic acid rather than oxidative phos-phorylation to generate energy under aerobic conditions. This effect is closely related to the occurrence, invasion, metastasis, drug resistance, and poor prognosis of gastric cancer (GC). Current research has further demonstrated that the Warburg effect in GC cells is not only mediated by the glycolysis pathway, but also includes roles for mitochondria, noncoding RNAs, and other proteins that do not directly regulate metabolism. As a result, changes in the glycolysis pathway not only lead to abnormal glucose metabolism, but they also affect mitochondrial functions, cellular processes such as apoptosis and cell cycle regulation, and the metabolism of lipids and amino acids. In this review, we discuss metabolic reprogramming in GC based on glycolysis, a possible link between glucose metabolism, lipid metabolism, and amino acid metabolism, and we clarify the role of mitochondria. We also examine recent studies of metabolic inhibitors in GC.

HR-MAS NMR tissue metabolomic signatures cross-validated by mass spectrometry distinguish bladder cancer from benign disease

Effective diagnosis and surveillance of bladder cancer (BCa) is currently challenged by detection methods that are of poor sensitivity, particularly for low-grade tumors, resulting in unnecessary invasive procedures and economic burden. We performed HR-MAS NMR-based global metabolomic profiling and applied unsupervised principal component analysis (PCA) and hierarchical clustering performed on NMR data set of bladder-derived tissues and identified metabolic signatures that differentiate BCa from benign disease. A partial least-squares discriminant analysis (PLS-DA) model (leave-one-out cross-validation) was used as a diagnostic model to distinguish benign and BCa tissues. Receiver operating characteristic curve generated either from PC1 loadings of PCA or from predicted Y-values resulted in an area under curve of 0.97. Relative quantification of more than 15 tissue metabolites derived from HR-MAS NMR showed significant differences (P < 0.001) between benign and BCa samples. Noticeably, striking metabolic signatures were observed even for early stage BCa tissues (Ta-T1), demonstrating the sensitivity in detecting BCa. With the goal of cross-validating metabolic signatures derived from HR-MAS NMR, we utilized the same tissue samples to analyze 8 metabolites through gas chromatography-mass spectrometry (GC-MS)-targeted analysis, which undoubtedly complements HR-MAS NMR-derived metabolomic information. Cross-validation through GC-MS clearly demonstrates the utility of a straightforward, nondestructive, and rapid HR-MAS NMR technique for clinical diagnosis of BCa with even greater sensitivity. In addition to its utility as a diagnostic tool, these studies will lead to a better understanding of aberrant metabolic pathways in cancer as well as the design and implementation of personalized cancer therapy through metabolic modulation.

Magic angle spinning NMR-based metabolic profiling of head and neck squamous cell carcinoma tissues

High-resolution magic-angle spinning (HR-MAS) proton NMR spectroscopy is used to explore the metabolic signatures of head and neck squamous cell carcinoma (HNSCC) which included matched normal adjacent tissue (NAT) and tumor originating from tongue, lip, larynx and oral cavity, and associated lymph-node metastatic (LN-Met) tissues. A total of 43 tissues (18 NAT, 18 Tumor and 7 LN-Met) from 22 HNSCC patients were analyzed. Principal Component Analysis of NMR data showed a clear classification between NAT and tumor tissues, however, LN-Met tissues were classified among tumor. A partial least-squares discriminant analysis model generated from NMR metabolic profiles was used to differentiate normal from tumor samples (Q(2) > 0.80, Receiver Operator Characteristic area under the curve >0.86, using 7-fold cross validation). HNSCC and LN-Met tissues showed elevated levels of lactate, amino acids including leucine, isoleucine, valine, alanine, glutamine, glutamate, aspartate, glycine, phenylalanine and tyrosine, choline containing compounds, creatine, taurine, glutathione, and decreased levels of triglycerides. These elevated metabolites were associated with highly active glycolysis, increased amino acids influx (anaplerosis) into the TCA cycle, altered energy metabolism, membrane choline phospholipid metabolism, and oxidative and osmotic defense mechanisms. Moreover, decreased levels of triglycerides may indicate lipolysis followed by β-oxidation of fatty acids that may exist to deliver bioenergy for rapid tumor cell proliferation and growth.

Biochemical alterations from normal mucosa to gastric cancer by ex vivo magnetic resonance spectroscopy

BACKGROUND AND AIMS

The metabolic profile and morphologic aspects of normal and pathologic human gastric mucosa were studied. The aim of the present research was the application of ex vivo high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) to the human gastric tissue to get information on the molecular steps involved in gastric carcinogenesis and the identification of biochemical markers useful for the development of in vivo MRS methodologies to diagnose gastric pathologies in clinical situations.

METHODS

Twelve normal subjects, five with autoimmune atrophic gastritis, five with Helicobacter pylori infection, and five with adenocarcinoma were examined. Ten biopsies were taken during endoscopy from each patient. Specimens from carcinoma were also obtained during gastrectomy. Of the 10 biopsies, 4 were used for histologic evaluation, 4 were fixed in glutaraldehyde and processed for transmission and scanning electron microscopy, and 2 were immersed in liquid nitrogen and stored at -85 degrees C for monodimensional and bidimensional ex vivo HR-MAS MRS analysis.

RESULTS

Ex vivo HR-MAS MRS identified glycine, alanine, free choline, and triglycerides as possible molecular markers related to the human gastric mucosa differentiation toward preneoplastic and neoplastic conditions. Ultrastructural studies of autoimmune atrophic gastritis and gastric adenocarcinoma revealed lipid accumulations intracellularly and extracellularly associated with a severe prenecrotic hypoxia and mitochondria degeneration.

CONCLUSIONS

This is the first report of synergic applications of ex vivo HR-MAS MRS and electron microscopy in studying the human gastric mucosa differentiation. This research provides useful information about some molecular steps involved in gastric carcinogenesis. The biochemical data obtained on gastric pathologic tissue could represent the basis for clinical applications of in vivo MRS.