Rapid discrimination of human oesophageal squamous cell carcinoma by mass spectrometry based on differences in amino acid metabolism

Tryptophan Metabolites as Biomarkers for Esophageal Cancer Susceptibility, Metastasis, and Prognosis

BACKGROUND

Perturbation of tryptophan (TRP) metabolism contributes to the immune escape of cancer; however, the explored TRP metabolites are limited, and their efficacy in clarifying the susceptibility and progression of esophageal cancer (EC) remains ambiguous. Our study sought to evaluate the effects of the TRP metabolic profile on the clinical outcomes of EC using a Chinese population cohort; and to develop a risk prediction model targeting TRP metabolism.

METHOD

A total of 456 healthy individuals as control subjects and 393 patients with EC who were followed up for one year as case subjects were enrolled. Quantification of the plasma concentrations of TRP and its metabolites was performed using HPLC-MS/MS. The logistic regression model was applied to evaluate the effects of the clinical characteristics and plasma metabolites of the subjects on susceptibility and tumor metastasis events, whereas Cox regression analysis was performed to assess the overall survival (OS) of the patients.

RESULTS

Levels of creatinine and liver enzymes were substantially correlated with multiple metabolites/metabolite ratios in TRP metabolism, suggesting that hepatic and renal function would exert effects on TRP metabolism. Age- and sex-matched case-control subjects were selected using propensity score matching. Plasma exposure to 5-HT was found to be elevated 3.94-fold in case subjects (N = 166) compared to control subjects (N = 203), achieving an AUC of 0.811 for predicting susceptibility event. Subsequent correlation analysis indicated that a higher plasma exposure to 5-HIAA significantly increased the risk of lymph node metastasis (OR: 2.16, p = 0.0114). Furthermore, it was figured out that OS was significantly shorter for patients with elevated XA/KYN ratio (HR: 1.99, p = 0.0016), in which medium and high levels of XA/KYN versus low level had a significantly lower OS (HR: 0.48, p = 0.0080 and HR: 0.42, p = 0.0031, respectively).

CONCLUSION

This study provides a pivotal basis for targeting endogenous TRP metabolism as a potential therapeutic intervention.

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.

Ambient mass spectrometry for the molecular diagnosis of lung cancer

Lung cancer is one of the most common malignancies and the leading cause of cancer-related death worldwide. Among the technologies suitable for the rapid and accurate molecular diagnosis of lung cancer, ambient mass spectrometry (AMS) has gained increasing interest as it allows the direct profiling of molecular information from various biological samples (e.g., tissue, serum, urine and sputum) in real-time and with minimal or no sample pretreatment. This minireview summarizes the applications of AMS in lung cancer studies (including tissue molecular identification, the discovery of potential biomarkers, and surgical margin assessment), and discusses the challenges and perspectives of AMS in the clinical precision molecular diagnosis of lung cancer.

Selective detection of phospholipids in human blood plasma and single cells for cancer differentiation using dispersed solid-phase microextraction combined with extractive electrospray ionization mass spectrometry

Rapid and selective determination of phospholipids in microvolume biofluid samples for cancer differentiation was achieved by d-SPME–iEESI-MS.

Investigation Of Small Molecular Substances As Potential Biomarkers For Discrimination Of Gastric Tumor

Background

Gastric tumor (GT) is associated with high morbidity and mortality, with surgery among the most effective treatment methods. Accurate interoperative determination of the tumor margin is crucial.

Methods

In this study, using internal extractive electrospray ionization-MS, mass spectral data of GT and gastric normal (GN) tissues from 36 patients were collected.

Results

In positive ion detection mode, the relative abundances of m/z 132, 147, 170, and 175 were increased, while the relative abundances of m/z 55, 83, 154, and 203 were decreased in GT tissue. Using partial least squares analysis, the mass spectral data of GT and GN tissues were discriminated, and differential ions (P≤0.01), including m/z 55, 83, 154, 170, and 203, were obtained from loading plots. After receiver operating characteristic curve analysis, peaks at m/z 83 and 203 showed high accuracy for distinguishing GT from GN tissue. These two peaks were then preliminarily attributed to 5-aminoimidazole and serylproline, respectively, which might be useful molecular biomarkers associated with GT development.

Conclusion

Further investigations of the functions of 5-aminoimidazole and serylproline might provide a better understanding of the underlying mechanisms involved in GT.