H-1 NMR-based metabolomics of paired tissue, serum and urine samples reveals an optimized panel of biofluids metabolic biomarkers for esophageal cancer

IntroductionThe goal of this study was to establish an optimized metabolic panel by combining serum and urine biomarkers that could reflect the malignancy of cancer tissues to improve the non-invasive diagnosis of esophageal squamous cell cancer (ESCC). MethodsUrine and serum specimens representing the healthy and ESCC individuals, together with the paralleled ESCC cancer tissues and corresponding distant non-cancerous tissues were investigated in this study using the high-resolution 600 MHz 1H-NMR technique. ResultsWe identified distinct 1H NMR-based serum and urine metabolic signatures respectively, which were linked to the metabolic profiles of esophageal-cancerous tissues. Creatine and glycine in both serum and urine were selected as the optimal biofluids biomarker panel for ESCC detection, as they were the overlapping discriminative metabolites across serum, urine and cancer tissues in ESCC patients. Also, the were the major metabolites involved in the perturbation of glycine, serine, and threonine metabolism, the significant pathway alteration associated with ESCC progression. Then a visual predictive nomogram was constructed by combining creatine and glycine in both serum and urine, which exhibited superior diagnostic efficiency (with an AUC of 0.930) than any diagnostic model constructed by a single urine or serum metabolic biomarkers. DiscussionOverall, this study highlighted that NMR-based biofluids metabolomics fingerprinting, as a non-invasive predictor, has the potential utility for ESCC detection. Further studies based on a lager number size and in combination with other omics or molecular biological approaches are needed to validate the metabolic pathway disturbances in ESCC patients.

Automated summary

The aim of this study was to improve the non-invasive diagnosis of esophageal squamous cell cancer (ESCC) by establishing an optimized metabolic panel using serum and urine biomarkers. The researchers used the high-resolution 600 MHz 1H-NMR technique to analyze urine and serum specimens from healthy individuals and ESCC patients. They identified distinct metabolites in serum and urine that were linked to the metabolic profiles of esophageal cancer tissues. Creatine and glycine were identified as the optimal biomarkers for ESCC detection. By combining creatine and glycine in serum and urine, a predictive nomogram with superior diagnostic efficiency was constructed. Overall, this study highlights the potential utility of NMR-based metabolomics in the non-invasive detection of ESCC.