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Circulating metabolites as potential biomarkers for the early detection and prognosis surveillance of gastrointestinal cancers

Guodong Song, Li Wang, Junlong Tang, Haohui Li, Shuyu Pang, Yan Li et al. · 2023 · 25 citationsRead the paper

BACKGROUND AND AIMS: Two of the most lethal gastrointestinal (GI) cancers, gastric cancer (GC) and colon cancer (CC), are ranked in the top five cancers that cause deaths worldwide. Most GI cancer deaths can be reduced by earlier detection and more appropriate medical treatment. Unlike the current "gold standard" techniques, non-invasive and highly sensitive screening tests are required for GI cancer diagnosis. Here, we explored the potential of metabolomics for GI cancer detection and the classification of tissue-of-origin, and even the prognosis management. METHODS: Plasma samples from 37 gastric cancer (GC), 17 colon cancer (CC), and 27 non-cancer (NC) patients were prepared for metabolomics and lipidomics analysis by three MS-based platforms. Univariate, multivariate, and clustering analyses were used for selecting significant metabolic features. ROC curve analysis was based on a series of different binary classifications as well as the true-positive rate (sensitivity) and the false-positive rate (1-specificity). RESULTS: GI cancers exhibited obvious metabolic perturbation compared with benign diseases. The differentiated metabolites of gastric cancer (GC) and colon cancer (CC) were targeted to same pathways but with different degrees of cellular metabolism reprogramming. The cancer-specific metabolites distinguished the malignant and benign, and classified the cancer types. We also applied this test to before- and after-surgery samples, wherein surgical resection significantly altered the blood-metabolic patterns. There were 15 metabolites significantly altered in GC and CC patients who underwent surgical treatment, and partly returned to normal conditions. CONCLUSION: Blood-based metabolomics analysis is an efficient strategy for GI cancer screening, especially for malignant and benign diagnoses. The cancer-specific metabolic patterns process the potential for classifying tissue-of-origin in multi-cancer screening. Besides, the circulating metabolites for prognosis management of GI cancer is a promising area of research.

What the full text shows

Shown in the lab
  • Metabolites in the CC and NC groups showed excellent diagnostic ability. — AUC > 0.95 (Comparison of colon cancer (CC) vs. non-cancer (NC) groups)
  • Specific phospholipids and a dihydroxyurs-12-en-28-oic acid distinguished between gastric and colon cancers. — mean AUC > 0.88 (Comparison of GC vs. CC groups)
  • Significant metabolic alterations were identified in colon cancer compared to non-cancer controls. — 245 metabolites altered (CC vs. NC group)
  • Significant metabolic alterations were identified in gastric cancer compared to non-cancer controls. — 133 metabolites altered (GC vs. NC group)
  • Surgical resection significantly altered blood-metabolic patterns in both cancer types. — 15 metabolites significantly altered per case (Before- and after-surgery samples)
Setup
94 plasma samples from 37 gastric cancer (GC), 17 colon cancer (CC), and 27 non-cancer (NC) patients.
How
Untargeted metabolomics and lipidomics were performed on plasma samples using three MS-based platforms (LC-MS polar, LC-MS lipid, and GC-MS). Data were processed using a non-linear autoencoder for batch correction and analyzed via univariate, multivariate, and ROC curve analysis.
Limitations
Small sample size for post-surgical analysis (5 GC and 8 CC patients). · Use of non-cancer patients as controls rather than healthy volunteers may affect reproducibility compared to previous studies.

Summarized by Gemma 4 from the open-access full text · 16 Oct 2026. Read it