Validation of Urinary Charged Metabolite Profiles in Colorectal Cancer Using Capillary Electrophoresis-Mass Spectrometry

Abstract

This study aimed to validate and reanalyze urinary biomarkers for detecting colorectal cancers (CRCs). We previously conducted urinary metabolomic analyses using capillary electrophoresis-mass spectrometry and found a significant difference in various metabolites, especially polyamines, between patients with CRC and healthy controls (HC). We analyzed additional samples and confirmed consistency between the newly and previously analyzed data. In total, we included 36 HC, 34 adenoma (AD), and 214 CRC samples, which were used for subsequent analyses. Among the 132 quantified metabolites, 16 exhibited consistent differences in both datasets, which included polyamines, etc. Pathway analyses of the integrated data revealed significant differences in many metabolites, such as glutamine, and metabolites of the TCA and urea cycles. The discrimination ability of the combination of multiple metabolites among the three groups was evaluated, which yielded higher sensitivity than tumor markers. The Mann–Whitney test was employed to evaluate the prognosis predictivity of the assessed metabolites and the difference between the patients with or without recurrence, which yielded 16 significantly different metabolites. Among these 16 metabolites, 11 presented significant prognosis predictivity. These data indicated the potential of metabolite-based discrimination of patients with CRC and AD from HC and prognosis predictivity of the monitored metabolites.

Salivary Metabolomics for Oral Cancer Detection: A Narrative Review

“…Polyamine levels were consistently elevated in both pancreatic tissues and urine samples Conventionally, only N 1 , N 12 -diacetylspermine was evaluated as a biomarker; however, a combination of various acetylated forms of urinary polyamines showed potential in screening various cancers [ 91 ]. Similar data have been reported in colon cancer cohorts [ 92 , 93 ]. Therefore, cancer-type specificity should be rigorously evaluated.…”

Salivary metabolomics with machine learning for colorectal cancer detection

“…We previously reported the high polyamines in the urine collected from CRC patients as a valuable biomarker. 20 , 22 The synthesis of polyamines is attributed to various pathways, with the activation of ornithine decarboxylase that converts ornithine to putrescine in cancer cells largely affecting the polyamine contents. 52 The activation of acetylation of spermine and spermidine resulted in high level of their acetylated forms, which spread to the scrounging biofluid (Figure S4 ).…”

“…In both ML models, acetylated polyamines were selected as predictive features. We previously reported the high polyamines in the urine collected from CRC patients as a valuable biomarker 20,22 . The synthesis of polyamines is attributed to various pathways, with the activation of ornithine decarboxylase that converts ornithine to putrescine in cancer cells largely affecting the polyamine contents 52 .…”

“… 15 , 16 , 17 Therefore, the metabolites in biofluids including blood and saliva that reflect these metabolic aberrances associated with CRC have been analyzed to establish a novel set of biomarkers. 18 , 19 , 20 , 21 , 22 , 23 , 24 …”

“…[15][16][17] Therefore, the metabolites in biofluids including blood and saliva that reflect these metabolic aberrances associated with CRC have been analyzed to establish a novel set of biomarkers. [18][19][20][21][22][23][24] Saliva is an ideal biofluid that enables various disease detections. 25 However, salivary components are expected to be fragile compared with those from other biofluids.…”