Metabolic Profiling of Human Colorectal Cancer Using High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HR-MAS NMR) Spectroscopy and Gas Chromatography Mass Spectrometry (GC/MS)

Abstract

Current clinical strategy for staging and prognostication of colorectal cancer (CRC) relies mainly upon the TNM or Duke system. This clinicopathological stage is a crude prognostic guide because it reflects in part the delay in diagnosis in the case of an advanced cancer and gives little insight into the biological characteristics of the tumor. We hypothesized that global metabolic profiling (metabonomics/metabolomics) of colon mucosae would define metabolic signatures that not only discriminate malignant from normal mucosae, but also could distinguish the anatomical and clinicopathological characteristics of CRC. We applied both high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) and gas chromatography mass spectrometry (GC/MS) to analyze metabolites in biopsied colorectal tumors and their matched normal mucosae obtained from 31 CRC patients. Orthogonal partial least-squares discriminant analysis (OPLS-DA) models generated from metabolic profiles obtained by both analytical approaches could robustly discriminate normal from malignant samples (Q(2) > 0.50, Receiver Operator Characteristic (ROC) AUC >0.95, using 7-fold cross validation). A total of 31 marker metabolites were identified using the two analytical platforms. The majority of these metabolites were associated with expected metabolic perturbations in CRC including elevated tissue hypoxia, glycolysis, nucleotide biosynthesis, lipid metabolism, inflammation and steroid metabolism. OPLS-DA models showed that the metabolite profiles obtained via HR-MAS NMR could further differentiate colon from rectal cancers (Q(2)> 0.60, ROC AUC = 1.00, using 7-fold cross validation). These data suggest that metabolic profiling of CRC mucosae could provide new phenotypic biomarkers for CRC management.

Tissue metabolomic fingerprinting reveals metabolic disorders associated with human gastric cancer morbidity

“…The use of GC/MS in the metabolic profiling of esophageal cancer (19), colorectal cancer (10,26,27,35), liver cancer (16), bladder cancer (30) and ovarian cancer (32) has been reported, while few studies have investigated the metabolic profiles of GC tissue. This study explored the metabolic fingerprinting of GC tumor specimens and their matched normal mucosa.…”

“…OpLs-DA modeling for the observation of overall separation trends between cancer and non-cancer cohorts has been adopted in human colorectal and bladder cancer (26,27,30,35). previous studies indicate that the supervised model is a robust model for discrimination.…”

Evaluation of High Resolution Magic-Angle Coil Spinning NMR Spectroscopy for Metabolic Profiling of Nanoliter Tissue Biopsies

“…Moreover, it enables enriching the biochemical information from a single tissue biopsy, and offers an improved disease assessment. 23 Another area where MACS could also be of benefit, besides human or animal studies, is examination of single small …”

Study of Metabolic Profiling Changes in Colorectal Cancer Tissues Using 1D1H HR-MAS NMR Spectroscopy

“…In previous reports, human colorectal cancer was related to several biomarkers, such as butyrate, acetate, lipids (saturated and unsaturated), cholinecontaining compounds, and amino acids (e.g., leucine, proline, cysteine). 2 The presence of these biomarkers varies depending on the type and species of the sample. For instance, Monleón et al 47 showed that in human fecal water extracts, normal and cancer samples showed different contents of butyrate, acetate, leucine, proline, and cysteine as determined by NMR spectroscopy.…”

“…For instance, Monleón et al 47 showed that in human fecal water extracts, normal and cancer samples showed different contents of butyrate, acetate, leucine, proline, and cysteine as determined by NMR spectroscopy. Chan et al 2 showed that human tissue samples contained lipids, choline-containing compounds, taurine, scyllo-inositol, glycine, polyethylene glycol, phosphoethanolamine, phosphocholine, lactate, and glucose using HR-MAS NMR analysis. In the present study, we investigated the differences between normal and cancerous colorectal tissue using HR-MAS NMR spectroscopy with two different analysis methods; target profiling and multivariate analysis techniques.…”