A Distinct Metabolic Signature of Human Colorectal Cancer with Prognostic Potential

Abstract

Purpose Metabolic phenotyping has provided important biomarker findings, which, unfortunately, are rarely replicated across different sample sets due to the variations from different analytical and clinical protocols used in the studies. To date, very few metabolic hallmarks in a given cancer type have been confirmed and validated by use of a metabolomic approach and other clinical modalities. Here, we report a metabolomics study to identify potential metabolite biomarkers of colorectal cancer with potential theranostic value. Experimental Design Gas chromatography–time-of-flight mass spectrometry (GC–TOFMS)–based metabolomics was used to analyze 376 surgical specimens, which were collected from four independent cohorts of patients with colorectal cancer at three hospitals located in China and City of Hope Comprehensive Cancer Center in the United States. Differential metabolites were identified and evaluated as potential prognostic markers. A targeted transcriptomic analysis of 29 colorectal cancer and 27 adjacent nontumor tissues was applied to analyze the gene expression levels for key enzymes associated with these shared metabolites. Results A panel of 15 significantly altered metabolites was identified, which demonstrates the ability to predict the rate of recurrence and survival for patients after surgery and chemotherapy. The targeted transcriptomic analysis suggests that the differential expression of these metabolites is due to robust metabolic adaptations in cancer cells to increased oxidative stress as well as demand for energy, and macromolecular substrates for cell growth and proliferation. Conclusions These patients with colorectal cancer, despite their varied genetic background, mutations, pathologic stages, and geographic locations, shared a metabolic signature that is of great prognostic and therapeutic potential.

Heat-Stress-Induced Metabolic Changes and Altered Male Reproductive Function

“…15 The final data set included sample grouping information, peak retention time, and peak area (quant mass) of each metabolic compound. Artificial peaks including column bleed, noise peaks, N,O-bis(trimethylsilyl) trifluoroacetamide (BSTFA) derivatization agents, and other signals known as interference peaks were all removed from the data set.…”

Osteocalcin Signaling in Myofibers Is Necessary and Sufficient for Optimum Adaptation to Exercise

“…Metabolites from freeze-clamped skeletal muscles were extracted, derivatized, and run for GC-TOFMS analysis (Qiu et al, 2014). LC/MS/MS analysis was used to quantify glycolytic and TCA cycle metabolites (Serasinghe et al, 2015).…”

Metabolomics in cell culture—A strategy to study crucial metabolic pathways in cancer development and the response to treatment

“…Like in case of breast cancer, metabolomics has already been applied to human biofluids [29,89,90] and tissue samples [91,92] from colon cancer patients towards the identification of biomarkers suitable for diagnosis and prognosis. A decrease in TCA cycle metabolism and lipid levels, together with increased intermediates of urea cycle metabolism, has been reported in colorectal cancer tissue [91], whereas a metabolic study on plasma samples from healthy individuals versus those suffering from colorectal cancer reported down-regulation in amino acid levels (among others, histidine) and glycerolipid metabolism from cancer patients.…”