Identification of potential metabolite markers for colon cancer and rectal cancer using serum metabolomics

Abstract

Background To determine the metabolic characteristics of patients with colon cancer (CC) and rectal cancer (RC) using gas chromatography‐mass spectrometry (GC‐MS)‐based metabolomics. Methods In this study, serum samples were collected from 22 CC patients and 23 RC patients preoperatively and postoperatively and 45 healthy volunteers (HVs), and subjected to metabolomics analysis by GC‐MS. Differential metabolites in the preoperative RC and CC samples and HVs were identified as potential biomarkers and evaluated for their utilities by receiver operating characteristic analyses. Results The different metabolic markers between CC and RC patients were identified, which may assist in distinguishing the two types of cancers. The area under the curve (AUC) was 0.805 for combination of d‐glucose and d‐mannose for CC diagnosis, and 0.889 for combination of 2‐aminobutanoic acid, 3‐hydroxypyridine, d‐glucose, d‐mannose, isoleucine, l‐tryptophan, urea, and uric acid for RC diagnosis. The combinations of metabolite markers showed a better predictability than CEA and CA199 two commonly used protein markers for CRC diagnosis in clinical practice. Combining the metabolite markers with these two protein markers effectively improved the diagnostic accuracy with the AUC reaching 0.936 and 0.937 for CC and RC diagnosis, respectively. Conclusions Metabolic profiles are different in the blood samples between CC and RC patients. The study has established a panel of metabolic markers as a predictive and multiplexing signature for CC and RC diagnosis.

The Application of Metabolomics in Recent Colorectal Cancer Studies: A State-of-the-Art Review

“…Most studies employed a case-control research design, using either a healthy (carcinoma-free) control, adenomatous polyp group, or both. Twenty-one studies compared CRC directly to healthy control [24][25][26]31,33,36,38,39,[42][43][44][45][46][48][49][50][51][52][53][54]56]. Jing et al and Gao et al, conversely, compared CRC patients to an adenomatous polyp control [32,55] while eleven studies utilized CRC, healthy control, and adenomatous polyp groups [28][29][30]34,35,37,40,41,47,57,58].…”

Predictive Value of Red Blood Cell Distribution Width in Poststroke Depression

“…Its diagnosis is very complicated and is currently only based on clinical parameters. Recent reports have shown that middle-aged PSD patients and stroke survivors without depression have different urine metabolism characteristics [14]. Urine metabolomics can be used to identify potential metabolite markers in patients with poststroke depression in middle-aged patients.…”

Comprehensive analysis of DNA methylation and gene expression profiles in rectal cancer

“…Colorectal cancer (CRC), which encompasses both colon cancer and rectal cancer (RC), is the third most common malignancy worldwide and the second most common cause of cancer-related death, only exceeded by lung cancer [1,2] . Its incidence and mortality have continually increased in recent years [3] . The 5-year survival rate of CRC is still dismal (only 8%-9%) once metastasis has occurred [3] .…”

“…Its incidence and mortality have continually increased in recent years [3] . The 5-year survival rate of CRC is still dismal (only 8%-9%) once metastasis has occurred [3] . RC accounts for approximately 30% of all CRC cases and is associated with worse clinical outcomes [1,4] .…”

“…Crucially, the rectum is enclosed by the pelvis, which elevates the likelihood of the local invasion of nearby tissue compared with colon cancer and increases the chance of local recurrence due to the challenging surgical resection [5,6] . In addition, the spread patterns and treatment strategies differ between colon cancer and RC [3] . Therefore, in contrast to most CRC bioinformatics research, we speci cally focus on RC.…”