4.3 Article

Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

期刊

ONCOTARGET
卷 8, 期 10, 页码 17115-17126

出版社

IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.15081

关键词

metabolomics; colorectal cancer; biomarker; gas chromatography/triple-quadrupole mass spectrometry; metabolite

资金

  1. Japan Society for the Promotion of Science (JSPS)
  2. JSPS
  3. Practical Research for Innovative Cancer Control from the Japan Agency for Medical Research and Development (AMED)
  4. Medical Research and Development Programs Focused on Technology Transfer: Development of Advanced Measurement and Analysis Systems (SENTAN) from AMED
  5. AMED-CREST from AMED
  6. Grants-in-Aid for Scientific Research [16H05227] Funding Source: KAKEN

向作者/读者索取更多资源

In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N= 79), I (N= 80), and II (N= 123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis.

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