[Proton nuclear magnetic resonance spectroscopy recognition of metabolic patterns in fecal extracts for early diagnosis of colorectal cancer].

结直肠癌 医学 粪便 内科学 胃肠病学 磁共振成像 代谢组学 阶段(地层学) 接收机工作特性 组织病理学 癌症 病理 放射科 生物信息学 生物 古生物学
作者
Yan Lin,Z N Wang,C C,C K Liu,J R Yang,Zhong Shen,Rongjin Wu
出处
期刊:PubMed [National Institutes of Health]
卷期号:50 (9): 788-793 被引量:1
标识
DOI:10.3760/cma.j.issn.0253-9624.2016.09.008
摘要

Objective: To characterize the metabolic " fingerprint" of fecal extracts for diagnosis of early-stage colorectal cancer(CRC)using proton nuclear magnetic resonance spectroscopy(1H-NMR)-based metabolomics coupled with pattern recognition. Methods: From January 2014 to December 2014, we collected fecal samples at the Second Affiliated Hospital of Shantou University Medical College, from 25 patients with colorectal adenomas(CR-Ad), 20 with stage Ⅰ/Ⅱ CRC, and 32 healthy controls(HCs). The patients were diagnosed by histopathology. No subjects had any complicating diseases. HCs showed no abnormalities from blood tests, endoscopic examination, diagnostic imaging, and/or medical interviews. We excluded participants who used antibiotics, NSAIDS, statins, or probiotics within two months of study participation, and any patients who underwent chemotherapy or radiation treatments prior to surgery. We used orthogonal partial least-squares-discriminant analysis(OPLS-DA)for pattern recognition(dimension reduction)on 1H-NMR processed data(1H frequency of 400.13 MHz), to find metabolic differences among CR-Ad, carcinoma and HC fecal samples; and receiver operating characteristic(ROC)analysis to determine the diagnostic value of the fecal metabolic biomarkers. Results: Fecal samples were collected from 20 patients with Stage Ⅰ/Ⅱ CRC(11 M, 9 F, median age(52±13)years), 25 with CR-Ad(14 M, 11 F, median age(53 ± 11)years)and 32 HCs(15 M, 17 F, median age(53 ± 14)years). OPLS-DA clearly distinguished CR-Ad and stage Ⅰ/Ⅱ CRC from HC samples, based on their metabolomic profiles. Relative signal intensities in HCs were significantly lower than in the cancer patients for butyrate(HC: 23.0±6.0; CR-Ad: 18.0±5.0; CRC: 14.0±6.0; Z=-2.07, P=0.008), acetate(HC: 45.0±11.0; CR-Ad: 31.0±11.0; CRC: 24.0±8.0; Z=- 2.32, P=0.011), propionate(HC: 26.0 ± 7.0; CR-Ad: 22.0 ± 6.0; CRC: 19.0 ± 5.0; Z=- 2.43, P=0.032), glucose(HC: 37.0±7.0; CR-Ad: 31.0±7.0; CRC: 26.0±8.0; Z=-2.07, P=0.044)and glutamine(HC: 4.5±2.0; CR-Ad: 4.9 ± 1.0; CRC: 5.4 ± 1.0; Z=2.21, P=0.044). However, relative signal intensities in HCs were significantly higher than in patients for lactate(HC: 4.8±1.0; CR-Ad: 6.9±2.0; CRC: 4.8± 1.0; Z=2.02, P= 0.038), glutamate(HC: 3.2 ± 2.0; CR-Ad: 4.9 ± 1.0; CRC: 3.2 ± 2.0; Z=2.21, P=0.044)and succinate(HC: 12.0±2.0; CR-Ad: 15.0±3.0; CRC: 12.0± 2.0; Z=2.25, P=0.011). Among the potential biomarkers, acetate at 1.92 ppm, and succinate at 2.41 ppm displayed relatively high area under ROC, with sensitivity and specificity both >90%, to distinguish early-stage CRC patients from HCs. Conclusion: Fecal metabolic profiles distinguish of HCs from patients with CRC patients, even in the early stages(stage Ⅰ/Ⅱ), highlighting the potential of NMR-based fecal metabolomic fingerprinting as tools for early CRC diagnosis.
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