Improved diagnosis of colorectal cancer using combined biomarkers including Fusobacterium nucleatum, fecal occult blood, transferrin, CEA, CA19‐9, gender, and age
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Published:2023-05-10
Issue:13
Volume:12
Page:14636-14645
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ISSN:2045-7634
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Container-title:Cancer Medicine
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language:en
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Short-container-title:Cancer Medicine
Author:
Zhao Ran1ORCID,
Xia Dongge2,
Chen Yingwei1,
Kai Zhentian3,
Ruan Fangying3,
Xia Chaoran3,
Gong Jingkai1,
Wu Jun4ORCID,
Wang Xueliang1
Affiliation:
1. Shanghai Center for Clinical Laboratory Shanghai China
2. Department of Clinical Laboratory Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine Shanghai China
3. Zhejiang Shaoxing Topgen Biomedical Technology CO., LTD. Shanghai China
4. Department of Clinical Laboratory Shanghai General Hospital Jiading Branch, Shanghai Jiao Tong University School of Medicine Shanghai China
Abstract
AbstractBackgroundConventional blood and stool tests are normally used for early screening of colorectal cancer (CRC) but the accuracy and efficiency remain to be improved. Recent findings suggest Fusobacterium nucleatum to be a biomarker for CRC. This study evaluated the role of F. nucleatum and developed CRC diagnostic models by combining F. nucleatum with fecal occult blood (FOB), transferrin (TRF), carcinoembryonic antigen (CEA), carbohydrate antigen 19‐9 (CA19‐9), gender, and age.Materials and MethodsCandidates including 71 healthy individuals and 59 CRC patients were recruited. Abundance of F. nucleatum in stool or tissue samples was measured by quantitative real‐time PCR. CEA, CA19‐9, TRF, and FOB were measured in parallel. These biomarkers together with genders and ages were the seven parameters used to develop CRC diagnostic models. Ten different machine learning algorithms were tested to achieve the best performance.ResultsFecal F. nucleatum abundance was found significantly higher in CRC group compared to healthy group (p = 0.0005). Among the CRC patients, F. nucleatum abundance in tumor tissue was significantly higher than that in paracancerous tissue (p = 0.0087). CRC diagnostic models using different parameters were generated based on Logistic Regression algorithm, which showed good performance. The area under the curve (AUC) score of fecal F. nucleatum as the single diagnostic biomarker was 0.68 while the accuracy was 0.56. The diagnostic performance was obviously improved with the highest AUC (0.93) and accuracy (0.87) achieved when using all the 7 clinical parameters. The combination F. nucleatum + FOB + gender + age had the second highest AUC (0.92) and accuracy (0.85). A more utilitarian model using F. nucleatum + FOB showed relatively high AUC at 0.86 and accuracy at 0.81.ConclusionsF. nucleatum is valuable for CRC diagnosis. Combination of different clinical parameters could significantly improve CRC diagnostic performance. The combination F. nucleatum + FOB + gender + age may be an effective and noninvasive method for clinical application.
Funder
Natural Science Foundation of Shanghai
Subject
Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology
Cited by
2 articles.
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