Analysis of Intestinal Microflora Combined With DNA Methylation in Stool to Detect Colorectal Cancer

NCT ID: NCT04302363

Last Updated: 2020-03-10

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2018-02-01

Study Completion Date

2021-12-01

Brief Summary

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Introduction: Colorectal cancer (CRC) has the third highest incidence rate and the fourth mortality rate in the world. Traditional colonoscopy as an invasive examination method cannot be widely used in screening for colorectal neoplasia. The fecal immunochemical test has some limitations in sensitivity. Also, race and regional differences may affect results. Abnormality in the composition of the gut microbiota has been implicated as a potentially important etiologic factor in the initiation and progression of colorectal cancer. Analyzing fecal flora and exfoliated cell genes may represent a new screening tool for colorectal cancer.This research aims to use 16S rRNA to compare differences in fecal flora between colorectal cancer patients and healthy controls. These data combined with DNA findings of fecal exfoliated cells may further clarify this difference to build a model for screening early colorectal cancer in Chinese people.

Methods and analysis: In total, 300 patients with positive colonoscopy results and 200 health controls will be recruited. All participants will complete an information form and questionnaires. Fecal samples will be examined by 16S rRNA analysis. Gene methylation levels will be detected in fecal exfoliated cells. Models of related intestinal microbiota and methylation genes will be built. Receiver operating characteristic (ROC) curve analysis will be used to select some models with appropriate sensitivity and specificity.The models will be further validated by multicenter studys.

Detailed Description

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Introduction: Colorectal cancer (CRC) has the third highest incidence rate and the fourth mortality rate in the world. In China, CRC is the fifth leading cause of cancer deaths. Age-standardized incidence rates in CRC have shown an upward trend.A Westernized lifestyle, particularly physical inactivity, and an increase in the prevalence of obesity in recent decades in China may explain the increase in CRC incidence .

The 5-year survival rate for people with CRC is 65%. Survival rates for CRC can vary depending on various factors, particularly cancer stage. The 5-year survival rate with localized-stage CRC is 90%. About 39% of patients are diagnosed at this early stage. Because of the lack of typical clinical symptoms, early CRC is difficult to detect, and most patients are already in the advanced stage when CRC is diagnosed, thus missing the best intervention stage. Therefore, early detection and early treatment are effective means to reduce the mortality with CRC. Screening has benefits, including diagnosis at an earlier stage, reduced incidence of CRC and reduced mortality.

At present, the main screening methods for CRC are fecal occult blood test and colonoscopy. Colonoscopy is the gold standard for screening for CRC. However, traditional colonoscopy, an invasive examination method, cannot be widely used in screening for colorectal neoplasia.

Fecal samples are easily obtained.Using feces to screen CRC is the current research consensus. According to the most updated Asia Pacific consensus recommendations for CRC screening,FIT(fecal immunochemical test) is used to select high-risk patients for colonoscopy. FIT has also been widely used in other world regions . The sensitivity of FIT is limited (0.79; 95% CI, 0.69-0.86), and a recent systematic meta-analysis showed wide variation in sensitivity among studies . In addition, race and regional differences may affect test results. Therefore, the early screening methods which is non-invasive, highly sensitive and suitable for Chinese people are needed.

Detection of molecular biomarkers in feces for non-invasive diagnosis of CRC may be a promising alternative to detecting blood/plasma biomarkers in current clinical settings. Abnormalities in the composition of the gut microbiota have been implicated as potentially important causes of CRC. With the widespread use of metagenomic sequencing and pyrosequencing in intestinal microbiota research, more bacteria have been found positively associated with CRC incidence. In a recent study, 16S rRNA sequencing was used to classify microbial communities in human intestinal mucosa at different stages of colorectal tumorigenesis, and Fusobacterium was found enriched in colorectal tumors.

For CRC, the main process of benign polyps becoming malignant tumors is the accumulation of genetic and epigenetic alterations that transform colonic epithelial cells into colon adenocarcinoma cells. These cells are continuously shed into colonic lumen and mixed with the stool. During tumor formation, epigenetic changes may occur earlier than mutations. Deregulation of epigenetic mechanisms plays an important role in cancer. Most epigenetic changes in cancer are triggered by genomic alterations in specific genes that are involved in controlling one of the epigenetic mechanisms.Aberrant DNA methylation of tumor suppressor genes induces abnormal expression of downstream genes, which is an important step in the process of tumorigenesis.The methylation status of DNA changes during CRC progression. A number of gene methylation abnormalities associated with CRC discovered in recent studies include SFRP2, SEPT9, BMP3, NDRG4, and SPG20. In addition, some gene mutations are related to CRC. For example, TP53 and KRAS mutations are common in CRC.

In previous research the investigators found that SEPT9, NDRG4, and SDC2 had higher frequency and level of methylation in tumors than in normal or non-tumor adjacent CRC tissues, indicating that these methylated genes may have diagnostic potential for CRC screening. However, BMP3 had very limited contribution to detection accuracy in stool samples. Furthermore, the combination of methylated SEPT9, NDRG4, and SDC2 showed high feasibility of detection of CRC and adenoma and further study showed better performance in detecting CRC than adenoma. Our research also demonstrates differences in fecal genes between different ethnic groups.

This research aims to detect intestinal microbiota differences in stool by 16S rRNA analysis between CRC patients and healthy controls. It will combine DNA analysis of fecal exfoliated cells to further clarify this difference to build some models for screening early colorectal cancer in Chinese people. At the same time, the research will also study the impact of Chinese eating habits on Intestinal Microflora.

Conditions

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Gastrointestinal Microbiome DNA Methylation Colorectal Neoplasms

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

RETROSPECTIVE

Study Groups

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Control Group

Healthy controls must be 18-75 years old with no tumors and no history of cancer.

Fecal microbiota detection and exfoliated cell gene detection

Intervention Type OTHER

Fecal microbiota detection and exfoliated cell gene detection

Test Group

Inclusion criteria in the experimental group are age 18-75 years old, colonoscopy revealing colon or rectal tumor, biopsy-confirmed adenocarcinoma or adenoma, no chemotherapy or surgery, and no history of other cancer. Both groups must be able to understand and be willing to sign informed consent.

Fecal microbiota detection and exfoliated cell gene detection

Intervention Type OTHER

Fecal microbiota detection and exfoliated cell gene detection

Interventions

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Fecal microbiota detection and exfoliated cell gene detection

Fecal microbiota detection and exfoliated cell gene detection

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* colonoscopy revealing colon or rectal tumor and biopsy-confirmed adenocarcinoma or adenoma.
* no chemotherapy or surgery, and no history of other cancer.
* must be able to understand and be willing to sign informed consent.
* Healthy controls don't have tumors and history of cancer.

Exclusion Criteria

* Those who not willing to provide specimens or answer questionnaires before the study began.
* People whose stool samples does not meet the requirements.
* People who are unwilling to sign written informed consent or follow a research protocol.
Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Natural Science Foundation of Hunan Province

UNKNOWN

Sponsor Role collaborator

WEIDONG LIU,MD

OTHER

Sponsor Role lead

Responsible Party

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WEIDONG LIU,MD

Director of day surgery center

Responsibility Role SPONSOR_INVESTIGATOR

Principal Investigators

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weidong Liu, PhD

Role: STUDY_CHAIR

Xiangya Hospital of Central South University

mingmei Liao, PhD

Role: STUDY_DIRECTOR

Xiangya Hospital of Central South University

xi Xie, PhD

Role: PRINCIPAL_INVESTIGATOR

Xiangya Hospital of Central South University

jie Chen, PhD

Role: PRINCIPAL_INVESTIGATOR

Xiangya Hospital of Central South University

zhan Qu, PhD

Role: PRINCIPAL_INVESTIGATOR

Xiangya Hospital of Central South University

Locations

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Xiangya Hospital of Central South University

Changsha, Hunan, China

Site Status RECRUITING

Countries

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China

Central Contacts

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weidong Liu, PhD

Role: CONTACT

86-13873124855

mingmei Liao, PhD

Role: CONTACT

86-15388023797

Facility Contacts

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Liu wei dong, doctor

Role: primary

0086-13873124855

References

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Brenner H, Kloor M, Pox CP. Colorectal cancer. Lancet. 2014 Apr 26;383(9927):1490-1502. doi: 10.1016/S0140-6736(13)61649-9. Epub 2013 Nov 11.

Reference Type RESULT
PMID: 24225001 (View on PubMed)

Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016 Mar-Apr;66(2):115-32. doi: 10.3322/caac.21338. Epub 2016 Jan 25.

Reference Type RESULT
PMID: 26808342 (View on PubMed)

Varghese C, Shin HR. Strengthening cancer control in China. Lancet Oncol. 2014 Apr;15(5):484-5. doi: 10.1016/S1470-2045(14)70056-7. No abstract available.

Reference Type RESULT
PMID: 24731401 (View on PubMed)

Wang YX, Zhu N, Zhang CJ, Wang YK, Wu HT, Li Q, Du K, Liao DF, Qin L. Friend or foe: Multiple roles of adipose tissue in cancer formation and progression. J Cell Physiol. 2019 Dec;234(12):21436-21449. doi: 10.1002/jcp.28776. Epub 2019 May 3.

Reference Type RESULT
PMID: 31054175 (View on PubMed)

Siegel RL, Miller KD, Fedewa SA, Ahnen DJ, Meester RGS, Barzi A, Jemal A. Colorectal cancer statistics, 2017. CA Cancer J Clin. 2017 May 6;67(3):177-193. doi: 10.3322/caac.21395. Epub 2017 Mar 1.

Reference Type RESULT
PMID: 28248415 (View on PubMed)

Hewitson P, Glasziou P, Watson E, Towler B, Irwig L. Cochrane systematic review of colorectal cancer screening using the fecal occult blood test (hemoccult): an update. Am J Gastroenterol. 2008 Jun;103(6):1541-9. doi: 10.1111/j.1572-0241.2008.01875.x. Epub 2008 May 13.

Reference Type RESULT
PMID: 18479499 (View on PubMed)

Sung JJ, Lau JY, Young GP, Sano Y, Chiu HM, Byeon JS, Yeoh KG, Goh KL, Sollano J, Rerknimitr R, Matsuda T, Wu KC, Ng S, Leung SY, Makharia G, Chong VH, Ho KY, Brooks D, Lieberman DA, Chan FK; Asia Pacific Working Group on Colorectal Cancer. Asia Pacific consensus recommendations for colorectal cancer screening. Gut. 2008 Aug;57(8):1166-76. doi: 10.1136/gut.2007.146316.

Reference Type RESULT
PMID: 18628378 (View on PubMed)

Lee JK, Liles EG, Bent S, Levin TR, Corley DA. Accuracy of fecal immunochemical tests for colorectal cancer: systematic review and meta-analysis. Ann Intern Med. 2014 Feb 4;160(3):171. doi: 10.7326/M13-1484.

Reference Type RESULT
PMID: 24658694 (View on PubMed)

Liang Q, Chiu J, Chen Y, Huang Y, Higashimori A, Fang J, Brim H, Ashktorab H, Ng SC, Ng SSM, Zheng S, Chan FKL, Sung JJY, Yu J. Fecal Bacteria Act as Novel Biomarkers for Noninvasive Diagnosis of Colorectal Cancer. Clin Cancer Res. 2017 Apr 15;23(8):2061-2070. doi: 10.1158/1078-0432.CCR-16-1599. Epub 2016 Oct 3.

Reference Type RESULT
PMID: 27697996 (View on PubMed)

Carmona FJ, Azuara D, Berenguer-Llergo A, Fernandez AF, Biondo S, de Oca J, Rodriguez-Moranta F, Salazar R, Villanueva A, Fraga MF, Guardiola J, Capella G, Esteller M, Moreno V. DNA methylation biomarkers for noninvasive diagnosis of colorectal cancer. Cancer Prev Res (Phila). 2013 Jul;6(7):656-65. doi: 10.1158/1940-6207.CAPR-12-0501. Epub 2013 May 21.

Reference Type RESULT
PMID: 23694962 (View on PubMed)

Maleszewska M, Wojtas B, Kaminska B. Deregulation of epigenetic mechanisms in cancer. Postepy Biochem. 2018 Oct 15;64(2):148-156. doi: 10.18388/pb.2018_125.

Reference Type RESULT
PMID: 30656897 (View on PubMed)

Park SK, Baek HL, Yu J, Kim JY, Yang HJ, Jung YS, Choi KY, Kim H, Kim HO, Jeong KU, Chun HK, Kim K, Park DI. Is methylation analysis of SFRP2, TFPI2, NDRG4, and BMP3 promoters suitable for colorectal cancer screening in the Korean population? Intest Res. 2017 Oct;15(4):495-501. doi: 10.5217/ir.2017.15.4.495. Epub 2017 Oct 23.

Reference Type RESULT
PMID: 29142517 (View on PubMed)

deVos T, Tetzner R, Model F, Weiss G, Schuster M, Distler J, Steiger KV, Grutzmann R, Pilarsky C, Habermann JK, Fleshner PR, Oubre BM, Day R, Sledziewski AZ, Lofton-Day C. Circulating methylated SEPT9 DNA in plasma is a biomarker for colorectal cancer. Clin Chem. 2009 Jul;55(7):1337-46. doi: 10.1373/clinchem.2008.115808. Epub 2009 Apr 30.

Reference Type RESULT
PMID: 19406918 (View on PubMed)

Melotte V, Lentjes MH, van den Bosch SM, Hellebrekers DM, de Hoon JP, Wouters KA, Daenen KL, Partouns-Hendriks IE, Stessels F, Louwagie J, Smits KM, Weijenberg MP, Sanduleanu S, Khalid-de Bakker CA, Oort FA, Meijer GA, Jonkers DM, Herman JG, de Bruine AP, van Engeland M. N-Myc downstream-regulated gene 4 (NDRG4): a candidate tumor suppressor gene and potential biomarker for colorectal cancer. J Natl Cancer Inst. 2009 Jul 1;101(13):916-27. doi: 10.1093/jnci/djp131. Epub 2009 Jun 17.

Reference Type RESULT
PMID: 19535783 (View on PubMed)

Okada S, Hata K, Kawai K, Yamamoto Y, Tanaka T, Nishikawa T, Sasaki K, Kaneko M, Emoto S, Murono K, Nozawa H. Association between KRAS G13D mutations and anastomotic recurrence in colorectal cancer: Two case reports. Medicine (Baltimore). 2019 Mar;98(12):e14781. doi: 10.1097/MD.0000000000014781.

Reference Type RESULT
PMID: 30896620 (View on PubMed)

Zeng N, Xiang J. Detection of KRAS G12D point mutation level by anchor-like DNA electrochemical biosensor. Talanta. 2019 Jun 1;198:111-117. doi: 10.1016/j.talanta.2019.01.105. Epub 2019 Jan 31.

Reference Type RESULT
PMID: 30876538 (View on PubMed)

Chen J, Sun H, Tang W, Zhou L, Xie X, Qu Z, Chen M, Wang S, Yang T, Dai Y, Wang Y, Gao T, Zhou Q, Song Z, Liao M, Liu W. DNA methylation biomarkers in stool for early screening of colorectal cancer. J Cancer. 2019 Aug 28;10(21):5264-5271. doi: 10.7150/jca.34944. eCollection 2019.

Reference Type RESULT
PMID: 31602277 (View on PubMed)

Rasmussen L, Wilhelmsen M, Christensen IJ, Andersen J, Jorgensen LN, Rasmussen M, Hendel JW, Madsen MR, Vilandt J, Hillig T, Klaerke M, Munster AM, Andersen LM, Andersen B, Hornung N, Erlandsen EJ, Khalid A, Nielsen HJ. Protocol Outlines for Parts 1 and 2 of the Prospective Endoscopy III Study for the Early Detection of Colorectal Cancer: Validation of a Concept Based on Blood Biomarkers. JMIR Res Protoc. 2016 Sep 13;5(3):e182. doi: 10.2196/resprot.6346.

Reference Type RESULT
PMID: 27624815 (View on PubMed)

Liu S, Wen L, Hou J, Nie S, Zhou J, Cao F, Lu Q, Qin Y, Fu Y, Yu X. Predicting the pathological response to chemoradiotherapy of non-mucinous rectal cancer using pretreatment texture features based on intravoxel incoherent motion diffusion-weighted imaging. Abdom Radiol (NY). 2019 Aug;44(8):2689-2698. doi: 10.1007/s00261-019-02032-0.

Reference Type RESULT
PMID: 31030244 (View on PubMed)

Other Identifiers

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CCRS-2

Identifier Type: -

Identifier Source: org_study_id

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