Development of Novel Gastric Cancer Screening and Diagnosis Technologies Using Tongue Imaging and Study of Tongue Image Changes Mechanisms

In this study, the investigators will prospectively recruit 100,000 individuals, including gastric cancer patients who have not undergone any anti-tumor treatment and non-gastric cancer participants. The investigators will construct a diagnostic model for malignant tumors based on the combination of tongue imaging, tongue coating, saliva, gastric juice, and fecal multi-omics data (including metagenomics, proteomics, metabolomics, etc.). Additionally, the study will explore the relationship between oral, gastric, and intestinal microbiota and the development of malignant tumors.

Sex

All

Minimum age

18 Years

Maximum age

90 Years

Inclusion Criteria for Gastric Cancer Patients:

* 18≤age≤90
* Histologically or cytologically confirmed gastric cancer
* No prior chemotherapy, radiotherapy, biotherapy, immunotherapy or other anti-tumor treatment for gastric cancer
* Subject volunteers to join the study, Signs informed consent, has good compliance and can cooperate with follow-up

Exclusion Criteria for Gastric Cancer Patients:

* Two or more kinds of malignant tumors at the same time
* Gastric cancer that has been treated by chemotherapy, radiotherapy, biotherapy, immunotherapy or other anti-tumor therapy
* The use of glucocorticoids and antibiotics in the past three months
* History of long-term medication
* Presence of oral diseases such as tooth and gum diseases
* Subjects who had other factors that might force them to terminate the research ahead of time, such as the development of other severe disease (including mental disease) that required combined treatment, seriously abnormal laboratory examination value, and family or social factors that might affect the subject safety or experimental data collection, as judged by the researchers

Inclusion Criteria for Healthy Participants:

* 18≤age≤90
* Willingness to participate in the study, signing an informed consent form, and demonstrating good compliance

Exclusion Criteria for Healthy Participants:

* History of malignant tumors
* The use of glucocorticoids and antibiotics in the past three months
* History of long-term medication
* Presence of oral diseases such as tooth and gum diseases
* Subjects who had other factors that might force them to terminate the research ahead of time, such as the development of other severe disease (including mental disease) that required combined treatment, seriously abnormal laboratory examination value, and family or social factors that might affect the subject safety or experimental data collection, as judged by the researchers

• RESULTYuan L, Yang L, Zhang S, Xu Z, Qin J, Shi Y, Yu P, Wang Y, Bao Z, Xia Y, Sun J, He W, Chen T, Chen X, Hu C, Zhang Y, Dong C, Zhao P, Wang Y, Jiang N, Lv B, Xue Y, Jiao B, Gao H, Chai K, Li J, Wang H, Wang X, Guan X, Liu X, Zhao G, Zheng Z, Yan J, Yu H, Chen L, Ye Z, You H, Bao Y, Cheng X, Zhao P, Wang L, Zeng W, Tian Y, Chen M, You Y, Yuan G, Ruan H, Gao X, Xu J, Xu H, Du L, Zhang S, Fu H, Cheng X. Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study. EClinicalMedicine. 2023 Feb 6;57:101834. doi: 10.1016/j.eclinm.2023.101834. eCollection 2023 Mar. PMID 36825238
• RESULTSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4. PMID 33538338
• RESULTWang FH, Zhang XT, Li YF, Tang L, Qu XJ, Ying JE, Zhang J, Sun LY, Lin RB, Qiu H, Wang C, Qiu MZ, Cai MY, Wu Q, Liu H, Guan WL, Zhou AP, Zhang YJ, Liu TS, Bi F, Yuan XL, Rao SX, Xin Y, Sheng WQ, Xu HM, Li GX, Ji JF, Zhou ZW, Liang H, Zhang YQ, Jin J, Shen L, Li J, Xu RH. The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021. Cancer Commun (Lond). 2021 Aug;41(8):747-795. doi: 10.1002/cac2.12193. Epub 2021 Jul 1. PMID 34197702
• RESULTLi MY, Zhu DJ, Xu W, Lin YJ, Yung KL, Ip AWH. Application of U-Net with Global Convolution Network Module in Computer-Aided Tongue Diagnosis. J Healthc Eng. 2021 Nov 18;2021:5853128. doi: 10.1155/2021/5853128. eCollection 2021. PMID 34840700