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Principal Investigator
Name
Shun Liu
Degrees
M.P.H.
Institution
Fujian Medical University
Position Title
Student
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-1669
Initial CDAS Request Approval
Sep 19, 2024
Title
Microbial characteristics of 16s sequencing in different esophageal diseases in PLCO
Summary
Esophageal Cancer is one of the most common malignant tumors of the upper gastrointestinal tract in the world. According to the global Cancer statistics reported by the International Agency for Research on Cancer (IARC) [1], in 2020, there were 19.3 million new cancer patients and about 10 million deaths due to cancer worldwide. The number of new cases of esophageal cancer was 604 000, ranking the seventh among malignant tumors. The number of cancer deaths was 544 000, ranking the sixth of malignant tumors, accounting for 3.1% of the incidence and 5.5% of the global total. China is one of the countries with a high incidence of esophageal cancer. The National Cancer Center of China reported that [2] there will be 224,000 new cases and 187,500 deaths of esophageal cancer in China in 2022. The incidence and mortality of esophageal cancer in China are 8.32/100 000, ranking sixth in the incidence and 6.68/100 000, ranking fifth in the cause of death of cancer. The incidence and mortality of esophageal cancer have been at a high level.
There are different types and amounts of microbial flora in the human digestive tract. Various bacterial flora have symbiosis, competition and antagonism to form a stable microecological network. In recent years, several studies have shown that the gastrointestinal flora of patients with esophagitis and eosinophilic esophagitis changes, accompanied by an increase or decrease in the relative abundance of some bacteria [3]. However, the group Settings of esophageal microbial studies are not uniform, and the bacteria associated with benign and precancerous esophageal lesions are different from each other. At present, there is no recognized candidate bacteria, and some bacteria, such as Helicobacter pylori, have shown conflicting conclusions in multiple studies. Therefore, it is necessary to conduct a study involving multiple stages of esophageal disease, clarify the complex relationship between gastrointestinal flora and esophageal disease, and find its specific bacteria, which can provide potential preventive measures and treatment options for delaying or even reversing the progression of esophageal cancer.
Our study included esophageal disease at multiple stages of PLCO ESCC evolution as much as possible to analyze microbial differences in esophageal disease. To explore the microbial changes in the process from normal tissues to esophageal cancer, and to provide a reference for distinguishing different esophageal diseases from normal esophageal tissues, early prevention of esophageal cancer, and finding effective biomarkers.
[1]Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249.
[2] Zheng R S, Chen R, Han B F, et al. Analysis of cancer incidence in China in 2022 [J]. Chin J Cancer, 2024: 221-231.
[3] Kashyap P C, Johnson S, Geno D M, et al. A decreased abundance of clostridia characterizes the gut microbiota in eosinophilic esophagitis[J]. Physiological Reports, 2019,7(20):e14261.
Aims

1. The PLCO 16s sequencing microbial data of different esophageal diseases were used as the training set to find the differential microorganisms between different esophageal diseases and normal esophagus, and the sequencing data of different esophageal diseases were used as the validation set to verify the differential microorganisms in the training set.
2.The PLCO 16s sequencing microbial data of different esophageal diseases were used as the training set to find the differential pathways between different esophageal diseases and normal esophagus, and the sequencing data of different esophageal diseases were used as the validation set to verify the differential pathways of the training set.
3.To explore the association between the above differential microorganisms and the differential pathways

Collaborators

Shun Liu, Zhifeng Lin, Menglin Yu(Fujian Medical University, Fuzhou)