Study of the Correlation of Tumor Tissue Microbiome to the Pathogenesis of Lung Cancer — STARS  

Lung Cancer Clinical Trial

Official title: A Cross-sectional Study of the Correlation of Tumor Tissue Microbiome to the Pathogenesis of Lung Cancer

Status Recruiting

Clinical Trial Summary

Lung cancer is the malignant tumor with the highest incidence, accounting for the first cause of tumor death. At present, smoking, occupational and environmental exposure, air pollution and genetic factors are considered to be related to the incidence of lung cancer. However, the occurrence of cancer is related to many factors. In recent years, researches have found that microorganisms are closely related to various human cancers. It is reported that 20% of cancers are related to multiple microorganisms, such as EB virus and nasopharyngeal cancer, HBV and liver cancer. Understanding the correlation between pathogenic microorganisms and cancer is of great significance for the pathogenesis, prevention and treatment of cancer. Basic researches have found that mycotoxins are related to animal models of lung cancer, but have not been confirmed in clinical and human.

With the help of microbial metagenome Next Generation Sequencing (mNGS) and bioinformatics analysis, the investigators initially found in clinical practice that some patients had fungal infections such as fungi in lung cancer tissues. This study intends to collect clinical cases (cross-sectional studies) to explore the correlation between the pathogenic microbiome and lung cancer, in order to confirm that the occurrence of lung cancer is closely related to microorganisms such as fungi.

Clinical Trial Description

The investigator designe a cross-sectional study to explore the correlation between the pathogenic microbiome and lung cancer, and to understand the specific pathogen distribution of the "lung cancer microbiome" in order to provide new ideas and strategies for the pathogenesis and prevention of lung cancer.

The subjects of this study are patients with lung shadow confirmed by CT-guided percutaneous lung biopsy. Lung shadows usually refer to high-density areas found in the parenchymal areas of the lungs on radiographs or radiographs, and often appear on CT as exudation, consolidation, masses, or nodules. Lung shadows mainly include infectious diseases of the lung, Tumors and interstitial lung diseases. The subjects are patients who cannot be diagnosed by conventional non-invasive testing methods (including blood, sputum and other specimens) and bronchoscopy, and the patients need to be diagnosed and treated as soon as possible (such as lung tumors, lung infections and other diseases ). Obtaining pathological and etiology of lung lesion tissue for examination is a necessary and effective diagnostic measure. Part of the biopsy tissue will be submitted for pathology and immunohistochemical detection, and the other part will be submitted for microbial mNGS detection.

Pulmonary shadow cases include lung cancer and non-lung cancer patients, which are intended to be included in 300 cases. According to the previous lung shadow patients admitted to respiratory department in Huashan Hospital, it is estimated that about 100 lung cancer patients and 200 non-lung cancer patients will be included, respectively.

Observation indicators in this study include histopathology of lung puncture biopsy, and next-generation sequencing of microorganisms in lung puncture biopsy.Baseline screening includes demographic data, medical history, combined medication records, symptoms, signs, electrocardiogram, lung function, and safety observation indicators. All patients will be followed up for 1 week for a total of three times, including baseline follow-up, 24 hours after lung puncture, and 1 week after lung puncture. ;

Related Conditions & MeSH terms

• Lung Cancer
• Lung Neoplasms
• Microbiome

• NCT number: NCT04260295
• Study type: Observational
• Source: Huashan Hospital
• Contact: Shengqing Li, PhD
• Phone: +8602152887072
• Email: shengqingli9655@163.com
• Status: Recruiting
• Start date: November 1, 2019
• Completion date: July 31, 2021