Developing an Artificial Intelligence-based Diagnostic Method Based on Oral Microbiome for Non-invasive Diagnosis of Lung Cancer
The study aims to develop a deep learning-based diagnostic method for lung cancer using the oral microbiome. This innovative approach involves establishing an observational cohort of 576 individuals, including lung cancer patients, non-cancerous benign lung disease patients, and healthy controls, to collect tongue swab samples for 16S rRNA sequencing. Additionally, an international cohort of approximately 1700 individuals will be formed using in silico data. The project will utilize deep learning methods to analyze all data integratively and develop an AI diagnostic algorithm capable of distinguishing lung cancer patients from others. The diagnostic method's performance will be tested in a pilot clinical trial with 96 individuals using a PRoBE design. Led by experts in chest surgery, molecular microbiology, and bioinformatics, the project spans over 30 months and aims to create a non-invasive, easily accessible lung cancer screening method that could lead to significant diagnostic advancements and potential spin-off companies in the field of liquid biopsy/molecular diagnosis.
• To be between the ages of 18 and 65,
• Not to have a diagnosed lung disease or suspicion thereof,
• Not to have complaints related to the lungs and/or respiratory tract,
• Not to have alcohol or severe substance dependency,
• Not having a hospitalization history in the last year,
• Not having used antibiotics in the last six months,
• Not having used products manufactured to support the oral microbiome, such as probiotics (lozenges, sublingual drops) for at least the last six months,
• Not being pregnant or breastfeeding,
• Not having undergone dental procedures such as root canal treatment, implants, prostheses, tooth extraction, fillings in the last 6 months
• Not having dominant immune-origin lesions (such as aphthous ulcers, erythema multiforme, pemphigus), viral-origin lesions (such as herpes, Koplik spots, herpangina), dominant bacterial infections like tonsillitis, and/or thermal or chemical mucosal traumas in the mouth.