Spots Global Cancer Trial Database for The Role of ctDNA Testing Plus AI-based Pathology in Resectable LSCC

Study Description

Brief Summary: The goal of this observational study is to explore whether ctDNA dynamic monitoring plus AI-based pathology can more effectively predict the therapeutic effect of neoadjuvant chemoimmunotherapy for resectable lung squamous cell carcinoma, so as to accurately guide clinical diagnosis and treatment.

Detailed Description: This study is a single-center, observational, non-interventional, prospective study. 50 patients diagnosed with lung squamous cell carcinoma receiving neoadjuvant chemoimmunotherapy (ranging 2 to 4 cycles) will be planned to be enrolled in the study. Pre-treatment biopsy tissues of enrolled patients will be collected for whole exon sequencing (WES) testing, and personalized detection panel will be customized based on WES testing results. Peripheral blood will be collected 1 day before each cycle of neoadjuvant therapy, 1 day before surgery, 3 days after surgery, and 3 weeks after surgery for ctDNA testing. In addition, the prediction model of AI-based pathology will be constructed by AI deep learning based on pathological sections of pre-treatment biopsy tissues. All inclued patients will be regularly followed up for at least 5 years.

Keywords

Eligibility

Minimum Age: 18 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: ALL

Healthy Volunteers: No

Locations

Contact Details

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