NCT06640348

Ultrasensitive SERS Platform With Highly Efficient Enrichment of Analyte for Screening and Diagnosis of Epithelial Ovarian Cancer

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 70 (estimated)
• Sponsor: Anhui Provincial Hospital · Other Government
• Sex: Female
• Age: 18 Years – 70 Years
• Healthy volunteers: Accepted

Summary

This project is an open, single-center, prospective study aimed at developing high-sensitivity, high-specificity enrichment SERS chips using femtosecond laser processing technology. It involves extracting information from blood samples of ovarian cancer patients and normal controls, specifically identifying cancer and non-cancer signals. The study will construct a statistical algorithm model for the early diagnosis of ovarian cancer, enabling early identification and intervention for ovarian cancer patients.

Detailed description

Epithelial Ovarian Cancer (EOC) poses a significant challenge in the field of gynecological oncology regarding precise early screening. In response to this critical scientific issue, the research team has designed and developed a high-sensitivity, high-specificity enrichment SERS chip, exploring its applications in the screening and diagnosis of ovarian cancer. The development of the SERS chip and its functional implementation has been done.Clinical research trials are conducted for ovarian cancer screening and diagnosis, analyzing the physicochemical properties of key biomolecules in the blood of ovarian cancer patients. The study reveals the interaction patterns between SERS active particles and biomolecules, establishing a competitive adsorption model between multiple biomolecules and active particles. Raman spectra of individual components are collected to create a characteristic Raman information database for key biomolecules. The analysis of Raman spectra from ovarian cancer patients and healthy individuals delves into the characteristic signals, constructing a statistical classification model for patient and normal Raman signals. Different tissue types and grades of ovarian cancer patients' Raman spectra signals are analyzed, establishing high-throughput classification methods for various ovarian cancers. By combining clinical gold-standard detection techniques, the sources of characteristic signals are determined, providing a theoretical foundation and technical support for conducting ovarian cancer research and establishing treatment plans in clinical settings.

Conditions

• Ovarian Cancer, Epithelial

Interventions

Type	Name	Description
OTHER	No intervention	No intervention

Timeline

• Start date: 2025-01-01
• Primary completion: 2027-12-31
• Completion: 2030-12-31
• First posted: 2024-10-15
• Last updated: 2024-10-15

Locations

1 site across 1 country: China