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

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.

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.

Eligibility Criteria:
Inclusion Criteria:

1. The subjects understand the trial process, sign the informed consent form, voluntarily participate in the study, and are capable of following the protocol;
2. Aged 18 to 70 (inclusive):

Cancer group: Ovarian cancer patients (50 cases of high-grade serous ovarian cancer, 15 cases of low-grade serous ovarian cancer, 20 cases of endometrioid ovarian cancer, 20 cases of clear cell carcinoma) i. All ovarian cancer patients are initial treatment patients with complete clinical data; ii. Patients have an ECOG performance status score of 0-3 and a life expectancy of more than 6 months; iii. Subjects consent to blood sample collection for SERS analysis (provided free of charge); iv. Good organ function.

Normal control group: (20 cases) i. Normal control subjects are patients undergoing surgery for benign diseases; ii. Patients have complete clinical data; iii. Subjects have not undergone any radical treatment for the benign lesion prior to blood collection.

Exclusion Criteria:

1. Severe or uncontrolled diseases, including but not limited to: uncontrollable nausea and vomiting, gastrointestinal diseases that may interfere with drug absorption and metabolism, mental illnesses affecting the patient's ability to sign the informed consent form, a history of severe cardiovascular disease, infectious diseases (such as syphilis, AIDS, active hepatitis C, or active hepatitis B), infectious conditions (such as abscesses), or active rheumatic diseases, etc.;
2. A history of blood transfusion within 4 weeks prior to the study;
3. Pregnant, postpartum, or breastfeeding patients, or patients planning to become pregnant during the study treatment;
4. Patients with a history of other tumors;
5. The investigator deems the subject unsuitable for participation in this clinical study.