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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| healthy control | By analyzing the Raman signals of peripheral serum from normal controls, unique signal characteristics specific to ovarian cancer patients are identified through comparative analysis with the control group. |
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| Ovarian cancer group | Extract information from blood samples of ovarian cancer patients, specifically identifying cancer and non-cancer signals to construct a statistical algorithm model for the early diagnosis of ovarian cancer. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No intervention | Other | No intervention |
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| Measure | Description | Time Frame |
|---|---|---|
| PFS PFS | progression free survival | one year |
| OS | OS (overall survival) is defined as the time which begins at diagnosis and up to the time of death | three year |
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Inclusion Criteria:
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:
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The subjects include patients with epithelial ovarian cancer, while the control group consists of patients undergoing surgery for benign diseases.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Ying Zhou, MD | Contact | _8613865901025 | caddiezy@ustc.edu.cn | |
| Ying Zhou, MD | Contact | caddiezy@ustc.edu.cn |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Anhui Provincal Hospital | Recruiting | Hefei | Anhui | China |
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| ID | Term |
|---|---|
| D000077216 | Carcinoma, Ovarian Epithelial |
| ID | Term |
|---|---|
| D002277 | Carcinoma |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |
| D009369 | Neoplasms |
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| D010051 |
| Ovarian Neoplasms |
| D004701 | Endocrine Gland Neoplasms |
| D009371 | Neoplasms by Site |
| D010049 | Ovarian Diseases |
| D000291 | Adnexal Diseases |
| D005831 | Genital Diseases, Female |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D005833 | Genital Neoplasms, Female |
| D014565 | Urogenital Neoplasms |
| D000091662 | Genital Diseases |
| D004700 | Endocrine System Diseases |
| D006058 | Gonadal Disorders |