A Study to Analyze Data on Metastatic Ovarian Cancer Using Multi-omics

Обзор

As one of the most common malignant tumors in women, the incidence of ovarian cancer is expected to increase year by year. Due to its lack of typical symptoms and effective screening methods, and the characteristics of implantation and distant metastasis, more than 70% of ovarian cancers were in the metastatic stage at the time of diagnosis. In this study, the investigators will collect large samples of tissue from patients with ovarian cancer, conduct multi-omics studies, and mapped the characteristic maps of the genome and transcriptome of patients with metastatic ovarian cancer, and explore the molecular mechanisms that can be used as new targets for the treatment of ovarian cancer. Besides, the investigators will design and establish a database of metastatic ovarian cancer, integrate multiple omics, imaging, pathology, and clinical information to study their potential relevance, and analyze the relationship between various omics, imaging, pathology, and prognosis, establish ovaries Cancer prediction model.

Первичные конечные точки

• Progression-Free-Survival [Срок оценки: The sample will be tested immediately after they are taken from patients and the statistical analysis will be taken through study completion, an average of 3 year]

Критерии участия

Критерии включения

• female, ≥18 years old;
• diagnosed as ovarian cancer by imaging and pathology;
• did not receive any anti-tumor drug treatment before surgery in the gynecology clinical department of the Sun Yat Sen Memorial Hospital of Sun Yat-Sen University;
• received ovarian cancer surgery and Follow-up treatment;
• Patients voluntarily participate in the research of this subject, have good compliance, and can complete the enrollment by the requirements of the trial;
• Sign informed consent and agree to the collection and use of their data.

Критерии исключения

• Patients who have received other anti-tumor treatments or received tumor surgery before enrollment;
• Patients with malignant tumors in other parts;
• Patients with uncontrollable neurological, psychiatric, or mental disorders;
• Poor compliance and inability to Cooperate and describe treatment responders.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Китай · 1 центр

• The Sun Yat-Sen Memorial Hospital of Sun Yat-Sen Universit — Гуанчжоу

Публикации

• Weidle UH, Birzele F, Kollmorgen G, Rueger R. Mechanisms and Targets Involved in Dissemination of Ovarian Cancer. Cancer Genomics Proteomics. 2016 11-12;13(6):407-423. doi: 10.21873/cgp.20004. PMID 27807064
• Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018 Nov;68(6):394-424. doi: 10.3322/caac.21492. Epub 2018 Sep 12. PMID 30207593
• Webb PM, Jordan SJ. Epidemiology of epithelial ovarian cancer. Best Pract Res Clin Obstet Gynaecol. 2017 May;41:3-14. doi: 10.1016/j.bpobgyn.2016.08.006. Epub 2016 Oct 3. PMID 27743768
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• Lheureux S, Braunstein M, Oza AM. Epithelial ovarian cancer: Evolution of management in the era of precision medicine. CA Cancer J Clin. 2019 Jul;69(4):280-304. doi: 10.3322/caac.21559. Epub 2019 May 17. PMID 31099893
• Deng K, Yang C, Tan Q, Song W, Lu M, Zhao W, Lou G, Li Z, Li K, Hou Y. Sites of distant metastases and overall survival in ovarian cancer: A study of 1481 patients. Gynecol Oncol. 2018 Sep;150(3):460-465. doi: 10.1016/j.ygyno.2018.06.022. Epub 2018 Jul 9. PMID 30001833
• Reid BM, Permuth JB, Sellers TA. Epidemiology of ovarian cancer: a review. Cancer Biol Med. 2017 Feb;14(1):9-32. doi: 10.20892/j.issn.2095-3941.2016.0084. PMID 28443200
• Piver MS. Treatment of ovarian cancer at the crossroads: 50 years after single-agent melphalan chemotherapy. Oncology (Williston Park). 2006 Sep;20(10):1156, 1158. No abstract available. PMID 17024868

Идентификаторы

NCT: NCT05251883 · SYSEC-KY-KS-2021-215

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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