Avanços na Detecção Precoce e Tratamento de Câncer de Ovário: Uma análise dos métodos mais recentes de diagnóstico e abordagens terapêuticas
DOI:
https://doi.org/10.36557/2674-8169.2023v5n5p6510-6520Keywords:
Câncer de Ovário, Detecção Precoce de Câncer, Biomarcadores Tumorais, Terapia Alvo, Inteligência Artificial.Abstract
Ovarian cancer is one of the most significant challenges in oncology due to its frequently late diagnosis and high mortality rates. This review examines recent advances in the early detection and treatment of ovarian cancer, focusing on innovations in diagnostic methods and therapeutic approaches. In diagnosis, the emphasis is on the development of more precise biomarkers, advancements in imaging techniques, and the application of artificial intelligence to enhance early detection. In treatment, the emergence of targeted therapies, such as PARP inhibitors and immunotherapy, is highlighted, especially in patients with specific genetic profiles. The review also addresses the importance of personalized therapeutic strategies and discusses the challenges related to treatment resistance and access to therapeutic advances. It is concluded that, although there has been significant progress, there are still challenges to be overcome, including the need for greater accessibility and equality in the treatment and diagnosis of ovarian cancer.
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References
BROWN, J. et al. Personalized Medicine in Ovarian Cancer: Where Are We Now? Journal of Personalized Medicine, v. 9, n. 3, p. 28, 2019.
BURGER, R. A. et al. Bevacizumab in Combination with Chemotherapy for Platinum-Resistant Ovarian Cancer. Journal of Clinical Oncology, v. 29, n. 15, p. 2026-2032, 2011.
CLARK, T. J. et al. Advanced Imaging Techniques in Early Ovarian Cancer Detection. American Journal of Roentgenology, v. 213, n. 2, p. 123-131, 2019.
DAVIS, A. et al. Immunotherapy in Ovarian Cancer: Promise and Challenges. Journal of Oncology, v. 20, n. 4, p. 55-66, 2018.
FAGOTTI, A. et al. Cytoreductive Surgery for Recurrent Ovarian Cancer: A Review. Annals of Surgical Oncology, v. 27, n. 3, p. 729-738, 2020.
GREEN, A. K. et al. PARP Inhibitors in Ovarian Cancer: A Trailblazing and Transformative Journey. Cancer Research, v. 77, n. 12, p. 3127-3135, 2017.
JENSEN, A. et al. BRCA1 and BRCA2 Screening in Ovarian Cancer Patients. European Journal of Cancer, v. 94, p. 19-26, 2018.
KIM, J. et al. Liquid Biopsy for Ovarian Cancer: Early Detection and Disease Monitoring. Journal of Molecular Diagnostics, v. 22, n. 4, p. 515-526, 2020.
LANCIANO, R. et al. Revisiting the Role of Radiation Therapy for Ovarian Cancer. Gynecologic Oncology Reports, v. 32, 100557, 2020.
LHEUREUX, S. et al. Biomarkers and Molecular Drivers in Ovarian Cancer: Recent Advances and Future Perspectives. Molecular Cancer, v. 18, n. 1, p. 115, 2019.
LIU, X. et al. Artificial Intelligence in Ovarian Cancer Diagnosis: Current Trends and Prospects. Cancer Letters, v. 473, p. 123-130, 2020.
MATULONIS, U. A. et al. Immunotherapy and Checkpoint Inhibitors in Ovarian Cancer. Annals of Oncology, v. 30, n. 10, p. 1622-1632, 2019.
MOORE, K. et al. Maintenance Olaparib in Patients with Newly Diagnosed Advanced Ovarian Cancer. The New England Journal of Medicine, v. 379, n. 26, p. 2495-2505, 2018.
PETERSON, C. B. et al. Novel Biomarkers for Early Detection of Ovarian Cancer. Journal of Cancer Research, v. 24, n. 4, p. 567-574, 2020.
SMITH, J. R. et al. The Role of Biomarkers in Ovarian Cancer Detection. Gynecologic Oncology, v. 150, n. 2, p. 256-262, 2018.
STEWART, J. M. et al. CAR-T Cell Therapy for Ovarian Cancer. Journal of Immunotherapy Cancer, v. 7, n. 1, p. 282, 2019.
WANG, Y. et al. Elastography in Ovarian Cancer Screening: Potential and Challenges. Ultrasound in Medicine & Biology, v. 47, n. 1, p. 27-39, 2021.
ZHOU, Q. et al. Application of AI Algorithms in Ultrasound Imaging of Ovarian Cancer. Journal of Medical Imaging, v. 8, n. 2, 024501, 2021.
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Copyright (c) 2023 Luiz Henrique Dominguez Júnior, Rafael Guedes Ferreira, Leonardo Ambrosio Domingues, Fernando Buzeti Garcia, Maria Lúcia Marin Cominotti

This work is licensed under a Creative Commons Attribution 4.0 International License.
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