New Predictive Biomarkers for Ovarian Cancer
Ovarian cancer is the eighth-most common cause of death among women worldwide. In the absence of distinctive symptoms in the early stages, the majority of women are diagnosed in advanced stages of the disease. Surgical debulking and systemic adjuvant chemotherapy remain the mainstays of treatment, w...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/11/3/465 |
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| author | Ghofraan Abdulsalam Atallah Nor Haslinda Abd. Aziz Chew Kah Teik Mohamad Nasir Shafiee Nirmala Chandralega Kampan |
| author_facet | Ghofraan Abdulsalam Atallah Nor Haslinda Abd. Aziz Chew Kah Teik Mohamad Nasir Shafiee Nirmala Chandralega Kampan |
| author_sort | Ghofraan Abdulsalam Atallah |
| collection | DOAJ |
| description | Ovarian cancer is the eighth-most common cause of death among women worldwide. In the absence of distinctive symptoms in the early stages, the majority of women are diagnosed in advanced stages of the disease. Surgical debulking and systemic adjuvant chemotherapy remain the mainstays of treatment, with the development of chemoresistance in up to 75% of patients with subsequent poor treatment response and reduced survival. Therefore, there is a critical need to revisit existing, and identify potential biomarkers that could lead to the development of novel and more effective predictors for ovarian cancer diagnosis and prognosis. The capacity of these biomarkers to predict the existence, stages, and associated therapeutic efficacy of ovarian cancer would enable improvements in the early diagnosis and survival of ovarian cancer patients. This review not only highlights current evidence-based ovarian-cancer-specific prognostic and diagnostic biomarkers but also provides an update on various technologies and methods currently used to identify novel biomarkers of ovarian cancer. |
| first_indexed | 2024-03-09T05:05:25Z |
| format | Article |
| id | doaj.art-c1d0ea03d68c4824bebbc09037b363de |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-09T05:05:25Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-c1d0ea03d68c4824bebbc09037b363de2023-12-03T12:55:37ZengMDPI AGDiagnostics2075-44182021-03-0111346510.3390/diagnostics11030465New Predictive Biomarkers for Ovarian CancerGhofraan Abdulsalam Atallah0Nor Haslinda Abd. Aziz1Chew Kah Teik2Mohamad Nasir Shafiee3Nirmala Chandralega Kampan4Department of Obstetrics and Gynaecology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, MalaysiaDepartment of Obstetrics and Gynaecology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, MalaysiaDepartment of Obstetrics and Gynaecology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, MalaysiaDepartment of Obstetrics and Gynaecology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, MalaysiaDepartment of Obstetrics and Gynaecology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, MalaysiaOvarian cancer is the eighth-most common cause of death among women worldwide. In the absence of distinctive symptoms in the early stages, the majority of women are diagnosed in advanced stages of the disease. Surgical debulking and systemic adjuvant chemotherapy remain the mainstays of treatment, with the development of chemoresistance in up to 75% of patients with subsequent poor treatment response and reduced survival. Therefore, there is a critical need to revisit existing, and identify potential biomarkers that could lead to the development of novel and more effective predictors for ovarian cancer diagnosis and prognosis. The capacity of these biomarkers to predict the existence, stages, and associated therapeutic efficacy of ovarian cancer would enable improvements in the early diagnosis and survival of ovarian cancer patients. This review not only highlights current evidence-based ovarian-cancer-specific prognostic and diagnostic biomarkers but also provides an update on various technologies and methods currently used to identify novel biomarkers of ovarian cancer.https://www.mdpi.com/2075-4418/11/3/465ovarian cancerbiomarkerstumour mutation burdenDNA repair pathwayscell-cycle-related genes |
| spellingShingle | Ghofraan Abdulsalam Atallah Nor Haslinda Abd. Aziz Chew Kah Teik Mohamad Nasir Shafiee Nirmala Chandralega Kampan New Predictive Biomarkers for Ovarian Cancer Diagnostics ovarian cancer biomarkers tumour mutation burden DNA repair pathways cell-cycle-related genes |
| title | New Predictive Biomarkers for Ovarian Cancer |
| title_full | New Predictive Biomarkers for Ovarian Cancer |
| title_fullStr | New Predictive Biomarkers for Ovarian Cancer |
| title_full_unstemmed | New Predictive Biomarkers for Ovarian Cancer |
| title_short | New Predictive Biomarkers for Ovarian Cancer |
| title_sort | new predictive biomarkers for ovarian cancer |
| topic | ovarian cancer biomarkers tumour mutation burden DNA repair pathways cell-cycle-related genes |
| url | https://www.mdpi.com/2075-4418/11/3/465 |
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