Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Ovarian cancer (OC) is one of the most lethal gynecologic malignancies in females worldwide. OC is frequently diagnosed at an advanced stage due to a lack of specific symptoms and effective screening tests, resulting in a poor prognosis for patients. Age, genetic alterations, and family history are the major risk factors for OC pathogenesis. Understanding the molecular mechanisms underlying OC progression, identifying new biomarkers for early detection, and discovering potential targets for new drugs are urgent needs. Liquid biopsy (LB), used for cancer detection and management, consists of a minimally invasive approach and practical alternative source to investigate tumor alterations by testing extracellular vesicles (EVs), circulating tumor cells, tumor-educated platelets, and cell-free nucleic acids. EVs are nanosize vesicles shuttling proteins, lipids, and nucleic acids, such as DNA, RNA, and non-coding RNAs (ncRNAs), that can induce phenotypic reprogramming of target cells. EVs are natural intercellular shuttles for ncRNAs, such as microRNAs (miRNAs) and circular-RNAs (circRNAs), known to have regulatory effects in OC. Here we focus on the involvement of circRNAs and miRNAs in OC cancer progression. The circRNA-microRNA-mRNA axis has been investigated with Circbank and miRwalk analysis, unraveling the intricate and detailed regulatory network created by EVs, ncRNAs, and mRNAs in OC.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324482PMC
http://dx.doi.org/10.3390/cancers14143404DOI Listing

Publication Analysis

Top Keywords

ovarian cancer
8
nucleic acids
8
extracellular vesicles-cernas
4
vesicles-cernas ovarian
4
cancer
4
cancer biomarkers
4
biomarkers circrna-mirna-mrna
4
circrna-mirna-mrna code
4
code ovarian
4
cancer lethal
4

Similar Publications

Background: Ovarian cancer remains the most lethal gynecological cancer, with fewer than 50% of patients surviving more than five years after diagnosis. This study aimed to analyze the global epidemiological trends of ovarian cancer from 1990 to 2021 and also project its prevalence to 2050, providing insights into these evolving patterns and helping health policymakers use healthcare resources more effectively.

Methods: This study comprehensively analyzes the original data related to ovarian cancer from the GBD 2021 database, employing a variety of methods including descriptive analysis, correlation analysis, age-period-cohort (APC) analysis, decomposition analysis, predictive analysis, frontier analysis, and health inequality analysis.

View Article and Find Full Text PDF

Objective: To investigate the clinical utility of diagnostic laparoscopy in guiding treatment strategy and surgical outcomes for patients with advanced-stage ovarian cancer, specifically regarding operability assessment and the likelihood of complete cytoreduction.

Methods: This retrospective cohort study analyzed 183 patients with histologically confirmed International Federation of Gynecology and Obstetrics (FIGO) stage III-IV ovarian cancer treated with curative intent between January 2018 and December 2023 at a tertiary referral center. Patients were divided into two groups: those who underwent diagnostic laparoscopy prior to primary treatment (n = 80) and those managed without laparoscopy (n = 103).

View Article and Find Full Text PDF

Causes of Death After Surgery Among Cancer Patients: A Population-based Cohort Study.

Int J Surg

September 2025

State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.

Introduction: Recent advancements in surgical techniques and perioperative care have improved cancer survival rates, yet postoperative comorbidity and mortality remain a critical concern. Despite progress in cancer control, systematic analyses of long-term mortality trends and competing risks in surgery-intervened cancer populations are lacking. This study aimed to quantify temporal patterns of postoperative mortality causes across 21 solid cancers and identify dominant non-cancer risk factors to inform survivorship care strategies.

View Article and Find Full Text PDF

Background: Ovarian cancer (OC) remains the most lethal gynecological malignancy, largely due to its late-stage diagnosis and nonspecific early symptoms. Advances in biomarker identification and machine learning offer promising avenues for improving early detection and prognosis. This review evaluates the role of biomarker-driven ML models in enhancing the early detection, risk stratification, and treatment planning of OC.

View Article and Find Full Text PDF