International Journal of Gynecological Cancer最新文献

Ovarian cancer is a leading cause of cancer-related mortality among women, with poor prognosis and limited survival in advanced stages. The integration of artificial intelligence with omics data offers new opportunities to enhance the diagnosis, prognosis, and treatment of this disease. This narrative review synthesizes evidence from 14 studies published between 2021 and 2024 that applied artificial intelligence to genomic, transcriptomic, metabolomic, micro-biomic, and epigenomic data sets in patients with epithelial ovarian cancer. These studies explored artificial intelligence models for disease detection, chemotherapy response prediction, and genetic risk stratification. Despite promising results (eg, high classification accuracy and area under the curve values in some models), significant limitations were observed, including small sample sizes, retrospective and single-center designs, and inconsistent use of validation data sets. The review highlights critical methodological considerations such as data preprocessing, normalization, and feature selection, which substantially influence model performance and reproducibility. Although classification models (eg, deep learning, random forest, and support vector machines) were most commonly used, regression approaches were less frequent and under-used, despite their value for modeling continuous outcomes such as survival time. Overall, artificial intelligence-based approaches demonstrate great potential for advancing personalized medicine in ovarian cancer. However, future research must prioritize larger, multi-center, prospective studies with robust validation strategies and improved model interpretability to enable clinical implementation.

Objective: Platinum-resistant ovarian cancer remains a major therapeutic challenge, with limited benefit from currently available cytotoxic agents. Elenagen is a newly developed plasmid DNA-based anti-cancer agent that encodes p62/SQSTM1 protein, a multi-functional adapter protein involved in selective autophagy, signal transduction, and modulation of the inflammatory response. We previously reported the progression-free survival outcomes of patients with platinum-resistant ovarian cancer treated with Elenagen. We report the overall survival results from a phase II randomized controlled trial comparing Elenagen plus gemcitabine with gemcitabine alone.

Methods: This open-label, prospective, randomized, 2-center study enrolled women with platinum-resistant ovarian cancer. Patients were randomly assigned (1:1) to receive gemcitabine monotherapy (1000 mg/m² on days 1 and 8 every 21 days) or gemcitabine plus Elenagen (2.5 mg intra-muscularly weekly). The primary end point was overall survival; secondary end points included safety, post-progression outcomes, and time-dependent analyses of Elenagen exposure. Survival was analyzed using Kaplan-Meier and Cox proportional hazards models.

Results: Thirty patients (15 per arm) were evaluable for overall survival. Baseline demographic and clinical characteristics were balanced between groups. Among patients with elevated CA-125 levels (> 35 U/mL), median overall survival was 13 months (95% confidence interval [CI] 10 to 27) in the gemcitabine arm and 25 months (95% CI 17 to not reached) in the Elenagen plus gemcitabine arm (log-rank p = .031). Treatment with Elenagen was associated with a 59% reduction in the risk of death (hazard ratio 0.41, 95% CI 0.18 to 0.94, p = .036). Time-dependent and landmark analyses demonstrated a positive association between longer Elenagen exposure and improved survival (p < .001). No additional safety signals were observed compared with gemcitabine alone. Post-progression survival and subsequent therapy patterns were comparable between arms.

Conclusions: The addition of Elenagen to gemcitabine prolonged overall survival in patients with platinum-resistant ovarian cancer without increasing toxicity.

Trial registration: NCT05979298, 2023-08-07.

Background: Radical hysterectomy remains the standard treatment for stage IB2 cervical carcinoma but is often accompanied by considerable peri-operative and long-term complications that impair quality of life. The increasing emphasis on functional preservation has prompted exploration of less extensive surgical options, whereas neoadjuvant chemoimmunotherapy may induce tumor downstaging, enabling more conservative surgery without compromising oncologic safety.

Primary objective: To evaluate the feasibility of extra-fascial hysterectomy after neoadjuvant chemoimmunotherapy as an alternative to radical hysterectomy in patients with stage IB2 cervical cancer.

Study hypothesis: Neoadjuvant chemoimmunotherapy promotes tumor regression and risk factor reduction, allowing patients with IB2 cervical cancer to meet pre-defined ConCerV-based criteria for extra-fascial hysterectomy while maintaining acceptable oncologic and quality-of-life outcomes.

Trial design: This is a multi-center, prospective, single-arm phase II trial. After 3 cycles of neoadjuvant chemoimmunotherapy (nab-paclitaxel, cisplatin, and cadonilimab), patients with post-treatment tumor size ≤2 cm who meet the ConCerV-based criteria on cone biopsy will undergo extra-fascial hysterectomy. Others will proceed to radical hysterectomy.

Major inclusion/exclusion criteria: Eligible patients have treatment-naïve International Federation of Gynecology and Obstetrics 2018 stage IB2 cervical cancer. Acceptable histologic sub-types include squamous cell carcinoma (all grades), common-type adenocarcinoma (grade 1/2 or Silva pattern A/B), and adenosquamous carcinoma (grade 1/2).

Primary endpoint: The proportion of patients meeting pre-defined ConCerV-based criteria after neoadjuvant chemoimmunotherapy.

Sample size: 50.

Estimated dates for completing accrual and presenting results: The recruitment is expected to be finalized by September 2027, with the primary analysis scheduled to occur 3 months after the final patient completes treatment and long-term follow-up at 2 and 5 years.

Trial registration: ClinicalTrials.gov NCT06289751.