Jin Li

PARP Inhibitors Rechallenge in Patients With Recurrent Ovarian Cancer: A Multicentre Real‐World Study in China

ABSTRACTObjectiveTo evaluate the treatment pattern, outcomes, safety and identify patient populations benefiting from PARP inhibitor (PARPi) rechallenge for recurrent ovarian cancer.DesignA multicentre, retrospective, real‐world study.SettingTwelve hospitals in China.PopulationSeventy patients with recurrent ovarian cancer underwent PARPi rechallenge between 1 June 2019 and 10 March 2023.MethodsData, including demographic, clinical characteristics and treatment‐related information, were retrospectively collected from electronic health records.Main Outcome MeasuresThe primary outcome was progression‐free survival (PFS) of PARPi rechallenge (PARPi2) as maintenance therapy. We also conducted exploratory analysis to identify factors influencing PFS and characteristics associated with favourable outcomes.ResultsOf the 70 patients, 37.1% had BRCA1/2 mutations. PARPi2 was used as a maintenance therapy in 81.4% of patients, with a median PFS of 8.6 months (95% confidence interval [CI]: 6.0–13.5). PFS did not significantly differ by BRCA status (hazard ratio = 1.25 [95% CI: 0.60–2.60], p = 0.55). Achieving complete response (CR) to the last chemotherapy was a significant predictor for receiving PARPi2 for ≥ 6 months (vs. partial response, odds ratio = 4.25 [95% CI: 1.21–14.9], p = 0.02). Patients receiving combination therapies (33.3%) had longer median PFS than those receiving monotherapy (11.0 [95% CI: 5.2–15.3] vs. 7.7 [95% CI: 5.0–13.5] months). Overall, 2.9% of patients discontinued PARPi2 due to adverse events.ConclusionsPARPi rechallenge as maintenance therapy may be feasible and tolerable. Achieving CR after the last chemotherapy is associated with longer PFS and combined therapies may improve outcomes, indicating potential to overcome PARPi resistance.

An Aptamer‐Based Nanoflow Cytometry Method for the Molecular Detection and Classification of Ovarian Cancers through Profiling of Tumor Markers on Small Extracellular Vesicles

AbstractMolecular profiling of protein markers on small extracellular vesicles (sEVs) is a promising strategy for the precise detection and classification of ovarian cancers. However, this strategy is challenging owing to the lack of simple and practical detection methods. In this work, using an aptamer‐based nanoflow cytometry (nFCM) detection strategy, a simple and rapid method for the molecular profiling of multiple protein markers on sEVs was developed. The protein markers can be easily labeled with aptamer probes and then rapidly profiled by nFCM. Seven cancer‐associated protein markers, including CA125, STIP1, CD24, EpCAM, EGFR, MUC1, and HER2, on plasma sEVs were profiled for the molecular detection and classification of ovarian cancers. Profiling these seven protein markers enabled the precise detection of ovarian cancer with a high accuracy of 94.2 %. In addition, combined with machine learning algorithms, such as linear discriminant analysis (LDA) and random forest (RF), the molecular classifications of ovarian cancer cell lines and subtypes were achieved with overall accuracies of 82.9 % and 55.4 %, respectively. Therefore, this simple, rapid, and non‐invasive method exhibited considerable potential for the auxiliary diagnosis and molecular classification of ovarian cancers in clinical practice.

Real‐world outcomes of niraparib treatment in patients with ovarian cancer: a multicenter non‐interventional study in China