Investigator
University Of Oklahoma
Developing a novel image marker to predict the clinical outcome of neoadjuvant chemotherapy (NACT) for ovarian cancer patients
Neoadjuvant chemotherapy (NACT) is one kind of treatment for advanced stage ovarian cancer patients. However, due to the nature of tumor heterogeneity, the clinical outcomes to NACT vary significantly among different subgroups. Partial responses to NACT may lead to suboptimal debulking surgery, which will result in adverse prognosis. To address this clinical challenge, the purpose of this study is to develop a novel image marker to achieve high accuracy prognosis prediction of NACT at an early stage. For this purpose, we first computed a total of 1373 radiomics features to quantify the tumor characteristics, which can be grouped into three categories: geometric, intensity, and texture features. Second, all these features were optimized by principal component analysis algorithm to generate a compact and informative feature cluster. This cluster was used as input for developing and optimizing support vector machine (SVM) based classifiers, which indicated the likelihood of receiving suboptimal cytoreduction after the NACT treatment. Two different kernels for SVM algorithm were explored and compared. A total of 42 ovarian cancer cases were retrospectively collected to validate the scheme. A nested leave-one-out cross-validation framework was adopted for model performance assessment. The results demonstrated that the model with a Gaussian radial basis function kernel SVM yielded an AUC (area under the ROC [receiver characteristic operation] curve) of 0.806 ± 0.078. Meanwhile, this model achieved overall accuracy (ACC) of 83.3%, positive predictive value (PPV) of 81.8%, and negative predictive value (NPV) of 83.9%. This study provides meaningful information for the development of radiomics based image markers in NACT treatment outcome prediction.
CircATL2 enhances paclitaxel resistance of ovarian cancer via impacting miR‐506‐3p/NFIB axis
AbstractCircular RNAs (circRNAs) play vital regulatory roles in the development of ovarian cancer (OC). However, the functions of circRNA Atlastin GTPase 2 (circATL2) in paclitaxel (PTX) resistance of OC are still unclear. As a result, circATL2 was upregulated in PTX‐resistant OC tissues and cells. CircATL2 knockdown reduced IC50 of PTX, inhibited colony formation ability and promoted cell cycle arrest and apoptosis in PTX‐resistant OC cells. Silencing of circATL2 restrained PTX resistance in vivo. Furthermore, miR‐506‐3p could be targeted by circATL2 and miR‐506‐3p inhibition reversed the impacts of circATL2 knockdown on PTX resistance and cell progression in PTX‐resistant OC cells. NFIB was identified as the target of miR‐506‐3p. MiR‐506‐3p overexpression suppressed PTX resistance and malignant behaviors of PTX‐resistant OC cells, with NFIB elevation rescued the impacts. To summarize, circATL2 promoted the resistance of OC to PTX by sponging miR‐506‐3p to upregulate NFIB expression, providing a new sight in chemoresistance of OC.
