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ObjectiveThe aim of the study is to develop and validate a deep learning model to predict the platinum sensitivity of patients with epithelial ovarian cancer (EOC) based on contrast-enhanced magnetic resonance imaging (MRI).MethodsIn this retrospective study, 93 patients with EOC who received platinum-based chemotherapy (≥4 cycles) and debulking surgery at the Sun Yat-sen Memorial Hospital from January 2011 to January 2020 were enrolled and randomly assigned to the training and validation cohorts (2:1). Two different models were built based on either the primary tumor or whole volume of the abdomen as the volume of interest (VOI) within the same cohorts, and then a pre-trained convolutional neural network Med3D (Resnet 10 version) was transferred to automatically extract 1,024 features from two MRI sequences (CE-T1WI and T2WI) of each patient to predict platinum sensitivity. The performance of the two models was compared.ResultsA total of 93 women (mean age, 50.5 years ± 10.5 [standard deviation]) were evaluated (62 in the training cohort and 31 in the validation cohort). The AUCs of the whole abdomen model were 0.97 and 0.98 for the training and validation cohorts, respectively, which was better than the primary tumor model (AUCs of 0.88 and 0.81 in the training and validation cohorts, respectively). In k-fold cross-validation and stratified analysis, the whole abdomen model maintained a stable performance, and the decision function value generated by the model was a prognostic indicator that successfully discriminates high- and low-risk recurrence patients.ConclusionThe non-manually segmented whole-abdomen deep learning model based on MRI exhibited satisfactory predictive performance for platinum sensitivity and may assist gynecologists in making optimal treatment decisions.

Triple negative breast cancer (TNBC) accounts for less than a quarter of breast cancer but has the poorest survival outcome and is prone to relapse as well as metastasis due to its aggressiveness and lack of therapeutic target. Herein, we analyzed the TCGA datasets of lncRNA expressional profiles of breast cancer vs. normal tissue and TNBC vs. Non-TNBC subtypes and screened a long non-coding RNA (lncRNA) MNX1-AS1 overexpressing in TNBC. We found that MNX1-AS1 were upregulated in TNBC tumor tissues and correlated with poor survival outcome in TNBC patients. Silencing MNX1-AS1 reduced the aggressiveness of TNBC in vitro and in vivo. By using RNA pulldown assay followed by western blotting and RNA immunoprecipitation (RIP), we identified Stat3 was the MNX1-AS1 binding protein and MNX1-AS1 upregulated the phosphorylation of Stat3 by enhancing the interaction between p-JAK and Stat3. The present study suggested that targeting MNX1-AS1 may represent a promising therapeutic strategy to TNBC.

MicroRNAs (miRNAs) play key roles in many physiologic and pathologic processes, including autophagy. Autophagy is cellular in an emergency response mechanism of environment stress, but their complex molecular regulatory mechanism under low-temperature stress is largely unknown in shrimp, especially miRNA-mediated regulation of autophagy in low-temperature tolerance. In this article, a shrimp PvTOR and miRNA pva-miR-151 cooperation in response to low-temperature stress has been reported. Pva-miR-151 showed expression patterns opposite to target PvTOR under low-temperature stress. The pva-miR-151 targets the 3′-UTR region of PvTOR, regulate the formation of autophagosome, which contribute to the degradation and recycling of damaged organelles. In addition, the low-temperature tolerance was correlated positively with autophagy in shrimp. Silenced pva-miR-151 increased sensitivity to low-temperature stress, whereas overexpression pva-miR-151 decreased the expression of PvTOR and p-TOR and increased tolerance to low-temperature stress by improving the formation of autophagosome and total hemocyte count. In addition, the TOR activator 3BDO can partially rescue autophagy induced by overexpression of pva-miR-151; these results indicate that miR-151 was necessary for the low-temperature tolerance in shrimp. Taken together, we provide a novel strategy and mechanism for shrimp breeding to improve shrimp low-temperature tolerance.