High-grade serous ovarian carcinoma (HGSC), the most common and aggressive histological type of ovarian cancer, remains the leading cause of cancer-related deaths among females. It is important to develop novel drugs to improve the therapeutic outcomes of HGSC patients, thereby reducing their mortality. Symmetry is one of the most important properties of the biological network, which determines the stability of a biological system. As aberrant gene expression is a critical symmetry-breaking event that perturbs the stability of biological networks and triggers tumor progression, we aim in this study to discover new candidate drugs and predict their targets for HGSC therapy based on differentially expressed genes involved in HGSC pathogenesis. Firstly, 98 up-regulated genes and 108 down-regulated genes were identified from three independent transcriptome datasets. Then, the small-molecule compounds PHA-793887, pidorubicine and lestaurtinib, which target cell-cycle-related processes, were identified as novel candidate drugs for HGSC treatment by adopting the connectivity map (CMap)-based drug repositioning approach. Furthermore, through a topological analysis of the protein–protein interaction network, cell cycle regulators CDK1, TOP2A and AURKA were identified as bottleneck nodes, and their expression patterns were validated at the mRNA and protein expression levels. Moreover, the results of molecular docking analysis showed that PHA-793887, pidorubicine and lestaurtinib had a strong binding affinity for CDK1, TOP2A and AURKA, respectively. Therefore, our study repositioned PHA-793887, pidorubicine and lestaurtinib, which can inhibit cell cycle regulators, as novel agents for HGSC treatment, thereby helping to optimize the therapeutic strategy for HGSC.

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BackgroundThe high recurrence rate of hepatocellular carcinoma (HCC) after surgery negatively affects the prognosis of patients. There is currently no widely accepted adjuvant therapy strategy for patients with HCC. A clinical study of effective adjuvant therapy is still needed.MethodsIn this prospective, single-arm, phase II clinical trial, an adjuvant regimen of donafenib plus tislelizumab combined with transarterial chemoembolization (TACE) will be used to treat enrolled HCC patients after surgery. Briefly, patients newly diagnosed with HCC by pathological examination who underwent curative resection and had a single tumor more than 5 cm in diameter with microvascular invasion as detected by pathological examination are eligible. The primary endpoint of the study is the recurrence-free survival (RFS) rate at 3 years, and secondary endpoints are the overall survival (OS) rate and the incidence of adverse events (AEs). The planned sample size, 32 patients, was calculated to permit the accumulation of sufficient RFS events in 3 years to achieve 90% power for the RFS primary endpoint.DiscussionVascular endothelial growth factor (VEGF) and programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) pathways regulate the relevant immunosuppressive mechanisms of HCC recurrence. Our trial will evaluate the clinical benefit of adding donafenib plus tislelizumab to TACE in patients with early-stage HCC and a high risk of recurrence.Clinical trial registrationwww.chictr.org.cn, identifier ChiCTR2200063003.

Simple summarySomatic and germline aberrations in homologous recombinant repair (HHR) genes are associated with increased incidence and poor prognosis for prostate cancer. Through next-generation sequencing of prostate cancer patients across all clinical states from north China, here the authors identified a somatic mutational rate of 3% and a germline mutational rate of 3.9% for HRR genes using 200 tumor tissues and 714 blood specimens. Thus, mutational rates in HRR genes were lower compared with previous studies.BackgroundHomologous recombination repair deficiency is associated with higher risk and poorer prognosis for prostate cancer. However, the landscapes of somatic and germline mutations in these genes remain poorly defined in Chinese patients, especially for those with localized disease and those from north part of China. In this study, we explore the genomic profiles of these patients.MethodsWe performed next-generation sequencing with 200 tumor tissues and 714 blood samples from prostate cancer patients at Peking University First Hospital, using a 32 gene panel including 19 homologous recombination repair genes.ResultsTP53, PTEN, KRAS were the most common somatic aberrations; BRCA2, NBN, ATM were the most common germline aberrations. In terms of HRR genes, 3% (6/200) patients harbored somatic aberrations, and 3.8% (28/714) patients harbored germline aberrations. 98.0% (196/200) somatic-tested and 72.7% (519/714) germline tested patients underwent prostatectomy, of which 28.6% and 42.0% had Gleason scores ≥8 respectively. Gleason scores at either biopsy or prostatectomy were predictive for somatic aberrations in general and in TP53; while age of onset <60 years old, PSA at diagnosis, and Gleason scores at biopsy were clinical factors associated with positive germline aberrations in BRCA2/ATM.ConclusionsOur results showed a distinct genomic profile in homologous recombination repair genes for patients with prostate cancer across all clinical states from north China. Clinicians may consider to expand the prostate cancer patients receiving genetic tests to include more individuals due to the weak guiding role by the clinical factors currently available.

Background. Accurate pathological diagnosis of gastric endoscopic biopsy could greatly improve the opportunity of early diagnosis and treatment of gastric cancer. The Japanese “Group classification” of gastric biopsy corresponds well with the endoscopic diagnostic system and can guide clinical treatment. However, severe shortage of pathologists and their heavy workload limit the diagnostic accuracy. This study presents the first attempt to investigate the applicability and effectiveness of AI-aided system for automated Japanese “Group classification” of gastric endoscopic biopsy. Methods. In total, 260 whole-slide images of gastric endoscopic biopsy were collected from Dalian Municipal Central Hospital from January 2015 to January 2021. These images were annotated by experienced pathologists according to the Japanese “Group classification.” Five popular convolutional neural networks, i.e., VGG16, VGG19, ResNet50, Xception, and InceptionV3 were trained and tested. The performance of the models was compared in terms of widely used metrics, namely, AUC (area under the receiver operating characteristic curve, i.e., ROC curve), accuracy, recall, precision, and F1 score. Results. Results showed that ResNet50 achieved the best performance with accuracy 93.16% and AUC 0.994. Conclusion. Our results demonstrated the applicability and effectiveness of DL-based system for automated Japanese “Group classification” of gastric endoscopic biopsy.