Triptonide induces apoptosis and inhibits the proliferation of ovarian cancer cells by activating the p38/p53 pathway and autophagy.

Ovarian cancer is a common malignant tumor in women, and 70 % of ovarian cancer patients are diagnosed at an advanced stage. Drug chemotherapy is an important method for treating ovarian cancer, but recurrence and chemotherapy resistance often lead to treatment failure. In this study, we screened 10 extracts of Tripterygium wilfordii, a traditional Chinese herb, and found that triptonide had potent anti-ovarian cancer activity and an IC50 of only 3.803 nM against A2780 cell lines. In addition, we determined that triptonide had a better antitumor effect on A2780 cell lines than platinum chemotherapeutic agents in vitro and that triptonide had no significant side effects in vivo. We found that triptonide induced apoptosis in ovarian cancer cells through activation of the p38/p53 pathway and it also induced cell cycle arrest at the S phase. In addition, we demonstrated that triptonide could activate lethal autophagy, which led to growth inhibition and cell death in ovarian cancer cells, resulting in an anti-ovarian cancer effect. Triptonide exerts its anti-ovarian cancer effect through activation of the p38/p53 pathway and induction of autophagy to promote apoptosis, which provides a new candidate drug and strategy for the treatment of ovarian cancer.

Amplification of Hippo Signaling Pathway Genes Is Governed and Implicated in the Serous Subtype-Specific Ovarian Carcino-Genesis.

Among women, ovarian cancer ranks as the fifth most common cause of cancer-related deaths. This study examined the impact of Hippo signaling pathway on ovarian carcinogenesis. Therefore, the signatures related to Hippo signaling pathway were derived from the molecular signatures database (MSigDB) and were used for further analysis. The Z score-based pathway activation scoring method was employed to investigate the expression patterns of these signatures in the mRNA expression profiles of ovarian cancer cohorts. Compared to other subtype tumors, the results of this study show that the Hippo signaling pathway signatures are dysregulated prominently in serous subtype-specific ovarian carcinogenesis. A receiver operating characteristic (ROC) curve-based results of the Hippo gene set, yes-associated protein 1 (YAP1), and mammalian sterile 20-like kinases 1 (MST1) genes can predict the serous subtype tumors by higher specificity and sensitivity with significant areas under the curve values also further reconfirmed these signaling dysregulations. Moreover, these gene sets were studied further for mutation analysis in the profile of high-grade serous ovarian adenocarcinoma in the cBioPortal database. The OncoPrint results reveal that these Hippo signaling pathway genes are amplified highly during the grade three and stage third or fourth of serous type ovarian tumors. In addition, the results of the Dependency Map (DepMap) plot also clearly show that these genes are amplified significantly across the ovarian cancer cell lines. Finally, overall survival (OS) curve plot investigations also revealed that these gene expressions show poor survival patterns linked to highly expressed conditions in serous subtypes of ovarian cancer patients with significant p-values (p < 0.05). Thus, the current finding would help to develop the targeted therapies treatment for serous subtype ovarian carcinogenesis.

DUB3 is a MAGEA3 deubiquitinase and a potential therapeutic target in hepatocellular carcinoma.

Although melanoma-associated antigen A3 and A6 (MAGEA3/6)-specific tumor vaccines have shown antitumor effects in melanoma and non-small cell lung cancer (NSCLC), many cancers do not respond because MAGEA3 can promote cancer without triggering an immune response. Here, we identified DUB3 as the MAGEA3 deubiquitinase. DUB3 interacts with, deubiquitinates and stabilizes MAGEA3. Depletion of DUB3 in hepatocellular carcinoma (HCC) cells results in MAGEA3 degradation and P53-dependent growth inhibition. Moreover, DUB3 knockout attenuates HCC tumorigenesis in vivo, which can be rescued by restoration of MAGEA3. Intriguingly, pharmacological inhibition of DUB3 by palbociclib promotes degradation of MAGEA3 and inhibits tumor growth in preclinical models implanted with parental HCC cells but not with DUB3 knockout HCC cells. In patients with HCC, DUB3 is highly expressed, and its levels positively correlate with MAGEA3 levels. Taken together, DUB3 is a MAGEA3 deubiquitinase, and abrogating DUB3 enzymatic activity by palbociclib is a promising therapeutic strategy for HCC.

Exploring the role of CD8+ T cells in clear renal cell carcinoma metastasis.

Clear cell renal cell carcinoma (ccRCC) accounts for approximately 75-80% of all patients with renal cell carcinoma. Despite its prevalence, little is known regarding the key components involved in ccRCC metastasis. In this study, scRNA-seq analysis was employed to classify CD8+ T cells into four sub-clusters based on their genetic profiles and immunofluorescence experiments were used to validate two key clusters. Through gene set enrichment analysis, these newly identified sub-clusters were found to exhibit distinct biological characteristics. Notably, TYMP, TOP2A, CHI3L2, CDKN3, CENPM, and RZH2 were highly expressed in these sub-clusters, indicating a correlation with poor prognosis. Among these sub-clusters, CD8+ T cells (MT-ND4) were identified as potentially playing a critical role in mediating ccRCC metastasis. These results contribute to our understanding of CD8+ T cell heterogeneity in ccRCC and shed light on the mechanisms underlying the loss of immune response against cancer.

BRAIxDet: Learning to detect malignant breast lesion with incomplete annotations.

Methods to detect malignant lesions from screening mammograms are usually trained with fully annotated datasets, where images are labelled with the localisation and classification of cancerous lesions. However, real-world screening mammogram datasets commonly have a subset that is fully annotated and another subset that is weakly annotated with just the global classification (i.e., without lesion localisation). Given the large size of such datasets, researchers usually face a dilemma with the weakly annotated subset: to not use it or to fully annotate it. The first option will reduce detection accuracy because it does not use the whole dataset, and the second option is too expensive given that the annotation needs to be done by expert radiologists. In this paper, we propose a middle-ground solution for the dilemma, which is to formulate the training as a weakly- and semi-supervised learning problem that we refer to as malignant breast lesion detection with incomplete annotations. To address this problem, our new method comprises two stages, namely: (1) pre-training a multi-view mammogram classifier with weak supervision from the whole dataset, and (2) extending the trained classifier to become a multi-view detector that is trained with semi-supervised student-teacher learning, where the training set contains fully and weakly-annotated mammograms. We provide extensive detection results on two real-world screening mammogram datasets containing incomplete annotations and show that our proposed approach achieves state-of-the-art results in the detection of malignant breast lesions with incomplete annotations.