Ceranib-2 potentiates cisplatin activity under an experimental in vitro hipec-like model by inducing integrated stress and cell death pathways in ovarian cancer
This study aims to investigate whether the addition of Ceranib-2, an acid ceramidase inhibitor, could enhance the cytotoxic efficacy of cisplatin under hyperthermic conditions using an OVCAR-3 ovarian cancer cell model. The combination of cisplatin and ceranib-2, administered at a tolerable hyperthermic temperature of 39 ˚C, significantly decreased cell viability and induced robust programmed cell death compared to monotherapies. Notably, our findings reveal a complex mechanistic interplay: while cisplatin monotherapy primarily relied on ROS-dependent pathways, the combination treatment triggered potent anticancer effects through ceramide-driven ER stress and autophagy, even exhibiting lower ROS levels than cisplatin alone. This suggests a shift toward ROS-independent death mechanisms. Furthermore, we observed a significant 4-fold upregulation of the anti-apoptotic protein Bcl-2 in the combination group. This increase is characterized as a compensatory pro-survival response to intense cellular stress, which was ultimately overwhelmed by the marked activation of caspase-3/7 and mitochondrial depolarization. The integration of in vitro GDH activity measurements and in silico molecular docking analyses suggests that ceranib-2 may interact with glutamate dehydrogenase (GDH), potentially contributing to the observed reduction in GDH activity. The docking results further indicate a possible interaction with the NAD⁺-binding domain and C-terminal α-helix, supporting a putative allosteric binding mode that warrants further experimental validation. Additionally, the combination treatment significantly impaired the colony-forming ability and spread of tumor cells. These results demonstrate that the cisplatin and ceranib-2 combination elicit a synergistic effect by utilizing complementary pathways to overcome chemoresistance. Consequently, this study provides valuable insights and experimental evidence for future optimization of HIPEC protocols by targeting ceramide metabolism and ER stress signaling to improve therapeutic outcomes in ovarian cancer.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.