Bone metastases (BoM) develop in 60–90% of men with advanced prostate cancer (PCa) and are associated with a significantly decreased quality of life and 5-fold increased risk of mortality. However, current frontline treatments offer only marginal improvements in survival and symptom management. In this study, we investigated the metabolic landscape of BoM lesions of PCa and found that prostate tumors rewire their metabolism to adapt to the bone microenvironment, utilizing lactate as an alternative nutrient source. Beyond its previously reported role in oxidative phosphorylation (OXPHOS), lactate serves as a net carbon source for fatty acid synthesis (FAS) in bone-colonized cancer cells. In turn, these cancer cells produce oleic acid (OA), which enhances osteoblast activity and drives pathological osteogenesis. At the molecular level, we identified monocarboxylate transporter 1 (MCT1) as the key membrane transporter enabling prostate tumor cells to take up lactate from the bone microenvironment. This process is subtly regulated by the nuclear factor of activated T cells (NFAT) and extracellular glucose levels, which together control both the transcription of SLC16A1 and the stability of MCT1 protein in response to the unique environmental challenges in bone. Notably, genetic ablation of MCT1, as well as pharmacological inhibition using the MCT1 inhibitor AZD3965, significantly suppressed PCa growth in bone. These findings highlight MCT1 as a critical metabolic vulnerability in PCa BoM and suggest that targeting lactate uptake may offer a promising therapeutic strategy for this lethal disease.
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
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Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
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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.