Results 151 to 160 of about 22,446 (263)

Integrating Spatial Proteogenomics in Cancer Research

open access: yesAdvanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang   +13 more
wiley   +1 more source

The ITGB2‐COPS3‐SOX2 Axis and SOX2 Liquid‐Liquid Phase Separation: Dual Mechanisms Governing Osteosarcoma Stemness

open access: yesAdvanced Science, EarlyView.
Osteosarcoma stemness is driven by the ITGB2‐COPS3‐SOX2 signaling axis. This study reveals that nuclear COPS3 stabilizes SOX2, which in turn undergoes liquid‐liquid phase separation to promote stemness. Based on this mechanism, a novel COPS3 inhibitor, Z‐5891, was developed, effectively suppressing tumor growth and stemness in vivo, offering a ...
Lei Guo   +7 more
wiley   +1 more source

Single‐Cell Dissection of Tumor‐Infiltrating Lymphocytes Reveals Cellular Architecture Predictive of Therapeutic Efficacy in Acral Melanoma

open access: yesAdvanced Science, EarlyView.
Autologous tumor‐infiltrating lymphocyte (TIL) therapy shows promising efficacy in acral melanoma, yet determinants of durable response remain unclear. By integrating single‐cell transcriptomics and TCR sequencing, this study reveals that TIL products enriched for T follicular helper and intermediate exhausted T cells establish persistent clonal ...
Chao Zhang   +12 more
wiley   +1 more source

Random Time‐Space Coding Metasurfaces for Spatial Control of the Temporal Statistics of Electromagnetic Fields

open access: yesAdvanced Science, EarlyView.
A probabilistic framework based on random time‐space coding metasurfaces enables control of the spatial distribution of electromagnetic fields temporal statistics. By tailoring the marginal and joint distributions of random codes, electromagnetic fields with desired mean and variance patterns are realized, enabling simultaneous transmission and jamming.
Jia Cheng Li   +3 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

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