癌症
表观遗传学
鉴定(生物学)
计算生物学
基因组学
疾病
政治学
生物
工程伦理学
系统生物学
生物信息学
血液肿瘤
范式转换
精密医学
约束(计算机辅助设计)
下载
数据科学
最佳实践
癌细胞
表观遗传学
癌症研究
癌症的体细胞进化
医学
信息学
转化研究
乳腺癌
大数据
癌症生物标志物
作者
Dachuan Huang,Wee‐Wei Tee,Sanjay De Mel,Koji Itahana,Kanaga Sabapathy,Kristijan Ramadan,Reshma Taneja,Le Minh Giang,Derrick Sek Tong Ong,Zhong Yi Yeow,S. Tiong Ong,Yilong Zhou,Anthony Khong,Soo Chin Lee,Sasidharan Swarnalatha Lucky,Wai Leong Tam,N. Gopalakrishna Iyer,Choon Kiat Ong
出处
期刊:Cancer Research
[American Association for Cancer Research]
日期:2026-07-01
卷期号:86 (13): 3106-3108
标识
DOI:10.1158/0008-5472.can-26-1788
摘要
The 17th Annual Frontiers in Cancer Science (FCS) conference (2025) highlighted the convergence of multiomics, computational biology, and ancestry-specific genomics to advance proactive cancer care. Key insights included the role of epigenetic plasticity in maintaining tumor-propagating states and the identification of metabolic vulnerabilities, such as the WNK1-mTORC1 axis in leukemia and MAF-driven glutamine metabolism in myeloma. The meeting underscored the systemic nature of cancer, detailing how "cancer-educated" neutrophils prime premetastatic niches and how spatial exclusion mechanisms hinder immunotherapy. Breakthroughs in therapeutic engineering were showcased, including CD7-directed chimeric antigen receptor T cells and irreversible KRASG12C inhibitors. A critical focus remained on precision oncology for diverse populations, advocating for ancestry-aware datasets and long-read sequencing to address genomic disparities in Asian cohorts. Furthermore, the integration of artificial intelligence-driven "fragmentomics" and machine learning offers new pathways for early detection and tracking disease lethality. Collectively, FCS 2025 demonstrated that the future of oncology lies in integrating high-resolution disease models with robust data science to transition from reactive treatment to personalized, interceptive management.
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