Oike Takahiro, Kambe Ryosuke, Darwis Narisa Dewi Maulany, Shibata Atsushi, Ohno Tatsuya
Gunma University Heavy Ion Medical Center, Maebashi, Gunma, Japan.
Department of Radiation Oncology, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan.
Cancer Sci. 2025 Mar;116(3):690-697. doi: 10.1111/cas.16334. Epub 2024 Dec 12.
Personalized radiotherapy based on the intrinsic sensitivity of individual tumors is anticipated, however, it has yet to be realized. To explore cancer radiosensitivity, analysis in combination with omics data is important. The Cancer Cell Line Encyclopedia (CCLE) provides multi-layer omics data for hundreds of cancer cell lines. However, the radiosensitivity counterpart is lacking. To address this issue, we aimed to establish a database of radiosensitivity, as assessed by the gold standard clonogenic assays, for the CCLE cell lines by collecting data from the literature. A deep learning-based screen of 33,284 papers identified 926 relevant studies, from which SF (survival fraction after 2 Gy irradiation) data were extracted. The median SF (mSF) was calculated for each cell line, generating an mSF database comprising 285 cell lines from 28 cancer types. The mSF showed a normal distribution among higher and lower cancer-type hierarchies, demonstrating a large variation across and within cancer types. In selected cell lines, mSF correlated significantly with the single-institution SF obtained using standardized experimental protocols or with integral survival, a radiosensitivity index that correlates with clonogenic survival. Notably, the mSF for blood cancer cell lines was significantly lower than that for solid cancer cell lines, which is in line with the empirical knowledge that blood cancers are radiosensitive. Furthermore, the CCLE-derived protein levels of NFE2L2 and SQSTM1, which are involved in antioxidant damage responses that confer radioresistance, correlated significantly with mSF. These results suggest the robustness and potential utility of the mSF database, linked to multi-layer omics data, for exploring cancer radiosensitivity.
基于个体肿瘤内在敏感性的个性化放疗虽备受期待,但尚未实现。为探索癌症放射敏感性,结合组学数据进行分析至关重要。癌症细胞系百科全书(CCLE)提供了数百种癌细胞系的多层组学数据。然而,缺乏与之对应的放射敏感性数据。为解决这一问题,我们旨在通过从文献中收集数据,为CCLE细胞系建立一个基于金标准克隆形成试验评估的放射敏感性数据库。基于深度学习对33284篇论文进行筛选,确定了926项相关研究,并从中提取了2 Gy照射后的存活分数(SF)数据。计算每个细胞系的中位SF(mSF),生成一个包含来自28种癌症类型的285个细胞系的mSF数据库。mSF在高低不同癌症类型层次中呈正态分布,表明在癌症类型之间和内部存在很大差异。在选定的细胞系中,mSF与使用标准化实验方案获得的单机构SF或与与克隆形成存活相关的放射敏感性指数——积分存活显著相关。值得注意的是,血液癌细胞系的mSF显著低于实体癌细胞系,这与血液癌症对放疗敏感的经验认识一致。此外,参与赋予放射抗性的抗氧化损伤反应的NFE2L2和SQSTM1的CCLE衍生蛋白水平与mSF显著相关。这些结果表明,与多层组学数据相关联的mSF数据库在探索癌症放射敏感性方面具有稳健性和潜在实用性。