Abstract
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(2) (survival fraction after 2 Gy irradiation) data were extracted. The median SF(2) (mSF(2)) was calculated for each cell line, generating an mSF(2) database comprising 285 cell lines from 28 cancer types. The mSF(2) 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(2) correlated significantly with the single-institution SF(2) obtained using standardized experimental protocols or with integral survival, a radiosensitivity index that correlates with clonogenic survival. Notably, the mSF(2) 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(2). These results suggest the robustness and potential utility of the mSF(2) database, linked to multi-layer omics data, for exploring cancer radiosensitivity.