Establishment of cancer cell radiosensitivity database linked to multi-layer omics data

Area of Science:

• Oncology
• Radiation Oncology
• Genomics

Background:

• Personalized radiotherapy requires understanding individual tumor radiosensitivity, which is currently lacking.
• The Cancer Cell Line Encyclopedia (CCLE) offers multi-omics data but lacks radiosensitivity information.
• Bridging this gap is crucial for advancing precision cancer treatment.

Purpose of the Study:

• To establish a comprehensive database of cancer cell line radiosensitivity using clonogenic assay data.
• To integrate this radiosensitivity data with existing CCLE multi-omics data.
• To explore correlations between radiosensitivity and molecular features for personalized radiotherapy.

Main Methods:

• A deep learning approach screened over 33,000 papers to identify relevant studies.
• Survival Fraction after 2 Gy irradiation (SF2) data were extracted and median SF2 (mSF2) calculated for 285 cell lines.
• mSF2 values were correlated with single-institution SF2, integral survival, and CCLE-derived protein levels.

Main Results:

• A robust mSF2 database was generated for 285 cell lines across 28 cancer types, showing significant variation.
• mSF2 correlated well with established radiosensitivity measures and showed lower values for blood cancers.
• CCLE protein levels of NFE2L2 and SQSTM1, involved in radioresistance, significantly correlated with mSF2.

Conclusions:

• The mSF2 database is a valuable resource for investigating cancer radiosensitivity.
• Linking radiosensitivity data with multi-omics profiles enables exploration of mechanisms underlying treatment response.
• This resource holds potential for the development of personalized radiotherapy strategies.