Advanced Omics and Radiobiological Tissue Archives: The Future in the Past

Abstract

Archival formalin-fixed, paraffin-embedded (FFPE) tissues and their related diagnostic records are an invaluable source of biological information. The archival samples can be used for retrospective investigation of molecular fingerprints and biomarkers of diseases and susceptibility. Radiobiological archives were set up not only following clinical performance such as cancer diagnosis and therapy but also after accidental and occupational radiation exposure events where autopsies or cancer biopsies were sampled. These biobanks provide unique and often irreplaceable materials for the understanding of molecular mechanisms underlying radiation-related biological effects. In recent years, the application of rapidly evolving “omics” platforms, including transcriptomics, genomics, proteomics, metabolomics and sequencing, to FFPE tissues has gained increasing interest as an alternative to fresh/frozen tissue. However, omics profiling of FFPE samples remains a challenge mainly due to the condition and duration of tissue fixation and storage, and the extraction methods of biomolecules. Although biobanking has a long history in radiation research, the application of omics to profile FFPE samples available in radiobiological archives is still young. Application of the advanced omics technologies on archival materials provides a new opportunity to understand and quantify the biological effects of radiation exposure. These newly generated omics data can be well integrated into results obtained from earlier experimental and epidemiological analyses to shape a powerful strategy for modelling and evaluating radiation effects on health outcomes. This review aims to give an overview of the unique properties of radiation biobanks and their potential impact on radiation biology studies. Studies recently performed on FFPE samples from radiobiology archives using advanced omics are summarized. Furthermore, the compatibility of archived FFPE tissues for omics analysis and the major challenges that lie ahead are discussed.