Integrative Bioinformatic Analysis of Transcriptomic Data Identifies Conserved Molecular Pathways Underlying Ionizing Radiation-Induced Bystander Effects (RIBE)

Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study

The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optimally predict radiation-associated contralateral breast cancer (RCBC) and to provide new biological insights into the carcinogenic process. Fifty-two women with contralateral breast cancer and 153 women with unilateral breast cancer were identified within the Women’s Environmental Cancer and Radiation Epidemiology (WECARE) Study who were at increased risk of RCBC because they were ≤ 40 years of age at first diagnosis of breast cancer and received a scatter radiation dose > 1 Gy to the contralateral breast. A previously reported algorithm, preconditioned random forest regression, was applied to predict the risk of developing RCBC. The resulting model produced an area under the curve (AUC) of 0.62 (p = 0.04) on hold-out validation data. The biological analysis identified the cyclic AMP-mediated signaling and Ephrin-A as significant biological correlates, which were previously shown to influence cell survival after radiation in an ATM-dependent manner. The key connected genes and proteins that are identified in this analysis were previously identified as relevant to breast cancer, radiation response, or both. In summary, machine learning/bioinformatics methods applied to genome-wide genotyping data have great potential to reveal plausible biological correlates associated with the risk of RCBC.

Gene Expression Studies for the Development of Particle Therapy

Proton therapy for cancer is now in widespread use, and facilities for carbon ion therapy are showing great promise, but a more complete understanding of the mechanisms underlying particle radiation therapy is still needed in order to optimize treatment. Studies of gene expression, especially those using whole genome techniques, can provide insight into many of the questions still remaining, from the molecular mechanisms involved to predicting patient outcome. This review will summarize gene expression studies of response to proton and carbon ion beams, as well as high-energy protons and high-z high-energy particles with relevance to particle therapy. In general, most such studies find that, in comparison with x-ray or gamma-ray exposure, particle irradiation increases both the number of genes responding and the magnitude of the response. Patterns of gene expression have suggested impacts on specific pathways of relevance to radiation therapy, such as enhancement or suppression of tumor progression or metastasis. However, even within the relatively small number of studies done to date there is no clear consensus of response, suggesting influence by multiple parameters, such as particle type, particle energy, and tumor type. Systematic gene expression studies can help to address these issues, and promoting a culture of data sharing will expedite the process, benefiting investigators across the radiation therapy field.

Changes in gene expression as one of the key mechanisms involved in radiation-induced bystander effect

The radiation-induced bystander effect (RIBE) refers to the manifestation of responses by non-targeted/non-hit cells or tissues situated in proximity to cells and tissues directly exposed to ionizing radiation (IR). The RIBE is elicited by agents and factors released by IR-hit cells. The growing body of data suggests that the underlying mechanisms of the RIBE are multifaceted depending both on the biological (characteristics of directly IR-exposed cells, bystander cells, intercellular milieu) and the physical (dose, rate and type of IR, time after exposure) factors/parameters. Although the exact identity of bystander signal(s) is yet to be identified, the published data indicate changes in gene expression for multiple types of RNA (mRNA, microRNA, mitochondrial RNA, long non-coding RNA, small nucleolar RNA) as being one of the major responses of cells and tissues in the context of the RIBE. Gene expression profiles demonstrate a high degree of variability between distinct bystander cell and tissue types. These alterations could independently, or in a signaling cascade, result in the manifestation of readily observable endpoints, including changes in viability and genomic instability. Here, the relevant publications on the gene candidates and signaling pathways involved in the RIBE are reviewed, and a framework for future studies, both in vitro and in vivo, on the genetic aspect of the RIBE is provided.