Michael D Story1,2, Marco Durante3,4. 1. Department of Radiation Oncology, University of Texas, Southwestern Medical Center, Dallas, TX, USA. 2. Simmons Comprehensive Cancer Center, University of Texas, Southwestern Medical Center, Dallas, TX, USA. 3. Trento Institute for Fundamental Physics Applications, National Institute for Nuclear Physics, Trento, Italy. 4. Department of Physics, University of Trento, Trento, Italy.
Abstract
PURPOSE: Radiogenomics is the study of genomic changes that underlie the radioresponse of normal and tumor tissues. And while this is generally regarded as a whole genome approach, one must keep in mind the impact of single gene biology on radioresponse, (ataxia telangiectasia, Nijmegen breakage syndrome). METHODS: This review begins with the association of single nucleotide polymorphisms in the DNA with adverse normal tissue events to the prediction of therapeutic outcome after radiotherapy. From there it covers transcriptome (protein coding RNA transcripts) analysis, which is where the greatest understanding of the molecular signaling responsible for the radioresponse of tumors and normal tissues is known. Non-protein coding RNA transcripts (miRNA, lncRNA), transcribed from what was once thought of as junk DNA, are now known to be negative regulators of the transcription of mRNA by multiple mechanisms. miRNA can act as tumor suppressors or oncogenes regulating a diverse range of cellular processes that drive radioresponse and biosignatures that predict outcome after radiotherapy are described. RESULTS: Biological signatures that explain differences in radioresponse based upon cell type, biological signatures that predict surviving fraction at 2 Gy and signatures that identify hypoxia have been described. The omics analysis of the response of mammalian cells to charged particle, predominantly proton and carbon ions, is less mature than that seen with low LET radiation exposures. However, there appear to be responses after charged particle exposure that parallel the responses seem with low LET exposures. This commonality of response is centered around the downstream signaling of p53. There are also novel omics responses to charged particles that help explain the response of tumors to charged particle exposures. For instance, signaling pathways associated with angiogenesis, vasculogenesis, migration and invasion appear to be downregulated in a number of cell types when exposed to charged particles. This response supports both in vitro and in vivo data suggesting that tumors exposed to charged particles are less invasive, unlike the response of tumors to low LET exposures. Profoundly lacking for low LET and charged particle exposures are predictive or prognostic signatures of radioresponse or tumor physiology affecting radioresponse that have been validated in prospective clinical trials. For example, the identification of low LET tumor radioresistance could be used as a marker of patient eligibility for carbon therapy. Tissue specific signatures, or accurate imaging of hypoxic regions, could be used for charged particle selection to overcome hypoxia per se, or could be used to prescribe a high LET therapeutic boost to a hypoxic region of a tumor. CONCLUSIONS: Integrating radiogenomics into radiation oncology has the potential to personalize an already precise form of cancer therapy.
PURPOSE: Radiogenomics is the study of genomic changes that underlie the radioresponse of normal and tumor tissues. And while this is generally regarded as a whole genome approach, one must keep in mind the impact of single gene biology on radioresponse, (ataxia telangiectasia, Nijmegen breakage syndrome). METHODS: This review begins with the association of single nucleotide polymorphisms in the DNA with adverse normal tissue events to the prediction of therapeutic outcome after radiotherapy. From there it covers transcriptome (protein coding RNA transcripts) analysis, which is where the greatest understanding of the molecular signaling responsible for the radioresponse of tumors and normal tissues is known. Non-protein coding RNA transcripts (miRNA, lncRNA), transcribed from what was once thought of as junk DNA, are now known to be negative regulators of the transcription of mRNA by multiple mechanisms. miRNA can act as tumor suppressors or oncogenes regulating a diverse range of cellular processes that drive radioresponse and biosignatures that predict outcome after radiotherapy are described. RESULTS: Biological signatures that explain differences in radioresponse based upon cell type, biological signatures that predict surviving fraction at 2 Gy and signatures that identify hypoxia have been described. The omics analysis of the response of mammalian cells to charged particle, predominantly proton and carbon ions, is less mature than that seen with low LET radiation exposures. However, there appear to be responses after charged particle exposure that parallel the responses seem with low LET exposures. This commonality of response is centered around the downstream signaling of p53. There are also novel omics responses to charged particles that help explain the response of tumors to charged particle exposures. For instance, signaling pathways associated with angiogenesis, vasculogenesis, migration and invasion appear to be downregulated in a number of cell types when exposed to charged particles. This response supports both in vitro and in vivo data suggesting that tumors exposed to charged particles are less invasive, unlike the response of tumors to low LET exposures. Profoundly lacking for low LET and charged particle exposures are predictive or prognostic signatures of radioresponse or tumor physiology affecting radioresponse that have been validated in prospective clinical trials. For example, the identification of low LET tumor radioresistance could be used as a marker of patient eligibility for carbon therapy. Tissue specific signatures, or accurate imaging of hypoxic regions, could be used for charged particle selection to overcome hypoxia per se, or could be used to prescribe a high LET therapeutic boost to a hypoxic region of a tumor. CONCLUSIONS: Integrating radiogenomics into radiation oncology has the potential to personalize an already precise form of cancer therapy.
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