Publication

Article

Contemporary Radiation Oncology
October 2015
Volume 1
Issue 2

Platform Technology Development for Biologically Targeted Dosimetry and Radiotherapy

The ability to obtain high-quality radiobiological information about the interactions between tumor and healthy tissue, when using ionizing radiations, would contribute to the development of more effective and personalized radiotherapy treatments.

Frederic Zenhausern, PhD, MBA

The ability to obtain high-quality radiobiological information about the interactions between tumor and healthy tissue, when using ionizing radiations, would contribute to the development of more effective and personalized radiotherapy treatments. It would also benefit both medical research and clinical radio-oncology communities involved in technology development of molecular assays, such as genomic-based biodosimetry or predictive proteomic assay for lateeffects toxicity. Today, biomedical imaging is also allowing noninvasive molecular phenotyping and providing molecular- specific predictive and response biomarkers to clinical therapies. The spectrum of approaches is broad, and our team at the University of Arizona’s Center for Applied NanoBioscience and Medicine (the Center) has since developed expertise in creating new platform technologies integrating genomic and proteomic biomarker signatures into assay platforms for molecular-based biodosimetry, or for assessing toxicity and tissue radio-sensitivity in view of gaining knowledge in the biological mechanisms that could guide precise therapies.

Our aim is to operate a Center of Excellence dedicated to translational research and to the convergence of multidisciplinary technological skills of national or international significance in the fields of nano-biotechnology and radiobiological sciences. Since 2005, the Center has innovated multiple molecular profiling platforms for biodosimetry through its projects portfolio sponsored by federal agencies (eg, Department of Health and Human Services/Biomedical Advanced Research and Development Authority and the National Institute of Allergy and Infectious Diseases); more recently, by international consortia (eg, RadioGenomic Consortium), that contributed to the emerging field of radiomics (ie, genomics, metabolomics, and imaging textural analysis) providing molecular biomarkers of tissue specific responses to radiations. The Center has also entered a memorandum of understanding agreement with the National Centre of Oncological Hadrontherapy in Italy allowing it access to facilities infrastructure for conducting comparative studies of photon, proton and carbon ion treatments. These resources provide an operational framework structured in 3 major research themes: (1) integrated microsystems for automating biospecimen workflow processing and molecular assay chemistries, (2) in vitro radiobiology models, and (3) preclinical trials on patients.

Radiomics Assays Platforms for Personalizing Radiotherapies

Radiomics Assays Platforms for Personalizing Radiotherapies

Over the last several years, the Center has developed microfluidic platforms and instrumentation for integrating the entire workflow processing of biological fluid samples onto lab-on-chip devices. The Lab-on-a-Chip technology has arisen out of the desire to incorporate multiple lab processes within a single platform. This is done for a variety of reasons: to optimize speed, reliability, reagent usage, cost reduction, contamination, and automation, among many others. In particular, rapid DNA analysis from buccal swabs, saliva, and a small volume of blood collected from a fingerstick have been implemented for multiplex genomic profiling of short tandem repeats bio-signatures used in tissue or human identification.1

Similarly, white blood cell separation from the whole blood is important for genomic or proteomic analysis of the cells for clinical diagnostics; and for medical countermeasures in a disaster response. In the case of a radiological event, such as a dirty bomb attack or a clinical radiotherapy accident, individuals may be exposed to different doses of radiation that shall trigger different medical treatments.

Current tests take several days to complete, far too long for patients who must be treated within hours of exposure with medications to bolster their blood and immune systems. A novel approach using gene expression-based biodosimetry can convert genomic testing into a rapid portable system that can assess a small volume of blood samples in less than 1 hour.2-3 The automation of the sample processing comprises the separation of white blood cells from a blood sample by using a low-cost deterministic hydrodynamic microfluidic plastic chip.4 Direct signal amplification assay chemistries (eg, quantitative nuclease protection assay, chemical ligation-dependent probe amplification) are then used to obtain a dose-response genetic profile derived from a set of less than 30 genes.5 Such an approach to measure the dose of radiation absorbed by the body could be applied in clinical situations such as for monitoring the dose of radiation received by patients undergoing radiotherapy treatments. Several preclinical studies have been initiated on patients undergoing radiotherapy treatment for validating these platforms and methodologies with in-vivo samples, (eg, from patients undergoing bone marrow transplantation or heterogeneous bone fracture radio-treatments).

Other potential biomarkers of response to radiations comprise proteins,6 small metabolite molecules, and microRNAs (miRNAs), which are small non-coding RNAs expressed in different tissue and cell types that function as major players of posttranscriptional gene regulation. MiRNAs represent a great opportunity to enhance the efficacy of radiotherapy treatments—they can be used to profile the radioresistance of tumors before radiotherapy, and monitor their response throughout the treatment; thus they help to select intensification strategies and to define the final response to therapy along with risks of recurrence or metastatization.7 It is now recognized miRNAs can be dysregulated in radioresistant cancer cells to promote cancer radioresistance. The Center is designing microfluidic devices for investigating circulating biomarkers identifying plasma miRNAs fingerprinting in patients treated by radiotherapy for correlating with radioresistance status (eg, in breast, cervical, or prostate tumors).

Novel radiation strategies (eg, particle beam or hadrons radiotherapy) are the subject of a growing interest in broad clinical use in the most common categories of cancers. However, there are still needs for developing platform technologies for assessing the biological response(s) and/or any potential adverse effects; more importantly, to optimize the conditions for predicting toxicity risk through novel imaging and biomarker approaches exploiting pretreatment biomolecular assay in the patient blood samples and tumor biopsy specimen. These biologically targeted dosimetry and radiotherapies will enable personalized care and guide precise treatment while providing new research tools for gaining fundamental knowledge in radiobiology with many applications in clinical oncology.

Corresponding Author: Frederic Zenhausern, PhD, MBA, Director and Professor, Center for Applied NanoBioscience and Medicine, University of Arizona, 145 S. 79th Street, AZ 85226, Chandler, USA; Phone: (602) 827-2051 ; Fax: (602)-827-9115 ; E-mail: fzenhaus@email.arizona.edu.

References

  1. Estes MD, Yang Jianing, Duane B, et al. Optimization of multiplexed PCR on an integrated microfluidic forensic platform for rapid DNA analysis. Analyst. 2012;137(23):5510-5519.
  2. Brengues M, Paap B, Bittner M, et al. Low density gene expression array for acute radiation dose assessment. Health Phys. 2010;98(2):179-185.
  3. Badie C, Kabacik S, Bernard N, et al. Comparison of established and emerging biodosimetry assays. Radiat Res. 2013;180(2):138-148.
  4. Brengues M, Gu J, Chen X, East P, et al. Automation of sample processing for gene expression radiobiological assays. Radiat Protect Dosimetry. 2015. 1-5, doi:10.1093/rpd/ncv138.
  5. Lucas J, Dressman HK, Suchindran S, et al. A translatable predictor of human radiation exposure. PLoS One. 2014;(9): e107897. doi:10.1371/journal. pone.0107897.
  6. Lacombe J, Azria D, Mange A, et al. Proteomic approaches to identify biomarkers predictive of radiotherapy outcomes. Expert Rev Proteomics. 2013;10(1):33-42.
  7. Ghandi SA, Weber W, Melo D, Doyle-Eisele M,et al. Effect of 90Sr internal emitter on gene expression in mouse blood. BMC Genomics. 2015 16:586:doi 10.1186. s12864-015-1774-z.

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