Biologically conformal treatment: biomarkers and functional imaging in radiation oncology (original) (raw)
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Human In vivo Radiation-Induced Biomarkers
Cancer Research, 2004
After initially identifying potential biomarkers of radiation exposure through microarray studies of ex vivo irradiated human peripheral white blood cells, we have now measured the in vivo responses of several of these biomarker genes in patients undergoing total body irradiation. Microarray analysis has identified additional in vivo radiation-responsive genes, although the general in vivo patterns of stress-gene induction appear similar to those obtained from ex vivo white blood cell experiments. Additional studies may reveal correlations between responses and either diagnosis or prognosis, and such in vivo validation marks an important step in the development of potentially informative radiation exposure biomarkers. of the CDKN1A, GADD45A, and DDB2 genes in a set of TBI patients, along with the identification of additional potential in vivo exposure marker genes. Materials and Methods Patients and RNA. Patients undergoing TBI at the Pittsburgh Cancer Institute were recruited into this study with informed consent for participation in University of Pittsburgh Cancer Institute (UPCI) Protocol 91-32. Blood was drawn into sodium citrate, frozen immediately in liquid nitrogen, and held at Ϫ80°C until processing. Samples were drawn within 2 hours before the initial radiation treatment, then 6 hours after the first 1.5-Gy fraction, at 24 hours, and at the same intervals after subsequent fractions (one patient only). Two daily 1.5-Gy fractions of X-rays were administered at 10 to 12 cGy/min 6 hours apart with a Siemans 10MV linear accelerator on 4 successive days. None of the patients had prior exposure to any genotoxic treatment for at least 2 weeks before the start of radiotherapy, although diagnosis and white blood cell differentials varied (Table 1). RNA was extracted from whole blood with two rounds of Trizol reagent (Invitrogen, Carlsbad, CA) and subsequent purification on RNeasy columns (Qiagen, Valencia, CA) in accordance with the instructions of the suppliers. Samples were monitored on the Agilent 2100 Bioanalyzer, and only patients yielding sufficient quantities of nondegraded RNA were included in this study. Microarray Hybridization. One hundred micrograms of whole-cell RNA was labeled and hybridized to 6485-element cDNA microarrays [Gene Expression Omnibus (GEO) accession no. GPL1217], as described previously (5). In brief, probes were prepared by PCR amplification of Integrated Molecular Analysis of Genomes and their Expression (IMAGE) consortium clones and arrayed on poly-L-lysine-coated glass slides. Fluorescently labeled cDNA was prepared from whole-cell RNA by a single round of reverse transcription with Superscript II (Invitrogen) in the presence of fluorescent dNTP (Cy3 dUTP or Cy5 dUTP, Amersham Biosciences, Piscataway, NJ). Probes and targets were hybridized together for 16 hours in 3ϫ SSC at 65°C in the presence of the blockers human CoT1 DNA, yeast tRNA, and polydeoxyadenine. Hybridized slides were washed and then scanned with a laser confocal scanner (Agilent Technologies, Palo Alto, CA), and images were analyzed with the use of the ArraySuite 2.1 extensions [Dr. Y. Chen, National Human Genome Research Institute (NHGRI)] in the IPLab program (Scanalytics Inc., Fairfax, VA; refs. 6, 7). Expression ratios were normalized to those of a set of 88 internal controls (8) with a theoretical ratio of 1.0. The variance in the housekeeping set was used to determine the significance of expression changes after treatment. Minimum Information About a Microarray Experiment (MIAME)-compliant intensity, quality, and normalized ratio data for this series of experiments has been deposited in the Gene Expression Omnibus (GEO) database maintained by the National Center for Biotechnology Information (accession no. GSE1366). Uncentered Pearson clustering was done with tools developed by the Division of Computational Bioscience of the Center for Information Technology and the Cancer Genetics Branch of the National Human Genome Research Institute at the NIH. 4 Quantitative Real-time PCR. Primer and probe sets for target genes were chosen with the aid of Primer Express (Applied Biosystems, Inc., Foster City, CA) and Oligo6 (Molecular Biology Insights, Inc., Cascade, CO), as described previously (3). FAM, HEX, and Texas Red were used as fluorochrome
Molecular biology: the key to personalised treatment in radiation oncology?
British Journal of Radiology, 2010
We know considerably more about what makes cells and tissues resistant or sensitive to radiation than we did 20 years ago. Novel techniques in molecular biology have made a major contribution to our understanding at the level of signalling pathways. Before the ''New Biology'' era, radioresponsiveness was defined in terms of physiological parameters designated as the five Rs. These are: repair, repopulation, reassortment, reoxygenation and radiosensitivity. Of these, only the role of hypoxia proved to be a robust predictive and prognostic marker, but radiotherapy regimens were nonetheless modified in terms of dose per fraction, fraction size and overall time, in ways that persist in clinical practice today. The first molecular techniques were applied to radiobiology about two decades ago and soon revealed the existence of genes/proteins that respond to and influence the cellular outcome of irradiation. The subsequent development of screening techniques using microarray technology has since revealed that a very large number of genes fall into this category. We can now obtain an adequately robust molecular signature, predicting for a radioresponsive phenotype using gene expression and proteomic approaches. In parallel with these developments, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) can now detect specific biological molecules such as haemoglobin and glucose, so revealing a 3D map of tumour blood flow and metabolism. The key to personalised radiotherapy will be to extend this capability to the proteins of the molecular signature that determine radiosensitivity.
Radiation-Induced Gene Translation Profiles Reveal Tumor Type and Cancer-Specific Components
Cancer Research, 2008
The microarray analysis of total cellular RNA is a common method used in the evaluation of radiation-induced gene expression. However, profiling the cellular transcriptome does not take into account posttranscriptional processes that affect gene expression. To better define the genes whose expression is influenced by ionizing radiation, we used polysome-bound RNA to generate gene translation profiles for a series of tumor and normal cell lines. Cell lines were exposed to 2 Gy, polysome-bound RNA isolated 6 hours later, and then subjected to microarray analysis. To identify the genes whose translation was affected by radiation, the polysome-bound RNA profiles were compared with their corresponding controls using significance analysis of microarrays (<1% false discovery rate). From the statistically significant genes identified for each cell line, hierarchical clustering was performed by average linkage measurement and Pearson's correlation metric. Ingenuity Pathway Analysis was used for distributing genes into biological networks and for evaluation of functional significance. Radiation-induced gene translation profiles clustered according to tissue of origin; the cell lines corresponding to each tissue type contained a significant number of commonly affected genes. Network analyses suggested that the biological functions associated with the genes whose translation was affected by radiation were tumor type-specific. There was also a set of genes/networks that were unique to tumor or normal cells. These results indicate that radiation-induced gene translation profiles provide a unique data set for the analysis of cellular radioresponse and suggest a framework for identifying and targeting differences in the regulation of tumor and normal cell radiosensitivity. [Cancer Res 2008;68(10):3819-26] Requests for reprints: Philip J. Tofilon,
International Journal of Radiation Biology, 2021
In a nuclear or radiological event, an early diagnostic or prognostic tool is needed to distinguish unexposed from low-and highly-exposed individuals with the latter requiring early and intensive medical care. Radiation-induced gene expression (GE) changes observed within hours and days after irradiation have shown potential to serve as biomarkers for either dose reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of GE markers lies in their capability for early (1-3 day after irradiation), high-throughput, and point-of-care diagnosis required for the prediction of the acute radiation syndrome (ARS). Conclusions As a key session of the ConRad conference in 2021, experts from different institutions were invited to provide state-of-the-art information on a range of topics including: (1) Biodosimetry: What are the current efforts to enhance the applicability of this method to perform retrospective biodosimetry? (2) Effect Prediction: Can we apply radiation-induced GE changes for prediction of acute health effects as an approach, complementary to and integrating retrospective dose estimation? (3) High-throughput and Point-of-Care Diagnostics: What are the current developments to make the GE approach applicable as a high-throughput as well as a point-of-care diagnostic platform? (4) Low Level Radiation: What is the lowest dose range where GE can be used for biodosimetry purposes? (5) Methodological Considerations: Different aspects of radiation-induced GE related to more detailed analysis of exons, transcripts and next-generation sequencing (NGS) were reported.