Cancer Clinical Trial
Official title:
Feasibility Study Testing Multi-panel Coding and Non-coding Transcriptional Responses as an Indicator of Individualised Responses to Radiation Effects in Radiation Therapy Patients
Peripheral blood samples will be taken with informed consent from radiotherapy patients undergoing standard radiotherapy at The Royal Marsden before and during treatment for breast, lung, gastrointestinal and genitourinary tumours. Responses from panels of up to 800 coding and non-coding RNAs will be assessed in the samples using the nCounter system. Candidate genes identified by Public Health England, Columbia University and/or in the literature as being specific to radiation responses will be included, together with genes relevant to systemic inflammatory responses, to identify transcriptional responses for a range of doses and exposures on an inter-individual basis. Data will be analysed using existing and new statistical tools focused on count data modelling. The intended outcome is identification of a radiation specific panel of genes to inform individual radiation responses and if the results are favourable, a large scale follow up to this proposed pilot is expected in due course.
Biological markers of radiation exposure play a crucial role in the triage of suspected
exposed persons following a radiation accident or incident. They can also estimate individual
doses that enable assessment of late radiation effects in affected individuals. In recent
years the gene expression assay has been shown to be a sensitive biological marker of
radiation exposure with the potential to be used for truly individualised dosimetry. The
possibility for this gene expression assay to be used in a large scale mass-casualty scenario
has been proposed and tested in a recent intercomparison exercise. Classic cytogenetic
techniques, and in particular the gold standard dicentric assay, have two main disadvantages:
(1) lack of high-throughput and (2) delays of several days between blood sampling and the
availability of results. Although more work needs to be done to further assess its
suitability for triage purposes, it is clear that gene expression analysis in blood samples
can provide valuable information, as there is a window of time (i.e. 12-48 hours) following
radiation exposure where specific radiation-responsive genes have linear dose responses (0-5
Gy). Most work to date has focused on developing sensitive assays for studying gene
expression modifications using state of the art technology, i.e. multiplex quantitative,
digital polymerase chain reaction (qPCR) and molecular counting systems.
At Public Health England (PHE), recently established technology allows direct counting of
nucleic acid molecules (DNA, mRNA, miRNA and lncRNA) without the need for enzymatic reaction
or amplification steps hence reducing time for data collection. The system offers
multiplexing capacity comparable to microarrays but with greater precision and sensitivity.
Another unique advantage of this technology is that there is no need for long, time consuming
bioinformatic analyses as the results are obtained as counted number of events. This new gene
expression analysis technique has been assessed for radiation biodosimetry applications with
promising results. Furthermore, gene expression has shown a high degree of promise as a
marker for late effects of radiation, for instance normal tissue reactions following curative
radiotherapy for breast cancer. Clinical data suggest that systemic inflammatory responses
plays a critical role in the progression of radiation effects: for instance, the
neutrophil-to-lymphocyte ratio represents a marker of systemic inflammation pre-treatment and
is an independent prognostic factor useful for individual risk assessment in breast cancer
patients undergoing radiotherapy. Genes relevant to inflammatory responses are thus
interesting candidates for further investigation. Linearity of the transcriptional
dose-response for specific radiation-responsive genes in ex vivo exposed human blood samples
has recently been demonstrated for the first time, and inter-individual variability in the
response after low doses and high doses exposures has been newly assessed. The logical next
stage for biological development of the gene expression assay is to validate these new
techniques with human blood samples exposed to radiation in vivo.
The use of samples from patients undergoing radiotherapy for validation of techniques has
been gaining popularity in recent years. Sophisticated treatment planning for clinical
radiotherapy leads to very accurate individual dose calculations that allow for validation of
biological estimates of dose. The range of standard radiotherapy schedules chosen for
inclusion in this study will provide a wide range of doses for assessment of the gene
expression assay alone and in combination with the other cytogenetic assays, to simulate a
range of potential exposure scenarios.
Peripheral blood samples will be taken with informed consent from patients undergoing
standard radiotherapy before and during treatment for breast, lung, gastrointestinal and
genitourinary tumours. Responses from panels of up to 800 coding and non-coding RNAs will be
assessed in the samples using the nCounter system. Candidate genes identified by PHE,
Columbia and/or in the literature as being specific to radiation responses will be included,
together with genes relevant to systemic inflammatory responses, to identify transcriptional
responses for a range of doses and exposures on an inter-individual basis. Data will be
analysed using existing and new statistical tools focused on count data modelling. The
intended outcome is identification of a radiation specific panel of genes to inform
individual radiation responses and if the results are favourable, a large scale follow up to
this proposed pilot is expected in due course.
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