Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT03809377 |
| Other study ID # |
IRAS258792 |
| Secondary ID |
|
| Status |
Active, not recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
May 9, 2019 |
| Est. completion date |
June 1, 2024 |
Study information
| Verified date |
August 2023 |
| Source |
Institute of Cancer Research, United Kingdom |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Peripheral blood samples will be taken with informed consent from radiotherapy patients
before and during treatment fractions for sarcoma, breast, lung, gut, genitourinary and head
& neck tumours at The Royal Marsden. Candidate genes identified by PHE, Columbia and/or in
the literature as being specific to radiation responses will be assessed, together with genes
relevant to systemic inflammatory and immune 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 project is
expected.
Description:
Biomarkers of radiation exposure are recognised to form an important component of the
'toolkit' for initial triage assessment of potentially exposed individuals in a mass casualty
radiation accident or incident. Furthermore, radiation is an important medical tool and
biomarkers can contribute to longer term assessment of radiation effects and public health
risks. The gene expression assay has been gaining popularity as a sensitive biological marker
of radiation exposure with the potential to be used for truly individualised dosimetry. The
possibility for this assay to be used for a large scale mass-casualty scenario has been
proposed and tested in a recent inter-comparison exercise. However, a fuller understanding of
genetic factors that contribute to individual radiation risks is needed to inform tailored
screening approaches - i.e. to identify a truly radiation specific panel of genetics
responses for use as a transcriptional biomarker.
At Columbia University, research has shown that transcriptional effects have the potential to
be used as individualised predictors of radiosensitivity to early and late effects. At Public
Health England (PHE), recently established molecular counting nCounter 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. 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.
In the earlier pilot RTGene study the investigators found genes that are consistently
down-regulated and up-regulated towards the end of the radiotherapy treatment. The next stage
of this work (RTGene 2) will be to validate the nCounter data for a small number of new genes
consistently found in the top 6 of differentially expressed. Importantly, in an attempt to
identify genes which are promising biomarkers of susceptibility to radiation-induced
toxicity, expression levels will need to be compared with normal tissue reaction to IR, and
combined with longer term radiation toxicity data to identify genes with the most pronounced
expression level fluctuations during and after radiotherapy.
Peripheral blood samples will be taken with informed consent from radiotherapy patients
before and during treatment fractions for sarcoma, breast, lung, gut, genitourinary and head
& neck tumours at The Royal Marsden. Candidate genes identified by PHE, Columbia and/or in
the literature as being specific to radiation responses will be assessed, together with genes
relevant to systemic inflammatory and immune 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 project is
expected.
