ReviewWorld journal of gastroenterology2007
Gene expression arrays as a tool to unravel mechanisms of normal tissue radiation injury and prediction of response.
Review in World journal of gastroenterology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Measuring Radiation Toxicity Using Circulating Cell-Free DNA in Prostate Cancer Patients.International journal of particle therapy · 2022Article
- Hepatic Gene Expression Changes in Rats Internally Exposed to RadioactiveCurrent issues in molecular biology · 2021Article
- A novel high-throughput irradiator for in vitro radiation sensitivity bioassays.Physics in medicine and biology · 2014Article
- Use of the comet-FISH assay to compare DNA damage and repair in p53 and hTERT genes following ionizing radiation.PloS one · 2012Article
- Microbial influences on the small intestinal response to radiation injury.Current opinion in gastroenterology · 2010Review
- Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype.Nature reviews. Cancer · 2009Review
- Molecular markers of radiation-related normal tissue toxicity.Cancer metastasis reviews · 2008Review
- Aberrant CDKN1A transcriptional response associates with abnormal sensitivity to radiation treatment.British journal of cancer · 2008Article
- Tissue toxicity induced by ionizing radiation to the normal intestine: understanding the pathophysiological mechanisms to improve the medical management.World journal of gastroenterology · 2007Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past 5 years there has been a rapid increase in the use of microarray technology in the field of cancer research. The majority of studies use microarray analysis of tumor biopsies for profiling of molecular characteristics in an attempt to produce robust classifiers for prognosis. There are now several published gene sets that have been shown to predict for aggressive forms of breast cancer, where patients are most likely to benefit from adjuvant chemotherapy and tumors most likely to develop distant metastases, or be resistant to treatment. The number of publications relating to the use of microarrays for analysis of normal tissue damage, after cancer treatment or genotoxic exposure, is much more limited. A PubMed literature search was conducted using the following keywords and combination of terms: radiation, normal tissue, microarray, gene expression profiling, prediction. With respect to normal tissue radiation injury, microarrays have been used in three ways: (1) to generate gene signatures to identify sensitive and resistant populations (prognosis); (2) to identify sets of biomarker genes for estimating radiation exposure, either accidental or as a result of terrorist attack (diagnosis); (3) to identify genes and pathways involved in tissue response to injury (mechanistic). In this article we will review all (relevant) papers that covered our literature search criteria on microarray technology as it has been applied to normal tissue radiation biology and discuss how successful this has been in defining predisposition markers for radiation sensitivity or how it has helped us to unravel molecular mechanisms leading to acute and late tissue toxicity. We also discuss some of the problems and limitations in application and interpretation of such data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.