ReviewHealth physics2012
Defining molecular and cellular responses after low and high linear energy transfer radiations to develop biomarkers of carcinogenic risk or therapeutic outcome.
Review in Health physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Multivariate piecewise linear regression model to predict radiosensitivity using the association with the genome-wide copy number variation.Frontiers in oncology · 2023Article
- Impaired DNA Repair Fidelity in a Breast Cancer Patient With Adverse Reactions to Radiotherapy.Frontiers in public health · 2021Article
- Donor-specific cell-based assays in studying sensitivity to low-dose radiation: a population-based perspective.Frontiers in public health · 2014Review
- Summary: achievements, critical issues, and thoughts on the future.Health physics · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
The variability in radiosensitivity across the human population is governed in part by genetic factors. The ability to predict therapeutic response, identify individuals at greatest risk for adverse clinical responses after therapeutic radiation doses, or identify individuals at high risk for carcinogenesis from environmental or medical radiation exposures has a medical and economic impact on both the individual and society at large. As radiotherapy incorporates particles, particularly particles larger than protons, into therapy, the need for such discriminators, (i.e., biomarkers) will become ever more important. Cellular assays for survival, DNA repair, or chromatid/chromosomal analysis have been used to identify at-risk individuals, but they are not clinically applicable. Newer approaches, such as genome-wide analysis of gene expression or single nucleotide polymorphisms and small copy number variations within chromosomes, are examples of technologies being applied to the discovery process. Gene expression analysis of primary or immortalized human cells suggests that there are distinct gene expression patterns associated with radiation exposure to both low and high linear energy transfer radiations and that those most radiosensitive are discernible by their basal gene expression patterns. However, because the genetic alterations that drive radio response may be subtle and cumulative, the need for large sample sizes of specific cell or tissue types is required. A systems biology approach will ultimately be necessary. Potential biomarkers from cell lines or animal models will require validation in a human setting where possible and before being considered as a credible biomarker some understanding of the molecular mechanism is necessary.
Indexed as
Identifiers
What OpenQuestion holds
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.