Evidence map›Paper›PMID 23032890›Full record

ReviewHealth physics2012

Defining molecular and cellular responses after low and high linear energy transfer radiations to develop biomarkers of carcinogenic risk or therapeutic outcome.

Michael Story, Liang-hao Ding, William A Brock, K Kian Ang, Ghazi Alsbeih, John Minna, Seongmi Park, Amit Das

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 25% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Michael StoryDepartment of Radiation Oncology, Division of Molecular Radiation Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA. michael.story@utsouthwestern.edu
Liang-hao Ding
William A Brock
K Kian Ang
Ghazi Alsbeih
John Minna
Seongmi Park
Amit Das
The University of Texas Southwestern Medical Center · USKing Faisal Specialist Hospital & Research Centre · SARadiation Oncology Associates · USThe University of Texas MD Anderson Cancer Center · US

Funding

UNIVERSITY OF TEXAS--SPORE IN LUNG CANCERP50CA070907 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GIBBONS, DON LYNN · 1996 to 2024
$57.4M
X-RAY BEAM SPECTRA MEASUREMENTP01CA006294 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ANG, K KIAN · 1985 to 2009
$11.0M
NCI NIH HHS CA 70907NCI NIH HHS P01 CA006294NCI NIH HHS P01 CA 06294NCI NIH HHS P50 CA070907
6 · The paper itself

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

Linear Energy TransferAnimalsBiomarkers, TumorCell LineHumansNeoplasmsRadiation ToleranceRiskTreatment OutcomeBiomarkers, Tumor

Identifiers

PMID23032890
PMCPMC4492459
OpenAlexW2134822995

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.