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Record W2135661335 · doi:10.2172/832808

The Adaptive Response in p53 Cancer Prone Mice: Loss of heterozygosity and Genomic Instability

2004· report· en· W2135661335 on OpenAlexaff
Lavoie Josee, J.-A. Dolling, Ron E. J. Mitchel, Douglas R. Boreham

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsAtomic Energy (Canada)Credit Valley HospitalMcMaster University
Fundersnot available
KeywordsGenome instabilityLoss of heterozygosityBiologyChromosome instabilityGeneCancer researchCancerLocus (genetics)Ionizing radiationIn vivoGeneticsAndrologyIrradiationMedicineDNA damageChromosomeDNAAllele

Abstract

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The Trp53 gene is clearly associated with increased cancer risk. This, coupled with the broad understanding of its mode of action at the molecular level, makes this gene a good candidate for investigating the relationship between genetic risk factors and spontaneous cancer occurring in a mouse model exposed to low dose radiation. We have shown that adaptive response to chronic low dose radiation could increase cancer latency, as well as overall lifespan. To better understand the molecular processes that influence cellular risk, modern tools in molecular biology were used to evaluate the loss of heterozigozity (LOH) at the Trp53 locus, and chromosomal instability in the cells from mice exposed to chronic low dose radiation. Female mice carrying a single defective copy of the Trp53 gene were irradiated with doses of gamma-radiation delivered at a low dose rate of about 0.7 mGy/hr. Groups of mice (5 irradiated and 5 unexposed) were exposed to 0.33 mGy per day for 15, 30, 45, 60, 67 and 75 weeks equaling total body doses of 2.4, 4.7, 7.2, 9.7, 10.9 and 12.1 cGy, respectively. The presence of a single defective copy of the Trp53 gene increases cancer risk in these mice. However, in vivo exposure to low dose radiation increased cancer latency. We hypothesized that: (1) These mice might have spontaneous chromosome instability, and (2) that this low dose adaptive exposure would reduce the chromosomal instability. This instability was investigated using spectral karyotyping (SKY). Bone marrow cells from 5 irradiated mice (doses of 10.9 and 12.1 cGy) and 5 control mice were collected for metaphase harvest. Briefly, the cells were incubated at 37 C for 4 hours in RPMI containing 25% heat-inactivated FBS and 0.1 mg/ml colcemid, and then given a hypotonic treatment of 0.075M KCl for 20 minutes at 37 C. An average of 100 metaphases per mouse were karyotyped. The Trp53 heterozygous mice do not show apparent structural chromosome instability. From both unexposed and irradiated mice, only numerical aberrations were observed in 5 to 20% of the cells. There seem to be an age related increase in numerical aberrations as mice grow old. The results indicate that the presence of a defective copy of the Trp53 gene does not seem to affect spontaneous chromosomal instability or in response to chronic low dose exposure to g-radiation. In previous studies it was speculated that low dose and low dose rate in vivo exposure to g-radiation induces an adaptive response, which reduces the risk of cancer death generated by subsequent DNA damage from either spontaneous or radiation induced events due to enhanced recombinational repair. Induced recombination could result from reversion to homozygosity at Trp53 gene locus (Trp53 +/- to +/+) or loss of heterozygosity in unexposed mice (Trp53 +/- to -/-). This hypothesis was investigated using the quantitative real-time Polymerase Chain Reaction (QRT-PCR) quantification method and the novel Rolling Circle Amplification technique (RCA). For these purposes, spleenocytes and bone marrow cells from all the mice were isolated for cell fixation and DNA extraction. The defective Trp53 allele is generated by integration of a portion of the cloning vector pKONEO DNA into the coding sequence. Therefore, the genotypic changes are monitored based on the detection of the NEO allele and the normal Trp53 allele in the cells. To evaluate loss of heterozygosity at the Trp53 gene locus in a cell, detection of the NEO allele and the normal Trp53 allele using the dual color RCA was utilized. In our hands, this protocol did not give the required sensitivity. The gene signal enumeration was inconsistent and not reproducible. The protocol was modified and could not be optimized. Therefore, the QRT-PCR method was selected to evaluate the loss of heterozygosity with greater sensitivity and efficiency. A set of 4 primers was designed to target the NEO allele and the normal Trp53 allele in a PCR experiment using the LightCycler instrument (Roche Diagnostics). Detection of the specific PCR amplicon using the SYBR Green fluorescent dye provided real-time analysis of amplified target sequences. More than 800 real-time PCR reactions were conducted on DNA extracted from tissues of the irradiated and unexposed mice from the 30, 45, 60, 67 and 75 week groups. The crossing point (Cp) value calculated from the amplification curve correlates to the original number of copies of the Trp53 gene in the DNA sample. The Cp values were evaluated using the quantification software. A statistical analysis of the data is in progress to confirm any changes in the original number of DNA copies. This research will provide important information regarding the health effects and cancer risk of low doses of low LET radiation and should support the development of a biologically based model for risk assessment and subsequent radiation protection policy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.308
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2004
Admission routes1
Has abstractyes

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