Application of inter–simple sequence repeat PCR to mouse models: Assessment of genetic alterations in carcinogenesis
Bibliographic record
Abstract
Genomic instability is believed to play a significant role in cancer development by facilitating tumor progression and tumor heterogeneity. Inter-simple sequence repeat (inter-SSR) PCR has been proved to be a fast and reproducible technique for quantitation of genomic instability (amplifications, deletions, translocations, and insertions) in human sporadic tumors. However, the use of inter-SSR PCR in animal models of cancer has never been described. This new technique has been adapted in our laboratory for the analysis of spontaneous and induced mouse tumors. We established the best PCR conditions for each microsatellite-anchored primer and critically evaluated the reproducibility of the band patterns. We also studied the variation of the fingerprints between and within various inbred mouse strains, including wild-derived lines. Tumor-specific alterations were detected as gains, losses, or intensity changes in bands when compared with matched normal DNA. We quantitated the extent of alterations by dividing the number of altered bands in the tumor by the total number of bands in normal DNA (instability index). By means of inter-SSR PCR, we successfully analyzed genomic alterations in various mouse tumors, including spontaneous thymic lymphomas developed in Msh2 knockout mice as well as chemically induced squamous cell carcinomas and thymic lymphomas. Instability index values ranged between 0 and 9%, the highest levels observed in N-methyl-N-nitrosourea-induced thymic lymphomas generated in Trp53 (p53) nullizygote (-/-) mice. We report here, for the first time, the use of inter-SSR PCR to detect somatic mutations in mouse tumoral DNA, including laser-capture microdissected, methanol-fixed tissues. These PCR-based fingerprints provide a novel approach to assessing the number and onset of mutational events in mouse tumors and will help to understand better the mechanisms of carcinogenesis in mouse models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".