Microarray Analysis of Bleomycin-Exposed Lymphoblastoid Cells for Identifying Cancer Susceptibility Genes
Bibliographic record
Abstract
The uncovering of genes involved in susceptibility to the sporadic cancer types is a great challenge. It is well established that the way in which an individual deals with DNA damage is related to the chance to develop cancer. Mutagen sensitivity is a phenotype that reflects an individual's susceptibility to the major sporadic cancer types, including colon, lung, and head and neck cancer. A standard test for mutagen sensitivity is measuring the number of chromatid breaks in lymphocytes after exposure to bleomycin. The aim of the present study was to search for the pathways involved in mutagen sensitivity. Lymphoblastoid cell lines of seven individuals with low mutagen sensitivity were compared with seven individuals with a high score. RNA was isolated from cells exposed to bleomycin (4 hours) and from unexposed cells. Microarray analysis (19K) was used to compare gene expression of insensitive and sensitive cells. The profile of most altered genes after bleomycin exposure, analyzed in all 14 cell lines, included relatively many genes involved in biological processes, such as cell growth and/or maintenance, proliferation, and regulation of cell cycle, as well as some genes involved in DNA repair. When comparing the insensitive and sensitive individuals, other differentially expressed genes were found that are involved in signal transduction and cell growth and/or maintenance (e.g., BUB1 and DUSP4). This difference in expression profiles between mutagen-sensitive and mutagen-insensitive individuals justifies further studies aimed at elucidating the genes responsible for the development of sporadic cancers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".