Oncogene Mutations, Copy Number Gains and Mutant Allele Specific Imbalance (MASI) Frequently Occur Together in Tumor Cells
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Activating mutations in one allele of an oncogene (heterozygous mutations) are widely believed to be sufficient for tumorigenesis. However, mutant allele specific imbalance (MASI) has been observed in tumors and cell lines harboring mutations of oncogenes. METHODOLOGY/PRINCIPAL FINDINGS: We determined 1) mutational status, 2) copy number gains (CNGs) and 3) relative ratio between mutant and wild type alleles of KRAS, BRAF, PIK3CA and EGFR genes by direct sequencing and quantitative PCR assay in over 400 human tumors, cell lines, and xenografts of lung, colorectal, and pancreatic cancers. Examination of a public database indicated that homozygous mutations of five oncogenes were frequent (20%) in 833 cell lines of 12 tumor types. Our data indicated two major forms of MASI: 1) MASI with CNG, either complete or partial; and 2) MASI without CNG (uniparental disomy; UPD), due to complete loss of wild type allele. MASI was a frequent event in mutant EGFR (75%) and was due mainly to CNGs, while MASI, also frequent in mutant KRAS (58%), was mainly due to UPD. Mutant: wild type allelic ratios at the genomic level were precisely maintained after transcription. KRAS mutations or CNGs were significantly associated with increased ras GTPase activity, as measured by ELISA, and the two molecular changes were synergistic. Of 237 lung adenocarcinoma tumors, the small number with both KRAS mutation and CNG were associated with shortened survival. CONCLUSIONS: MASI is frequently present in mutant EGFR and KRAS tumor cells, and is associated with increased mutant allele transcription and gene activity. The frequent finding of mutations, CNGs and MASI occurring together in tumor cells indicates that these three genetic alterations, acting together, may have a greater role in the development or maintenance of the malignant phenotype than any individual alteration.
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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 it