High resolution analysis of non-small cell lung cancer cell lines by whole genome tiling path array CGH
Bibliographic record
Abstract
Chromosomal regions harboring tumor suppressors and oncogenes are often deleted or amplified. Array comparative genomic hybridization detects segmental DNA copy number alterations in tumor DNA relative to a normal control. The recent development of a bacterial artificial chromosome array, which spans the human genome in a tiling path manner with >32,000 clones, has facilitated whole genome profiling at an unprecedented resolution. Using this technology, we comprehensively describe and compare the genomes of 28 commonly used non-small cell lung carcinoma (NSCLC) cell models, derived from 18 adenocarcinomas (AC), 9 squamous cell carcinomas and 1 large cell carcinoma. Analysis at such resolution not only provided a detailed genomic alteration template for each of these model cell lines, but revealed novel regions of frequent duplication and deletion. Significantly, a detailed analysis of chromosome 7 identified 6 distinct regions of alterations across this chromosome, implicating the presence of multiple novel oncogene loci on this chromosome. As well, a comparison between the squamous and AC cells revealed alterations common to both subtypes, such as the loss of 3p and gain of 5p, in addition to multiple hotspots more frequently associated with only 1 subtype. Interestingly, chromosome 3q, which is known to be amplified in both subtypes, showed 2 distinct regions of alteration, 1 frequently altered in squamous and 1 more frequently altered in AC. In summary, our data demonstrate the unique information generated by high resolution analysis of NSCLC genomes and uncover the presence of genetic alterations prevalent in the different NSCLC subtypes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".