Genome-wide copy number analyses of samples from LACE-Bio project identify novel prognostic and predictive markers in early stage non-small cell lung cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Adjuvant chemotherapy (ACT) provides modest benefit in resected non-small cell lung cancer (NSCLC) patients. Genome-wide studies have identified gene copy number aberrations (CNA), but their prognostic implication is unknown. Methods: DNA from 1,013 FFPE tumor samples from three pivotal multicenter randomized trials (ACT vs. control) in the LACE-Bio consortium (median follow-up: 5.2 years) was successfully extracted, profiled using a molecular inversion probe SNP assay, normalized relative to a pool of normal tissues and segmented. Minimally recurrent regions were identified. P values were adjusted to control the false discovery rate (Q values). Results: A total of 976 samples successfully profiled, 414 (42%) adenocarcinoma (ADC), 430 (44%) squamous cell carcinoma (SCC) and 132 (14%) other NSCLC; 710 (73%) males. We identified 431 recurrent regions, with on average 51 gains and 43 losses; 253 regions (59%) were ≤3 Mb. Most frequent gains (up to 48%) were on chr1, 3q, 5p, 6p, 8q, 22q; most frequent losses (up to 40%) on chr3p, 8p, 9p. CNA frequency of 195 regions was significantly different (Q≤0.05) between ADC and SCC. Fourteen regions (7p11–12, 9p21, 18q12, and 19p11–13) were associated with disease-free survival (DFS) (univariate P≤0.005, Q<0.142), with poorer DFS for losses of regions including CDKN2A/B [hazard ratio (HR) for 2-fold lower CN: 1.5 (95% CI: 1.2–1.9), P<0.001, Q=0.020] and STK11 [HR =2.4 (1.3–4.3), P=0.005, Q=0.15]. Chromosomal instability was associated with poorer DFS (HR =1.5, P=0.015), OS (HR =1.2, P=0.189) and lung-cancer specific survival (HR =1.7, P=0.003). Conclusions: These large-scale genome-wide analyses of gene CNA provide new candidate prognostic markers for stage I–III NSCLC.
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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