Genomic markers for malignant progression in pulmonary adenocarcinoma with bronchioloalveolar features
Bibliographic record
Abstract
Bronchioloalveolar carcinoma (BAC), a subtype of lung adenocarcinoma (ADC) without stromal, vascular, or pleural invasion, is considered an in situ tumor with a 100% survival rate. However, the histological criteria for invasion remain controversial. BAC-like areas may accompany otherwise invasive adenocarcinoma, referred to as mixed type adenocarcinoma with BAC features (AWBF). AWBF are considered to evolve from BAC, representing a paradigm for malignant progression in ADC. However, the supporting molecular evidence remains forthcoming. Here, we have studied the genomic changes of BAC and AWBF by array comparative genomic hybridization (CGH). We used submegabase-resolution tiling set array CGH to compare the genomic profiles of 14 BAC or BAC with focal area suspicious for invasion with those of 15 AWBF. Threshold-filtering and frequency-scoring analysis found that genomic profiles of noninvasive and focally invasive BAC are indistinguishable and show fewer aberrations than tumor cells in BAC-like areas of AWBF. These aberrations occurred mainly at the subtelomeric chromosomal regions. Increased genomic alterations were noted between BAC-like and invasive areas of AWBF. We identified 113 genes that best differentiated BAC from AWBF and were considered candidate marker genes for tumor invasion and progression. Correlative gene expression analyses demonstrated a high percentage of them to be poor prognosis markers in early stage ADC. Quantitative PCR also validated the amplification and overexpression of PDCD6 and TERT on chromosome 5p and the prognostic significance of PDCD6 in early stage ADC patients. We identified candidate genes that may be responsible for and are potential markers for malignant progression in AWBF.
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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 | 0.001 | 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 | 0.001 |
| 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".