The effect of prior smoking history on the molecular profile of EGFR mutant (EGFRm) non-small cell lung cancer (NSCLC).
Bibliographic record
Abstract
8533 Background: Although EGFRm NSCLC occurs mainly in non-smoking patients, most series report 20%-35% of cases in current or previous smokers. Broad molecular profiling of EGFRm NSCLC in smokers has not been reported. Methods: Surgically resected primary EGFR exon 19 or 21 mutated NSCLC tumors from 108 patients were molecularly profiled by whole exome sequencing using the Illumina HiSeq2000 platform. Alignment and variant discovery analysis was performed according to GATK best practices workflow; 87 sequenced to a mean coverage of 65.1x. Demographics and outcomes were compared for smokers and non-smokers (non-S), and by mutation profile. Results: Of the 63 non-smokers and 24 smokers (7 current/recent within 10 years), 71% were female, 53% were non-Asian, 64.5 years was the median age and 57.5% were EGFR exon 19. Of the 87 patients, 52% were stage I, 20.5% were stage II and 27.5% were stage III+. Smoking was associated with male sex (p = 0.0028) and non-Asian ethnicity (p = 0.0006) but not with age, stage or EGFR exon 19/21 subtype. Multiple “driver” mutations occurred in tumors of 25% smokers and 23.8% non-S. TP53/EGFR co-mutation occurred in 57.9% smokers and 46.2% non-S. Total non-synonymous mutation burden (TMB) was higher in smokers: median TMB in smokers 175.35 (84.93-388.24) compared to 155.31 (56.52-414.84) in non-S (p = 0.096). The strongest prognostic factor for OS and DFS was stage (I, II, III+) (p < 0.001 for each). In univariate analysis, there was a trend to shorter OS in smokers: HR 1.9 (CI 0.98-3.67, p = 0.05). Smoking within 10 years of NSCLC diagnosis was associated with shorter DFS HR 0.37(0.13-1.09) (p = 0.06) but not OS (p = 0.34). Neither EGFRm subtype nor TP53/EGFR co-mutation was associated with DFS or OS. High TMB was associated with shorter DFS: HR above vs below the median 1.96 (CI 1.06-3.62, p = 0.028), and OS HR 2.04 (CI 1.01-4.11, p = 0.043). TMB was still significant for DFS after adjusting for smoking status (p = 0.033), but not for OS (p = 0.1). Conclusions: EGFRm NSCLC in smokers is associated with a trend to higher non-synonymous TMB. Stage remains the strongest prognostic factor, but TMB appears to have a greater effect on survival outcomes than smoking status.
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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 | 0.001 | 0.003 |
| 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) | 0.004 | 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".