Frequency of targetable genetic alterations in resectable lung adenocarcinoma: Results from the LORD project
Bibliographic record
Abstract
There is still limited data on the prevalence of actionable molecular alterations in patients with early-stage resectable lung adenocarcinoma and prior studies reported important differences across geographic locations, demographic and pathologic characteristics. The tumors of 1,603 French Canadian patients with pathologically confirmed lung adenocarcinoma were interrogated using a 50-gene next-generation sequencing panel. The goal was to assess the prevalence of genetic alterations in eleven guideline-based oncogenic genes in resectable lung adenocarcinoma. Age, sex, pathological stage, smoking history and predominant histologic patterns were associated with molecular subtypes defined by oncogenic drivers. Age at surgery for the 1,603 patients was 65 ± 8 and includes 61 % of females, 6 % of patients without a smoking history and 70 % of stage I. The overall prevalence of targetable alterations for approved and investigational therapies was 65.9 % and 56.7 % of patients had tumors harboring at least one variant of strong clinical significance (tier I of the AMP/ASCO/CAP categorization). The most frequently mutated genes were KRAS (45.3 %), EGFR (11.5 %) and BRAF (3.9 %). MET exon 14 skipping alterations were identified in 47 patients (2.9 %) and oncogenic fusions in ALK, ROS1, RET and MET were found in 1.7 % of cases. As expected, EGFR activating mutations were associated with patients who never smoked, females, earlier disease stages, with more lepidic/acinar and less solid predominant patterns. Quasi similar but inverted relationships with clinico-pathological features were observed in one third of patients (n = 534) free of molecular alterations characterized by more males, patients who smoked, with later stage diagnosis and with more solid and less lepidic/acinar adenocarcinomas. This study highlights the epidemiology of guideline-based targetable alterations in French-Canadian patients with resectable lung adenocarcinoma. The large proportion of patients eligible for targeted therapies will have important impact on oncological practices in the current era of neoadjuvant and perioperative treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".