<i>KRAS</i> and <i>MET</i> Co-Mutation in One Lesion and <i>EGFR</i> Mutation in Another Lesion of Early-Stage Synchronous Multiple Lung Adenocarcinomas: A Case Report
Bibliographic record
Abstract
Recent advances in medical technology have led to an increased number of reports of various driver mutations and cases of synchronous multiple primary lung cancer. Although multiple driver mutations in a lung cancer lesion are generally considered mutually exclusive, recent studies have reported rare cases of coexisting mutations known as co-mutations. In this case report, we describe a rare case of three synchronous lung adenocarcinomas presenting as ground-glass opacities in the left upper lung lobe of a 68-year-old man. The patient underwent a thoracoscopic left upper division segmentectomy. Pathological examination of these lesions revealed early-stage lung adenocarcinomas with varying degrees of invasiveness. Genetic testing revealed a MET exon 14 skipping mutation and a KRAS mutation in one lesion, and an EGFR L858R mutation in another. The postoperative course was uneventful, and no recurrence has been detected since 1 year and 9 months after surgery (without adjunctive treatment). This case is notable because co-mutations were present in one lesion, while a different driver mutation was present in another ground-glass nodule. To the best of our knowledge, only one case of synchronous multiple primary lung cancer harboring a co-mutation has been reported to date. The findings of this case report suggest that multiple driver mutations and even co-mutations can arise in the early stages of carcinogenesis. The accumulation of similar cases in the future is expected to help elucidate the molecular mechanisms and clinical significance of these mutations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".