Therapeutic Potential of Afatinib in<i>NRG1</i>Fusion-Driven Solid Tumors: A Case Series
Bibliographic record
Abstract
BACKGROUND: Neuregulin 1 (NRG1) fusions, which activate ErbB signaling, are rare oncogenic drivers in multiple tumor types. Afatinib is a pan-ErbB family inhibitor that may be an effective treatment for NRG1 fusion-driven tumors. PATIENTS AND METHODS: This report summarizes pertinent details, including best tumor response to treatment, for six patients with metastatic NRG1 fusion-positive tumors treated with afatinib. RESULTS: The six cases include four female and two male patients who ranged in age from 34 to 69 years. Five of the cases are patients with lung cancer, including two patients with invasive mucinous adenocarcinoma and three patients with nonmucinous adenocarcinoma. The sixth case is a patient with colorectal cancer. NRG1 fusion partners for the patients with lung cancer were either CD74 or SDC4. The patient with colorectal cancer harbored a novel POMK-NRG1 fusion and a KRAS mutation. Two patients received afatinib as first- or second-line therapy, three patients received the drug as third- to fifth-line therapy, and one patient received afatinib as fifteenth-line therapy. Best response with afatinib was stable disease in two patients (duration up to 16 months when combined with local therapies) and partial response (PR) of >18 months in three patients, including one with ongoing PR after 27 months. The remaining patient had a PR of 5 months with afatinib 40 mg/day, then another 6 months after an increase to 50 mg/day. CONCLUSION: This report reviews previously published metastatic NRG1 fusion-positive tumors treated with afatinib and summarizes six previously unpublished cases. The latter include several with a prolonged response to treatment (>18 months), as well as the first report of efficacy in NRG1 fusion-positive colorectal cancer. This adds to the growing body of evidence suggesting that afatinib can be effective in patients with NRG1 fusion-positive tumors. KEY POINTS: NRG1 fusions activate ErbB signaling and have been identified as oncogenic drivers in multiple solid tumor types. Afatinib is a pan-ErbB family inhibitor authorized for the treatment of advanced non-small cell lung cancer that may be effective in NRG1 fusion-driven tumors. This report summarizes six previously unpublished cases of NRG1 fusion-driven cancers treated with afatinib, including five with metastatic lung cancer and one with metastatic colorectal cancer. Several patients showed a prolonged response of >18 months with afatinib treatment. This case series adds to the evidence suggesting a potential role for afatinib in this area of unmet medical need.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".