Selinexor for the treatment of recurrent or metastatic salivary gland tumors: results from the GEMS-001 clinical trial.
Bibliographic record
Abstract
Abstract Background Salivary gland tumors (SGT) are rare with limited systemic treatments. We aimed to evaluate the activity of selinexor, an oral selective inhibitor of nuclear export, in patients with recurrent unresectable or metastatic SGT. Methods GEMS-001 is an open-label phase 2 study for patients with recurrent or metastatic SGT with two parts. In part 1 of the protocol, patients had tumor samples profiled with targeted next generation sequencing as well as immunohistochemistry for androgen receptor, HER-2 and ALK. For part 2, patients with no targetable alterations identified or no matched agents available are eligible to receive selinexor 60 mg given twice weekly every 28 days. The primary endpoint was objective response rate. Secondary endpoints included progression-free survival (PFS) and prevalence of druggable alterations across SGT. Results Between July 2014 and September 2021, 100 patients were enrolled in GEMS-001 and underwent genomic and proteomic profiling. A total of 21 patients (12 female) with a median age of 61 years (range 36–79) who lacked actionable alterations or available matched therapies were treated with selinexor. Histological subtypes (World Health Organization classification) included adenoid cystic carcinoma (n = 10), salivary duct carcinoma (n = 3), acinic cell carcinoma (n = 2) and other (n = 6). Fourteen patients were treatment naïve and 7 patients had received 1 or more lines of treatment prior to enrollment. Of 18 evaluable patients, stable disease as best response was observed in 17 patients (94%) (stable disease ≥ 6 months in 7 patients (39%)). Tumor reduction of target lesions was observed in 11 patients (61%). However, no partial or complete responses were observed. The median PFS was 4.9 months (95% confidence interval, 3.4–10). The most common treatment-related grade 1–2 adverse events were nausea [17 patients (81%)], fatigue [16 patients (76%)] and dysgeusia [12 patients (57%)]. Most common treatment-related grade 3–4 adverse events were hyponatremia [3 patients (14%)], neutrophil count decrease [3 patients (14%)] and cataracts [2 patients (10%)]. No treatment-related deaths were observed. Conclusions Although tumor reduction was observed across participants single agent selinexor antitumor activity was limited. Trial registration This clinical trial is registered at ClinicalTrials.gov (NCT02069730) first posted February 24 2014.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".