Diagnostic Value of Next-Generation Sequencing in an Unusual Sphenoid Tumor
Bibliographic record
Abstract
Extraordinary advancements in sequencing technology have made what was once a decade-long multi-institutional endeavor into a methodology with the potential for practical use in a clinical setting. We therefore set out to examine the clinical value of next-generation sequencing by enrolling patients with incurable or ambiguous tumors into the Personalized OncoGenomics initiative at the British Columbia Cancer Agency whereby whole genome and transcriptome analyses of tumor/normal tissue pairs are completed with the ultimate goal of directing therapeutics. First, we established that the sequencing, analysis, and communication with oncologists could be completed in less than 5 weeks. Second, we found that cancer diagnostics is an area that can greatly benefit from the comprehensiveness of a whole genome analysis. Here, we present a scenario in which a metastasized sphenoid mass, which was initially thought of as an undifferentiated squamous cell carcinoma, was rediagnosed as an SMARCB1-negative rhabdoid tumor based on the newly acquired finding of homozygous SMARCB1 deletion. The new diagnosis led to a change in chemotherapy and a complete nodal response in the patient. This study also provides additional insight into the mutational landscape of an adult SMARCB1-negative tumor that has not been explored at a whole genome and transcriptome level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".