Case Report: Next generation sequencing identifies a NAB2-STAT6 fusion in Glioblastoma
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Bibliographic record
Abstract
BACKGROUND: Molecular profiling has uncovered genetic subtypes of glioblastoma (GBM), including tumors with IDH1 mutations that confer increase survival and improved response to standard-of-care therapies. By mapping the genetic landscape of brain tumors in routine clinical practice, we enable rapid identification of targetable genetic alterations. CASE PRESENTATION: A 29-year-old male presented with new onset seizures prompting neuroimaging studies, which revealed an enhancing 5 cm intra-axial lesion involving the right parietal lobe. He underwent a subtotal resection and pathologic examination revealed glioblastoma with mitoses, microvascular proliferation and necrosis. Immunohistochemical (IHC) analysis showed diffuse expression of GFAP, OLIG2 and SOX2 consistent with a tumor of glial lineage. Tumor cells were positive for IDH1(R132H) and negative for ATRX. Clinical targeted-exome sequencing (DFBWCC Oncopanel) identified multiple functional variants including IDH1 (p.R132H), TP53 (p.Y126_splice), ATRX (p.R1302fs*), HNF1A (p.R263H) and NF1 (p.H2592del) variants and a NAB2-STAT6 gene fusion event involving NAB2 exon 3 and STAT6 exon 18. Array comparative genomic hybridization (aCGH) further revealed a focal amplification of NAB2 and STAT6. IHC analysis demonstrated strong heterogenous STAT6 nuclear localization (in 20 % of tumor cells). CONCLUSIONS: While NAB2:STAT6 fusions are common in solitary fibrous tumors (SFT), we report this event for the first time in a newly diagnosed, secondary-type GBM or any other non-SFT. Our study further highlights the value of comprehensive genomic analyses in identifying patient-specific targetable mutations and rearrangements.
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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 | 0.004 |
| 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 it