Case Report: Next generation sequencing identifies a NAB2-STAT6 fusion in Glioblastoma
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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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".