Epithelioid Versus Rhabdoid Glioblastomas Are Distinguished by Monosomy 22 and Immunohistochemical Expression of INI-1 but not Claudin 6
Bibliographic record
Abstract
Epithelioid and rhabdoid glioblastomas are rare entities that share some overlapping morphologic features, but remain poorly characterized at the immunohistochemical and genetic level. We report 10 examples: 8 epithelioid glioblastomas (E-GBMs) and 2 rhabdoid GBMs (R-GBMs). E-GBMs tended to be superficially located, circumscribed, supratentorial tumors composed of monotonous, discohesive sheets of small rounded cells that mimicked metastatic malignant melanoma. R-GBMs showed tumor with classic rhabdoid features arising as a subpopulation of an otherwise classic GBM, fitting the definition of composite extrarenal rhabdoid tumors. Polyphenotypic immunohistochemical expression and focal loss of INI-1 protein in the rhabdoid areas of R-GBMs distinguished them from E-GBMs. Monosomy 22 was identified in R-GBMs, but not E-GBMs. Immunostaining for claudin-6, a key component of tight junctions that we have earlier shown to be a positive cytoplasmic immunohistochemical marker for atypical teratoid or rhabdoid tumors (AT/RTs), was also conducted. None of the E-GBMs or R-GBMs showed claudin-6 cytoplasmic expression, including the focal areas in the 2 R-GBMs in which there was loss of INI-1 protein nuclear expression. Thus, in the CNS, claudin-6 expression may be a good discriminator of atypical teratoid or rhabdoid tumors from other CNS rhabdoid or epithelioid neoplasms.
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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 | 0.001 |
| 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".