Primitive Desmoplastic Neuroepithelial Tumor of the Skull Base
Bibliographic record
Abstract
The WHO categorizes desmoplastic infantile astrocytoma (DIA) and desmoplastic infantile ganglioglioma (DIG) as one diagnosis. Little genetic/ molecular characterization of DIG/DIA has been published, with scattered results. We aim to better understand genetic underpinnings of DIG and DIA, natural histories, and their relationships to other glial-neuronal CNS tumors. Methods: Targeted, massively-parallel gene sequencing assays that detect mutations of cancer-related genes using next-generation “deep” sequencing was performed on specimens obtained from 30 patients diagnosed with DIG/DIA by histology. An individual patient data meta-analysis (IPDMA) was performed after an exhaustive search of the existing literature on DIG/DIA. Outcome measures were mortality and tumor recurrence. We performed univariate Cox regression analyses to determine the effect of age, pathology, extent of resection (EOR), radiation, chemotherapy, malignant transformation, leptomeningeal metastasis at presentation, BRAF mutation, and deep tumor location on outcome. A multi-variable Cox regression analysis was performed on variables with a p-value <0.2 on univariate analysis to identify independent predictors of outcome. Results: Among the 30 native tumor samples, we found no genetic aberrations in 22 (73.3%). Within the other eight native tumors, we discovered four (13.3%) BRAFV600E mutations, three (10%) BRAFV600D mutations, and one ALK-EML4 fusion. BRAF mutation defines a subset of DIG/DIA. Seven of 30 (23.3%) patients harbored non-synonymous single nucleotide substitutions on the BRAF gene. Four were of the canonical V600E valine-to-glutamic acid variety; interestingly, 3 of these 4 were found in histologically-diagnosed DIAs. The other 3 were exceptionally rare V600D valine-to-aspartic acid point mutations, which account for <1% of all V600 BRAF mutations. BRAF mutations were discovered in 4 of 26 (15.4%) of DIGs, but in 3 of 4 (75%) of DIAs. Deep-seated DIGs and DIAs have a more malignant natural history. We obtained individual patient data in 100 articles with a total of 239 relevant patients. Of this cohort, 75 articles with a total of 137 patients contained outcome variables of interest eligible for this IPDMA. The first endpoint was mortality. Univariate Cox regression analyses demonstrate that skull base tumor location, EOR, and leptomeningeal metastasis at presentation were predictors of mortality. Specifically, gross total resection (GTR) was associated with a mortality HR of 0.048 ( p = 0.003). Tumor recurrence was a second variable analyzed with time-to-analysis. Tumor pathology, leptomeningeal disease at presentation, skull base tumor location, EOR, and malignant transformation all contribute to statistically significant differences in outcome in Cox regression analysis. Multivariate analysis was performed for co-variates for both outcomes (death and tumor recurrence). The multivariate analysis of predictors of tumor recurrence includes skull base tumor location ( p = 0.015) and malignant transformation ( p = 0.015). Though tumor biology is typically benign, patients experienced poorer outcomes after subtotal resection of DIG/DIAs in comparison to complete resection. Thirteen (56.5%) DIAs presented in deep-seated locations. In comparison, of the 208 cases of DIG, only 10 (4.8%) were deep-seated. DIG and DIA had not been previously differentiated in terms of natural history or expected outcomes. However, a skull base location portends worse prognosis, which could potentially be affected by better EOR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".