Abstract 2479: TP53 status as a marker of recurrence and survival in choroid plexus carcinomas
Bibliographic record
Abstract
Abstract Choroid plexus carcinoma (CPC) is a rare intraventricular tumor more frequently observed in children, accounting for ∼20% of brain tumors in children under 2 yrs of age. This malignant neoplasm is categorized as a grade III tumor by the WHO, while benign choroid plexus papilloma (CPP) and atypical choroid plexus papilloma (aCPP) are categorized as grade I and II, respectively. More than 50% of CPC's carry a mutation in TP53. The role of p53 in the malignant progression of this tumor is not well understood, yet this knowledge is crucial to optimize patient treatment, increase survival and reduce long-term sequelae. The current treatment approach for CPC includes surgical resection and combination chemo- and radiation therapy. However, treatment response is highly variable; tumor progression and relapse is observed in ∼60% of patients, and most survivors experience significant long-term deficits. In this study, we sought to determine whether TP53 status could be used as a reliable marker to predict tumor aggressiveness and response to treatment in CPC patients. Thirty CPC, 26 CPP and 8 aCPP tumor samples for which TP53 status was available were selected from the SickKids Cancer Genetics tissue bank. Sequencing analysis revealed somatic TP53 in 60% of CPCs. These mutations were significantly less frequent in CPPs (12%, p=1.84x10−4). All aCPPs were wildtype (wt) for TP53. Relapse-free survival was only 12% in TP53 mut CPC patients compared to 40% for TP53 wt patients. Only 1 CPP patient relapsed 9 months after initial diagnosis. Five-year overall survival for TP53 mut CPC patients was significantly lower than that of TP53 wt patients (39% vs. 80%, respectively, p=0.04). Overall survival for 18 CPP patients for which we had 5-year survival data was 94%, and 100% for aCPP patients. Allele-specific copy number (ASCN) and FISH analysis, revealed extensive chromosomal imbalances in CPC tumors with TP53 mutations. TP53 wt CPCs had fewer chromosomal imbalances or none at all, very similar to CPPs. Gene expression data was used to examine the unsupervised clustering of our tumors. As expected, CPCs and CPPs cluster independently according to raw gene expression intensity, with TP53 wt CPCs segregating from the CPC mutant samples and clustering more closely to CPPs. Using an integrative analysis, we were able to identify unique behaviors and molecular characteristics that distinguish TP53 wt from TP53 mut CPCs. The clinical outcomes observed, supported by the genomic and transcriptomic data analyzed, suggest that TP53 mut and wt CPCs indeed form two distinct subgroups. This molecular genotyping approach may be valuable in stratifying patients to modulated therapy protocols in order to diminish treatment-related toxicity, and improve disease response and survival. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2479. doi:1538-7445.AM2012-2479
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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) | 0.000 | 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".