Data from Genetic Aberrations Leading to MAPK Pathway Activation Mediate Oncogene-Induced Senescence in Sporadic Pilocytic Astrocytomas
Bibliographic record
Abstract
Abstract Purpose: Oncogenic BRAF/Ras or NF1 loss can potentially trigger oncogene-induced senescence (OIS) through activation of the mitogen-activated protein kinase (MAPK) pathway. Somatic genetic abnormalities affecting this pathway occur in the majority of pilocytic astrocytomas (PA), the most prevalent brain neoplasm in children. We investigated whether OIS is induced in PA. Experimental Design: We tested expression of established senescence markers in three independent cohorts of sporadic PA. We also assessed for OIS in vitro, using forced expression of wild-type and V600E-mutant BRAF in two astrocytic cell lines: human telomerase reverse transcriptase (hTERT)-immortalized astrocytes and fetal astrocytes. Results: Our results indicate that PAs are senescent as evidenced by marked senescence-associated acidic β-galactosidase activity, low KI-67 index, and induction of p16INK4a but not p53 in the majority of 52 PA samples (46 of 52; 88.5%). Overexpression of a number of senescence-associated genes [CDKN2A (p16), CDKN1A (p21), CEBPB, GADD45A, and IGFBP7] was shown at the mRNA level in two independent PA tumor series. In vitro, sustained activation of wild-type or mutant BRAF induced OIS in both astrocytic cell lines. Loss of p16INK4a in immortalized astrocytes abrogated OIS, indicative of the role of this pathway in mediating this phenomenon in astrocytes. OIS is a mechanism of tumor suppression that restricts the progression of benign tumors. We show that it is triggered in PAs through p16INK4a pathway induction following aberrant MAPK activation. Conclusions: OIS may account for the slow growth pattern in PA, the lack of progression to higher-grade astrocytomas, and the high overall survival of affected patients. Clin Cancer Res; 17(14); 4650–60. ©2011 AACR.
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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 | 0.000 |
| 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) | 0.002 | 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".