BIOM-09. GUIDING PRECISION THERAPEUTICS THROUGH INTERROGATING ONCOGENIC PATHWAY ACTIVATION
Bibliographic record
Abstract
Abstract The deregulation of canonical oncogenic pathways are largely responsible for driving pediatric cancers and can be targeted for therapeutics. Currently, we interrogate these pathways clinically by looking for gene mutations, but these are not found in all cases, and in others multiple genes are. We hypothesized that assessing transcriptomic and proteomic-based pathway activation will allow a better understanding of the most active oncogenic pathways and help guide therapy. To do this, we developed and validated a nanostring based assay that interrogates 4 key actionable pathways (MAPK, PI3K-AKT-mTOR, JAK-STAT, and NFkB) including RNA, protein and phosphoprotein expression. The assay was clinically validated using isogenic cell lines and a cohort of 40 gliomas with previous RNAseq. We then interrogated over 400 tumor samples, including 15 ependymomas, 11 medulloblastomas, 250 low grade gliomas (LGG), 145 high grade gliomas and 10 control normal brain specimens. Interestingly, although pediatric LGG exhibited higher MAPK activation than control tissue and other tumor types, a subset of these tumors have increased activity in PI3K , JAK and NFKB pathways. Furthermore, high PI3K activation score was correlated with worse PFS in a subset of pediatric LGGs that required adjuvant chemotherapy (p=0.018). To further explore the therapeutic implication of the assay, we analyzed a cohort of patients treated with MEK inhibitors (n=20). Strikingly, on top of universal RAS/MAPK activation, crosstalk between additional activated pathways such as PI3K and JAK-STAT may contribute to lack of response. In particular, pre-treatment and post-progression PLGG who failed therapy, revealed mild reduction in MAPK signature accompanied by increased PI3K phospho-proteins (p-S6/p-4EBP1,p-AKT)(p< 0.01). We conclude that assessing oncogenic pathway activation can add to DNA sequencing to predict different outcome and response to targeted therapies in childhood brain tumors. This can inform future therapeutic strategies including the identification of potential responders and combination strategies for non-responders.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".