Abstract B29: Defining subclonal signaling heterogeneity in glioblastoma multiforme (GBM)
Bibliographic record
Abstract
Abstract Glioblastoma Multiforme (GBM, WHO grade IV) is the most common and malignant brain tumor of the adult central nervous system, with a median survival of between 12 and 15 months. Interestingly, the presence of genetically unique subclones in GBMs has been previously implicated in GBMs using Fluorescence in situ hybridization (FISH) and surgical multisampling approaches.1,2 The purpose of this study are to unequivocally demonstrate clinically relevant phenotypic heterogeneity in GBM subclones, and to identify genetic and phenotypic biomarkers predictive of subclonal drug responses. Previous work in the Dirks laboratory has allowed for the generation of 44 single-cell derived clonal cultures from 4 GBM tumors, by Fluorescence Activated Cell Sorting (FACS) and clonal expansion in vitro. Comparisons of clones derived from the same tumor uniquely allows for the identification and characterization of genetic and functional intratumoral diversity in GBM. We demonstrate that single-cell derived clonal cultures from the same primary tumor can differ in key phenotypes such as proliferation in vitro and responsiveness to the chemotherapeutic Temozolomide. Our work has also shown that expression of the oncogene EGFRvIII is exclusive to some clones within a tumor, and not others. Profiling of basal and activated EGFR signaling states also revealed subclonal variability in pERK and pS6 activity, suggesting subclonal differences in pathway dependencies which could be exploited for targeted therapies. Importantly, we observed clonal differences in sensitivity to the EGFR small molecule inhibitor Erlotinib, suggesting that clonal phenotypes can be correlated to differences in signaling activity between tumor subclones. The existence of inherently drug resistant clones in GBM tumors may lead to ineffective therapies and tumor relapses, and subclonal interrogation of patient specimens may lead to better treatment stratification. References 1) Snuderl, M., L. Fazlollahi, et al. “Mosaic amplification of multiple receptor tyrosine kinase genes in glioblastoma.” Cancer Cell 20, 810-817(2011). 2) Sottoriva, A., I. Spiteri, et al. (2013). “Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics.” Proc Natl Acad Sci USA 110, 4009-4014(2013). Citation Format: Xiaoyang Lan, Mona Meyer, Jüri Reimand, Xueming Zhu, Michelle Kushida, Renee Head, Ian Clarke, Gary Bader, Peter Dirks. Defining subclonal signaling heterogeneity in glioblastoma multiforme (GBM). [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr B29.
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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".