Abstract 4795: A novel gene fusion in glioblastoma and a radiation response methylation signature identified by genomic characterization of glioma sphere-forming cells
Bibliographic record
Abstract
Abstract Purpose: High fidelity models of the lethal primary brain tumor glioblastoma (GBM) are essential to develop new therapies. Glioma sphere-forming cells (GSCs) are derived from surgical specimens and are thought to play important roles in tumor maintenance and treatment resistance. We performed genomic characterization of the largest reported panel of GSCs. We hypothesized that GSCs would recapitulate the genomic alterations of their GBMs of origin while identifying novel changes identifiable only in a pure tumor cell population. Methods: All GSCs were obtained at the time of surgical resection and all analyses were conducted at early passage. We performed exome and transcriptome sequencing, DNA methylation profiling (Illumina Infinium 450K Bead Arrays) and DNA copy number determination (Affymetrix OncoScan). Radiation (RT) sensitivity was determined by clonogenic survival and in vivo survival by orthotopic xenograft. Results: We analyzed 43 GSCs, 40 of which had tissue available from their tumors of origin. Somatically mutated genes previously described in GBM, such as TP53, EGFR, PTEN, NF1, PIK3CA and RB1, were found at similar mutation frequencies. Likewise, DNA copy number variations were similar to their matched tumor and those reported by the TCGA, with novel or more pronounced alterations, such as MYC application and QKI deletion, identified in the GSCs. GSCs were classified into TCGA GBM subtypes by expression signatures, identifying a subset of GSCs with a subtype differing from their matched tumors that correlated to decreased stromal enrichment. GSCs exhibited upregulation of self-renewal pathways, such as MYC, WNT, and NOTCH, and of stem-cell factors, such as MSI1, NESTIN, OLIG2, and SOX2, consistent with the stem-like phenotype attributed to GSCs. Transcript analyses identified the previously reported FGFR3-TACC3 and EGFR-SEPT14 gene fusions as well as a novel KIF1B-KMT2A (MLL) fusion, which was found to have been retained in the matching recurrent GBM as well as the GSC derived from the recurrence. A signature derived by the differential methylation pattern of RT sensitive vs. resistant GSCs was applied to the subset of TCGA cases that received upfront RT. Survival by methylation class in this subset was significantly different (median survival 84 vs. 61 weeks; HR 1.64 adjusting for patient age, p-value<0.008), suggesting this signature is predictive of clinical RT response. Conclusions: Based on genomic analyses, GSCs are robust models of GBM which can be used for therapeutic development. We have identified a novel gene fusion involving MLL with a predicted driving role suggesting a new mode of gliomagenesis. A methylation signature predictive of RT response may have potential for personalizing RT treatment of GBM patients and provides insights into RT sensitivity phenotypes. Citation Format: Qianghu Wang, Ravesanker Ezhilarasan, Lindsey D. Goodman, Joy Gumin, Siyuan Zheng, Kosuke Yoshihara, Peng Sun, Jie Yang, Tim Heffernan, Giulio Draetta, Kenneth D. Aldape, Frederick F. Lang, Roel G.W. Verhaak, Erik P. Sulman. A novel gene fusion in glioblastoma and a radiation response methylation signature identified by genomic characterization of glioma sphere-forming cells. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4795. doi:10.1158/1538-7445.AM2015-4795
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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 | 0.000 | 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) | 0.001 | 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".