Abstract PR02: Integrated genomic analysis of a recurrent ghost cell odontogenic carcinoma
Bibliographic record
Abstract
Abstract Introduction: The Personalized OncoGenomics (POG) project launched at the British Columbia Cancer Agency uses genome analyses to support cancer treatment decision making. The POG project enrolls patients with incurable cancers for which standard chemotherapy regimens fail or do not exist. Here we report the first genomic sequence of a ghost cell odontogenic carcinoma (GCOC) patient enrolled in the POG program. GCOC is a very rare cancer of the maxillofacial apparatus and only 35 GCOC cases have been reported in the literature. The etiology of GCOC is largely unknown and genomic profiling of this rare cancer-type has not been previously reported. Methods: We performed whole genome sequencing (WGS; ~100X coverage) and transcriptome sequencing (RNA-seq) of a fresh tumor biopsy sample and WGS (~50X coverage) of DNA purified from peripheral blood. Bioinformatics approaches were used to identify genes with somatic single nucleotide variants (SNVs), copy number variants (CNVs), structural variants (SVs), and expression changes. All variants were integrated to build an individual somatic molecular profile, followed by intensive pathway analysis and literature searches to identify the candidate biological processes that are deregulated. Based on the integration of these results, therapeutic options were explored. Results: The tumor genome was highly aneuploid with extensive regions of loss of heterozygosity. Homozygous deletion of RB1 and heterozygous loss of PTEN, RASSF4 and FHIT tumor suppressors was observed. Oncogenes belonging to the sonic hedgehog pathway (GLI1 and SHH) as well as a variety of other oncogenes including AURKA, AKT1, GSK3B, MYCN also showed gains in copy number. Among the genes with predicted protein altering SNVs were APC, HLF, TWIST1 and UBR5. The only translocation resulting in an expressed RNA product, a reciprocal t(3;18), resulted in a novel fusion involving the TCF4 and PTPRG genes. The predicted fusion product lacks all the functional domains of the PTPRG gene including the phosphatase domain, possibly leading to the loss of tumor suppressor activity. Oncogenes involved in tyrosine kinase signaling (EGFR, KIT, FGFR1), various members of the PI3-kinase-mTOR pathway including PIK3R2, PIK3CA and MYCN, members of the NOTCH signaling pathway (NOTCH1, NOTCH3, JAG1, DTX4, HES2 and HEY1), the hedgehog pathway (PTCH1, GLI1, TWIST1 and TWIST2), and the WNT pathway (WNT4, WNT5A, FZD2, FZD10, DVL3 and GSK3B) were highly expressed in the GCOC sample. Conclusions: This study represents the first integrated genomic and transcriptomic analysis of a GCOC genome. Based on alterations in tyrosine kinase, PI3-kinase-mTOR, hedgehog and NOTCH pathways, inhibitors to these pathways were identified as therapeutic options. This abstract is also presented as Poster 06. Citation Format: Pinaki Bose, Erin Pleasance, Martin Jones, Yaoqing Shen, Carolyn Ch'ng, Caralyn Reisle, Jacqueline E. Schein, Andrew Mungall, Richard Moore, Yussanne Ma, Brandon S. Sheffield, Thomas Thomson, Steven Rasmussen, Christopher Lee, Stephen Yip, Marco A. Marra, Janessa Laskin, Cheryl Ho, Steven J. M. Jones. Integrated genomic analysis of a recurrent ghost cell odontogenic carcinoma. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr PR02.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".