Abstract 3163: ZMAT3, a signature gene for sporadic osteosarcoma.
Bibliographic record
Abstract
Abstract Osteosarcoma (OS) is a primary bone malignancy with high incidence in children and young adults. It frequently occurs in patients with strong cancer history (Li-Fraumeni syndrome, retinoblastoma), but the etiology of sporadic OS is still uncertain. The present study is an intensive investigation on susceptibility to sporadic osteosarcoma by genome wide copy number analysis. We evaluated the hypothesis that germline copy number variants (CNVs) could act as a source of genetic susceptibility that may contribute to the development of sporadic osteosarcoma. We analyzed 78 sporadic pediatric OS cases and 2375 controls using Affymetrix SNP 6.0 Array. Two independent methods, Genotyping Console™ (Affymetrix) and Birdsuite (Broad Institute) were employed to call for CNVs. Outliers with large genomic alterations and TP53 mutations were flagged and filtered out. Both bioinformatics methods show similar distribution of CNVs per chromosome, with slightly higher range depicted by Genotyping Console™, with an enriched set of CNVs in the diseased data. Bioinformatics analysis predicts overlap of copy number variable regions with several candidate genes (PIK3CA, STK11, AKT3, ZMAT3, BAI1), for selected samples. We validated these findings by performing real time quantitative PCR experiments that not only verified most of the computational results, but also identified more amplifications, in an extended selection of samples and regions. The most affected candidate gene, showing gain in 66% of osteosarcoma samples tested, is ZMAT3 (Chr. 3q26.32). A very recent method, digital droplet PCR (BioRAD), with very high sensitivity, also confirms qPCR results, although for a smaller number of samples. In addition to calling for CNVs, pathways analyses have been also pursued, to address the hypothesis that disruption of multiple genes from the same pathway in the germline of a particular individual may cause susceptibility for developing osteosarcoma. DAVID software predicted several pathways that are enriched, p53 being one of them. Further investigations by KEGG suggest that several genes, including ZMAT3, are disrupted in the p53 signaling pathway. In order to validate these findings, functional assays on osteosarcoma derived lymphoblastoid cell lines are designed and currently in progress. In all, the current study suggests that ZMAT3 could represent a good candidate signature gene for susceptibility to sporadic osteosarcoma. Citation Format: Cristina Baciu, Rinnat Porat, Margaret Pienkowska, Noa Alon, Jonathan Wasserman, David Malkin. ZMAT3, a signature gene for sporadic osteosarcoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3163. doi:10.1158/1538-7445.AM2013-3163
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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 | 0.001 |
| 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) | 0.003 | 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".