Abstract C31: Identification of causal genetic events in oral cancer progression
Bibliographic record
Abstract
Abstract Background: Oral cancer is one of the world's leading causes of cancer death, with late stage disease diagnoses and high rates of recurrence accounting for poor survival rates. Like many solid tumors, oral cancer develops through a series of histopathological stages from dysplasia, to carcinoma in situ (CIS), to invasive disease. Escalating genomic instability and the accumulation of critical gene alterations is thought to drive disease progression. Causal gene changes remain to be identified for oral cancer. The objective of this study is to determine the essential gene alterations underpinning oral cancer progression. Hypothesis: Since cancers arise through the accumulation of genetic alterations, gene changes detected in the earliest stages of disease are the foundation of observed cancer phenotypes and essential for oral tumorigenesis. Experimental Approaches: Oral premalignant lesions and tumor samples were obtained from the Oral Biopsy Service of British Columbia and are associated with well annotated patient information (including disease outcomes). High resolution tiling-path array comparative genomic hybridization was used to define segmental DNA changes for each sample. Recurring regions of DNA alteration detected in premalignant lesions known to progress and preserved in later stage disease were flagged as critical events. Our list of candidate genes within these regions will be refined by analysis of publicly available genomic and gene expression data from oral tumors. Results: Whole genome copy number profiles from over 100 oral lesions and tumors have been successfully generated using array comparative genomic hybridization. From this data we have identified several molecular subgroups associated with initiation and progression of oral cancer. Significance: With knowledge of the key genes fueling oral tumorigenesis, we will be able to derive novel biomarkers capable of predicting disease behavior as well as gain a better understanding of the molecular pathways and gene networks responsible for driving oral cancer progression. Citation Information: Cancer Res 2009;69(23 Suppl):C31.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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; 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".