Abstract A9: The pancreatic ductal adenocarcinoma project at the Ontario Institute for Cancer Research.
Bibliographic record
Abstract
Pancreatic cancer is the fifth leading cause of cancer-related death with a poor prognosis and 5-year survival rates of less than 5%. As a contributing member of the International Cancer Genome Consortium (ICGC), the Ontario Institute for Cancer Research (OICR) has committed to generating a comprehensive catalogue of genomic abnormalities found in pancreatic ductal adenocarcinomas (PDAC). Using next-generation sequencing technologies, 375 independent pancreatic tumors and their matched controls will be characterized over a 3- to 5-year time span. Many of the samples also have derived matching xenografts and a few have cell lines derived from the xenograft tumors. To date, this project has collected 173 ICGC consented matched samples comprised of 85 PDAC tumor/reference and 21 xenograft/ reference pairs. 32 sample sets have matched tumor/xenograft/reference. In addition, there are 16 cell lines derived from some of these xenografts. Whole-genome and exome target-enrichment sequencing is currently performed using the HiSeq 2000 platform. For efficient variant calling, all whole-genome analyses used a minimal depth of 30x reference and 50x tumor/xeno/cell line and exome analyses used greater than 100x target coverage, with most samples exceeding these targets. Sequence alignment is primarily performed with Novoalign (Novocraft.com) and variants called with the Genome Analysis Toolkit (McKenna et al., Genome Res. 20:1297) to identify germline and somatic variants in all matched sample sets. On average 35 coding non-synonymous variants have been observed per primary tumor exome. Validation of the coding non-synonymous variants is ongoing with data deposited in the ICGC Data Coordinating Center (www.icgc. org). Initial data have been combined with PDAC data sets from the Australian ICGC effort (S. Grimmond and A. Biankin) and from sequencing efforts at the Baylor College of Medicine (R. Gibbs) to increase analytical power. Sequencing of primary tumors and xenografts was complicated by human and mouse stroma, respectively. Complete whole-genome sequencing of the host mouse strain was needed for removal of “interspecies SNP” observed due to alignment of both species to regions of similarity in the human reference sequence. The “SNPs” are falsely identified as somatic variants after subtracting the human germline SNP. Methods are under development to improve this removal process. Current sequencing is focusing on expanding the data set of matched normal and primary tumor pairs. It is anticipated that 150 exome pairs will be sequenced by 4th quarter 2012 with whole-genome sequencing following closely. Continued development of xenograft resources is ongoing in parallel. Whole genome sequences will be generated from selected xenografts. Collectively, the sequence data, xenografts, and cell line models will make a rich resource for studying PDAC. Citation Format: Kimberly N. Begley, Debabrata Mukhopadhyay, Gloria M. Petersen, Alexei Protopopov, Sarah Thayer, Lynda Chin, Emin Ibrahimov, Patricia Shaw, Thomas Hudson, Steve Gallinger, Ming-Sound Tsao, Lincoln Stein, John D. McPherson, Lakshmi Muthuswamy, Timothy Beck, Christina Yung, Michelle Sam, Lee Timms, Carson Holt. The pancreatic ductal adenocarcinoma project at the Ontario Institute for Cancer Research. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Progress and Challenges; Jun 18-21, 2012; Lake Tahoe, NV. Philadelphia (PA): AACR; Cancer Res 2012;72(12 Suppl):Abstract nr A9.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".