Abstract B036: The role of whole genome duplication in progression of pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
Abstract Introduction: Pancreatic ductal adenocarcinoma (PDA) is a lethal disease that tends to present at an advanced stage, but the evolutionary mechanisms responsible for rapid progression in PDA are poorly understood. Whole genome duplication (WGD) is a hallmark of cancer observed more frequently in late-stage tumors that predicts poorer overall patient survival across cancer types, including PDA. The genome-wide instability that occurs during WGD events can lead to gene dosage imbalances that promote tumor progression and may explain the rapid progression of aneuploidy. Although WGD has been studied extensively in advanced cancer, there is limited data on WGD in primary tumors. We hypothesize that WGD occurs frequently in primary PDA and promotes the rapid progression and high rate of relapse in early stage PDA. We leveraged scWGS to infer copy number profiles and WGD events from tumor cells to determine the rate of subclonal WGD in primary PDA tumors and understand how aneuploidy and genome instability evolve in the earliest stages of tumor progression. Methods: Single cell barcoded libraries from primary treatment naive tumors were prepared with the 10X Genomics Single Cell CNV platform and sequenced to a depth of 20-60x per tumor. Reads were processed using CellRanger DNA pipeline, demultiplexed, and analyzed with Gingko CNV. A total of 10,323 cells from 8 primary PDA tumors (range, 192 – 3146; median = 1286) were recovered, resulting in an average coverage of 0.06x per single cell (range, 0.02x – 0.14x). Results: 5/8 tumors analyzed had evidence of at least one WGD event. The WGD event was identified as a minor subclone in 3 of these 5. Copy number profiles revealed 1-6 distinct subclones in each tumor, demonstrating copy number evolution is ongoing. WGD+ tumors trend towards having higher diversity and higher percentage of genome altered. Conclusion: WGD occurs more frequently in primary PDA than previously understood, and may confer high levels of genetic instability. Citation Format: Lauren Hummel, Irene Xie, Karen Ng, Amy Zhang, Stephanie Ramotar, Anna Dodd, Grainne O'Kane, Jennifer Knox, Julie Wilson, Steven Gallinger, Faiyaz Notta. The role of whole genome duplication in progression of pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B036.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".