Abstract B113: Imaging mass cytometry guided shallow whole genome sequencing for phenotype informed regional copy number profiling in a pancreatic tumor
Bibliographic record
Abstract
Abstract Pancreatic adenocarcinoma (PDAC) exhibits a huge range of genomic plasticity due to prevalent genomic instability across tumors. Longitudinal whole genome sequencing of patients at primary diagnosis and metastatic disease progression have shown KRAS copy number amplification and allelic imbalance as drivers of classical to basal-like phenotypic switch, resulting in propensity for whole genome duplication, genomic instability and aggressive metastasis. High-plex spatial proteomics have revealed that primary tumors are phenotypically mixed, but the relationship between intratumorally distinct phenotypes and their genomics remain unclear as existing genomics relies on bulk captured tumors. Therefore, this drives the need to spatially resolve the intra-tumoral genomic heterogeneity associated with distinct tumor phenotypes. We leveraged whole-slide high-plex Imaging Mass Cytometry (IMC) to stain a phenotypically mixed primary tumor with 41 different markers covering the classical (AGR2, TFF1, CEACAM6) and basal (TP63, KRT5, S100A2, CAV1) phenotype, pan-immune markers, epithelial transcription factors (GATA6, FOXA2, PDX1) and stroma. Bulk whole genome sequencing (30X) reveals that this tumor had undergone losses of chr 1p, 6p, 9, 17 and 8, in addition to 12p focal amplification and whole genome doubling. To address the association of spatial phenotypes to regional genomics, IMC guided laser capture microdissection (LCM) was performed on a serial section aligned to 4 classical (C1-4), 4 basal (B1-4) and 4 hybrid-staining (H1-4) regions, followed by independent shallow whole genome sequencing (sWGS) at 2X coverage for each captured region (n = 12). Quality control, alignment and variant calling was performed utilizing standard whole-genome sequencing workflow. Integer copy number was determined through 100kb bins and segmentation. A full range of ploidy solutions (2N, 3N and 4N) was fit for each region using Absolute Copy Number Estimation (ACE) and the best fit was used for each region. We observed that in region C2, losses in many chromosomes (1p, 6, 9, 17, 18) but had no arm level amplifications, indicating a mitotic defect. At region C3, we observed a small increase in the 12p segment harboring the KRAS locus, suggesting that a sub-clonal event had occurred resulting in amplification. At region H3, a phenotypically mixed region, a strong 12p amplification was observed along with widespread genomic instability. Finally, at region B1, the whole genome duplication is observed. Our initial pilot reveals a stepwise, orchestrated genome evolution process in a phenotypically mixed primary tumor which was not obvious in bulk whole genome sequencing, highlighting the need for spatially informed regional capture of tumors to uncover phenotypically and potentially clinically important genomic alterations. Citation Format: Tiak Ju Tan, Deni Van. Sechie, Ferris Nowlan, Noor Shakfa, Elizabeth Sunnucks, Sibyl Drissler, Jenn Gorman, Michael J. Geuenich, Chengxin Yu, Grannie O. Kane, Faiyaz Notta, Rob Grant, Julie Wilson, Steve Gallinger, Kieran R. Campbell, Hartland W. Jackson. Imaging mass cytometry guided shallow whole genome sequencing for phenotype informed regional copy number profiling in a pancreatic tumor [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr B113.
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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 | 0.000 |
| 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) | 0.002 | 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".