Abstract B113: Imaging mass cytometry guided shallow whole genome sequencing for phenotype informed regional copy number profiling in a pancreatic tumor
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».