Abstract 173: Genomic characterization of patient-derived pancreatic cancer organoids
Bibliographic record
Abstract
Abstract Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death with few effective therapies. Patient-derived organoids (PDOs) are a 3-D culture model that allow primary tumour cells to propagate, and have gained considerable traction in many cancer types such as PDAC. However, concerns remain regarding whether these models can predict what occurs in patients. We hypothesize that genomic and transcriptomic drift occurring in PDO models impacts the fidelity of drug response. To investigate, matched WGS and bulk RNAseq was performed on paired PDAC organoids and tumour tissue (n=41). Core biopsies were obtained from in patients with Stage III-IV PDAC enrolled in the COMPASS trial (NCT02750657) and divided for sequencing and organoid generation. Tumour cellularity was enriched by laser capture microdissection. Although alterations in the four major driver genes (KRAS, TP53, SMAD4, CDKN2A) remained consistent, other genomic differences were identified. SNV count was higher in organoids (median 6584 vs 5931, p<0.0001), and enriched in SBS5 mutational signature (p<0.0001). This was not significantly correlated with passage number, and private mutations were identified in both tumours and organoids (median 67% overlap). Two organoids showed significant shifts in ploidy, with both diploid to polyploid shifts and vice versa observed. In the transcriptome, expression of Basal-like genes (KRT5, TP63) was decreased. Bias towards the Classical transcriptomic subtype have previously been observed in PDAC organoid cultures. PDO responses to 5-FU, irinotecan, and oxaliplatin correlated with patient response to FFX (n=22, 72% concordance). However, PDO responses to gemcitabine and paclitaxel were poorly predictive of patient responses to GnP (n=10, 38% concordance), and notably, expression of the biomarker hENT1 was not correlated in matched tumors and PDOs (R=0.17, p=0.40). Despite this, tumour expression of the biomarker hENT1 successfully stratified patient responses to gemcitabine, and organoid hENT1 expression was correlated to gemcitabine response in vitro (R=0.47, p=0.005), indicating that transcriptomic drift may be a major contributor to discrepancies in patient-PDO drug response. In summary, organoids recapitulate major histologic features and driver mutations of patient tumours, but genetic drift and subclonal selection are observed even at lower passages. Further study is required to improve the utility of organoids in translational precision medicine. Citation Format: Irene Y. Xie, Yuanchang Fang, Amy X. Zhang, Karen Ng, Zhen-Mei Liu, Eugenia Flores-Figueroa, Gun Ho Jang, Stephanie Ramotar, Anna Dodd, Julie Wilson, Jennifer J. Knox, Steven Gallinger, Faiyaz Notta. Genomic characterization of patient-derived pancreatic cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 173.
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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 | 0.001 |
| 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) | 0.002 | 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".