Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing
Bibliographic record
Abstract
Abstract Purpose Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies, with limited benefit from current cytotoxic regimens and poor predictive value of genomics alone. Patient-derived organoids (PDOs) represent a promising platform for functional precision oncology, yet systematic pharmacotyping of genomically annotated PDAC PDOs remains sparse. Experimental Design We established a clinically annotated panel of ten treatment-naïve PDAC PDOs spanning well-, moderately-, and poorly differentiated tumors. PDOs were evaluated for morphologic and genomic fidelity and screened against 1,813 clinically relevant small molecules in a high-throughput 384-well format. Drug sensitivities were quantified at the compound and drug-family levels and integrated with histologic grade, pathway-level mutational profiles, and available clinical treatment information. Results PDOs preserved hallmark tumor features, including glandular organization and subclonal mutational architecture. Pharmacotyping revealed both shared and subtype-specific vulnerabilities. Classical (well/moderately differentiated) PDOs showed enriched mutations in DNA repair, mitotic spindle, and chromatin-regulatory pathways and were preferentially sensitive to topoisomerase inhibitors, microtubule poisons, and HDAC inhibitors. In contrast, basal (poorly differentiated) PDOs displayed coordinated defects in mitochondrial function, vesicle trafficking, and ubiquitin-mediated proteostasis, at the pathway level, that conferred a previously unrecognized vulnerability to cardiac glycosides. Sensitivities to standard PDAC agents were heterogeneous across models, underscoring the limited predictive value of genotype alone and the need for functional drug testing. Conclusions This integrated genomic and pharmacologic analysis demonstrates that PDO pharmacotyping identifies biologically grounded, actionable vulnerabilities in PDAC, including novel therapeutic opportunities in basal, chemo-resistant tumors. These findings support PDO-guided functional profiling as a clinically relevant platform for refining drug selection and expanding treatment options for patients with PDAC. Significance PDAC is dominated by chemoresistance and lacks reliable genomic predictors of therapy response. By integrating high-throughput drug screening with mutation-informed pathway analysis in patient-derived organoids, we identify differentiation-linked therapeutic liabilities, including a previously unrecognized vulnerability to cardiac glycosides in basal PDAC. These results highlight PDO pharmacotyping as a powerful functional complement to genomics for guiding treatment selection in pancreatic cancer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".