Abstract 3161: High throughput drug screening to uncover molecular vulnerabilities in pancreatic ductal adenocarcinoma

Abstract Introduction: High-throughput drug screening enables rapid testing of numerous drugs on tumor samples and has achieved breakthroughs in treatment selection for fatal diseases such as acute myeloid leukemia. This study leverages high-throughput screening to identify molecular vulnerabilities in pancreatic ductal adenocarcinoma (PDAC), a highly lethal cancer with a 5-year survival rate of just 13%. Methods: Using PDAC patient-derived organoids (PDOs), we developed a platform to screen approximately 3, 000 compounds at a single dose and 600 compounds across six doses on 120 PDOs. Additionally, we designed a tailored focused screening of 22 drugs at 20 doses, prioritizing Health Canada-approved drugs identified as promising in earlier screenings. To ensure robust data analysis, we developed an optimized bioinformatics pipeline incorporating a three-tier evaluation: Area Under the Curve (AUC), Drug Sensitivity Score (DSS), and maximum efficacy (Emax). Results from each PDO were systematically compared against the entire cohort, ensuring that sensitivity profiles reflect reliable outcomes. Additionally, we integrated drug response data with genomics and transcriptomics obtained through whole-genome and whole-exome sequencing of PDOs. Results: We identified highly potent compounds capable of suppressing tumor growth in over 55% of PDOs, prioritizing clinically approved drugs to facilitate rapid translation to patient care. Drug sensitivity patterns from single-dose screenings were corroborated through six-dose validation and a focused screening platform. By integrating drug response data with multi-omics analyses, we uncovered patient-specific drug response profiles linked to molecular vulnerabilities. Notably, we validated a gene-drug association involving anagrelide, a selective agent that induces cytotoxicity in cancer cells with elevated phosphodiesterase PDE3A levels, highlighting the robustness of our approach. Preliminary findings demonstrate a strong concordance between PDO-derived and patient drug responses, establishing a foundation for actionable clinical insights in the ADOPT trial to guide personalized treatment strategies. Conclusion: In conclusion, our high-throughput drug screening platform, integrated with multi-omics analysis and robust bioinformatics, enables the identification of patient-specific molecular vulnerabilities in PDAC. This approach advances the potential for precision oncology, providing a foundation for tailored therapeutic strategies in this highly lethal cancer. Citation Format: Nikta Feizi, Eugenia Flores-Figueroa, Karen Ng, Zhen-Mei Liu, Farnoosh Abbas Aghababazadeh, Gun Ho Jang, Daniela Bevacqua, Stephanie Ramotar, Shawn Hutchinson, Anna Dodd, Julie Wilson, Robert Grant, Ronan Mclaughlin, Erica Tsang, Jennifer Knox, Steven Gallinger, Benjamin Haibe-Kains, Faiyaz Notta. High throughput drug screening to uncover molecular vulnerabilities in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3161.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-3161
Primary Topic
Pancreatic and Hepatic Oncology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 3161: High throughput drug screening to uncover molecular vulnerabilities in pancreatic ductal adenocarcinoma

Erica S. Tsang, Benjamin Haibe‐Kains, Shawn Hutchinson, Steven Gallinger et al.
1 links
Cancer Research
Pancreatic and Hepatic Oncology Research
article

Abstract 3161: High throughput drug screening to uncover molecular vulnerabilities in pancreatic ductal adenocarcinoma

Erica S. Tsang, Benjamin Haibe‐Kains, Shawn Hutchinson, Steven Gallinger, Nikta Feizi, Zhen-Mei Liu, Anna Dodd, Karen Ng, R.A. McLaughlin, Faiyaz Notta, Farnoosh Abbas‐Aghababazadeh, Jennifer J. Knox, Eugenia Flores‐Figueroa, Julie M. Wilson, Robert C. Grant, Gun Ho Jang, Stephanie Ramotar, Daniela Bevacqua
article en

Abstract

Abstract Introduction: High-throughput drug screening enables rapid testing of numerous drugs on tumor samples and has achieved breakthroughs in treatment selection for fatal diseases such as acute myeloid leukemia. This study leverages high-throughput screening to identify molecular vulnerabilities in pancreatic ductal adenocarcinoma (PDAC), a highly lethal cancer with a 5-year survival rate of just 13%. Methods: Using PDAC patient-derived organoids (PDOs), we developed a platform to screen approximately 3, 000 compounds at a single dose and 600 compounds across six doses on 120 PDOs. Additionally, we designed a tailored focused screening of 22 drugs at 20 doses, prioritizing Health Canada-approved drugs identified as promising in earlier screenings. To ensure robust data analysis, we developed an optimized bioinformatics pipeline incorporating a three-tier evaluation: Area Under the Curve (AUC), Drug Sensitivity Score (DSS), and maximum efficacy (Emax). Results from each PDO were systematically compared against the entire cohort, ensuring that sensitivity profiles reflect reliable outcomes. Additionally, we integrated drug response data with genomics and transcriptomics obtained through whole-genome and whole-exome sequencing of PDOs. Results: We identified highly potent compounds capable of suppressing tumor growth in over 55% of PDOs, prioritizing clinically approved drugs to facilitate rapid translation to patient care. Drug sensitivity patterns from single-dose screenings were corroborated through six-dose validation and a focused screening platform. By integrating drug response data with multi-omics analyses, we uncovered patient-specific drug response profiles linked to molecular vulnerabilities. Notably, we validated a gene-drug association involving anagrelide, a selective agent that induces cytotoxicity in cancer cells with elevated phosphodiesterase PDE3A levels, highlighting the robustness of our approach. Preliminary findings demonstrate a strong concordance between PDO-derived and patient drug responses, establishing a foundation for actionable clinical insights in the ADOPT trial to guide personalized treatment strategies. Conclusion: In conclusion, our high-throughput drug screening platform, integrated with multi-omics analysis and robust bioinformatics, enables the identification of patient-specific molecular vulnerabilities in PDAC. This approach advances the potential for precision oncology, providing a foundation for tailored therapeutic strategies in this highly lethal cancer. Citation Format: Nikta Feizi, Eugenia Flores-Figueroa, Karen Ng, Zhen-Mei Liu, Farnoosh Abbas Aghababazadeh, Gun Ho Jang, Daniela Bevacqua, Stephanie Ramotar, Shawn Hutchinson, Anna Dodd, Julie Wilson, Robert Grant, Ronan Mclaughlin, Erica Tsang, Jennifer Knox, Steven Gallinger, Benjamin Haibe-Kains, Faiyaz Notta. High throughput drug screening to uncover molecular vulnerabilities in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3161.

Cancer ResearchVol. 85(8_Supplement_1)
Ontario Institute for Cancer Research (CA), University Health Network (CA), University of Toronto (CA)
Openalex Percentile: Top 89%
Pancreatic and Hepatic Oncology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.