ResearcherUniversity of HelsinkiActive in the last 2 years
Toni T. Seppälä
Matched on ORCID iD 0000-0002-4940-3498; OpenAlex author ID A5024265800. Sources: OpenAlex.
Their work
- Papers
- 9
- Trials
- 0
- Grants
- 0
- Labs led
- 0
- Collaborators
- 45
2020: 1 paper · 2021: 1 paper · 2022: 2 papers · 2023: 1 paper · 2024: 2 papers · 2025: 1 paper · 2026: 1 paper
Papers 9
- Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcinoma. Co-author DOI 10.1097/sla.0000000000006517↗
- Therapeutic Targeting of Oncogene-Induced Transcription-Replication Conflicts in Pancreatic Ductal Adenocarcinoma. Co-author DOI 10.1053/j.gastro.2025.02.038↗
- In vivo CRISPR screening identifies geranylgeranyl diphosphate as a pancreatic cancer tumor growth dependency. Co-author DOI 10.1016/j.molmet.2024.101964↗
- Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Inflammation in Cancer Cells in Pancreatic Du… Co-author DOI 10.1158/0008-5472.can-23-1660↗
- Hereditary colorectal, gastric, and pancreatic cancer: comprehensive review. Co-author DOI 10.1093/bjsopen/zrad023↗
- Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture Co-author DOI 10.1101/2022.07.14.500096↗
- Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical Treatment Response. Co-author DOI 10.1158/1078-0432.ccr-21-4165↗
- Can Pancreatic Organoids Help in the Treatment of Pancreatic Cancer? Co-author DOI 10.1016/j.yasu.2021.05.015↗
- Patient-derived Organoid Pharmacotyping is a Clinically Tractable Strategy for Precision Medicine in Pancreatic Cancer. Co-author DOI 10.1097/sla.0000000000004200↗
Closest collaborators
The 25 strongest of 45 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Richard Andrew Burkhart · 6 shared papers, 2020–2024 · strength 1.01
- Paper Can Pancreatic Organoids Help in the Treatment of Pancreatic Cancer? DOI 10.1016/j.yasu.2021.05.015↗
- Paper In vivo CRISPR screening identifies geranylgeranyl diphosphate as a pancreatic cancer tumor growth dependency. DOI 10.1016/j.molmet.2024.101964↗
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Richard A. Burkhart · 3 shared papers, 2023–2026 · strength 0.75
- Paper Hereditary colorectal, gastric, and pancreatic cancer: comprehensive review. DOI 10.1093/bjsopen/zrad023↗
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Therapeutic Targeting of Oncogene-Induced Transcription-Replication Conflicts in Pancreatic Ductal Adenocarcinoma. DOI 10.1053/j.gastro.2025.02.038↗
- Jin Peng He · 5 shared papers, 2020–2026 · strength 0.69
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Elizabeth M. Jaffee · 5 shared papers, 2020–2026 · strength 0.69
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Jacquelyn W. Zimmerman · 5 shared papers, 2020–2026 · strength 0.69
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Elana Judith Fertig · 3 shared papers, 2022–2026 · strength 0.49
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Samantha R. Guinn · 3 shared papers, 2022–2026 · strength 0.49
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- David Tsai Ting · 4 shared papers, 2020–2024 · strength 0.45
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Reecha Suri · 4 shared papers, 2020–2024 · strength 0.45
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- David P. Ryan · 4 shared papers, 2020–2024 · strength 0.45
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Christopher L. Wolfgang · 3 shared papers, 2022–2024 · strength 0.36
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Alec C. Kimmelman · 3 shared papers, 2022–2024 · strength 0.36
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Lei Zheng · 3 shared papers, 2022–2024 · strength 0.36
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Christopher R. Shubert · 2 shared papers, 2022–2026 · strength 0.36
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Kelly J. Lafaro · 2 shared papers, 2022–2026 · strength 0.36
- Paper Patient-derived Organoid Pharmacotyping as a Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcin… DOI 10.1097/sla.0000000000006517↗
- Paper Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical … DOI 10.1158/1078-0432.ccr-21-4165↗
- Bryson W. Katona · 1 shared paper, 2023 · strength 0.31
- Peter J. Espenshade · 1 shared paper, 2024 · strength 0.28
- Casie S. Kubota · 1 shared paper, 2024 · strength 0.28
- Dimitrios N. Sidiropoulos · 2 shared papers, 2022–2024 · strength 0.25
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Jacob T. Mitchell · 2 shared papers, 2022–2024 · strength 0.25
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Luciane Tsukamoto Kagohara · 2 shared papers, 2022–2024 · strength 0.25
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Jun Yu · 2 shared papers, 2022–2024 · strength 0.25
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Benedict Kinny‐Köster · 2 shared papers, 2022–2024 · strength 0.25
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- Laura DeLong Wood · 2 shared papers, 2022–2024 · strength 0.25
- Paper Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Infla… DOI 10.1158/0008-5472.can-23-1660↗
- Paper Inflammatory Signaling in Pancreatic Cancer Transfers Between a Single-cell RNA Sequencing Atlas and Co-Culture DOI 10.1101/2022.07.14.500096↗
- William Reece Burns · 1 shared paper, 2026 · strength 0.24
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.