Author

F. Eduati

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 4

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 4 Organism:human· 4 Approach:deep learning· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Assay:clinical cohort / trial· 1

Frequent Co-Authors

F. Finotello· 2 shared J. Saez-Rodriguez· 2 shared O. Lapuente-Santana· 2 shared A. D. Sahu· 1 shared A. S. Halkola· 1 shared A. Sieber· 1 shared B. G. Vincent· 1 shared B. Klinger· 1 shared

Activity by Year

2016-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersCancer Biology

F. Finotello

Mutual co-authors in cluster

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4 papers

Recent·Most cited

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

M. Mason, O. Lapuente-Santana, A. S. Halkola, W. Wang, R. Mall, X. Xiao, J. Kaufman, J. Fu, J. Pfeil, J. Banerjee, V. Chung, H. Chang, S. D. Chasalow, H. Y. Lin, R. Chai, , B. G. Vincent

The paper evaluates predictive models for immune checkpoint inhibitor outcomes in NSCLC using clinical trial data from two RCTs, finding that models combining PD-L1, TMB, and immune signatures outperform single biomarkers.

Journal of Translational Medicine · Feb 21, 2024Peer-reviewedCancer Biology

Predictive systems biomarkers of response to immune checkpoint inhibitors

O. Lapuente-Santana, M. van Genderen, P. Hilbers, F. Finotello, F. Eduati

This study develops EaSIeR, a method using RNA-seq data and prior knowledge to predict immune response to PD-1 inhibitors by analyzing tumor microenvironment signatures.

bioRxiv · Feb 5, 2021Cancer Biology

Dissecting cancer resistance to therapies with cell-type-specific dynamic logic models

F. Eduati, V. Doldan-Martelli, B. Klinger, T. Cokelaer, A. Sieber, F. Kogera, M. Dorel, M. J. Garnett, N. Bluthgen, J. Saez-Rodriguez

The paper uses dynamic logic models of signaling pathways to predict drug sensitivity in colorectal cancer cell lines and identifies drug combinations to overcome resistance.

bioRxiv · Dec 16, 2016Cancer Biology

Rapid identification of optimal drug combinations for personalized cancer therapy using microfluidics

F. Eduati, R. Utharala, D. Madhavan, U. P. Neumann, T. Cramer, J. Saez-Rodriguez, C. A. Merten

This paper presents a microfluidics-based method to rapidly screen drug combinations on patient cancer cells, identifying personalized treatment options validated in pancreatic cancer cell lines.

bioRxiv · Dec 14, 2016Cancer Biology