Author

O. Engebraaten

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· 3

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:chromatin & epigenetic regulation· 1 Assay:clinical cohort / trial· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1

Frequent Co-Authors

A.-L. Borresen-Dale· 2 shared T. Fleischer· 2 shared V. N. Kristensen· 2 shared A. Frigessi· 1 shared A. Hurtado-Rodriguez· 1 shared A. Kohn-Luque· 1 shared A.-L. Boerresen-Dale· 1 shared A.-M. Fosdahl· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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2 shared papersCancer Biology

A.-L. Borresen-Dale

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3 papers

Recent·Most cited

An integrated 'omics approach highlights the role of epigenetic events to explain and predict response to neoadjuvant chemotherapy and bevacizumab

T. Fleischer, M. H. Haugen, J. Ankill, L. Silwal-Pandit, A.-L. Borresen-Dale, I. Hedenfalk, T. Hatschek, J. Tost, O. Engebraaten, V. N. Kristensen

This study uses an integrated omics approach to show that DNA methylation at enhancer CpGs can predict response to neoadjuvant chemotherapy and bevacizumab in ER-positive patients.

bioRxiv · Jul 6, 2022 · PreprintCancer Biology

Breast tumors escape endocrine therapy by ER-independent mechanisms triggered by the coordinated activities of HER2/HER3 and deacetylated FOXA1

S. Gilfillan, S. Wang, M. R. Katika, J. H. Norum, H. Bergholtz, E. Fiorito, S. Nordhagen, Y. Sharma, S. Singh, V. S. Somisety, A.-M. Fosdahl, S. Nord, O. Engebraaten, O. C. Lingjaerde, A.-L. Borresen-Dale, , A. Hurtado-Rodriguez

This study shows that HER2/HER3 signaling and FOXA1 deacetylation drive ER-independent growth in hormone-resistant breast tumors by altering FOXA1 chromatin binding and function.

bioRxiv · Sep 22, 2020 · PreprintCancer Biology

Towards personalized computer simulation of breast cancer treatment: a multi-scale pharmacokinetic and pharmacodynamic model informed by multi-type patient data

X. Lai, O. Geier, T. Fleischer, O. Garred, E. F. Borgen, S. Funke, S. Kumar, M. E. Rognes, T. Seierstad, A.-L. Boerresen-Dale, V. N. Kristensen, O. Engebraaten, A. Kohn-Luque, A. Frigessi

This study develops a multi-scale pharmacokinetic and pharmacodynamic model of breast cancer treatment, personalized with patient data to simulate and improve treatment outcomes.

bioRxiv · Jul 19, 2018Cancer Biology