Author

E. M. Vuorinen

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

Biology Disciplines

Click to filter author papers

Cancer Biology· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

A. D. Lamb· 1 shared A. Erickson· 1 shared A. Goga· 1 shared A. Kiviaho· 1 shared A. Peura· 1 shared A. Urbanucci· 1 shared B. Boeckx· 1 shared D. Lambrechts· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperCancer Biology

A. D. Lamb

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Respiratory Complex I Regulates Dendritic Cell Maturation in Explant Model of Human Tumor Immune Microenvironment

R. Turpin, R. Liu, P. Munne, A. Peura, J. H. Rannikko, G. Philips, B. Boeckx, N. Salmelin, E. Hurskainen, I. Suleymanova, E. M. Vuorinen, L. Lehtinen, M. Mutka, P. E. Kovanen, L. Niinikoski, , J. Klefstrom

The paper uses a patient-derived explant model to show metformin enhances dendritic cell maturation by inhibiting complex I, improving anti-tumor immunity when combined with venetoclax.

bioRxiv · May 10, 2023Cancer Biology

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

S. Taavitsainen, N. Engedal, S. Cao, F. Handle, A. Erickson, S. Prekovic, D. Wetterskog, T. Tolonen, E. M. Vuorinen, A. Kiviaho, R. Nätkin, T. Häkkinen, W. Devlies, S. Henttinen, R. Kaarijärvi, , A. Urbanucci

The paper uses single-cell ATAC and RNA sequencing to identify pre-existing and treatment-persistent stem-like cell subpopulations in prostate cancer models that predict treatment response.

bioRxiv · Feb 9, 2021Cancer Biology