Author

R. Romee

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· 2 Immunology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:host-pathogen & immune response· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

A. Chesney· 1 shared A. Hernandez· 1 shared A. Keating· 1 shared A. Matsui· 1 shared A. Morita· 1 shared A. Näätänen· 1 shared A. Toor· 1 shared B. Ghimire· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperCancer Biology

A. Chesney

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Liver fibrosis uncouples tumor control from survival after multikinase inhibitor immunotherapy in hepatocellular carcinoma

S. Morita, T. Ando, H. Kikuchi, A. Morita, T. Kobayashi, G. Birch, R. Tanaka, A. Matsui, Z. Ruan, P. Huang, Y. Cho, A. Hernandez, J. W. Lee, E. M. Coyne, S. M. Shin, , D. G. Duda

Liver fibrosis limits the survival benefit of multikinase inhibitor immunotherapy in hepatocellular carcinoma by promoting innate immune-mediated hepatotoxicity despite preserved tumor control.

bioRxiv · Oct 20, 2023 · PreprintCancer Biology

Single-cell functional genomics of natural killer cell evasion in blood cancers

O. Dufva, S. Gandolfi, J. Huuhtanen, O. Dashevsky, K. Saeed, J. Klievink, P. Nygren, J. Bouhlal, J. Lahtela, A. Näätänen, B. Ghimire, T. Hannunen, P. Ellonen, H. Duan, J. Theodoropoulos, , S. Mustjoki

The paper uses single-cell and genome-scale functional genomics to study how blood cancer cells evade NK cells, identifying key genes and pathways involved in resistance and sensitivity.

bioRxiv · Aug 22, 2022 · PreprintImmunology

Killer Immunoglobulin-like Receptor-Ligand Interactions Predict Clinical Outcomes Following Unrelated Donor Transplants

E. O. Krieger, R. Sabo, S. Moezzi, C. Cain, C. Roberst, P. Kimball, A. Chesney, J. McCarty, A. Keating, R. Romee, C. Wiedl, R. Qayyum, A. Toor

The paper develops a mathematical model to quantify KIR-KIRL interactions and shows that these interactions predict clinical outcomes in HLA-matched unrelated donor transplants.

bioRxiv · Jun 23, 2019Cancer Biology