Author

Meisam Bagheri

Dartmouth CollegeORCID 0000-0002-5468-321XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:scRNA-seq· 3 Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Organism:mouse· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Fred KollingiD· 2 shared Aaron McKennaiD· 1 shared Abigail C. MarshalliD· 1 shared Arthur SaniotisiD· 1 shared Brock C. ChristenseniD· 1 shared Diwakar Ram PattabiramaniD· 1 shared Hanxu LuiD· 1 shared Jackie Vahey· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersCancer Biology

Fred KollingORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Epithelial-Mesenchymal Transition is Associated with Altered Immune Composition and Cytotoxic Function in Triple-Negative Breast Cancer

Hanxu Lu, Meisam Bagheri, Fred Kolling, Lucas A. Salas, Xiaofeng Wang, Todd W. Miller, Diwakar Ram Pattabiraman, Brock C. Christensen

This study shows that EMT progression in breast cancer correlates with reduced immune cell infiltration and function, including decreased cytotoxic T cells and altered B cell composition.

Breast Cancer Research · Jul 16, 2026Peer-reviewedCancer Biology

Mapping breast cancer lineage in radiation and immunotherapy using the REMAP mouse

Abigail C. Marshall, Jackie Vahey, Meisam Bagheri, Rachel Saxe, Jennifer Fields, Fred Kolling, Aaron McKenna

The paper introduces REMAP, a mouse model for tracking breast cancer lineage, and shows how treatment affects tumor evolution and immune response.

bioRxiv · Apr 18, 2026 · PreprintCancer Biology

Relationship Between Gene Expression and Drug Response in Triple-Negative Breast Cancer: Leveraging Single-Cell RNA Sequencing and Machine Learning to Identify Biomarker Profiles

Kazhaleh Mohammadi, Nasim Afhami, Arthur Saniotis, Maciej Henneberg, Meisam Bagheri, Kaveh Kavousi

This study identifies biomarkers for drug response in TNBC using scRNA-seq and machine learning, showing high predictive accuracy and highlighting blood-derived biomarkers.

bioRxiv · Mar 8, 2026 · PreprintBioinformatics