Author

M. Lustberg

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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Research Focus:differential expression· 3 Assay:bulk RNA-seq· 2 Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Organism:human· 2 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

B. Ramaswamy· 2 shared A. Bratasz· 1 shared A. C. DeVries· 1 shared C. C. Coss· 1 shared C. E. Bennett· 1 shared D. G. Stover· 1 shared D. Stover· 1 shared D. Tallman· 1 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersCancer Biology

B. Ramaswamy

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Aromatase Inhibitor Induced Musculoskeletal Inflammation is Observed Independent of Oophorectomy in a Novel Mouse Model

N. A. Young, J. Hampton, J. Sharma, K. Jablonski, A. C. DeVries, A. Bratasz, L.-C. Wu, M. Lustberg, R. Reinbolt, W. N. Jarjour

This study develops a novel mouse model showing aromatase inhibitor-induced musculoskeletal inflammation occurs independently of oophorectomy and estrogen deficiency.

bioRxiv · Jun 22, 2022Immunology

Activity of Estrogen Receptor β Agonists in Therapy-Resistant Estrogen Receptor-Positive Breast Cancer

J. Datta, N. Willingham, J. Manouchehri, P. Schnell, M. Sheth, J. J. David, M. Kassem, T. A. Wilson, H. S. Radomska, C. C. Coss, C. E. Bennett, R. K. Ganju, S. D. Sardesai, M. Lustberg, B. Ramaswamy, , M. A. Cherian

This study shows that selective ERβ agonists reduce viability of ER+ breast cancer cells and suggest their potential as a therapeutic strategy when combined with ER blockade.

bioRxiv · Jan 14, 2022Cancer Biology

Machine learning predicts rapid relapse of triple negative breast cancer

Y. Zhang, W. Nock, M. Wyse, Z. Weber, E. Adams, S. Stockard, D. Tallman, S. Asad, E. P. Winer, N. U. Lin, M. Cherian, M. Lustberg, B. Ramaswamy, S. Sardesai, J. Vandeusen, , D. G. Stover

The paper uses machine learning to predict rapid relapse of triple-negative breast cancer based on clinical and genomic features.

bioRxiv · Apr 21, 2019Cancer Biology