Author

B. Reardon

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 Approach:statistical model· 3 Research Focus:differential expression· 2 Assay:whole-exome sequencing· 2 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:clustering· 1 Approach:deep learning· 1

Frequent Co-Authors

J. Park· 3 shared D. Liu· 2 shared E. M. Van Allen· 2 shared R. Haq· 2 shared A. Cheung· 1 shared A. Giobbie-Hurder· 1 shared A. Imamovic· 1 shared A. Roesch· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersCancer Biology

J. Park

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3 papers

Recent·Most cited

Genomic heterogeneity and ploidy identify patients with intrinsic resistance to PD-1 blockade in metastatic melanoma

G. Tarantino, C. A. Ricker, A. Wang, W. Ge, T. J. Aprati, A. Y. Huang, S. Madha, J. Chen, Y. Shi, M. Glettig, D. T. Frederick, S. Freeman, M. M. Holovatska, M. P. Manos, L. Zimmer, , D. Liu

This study identifies genomic heterogeneity and ploidy as markers of intrinsic resistance to PD-1 blockade in metastatic melanoma, with a decision tree model predicting resistance with high confidence.

Science Advances · Nov 29, 2024Peer-reviewedCancer Biology

Somatic structural variants driving distinct modes of oncogenesis in melanoma

J. M. Conway, R. Gillani, J. Crowdis, B. Reardon, J. Park, S. Han, B. Titchen, M. Benamar, R. Haq, E. Van Allen

This study analyzes structural variants in melanoma subtypes, identifying distinct genomic properties and molecular drivers that may inform therapeutic strategies.

bioRxiv · Nov 1, 2023 · PreprintCancer Biology

Clinical interpretation of integrative molecular profiles to guide precision cancer medicine

B. Reardon, N. D. Moore, N. Moore, E. Kofman, S. Aldubayan, A. Cheung, J. Conway, H. Elmarakeby, A. Imamovic, S. C. Kamran, T. Keenan, D. Keliher, D. J. Konieczkowski, D. Liu, K. Mouw, , E. M. Van Allen

This paper introduces MOAlmanac, a clinical interpretation algorithm that integrates genomic and transcriptional data to improve precision cancer treatment decisions by considering second-order molecular features.

bioRxiv · Sep 22, 2020Cancer Biology