Author

K. C. Anderson

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 Biochemistry· 1

Signature Assays, Organisms & Methods

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Research Focus:cancer & tumor microenvironment· 2 Approach:genetic perturbation / CRISPR· 2 Organism:human· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:clustering· 1 Approach:deep learning· 1

Frequent Co-Authors

M. Fulciniti· 2 shared M. K. Samur· 2 shared T. Hideshima· 2 shared A. Aktas-Samur· 1 shared A. Fullam· 1 shared A. Gulla· 1 shared A. Neri· 1 shared B. Rodriguez-Martin· 1 shared

Activity by Year

2018-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersCancer Biology

M. Fulciniti

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Cancer BiologybioRxivPreprintDec 8, 2021

Long Noncoding RNA RROL Provides Chromatin Scaffold for MYC-WDR82 Interaction to Impact Lipid Metabolism and Tumor Cell Growth in Multiple Myeloma

E. Morelli, M. Fulciniti, M. K. Samur…·N. C. Munshi

This study identifies RROL as a therapeutically actionable lncRNA in multiple myeloma that supports tumor growth through chromatin scaffolding of MYC-WDR82 interaction.

DOI 10.1101/2021.12.08.471297

humanbulk RNA-seq

𝕏 PostBluesky

BiochemistrybioRxivPreprintNov 30, 2021

Development of PRPK Directed Phthalimides

H.-S. Seo, T. Mizutani, T. Hideshima…·S. Dhe-Paganon

This paper develops PRPK-directed phthalimides based on pomalidomide, identifies a potent and selective PRPK binder, and highlights distinct binding mechanisms compared to cereblon.

DOI 10.1101/2021.11.30.469594

deep learningstatistical model

𝕏 PostBluesky

Cancer BiologybioRxivAug 12, 2018

Genomic landscape and chronological reconstruction of driver events in multiple myeloma

F. Maura, N. Bolli, N. Angelopoulos…·P. J. Campbell

This study reconstructs the genomic evolution of multiple myeloma by analyzing 67 genomes from 30 patients and public datasets, identifying 7 subgroups defined by distinct driver mutations and chronological patterns of genomic events.

DOI 10.1038/s41467-019-11680-1

humanwhole-genome sequencing

𝕏 PostBluesky