Author

Aaron E. Atkinson

Huntsman Cancer InstituteORCID 0000-0002-0082-3280Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:bulk RNA-seq· 3 Organism:human· 3 Research Focus:cancer & tumor microenvironment· 2 Approach:experimental assay· 2 Assay:ATAC-seq· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

David Austin NixiD· 2 shared David Henry LumiD· 2 shared Adanma AyanambakkamiD· 1 shared Alana L. WelmiD· 1 shared Bing FengiD· 1 shared Bradley Robert CairnsiD· 1 shared Bryan E. WelmiD· 1 shared Casey SedermaniD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersCancer Biology

David Austin NixORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

SWI/SNF Alterations Define a Chromatin-Dependent Subtype of Urothelial Carcinoma

Bing Feng, Kaniz Fatema, David Austin Nix, Aaron E. Atkinson, Constance Caparas, Chris Stubben, David Henry Lum, Timothy J. Parnell, Courtney Carroll, G. Daniel Grass, Laura Graham, Eric A. Singer, Kenneth Gerard Nepple, Zarko Manojlovic, ERIC C. KAUFFMAN, , Sumati V. Gupta

This paper identifies a chromatin-altered subtype of urothelial carcinoma defined by SWI/SNF alterations, showing it is sensitive to HDAC inhibition and immunotherapy.

bioRxiv · Aug 6, 2026 · PreprintCancer Biology

A precision oncology-focused deep learning framework for personalized selection of cancer therapy

Casey Sederman, Chieh‐Hsiang Yang, Emilio Cortes-Sanchez, Tonya DiSera, Xiaomeng Huang, Sandra D. Scherer, Ling Zhao, Zhengtao Chu, Eliza R. White, Aaron E. Atkinson, Jadon Wagstaff, Katherine Elena Varley, Michael T. Lewis, Yi Qiao, Bryan E. Welm, , Gábor Marth

This paper introduces ScreenDL, a deep learning model that predicts effective cancer therapies using tumor omic and drug screening data, outperforming existing methods in preclinical trials.

bioRxiv · Dec 12, 2024 · PreprintCancer Biology

Zinc Alpha-2-Glycoprotein (ZAG/AZGP1) secreted by triple-negative breast cancer promotes tumor microenvironment fibrosis.

Surbhi Verma, Stephanie Dudics Giagnocavo, Meghan C. Curtin, Menusha Arumugam, Sandra M. Osburn-Staker, Guoying Wang, Aaron E. Atkinson, David Austin Nix, David Henry Lum, James Eric Cox, Keren I. Hilgendorf

This study identifies ZAG/AZGP1 as a secreted factor from triple-negative breast cancer cells that promotes fibrosis in the tumor microenvironment and is linked to poor patient prognosis.

Cancer Research Communications · Jun 18, 2024Peer-reviewedCancer Biology