Author

S. A. Stopka

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· 5 Biochemistry· 1

Signature Assays, Organisms & Methods

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Organism:mouse· 4 Research Focus:drug response / drug discovery· 3 Approach:experimental assay· 3 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Organism:human· 2 Research Focus:cancer & tumor microenvironment· 1

Frequent Co-Authors

K. L. Ligon· 2 shared M. R. Savani· 2 shared M. S. Regan· 2 shared N. Agar· 2 shared N. Y. R. Agar· 2 shared Q.-D. Nguyen· 2 shared A. C. Wang· 1 shared A. Chimento· 1 shared

Activity by Year

2021-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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2 shared papersCancer Biology

K. L. Ligon

Mutual co-authors in cluster

Author profile →

6 papers

Recent·Most cited

Ketogenic diet as a metabolic vehicle for enhancing the therapeutic efficacy of mebendazole and devimistat in preclinical high-grade gliomas grown in juvenile mice

P. Mukherjee, J. Maurer, S. A. Stopka, B. Greenwood, J. J. A. Henao, S. Karmacharya, A. Chimento, N. Ta, D. C. Lee, T. Duraj, R. T. Bronson, M. A. Kiebish, T. N. Seyfried

This study shows that combining a ketogenic diet with mebendazole or devimistat improves therapeutic outcomes in preclinical high-grade glioma models in juvenile mice.

bioRxiv · Jun 9, 2023 · PreprintCancer Biology

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images

M. I. U. Haque, D. Mukherjee, S. A. Stopka, N. Agar, J. Hinkle, O. Ovchinnikova

This paper develops a deep learning system that combines H&E staining and MALDI imaging to predict prostate cancer from tissue images with 80% accuracy.

bioRxiv · May 11, 2022Cancer Biology

Single Cell Spatial Analysis Reveals the Topology of Immunomodulatory Purinergic Signaling in Glioblastoma

S. Coy, S. Wang, S. A. Stopka, J.-R. Lin, R. Rashid, C. Yapp, C. C. Ritch, P. Khadka, M. Regan, J. Hwang, P. Y. Wen, P. Bandopadhayay, K. L. Ligon, N. Y. Agar, P. K. Sorger, , S. Santagata

The paper uses spatial single-cell analysis to show that CD73 and CD39 expression in glioblastoma correlates with poor clinical outcomes and immunosuppressive signaling.

bioRxiv · Jan 12, 2022Cancer Biology

Characterization of metabolic compartmentalization in the liver using spatially resolved metabolomics

J. van der Reest, S. A. Stopka, W. M. Abdelmoula, D. F. Ruiz, S. Joshi, A. Ringel, M. C. Haigis, N. Y. R. Agar

This study uses spatially resolved metabolomics to characterize metabolic compartmentalization in the liver and shows how nutrient stress disrupts this organization.

bioRxiv · Dec 13, 2021 · PreprintBiochemistry

De Novo Pyrimidine Synthesis is a Targetable Vulnerability in IDH Mutant Glioma

D. D. Shi, M. R. Savani, M. M. Levitt, A. C. Wang, J. E. Endress, C. E. Bird, J. Buehler, S. A. Stopka, M. S. Regan, Y.-F. Lin, W. Gao, J. Khanal, M. Xu, B. Huang, R. B. Jennings, , McBray

This study identifies de novo pyrimidine synthesis as a therapeutic target in IDH mutant gliomas, showing that DHODH inhibitors are effective in preclinical models.

bioRxiv · Nov 30, 2021Cancer Biology

A druggable addiction to de novo pyrimidine biosynthesis in diffuse midline glioma

S. PAL, J. P. Kaplan, H. Nguyen, S. A. Stopka, M. R. Savani, M. S. Regan, Q.-D. Nguyen, K. L. Jones, L. A. Moreau, J. Peng, M. G. Dipiazza, A. Perciaccante, X. Zhu, B. Hunsel, K. X. Liu, , D. Haas-Kogan

This paper identifies a druggable metabolic vulnerability in diffuse midline glioma through a CRISPR screen, showing that inhibition of DHODH reduces pyrimidine biosynthesis and extends survival in mouse models.

bioRxiv · Nov 30, 2021Cancer Biology