Author

D. Hirsch

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 Immunology· 1

Signature Assays, Organisms & Methods

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Organism:human· 4 Assay:bulk RNA-seq· 2 Approach:deep learning· 2 Approach:statistical model· 2 Research Focus:cell signaling & trafficking· 1 Research Focus:cell-cell communication· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:differential expression· 1

Frequent Co-Authors

D. Bronder· 2 shared D. Wangsa· 2 shared K. Heselmeyer-Haddad· 2 shared T. Ried· 2 shared A. B. Riemer· 1 shared A. C. Greenwald· 1 shared A. Lischka· 1 shared A. Nussenzweig· 1 shared

Activity by Year

2019-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersCancer Biology

D. Bronder

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Integrative spatial analysis reveals a multi-layered organization of glioblastoma

A. C. Greenwald, N. G. Darnell, R. Hoefflin, D. Simkin, L. N. Gonzalez-Castro, C. Mount, D. Hirsch, M. Nomura, T. Talpir, M. Kedmi, I. Goliand, G. Medici, B. Li, H. Keren-Shaul, M. Weller, , I. Tirosh

This study uses spatial transcriptomics and proteomics to reveal three modes of cellular organization in glioblastoma, with hypoxia driving a 5-layered global architecture.

bioRxiv · Jul 6, 2023Cancer Biology

TP53 loss initiates chromosomal instability in high-grade serous ovarian cancer

D. Bronder, D. Wangsa, D. Zong, T. J. Meyer, R. Wardenaar, P. Minshall, A. Tighe, D. Hirsch, K. Heselmeyer-Haddad, L. Nelson, D. Spierings, J. C. McGrail, M. Cam, A. Nussenzweig, F. Foijer, , S. S. Taylor

This study shows that TP53 loss in fallopian tube epithelial cells drives chromosomal instability through cell cycle deregulation, without requiring additional mutations.

bioRxiv · Mar 12, 2021Cancer Biology

High-throughput prediction of MHC Class I and Class II neoantigens with MHCnuggets

X. M. Shao, R. Bhattacharya, J. Huang, I. K. A. Sivakumar, C. Tokheim, L. Zheng, D. HIrsch, B. Kaminow, A. Omdahl, M. Bonsack, A. B. Riemer, V. Velculescu, V. Anagnostou, K. Pagel, R. Karchin

The paper introduces MHCnuggets, a deep learning method for predicting MHC class I and II neoantigen binding, showing improved performance and scalability across 26 cancer types.

bioRxiv · Oct 4, 2019Immunology

Cancer-type specific aneuploidies hard-wire chromosome-wide gene expression patterns of their tissue of origin

N. Auslander, K. Heselmeyer-Haddad, S. Patkar, D. Hirsch, J. Camps, M. Brown, D. Bronder, W.-D. Chen, R. Lokanga, D. Wangsa, D. Wangsa, Y. Hu, A. Lischka, R. Braun, G. Emons, , t. ried

The paper shows cancer-type specific aneuploidies correlate with normal tissue gene expression patterns, suggesting they hard-wire chromosome-wide expression levels to support tumorigenesis.

bioRxiv · Mar 1, 2019Cancer Biology