Author

M. W. Hurd

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Cancer Biology· 3

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Research Focus:differential expression· 3 Organism:human· 3 Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Research Focus:gene regulatory network inference· 2 Organism:mouse· 2 Assay:spatial transcriptomics· 2 Assay:bulk RNA-seq· 1

Frequent Co-Authors

A. Maitra· 3 shared K. I. Rajapakshe· 3 shared P. A. Guerrero· 3 shared C. M. Schmidt· 2 shared F. I. Thege· 2 shared J. Min· 2 shared M. P. Kim· 2 shared M. Sans· 2 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersCancer Biology

A. Maitra

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Author profile →

3 papers

Recent·Most cited

Integrated spatial transcriptomics and lipidomics of precursor lesions of pancreatic cancer identifies enrichment of long chain sulfatide biosynthesis as an early metabolic alteration

M. Sans, Y. Chen, F. I. Thege, R. Dou, J. Min, M. Yip-Schneider, J. Zhang, R. Wu, E. Irajizad, Y. Makino, K. I. Rajapakshe, M. W. Hurd, R. A. Leon, J. Vykoukal, J. B. Dennison, , J. F. Fahrmann

bioRxiv · Aug 14, 2023 · PreprintCancer Biology

Spatial Transcriptomics of Intraductal Papillary Mucinous Neoplasms of The Pancreas Identifies NKX6-2 as a Driver of Gastric Differentiation and Indolent Biological Potential

M. Sans, Y. Makino, J. Min, K. I. Rajapakshe, M. Yip-Schneider, C. M. Schmidt, M. W. Hurd, J. K. Burks, J. A. Gomez, F. I. Thege, J. Fahrmann, R. A. Wolff, M. P. Kim, P. A. Guerrero, A. Maitra

This study identifies NKX6-2 as a driver of gastric differentiation in IPMNs, linking its expression to indolent biological potential and progression.

Cancer Discovery · Jun 7, 2023Peer-reviewedCancer Biology

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype

V. Bahrambeigi, J. J. Lee, V. Branchi, J. T. Henry, K. I. Rajapakshe, B. M. Stephens, S. Dhebat, M. W. Hurd, R. Sun, P. Yang, W. Wang, S. E. Kopetz, A. Maitra, P. A. Guerrero, Z. Xu, , E. Ruppin

This study uses deep learning on plasma extracellular vesicle RNA to predict cancer subtypes, monitor treatment effects, and identify gene fusions and neoepitopes without tissue sampling.

bioRxiv · Oct 27, 2022Cancer Biology