Author

Katelyn Smith

UPMC Hillman Cancer Center

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

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:cell type annotation· 2 Research Focus:cell-cell communication· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Approach:experimental assay· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Aatur Dilip SinghiiD· 2 shared Brian Robert IsettiD· 2 shared Carl Kim· 2 shared Carly ReederiD· 2 shared Dan Paul ZandbergiD· 2 shared Heath Devin SkinneriD· 2 shared Jason J. LukeiD· 2 shared Krishna Beer SinghiD· 2 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersCancer Biology

Aatur Dilip SinghiORCID

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3 papers

Recent·Most cited

Integrative multi-omic analysis identifies tumor-intrinsic p38 as a driver of immune exclusion in human epithelial cancers

Rebekah Dadey, Krishna Beer Singh, Rose Doerfler, Riley Santiago, Brian Robert Isett, Christopher Deitrick, Carl Kim, Sarah Newman, Marion Joy, Katelyn Smith, Carly Reeder, Armando P. Signore, Ernest Michael Meyer, Tullia Carmela Bruno, Aditi Kulkarni, , Riyue Bao

This study identifies tumor-intrinsic p38 activation as a driver of immune exclusion in epithelial cancers and suggests it as a therapeutic target to overcome immunotherapy resistance.

bioRxiv · Jun 16, 2026 · PreprintCancer Biology

High-Sensitive Spatial Proteomics for Pancreatic Cancer Progression Analysis

Jongmin Jacob Woo, Zhenyu Sun, Yingwei Hu, Trung Hoàng, Christine Worthington, Katelyn Smith, Aatur Dilip Singhi, Randall E. Brand, Daniel W. Chan, Qing Kay Li, Ralph H. Hruban, Hui Zhang

This study develops a high-sensitivity spatial proteomics method, SP-Max, to analyze protein expression changes in pancreatic tissues from normal to cancerous states.

Analytical Chemistry · Feb 18, 2026Peer-reviewedCancer Biology

Integrating Artificial Intelligence-Driven Digital Pathology and Genomics to Establish Patient-Derived Organoids as a Novel Alternative Model for Drug Response in Head and Neck Cancer

Rose Doerfler, Jie Chen, Carl Kim, Joshua D. Smith, Micah K. Harris, Krishna Beer Singh, Brian Robert Isett, Rebekah Dadey, Daniel D. Brown, Adrian V. Lee, Xuefeng Wang, Matthew E. Spector, Seungwon Kim, Shaum Sridharan, Kevin J. Contrera, , Riyue Bao

This study establishes patient-derived organoids (PDOs) for HNSCC drug response testing, integrating AI-driven histopathology and multi-omics analysis to create a scalable preclinical model.

bioRxiv · Jun 24, 2025 · PreprintCancer Biology