Cross-Modality Learning for Predicting Immunohistochemistry Biomarkers from Hematoxylin and Eosin-Stained Whole Slide Images.

Amit Das¹, Naofumi Tomita², Kyle J Syme³, Weijie Ma³, Paige O'Connor³, Kristin N Corbett³, Bing Ren³, Xiaoying Liu³, Saeed Hassanpour⁴

¹Department of Computer Science, Dartmouth College, Hanover, New Hampshire.

²Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.

³Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.

⁴Department of Computer Science, Dartmouth College, Hanover, New Hampshire; Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire. Electronic address: saeed.hassanpour@dartmouth.edu.

PubMed PMC DOI PDF

Abstract

Hematoxylin and eosin (H&E) staining is a cornerstone of pathologic analysis, offering reliable visualization of cellular morphology and tissue architecture for cancer diagnosis, subtyping, and grading. Immunohistochemistry (IHC) staining provides insights by detecting specific proteins within tissues, enhancing diagnostic accuracy, and improving treatment planning. However, IHC staining is costly…

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NIH Funding

Grant #10475120
Clinicopathologic and Genetic Profiling through Machine Learning and Natural Language Processing for Precision Lung Cancer Management
DARTMOUTH COLLEGE
$367,647 (FY2022)
Grant #11331979
Advancing Digital Pathology through Novel Machine Learning Methodologies
DARTMOUTH COLLEGE
$591,896 (FY2026)
Grant #10316231
Improving Colorectal Cancer Screening and Risk Assessment through Deep Learning on Medical Images and Records
DARTMOUTH COLLEGE
$356,700 (FY2022)

Other Funding

NCI NIH HHS(R01 CA249758)
United States
NLM NIH HHS(R01 LM012837)
United States
NLM NIH HHS(R01 LM013833)
United States

MeSH Terms

Humans0Immunohistochemistry*Hematoxylin*Eosine Yellowish-(YS)*Biomarkers, Tumor*Staining and Labeling0Deep Learning*Lung Neoplasms0

Article Info

PMID: 40946794
PMCID: PMC12799405
DOI: 10.1016/j.ajpath.2025.08.014
Received: June 13, 2025
Accepted: August 19, 2025

How to Cite

Das A et al. Cross-Modality Learning for Predicting Immunohistochemistry Biomarkers from Hematoxylin and Eosin-Stained Whole Slide Images. Am J Pathol2025;195(12):2400-2410. doi:10.1016/j.ajpath.2025.08.014

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