A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer

Mohamed Amgad, James M. Hodge, Maha A.T. Elsebaie, Clara Bodelon, Samantha Puvanesarajah, David A. Gutman, Kalliopi P. Siziopikou, Jeffery A. Goldstein, Mia M. Gaudet, Lauren R. Teras, Lee A.D. Cooper*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists grade the microscopic appearance of breast tissue using the Nottingham criteria, which are qualitative and do not account for noncancerous elements within the tumor microenvironment. Here we present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast tumor microenvironment morphology. HiPS uses deep learning to accurately map cellular and tissue structures to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study-II and validated using data from three independent cohorts, including the Prostate, Lung, Colorectal, and Ovarian Cancer trial, Cancer Prevention Study-3, and The Cancer Genome Atlas. HiPS consistently outperformed pathologists in predicting survival outcomes, independent of tumor–node–metastasis stage and pertinent variables. This was largely driven by stromal and immune features. In conclusion, HiPS is a robustly validated biomarker to support pathologists and improve patient prognosis.

Original languageEnglish (US)
Pages (from-to)85-97
Number of pages13
JournalNature Medicine
Volume30
Issue number1
DOIs
StatePublished - Jan 2024

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology

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