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From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.

Authors :
Chang H
Yang X
Moore J
Liu XP
Jen KY
Snijders AM
Ma L
Chou W
Corchado-Cobos R
García-Sancha N
Mendiburu-Eliçabe M
Pérez-Losada J
Barcellos-Hoff MH
Mao JH
Source :
Frontiers in oncology [Front Oncol] 2022 Feb 11; Vol. 11, pp. 819565. Date of Electronic Publication: 2022 Feb 11 (Print Publication: 2021).
Publication Year :
2022

Abstract

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53 -null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan-Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.<br />Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2022 Chang, Yang, Moore, Liu, Jen, Snijders, Ma, Chou, Corchado-Cobos, García-Sancha, Mendiburu-Eliçabe, Pérez-Losada, Barcellos-Hoff and Mao.)

Details

Language :
English
ISSN :
2234-943X
Volume :
11
Database :
MEDLINE
Journal :
Frontiers in oncology
Publication Type :
Academic Journal
Accession number :
35242697
Full Text :
https://doi.org/10.3389/fonc.2021.819565