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

Journal Article · · Frontiers in Oncology
 [1];  [2];  [3];  [1];  [4];  [1];  [3];  [3];  [5];  [5];  [5];  [5];  [3];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nanjing Medical University (China)
  3. Univ. of California, San Francisco, CA (United States)
  4. Univ. of California, Davis, CA (United States)
  5. Universidad de Salamanca (Spain); Consejo Superior de Investigaciones Cientificas (CSIC), Salamanca (Spain)
+ Show Author Affiliations

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.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
National Cancer Institute (NCI); National Institutes of Health (NIH); USDOD
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1891477
Journal Information:
Frontiers in Oncology, Journal Name: Frontiers in Oncology Vol. 11; ISSN 2234-943X
Publisher:
Frontiers Research FoundationCopyright Statement
Country of Publication:
United States
Language:
English

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60 APPLIED LIFE SCIENCES
cellular morphometric biomarkers
cellular morphometric subtypes
human breast cancers
metastasis
mouse mammary tumor
overall survival (OS)
transfer learning