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Título: | Table_8_From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.xlsx [Dataset] |
Autor: | Chang, Hang; Yang, Xu; Moore, Jade; Liu, Xiao-Ping; Jen, Kuang-Yu; Snijders, Antoine M.; Ma, Lin; Chou, William; Corchado Cobos, Roberto CSIC ORCID; García-Sancha, Natalia CSIC ORCID; Mendiburu-Eliçabe, Marina CSIC ORCID; Pérez-Losada, J. CSIC ORCID ; Barcellos-Hoff, Mary Helen; Mao, Jian-Hua | Palabras clave: | Mouse mammary tumor Metastasis Human breast cancers Transfer learning Cellular morphometric biomarkers Cellular morphometric subtypes Overall survival (OS) |
Fecha de publicación: | 15-feb-2022 | Editor: | Figshare | Citación: | Chang, Hang; Yang, Xu; Moore, Jade; Liu, Xiao-Ping; Jen, Kuang-Yu; Snijders, Antoine M.; Ma, Lin; Chou, William; Corchado Cobos, Roberto; García-Sancha, Natalia; Mendiburu-Eliçabe, Marina; Pérez-Losada, J.; Barcellos-Hoff, Mary Helen; Mao, Jian-Hua; 2022; Table_8_From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.xlsx [Dataset]; Figshare; https://doi.org/10.3389/fonc.2021.819565.s012 | Resumen: | 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. | Descripción: | Supplementary Table 8. Gene ontology (GO) functional enrichment analysis of the differentially expressed genes (DEGs) for biological processes. | Versión del editor: | https://doi.org/10.3389/fonc.2021.819565.s012 | URI: | http://hdl.handle.net/10261/328258 | DOI: | 10.3389/fonc.2021.819565.s012 | Referencias: | Chang, Hang; Yang, Xu; Moore, Jade; Liu, Xiao-Ping; Jen, Kuang-Yu; Snijders, Antoine M.; Ma, Lin; Chou, William; Corchado Cobos, Roberto; García-Sancha, Natalia; Mendiburu-Eliçabe, Marina; Pérez-Losada, J.; Barcellos-Hoff, Mary Helen; Mao, Jian-Hua. From mouse to human: cellular morphometric subtype learned from mouse mammary tumors provides prognostic value in human breast cancer. http://dx.doi.org/10.3389/fonc.2021.819565. http://hdl.handle.net/10261/282866 |
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Fichero | Descripción | Tamaño | Formato | |
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Table_8_From Mouse to Human_.xlsx | 146,61 kB | Microsoft Excel XML | Visualizar/Abrir | |
README_Table_8_From Mouse to Human.txt | 3,85 kB | Text | Visualizar/Abrir |
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