@article {331,
	title = {Distinct Clinical Impact and Biological Function of Angiopoietin and Angiopoietin-like Proteins in Human Breast Cancer.},
	journal = {Cells},
	volume = {10},
	year = {2021},
	month = {2021 09 29},
	abstract = {<p>Secreted angiopoietin/angiopoietin-like (/) proteins are involved in many biological processes. However, the role of these proteins in human breast cancers (BCs) remains largely unclear. Here, we conducted integrated omics analyses to evaluate the clinical impact of / proteins and to elucidate their biological functions. In BCs, we identified rare mutations in / genes, frequent gains of , , and , and frequent losses of , , and , but observed that , , and were robustly downregulated in multiple datasets. The expression levels of , , and were positively correlated with overall survival (OS), while the expression levels of were negatively correlated with OS. Additionally, the expression levels of and were positively correlated with distant metastasis-free survival (DMFS), while the expression levels of and were negatively correlated with DMFS. The prognostic impacts of / genes depended on the molecular subtypes and on clinical factors. We discovered that various / genes were co-expressed with various genes involved in different pathways. Finally, with the exception of , the remaining genes showed significant correlations with cancer-associated fibroblasts, endothelial cells, and microenvironment score, whereas only was significantly correlated with immune score. Our findings provide strong evidence for the distinct clinical impact and biological function of / proteins, but the question of whether some of them could be potential therapeutic targets still needs further investigation in BCs.</p>
},
	keywords = {Angiopoietin-like Proteins, Angiopoietins, Breast Neoplasms, Female, Humans, Prognosis},
	issn = {2073-4409},
	doi = {10.3390/cells10102590},
	author = {Yang, Hui and Zhang, Melody and Mao, Xuan-Yu and Chang, Hang and Perez-Losada, Jesus and Mao, Jian-Hua}
}
@article {323,
	title = {From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.},
	journal = {Front Oncol},
	volume = {11},
	year = {2021},
	month = {2021},
	pages = {819565},
	abstract = {<p>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\&amp;E) micrographs of orthotopic -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 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\&amp;E preparations can provide unbiased biological stratification to inform patient care.</p>
},
	issn = {2234-943X},
	doi = {10.3389/fonc.2021.819565},
	author = {Chang, Hang and Yang, Xu and Moore, Jade and Liu, Xiao-Ping and Jen, Kuang-Yu and Snijders, Antoine M and Ma, Lin and Chou, William and Corchado-Cobos, Roberto and Garc{\'\i}a-Sancha, Natalia and Mendiburu-Eli{\c c}abe, Marina and Perez-Losada, Jesus and Barcellos-Hoff, Mary Helen and Mao, Jian-Hua}
}
