Xueyan Zhang1, Yingnan Cui2, Miao He3, Yan Jiao4, Zhaoying Yang2. 1. School of Nursing, Jilin University, Changchun, China. 2. Department of Breast Surgery, China-Japan Union Hospital of Jilin University, Changchun, China. 3. Department of Anesthesia, The Second Hospital of Jilin University, Changchun, China. 4. Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Changchun, China.
Abstract
PURPOSE: LCN1 (lipocalin-1), a gene that encodes tear lipocalin (or von Ebner's gland protein), is mainly expressed in secretory glands and tissues, such as the lachrymal and lingual gland, and nasal, mammary, and tracheobronchial mucosae. Analysis of the Cancer Genome Atlas (TCGA) Breast Carcinoma (BRCA) level 3 data revealed a relationship between LCN1 expression and survival in breast cancer patients. METHODS: The χ2 test and Fisher exact test were applied to analyze the clinical data and RNA sequencing expression data, and the association between LCN1 expression and clinicopathologic features was determined. The receiver-operating characteristic (ROC) curve of LCN1 was drawn to assess its ability as a diagnostic marker, and the optimal cutoff value was obtained from the ROC curve to distinguish groups with high and low LCN1 expression. Cox regression was used to compare both groups, and a log-rank test was applied to calculate p values and compare the -Kaplan-Meier curves. Furthermore, GEO datasets were employed for external data validation. RESULTS: Analysis of 1,104 breast cancer patients with a primary tumor revealed that LCN1 was overexpressed in breast cancer. High LCN1 expression was associated with clinicopathologic features and poor survival. Analyzing the area under the ROC curve (AUC) of LCN1, it was found that its diagnostic ability was limited. Multivariate analysis indicated that LCN1 expression is an independent predictor of survival in breast cancer patients. Through validation in GEO datasets, LCN1 expression was higher in tumor than normal tissue of the breast. High LCN1 expression was associated with poor survival in breast cancer patients. CONCLUSIONS: High LCN1 expression is an independent prognosticator of a poor prognosis in breast cancer.
PURPOSE: LCN1 (lipocalin-1), a gene that encodes tear lipocalin (or von Ebner's gland protein), is mainly expressed in secretory glands and tissues, such as the lachrymal and lingual gland, and nasal, mammary, and tracheobronchial mucosae. Analysis of the Cancer Genome Atlas (TCGA) Breast Carcinoma (BRCA) level 3 data revealed a relationship between LCN1 expression and survival in breast cancer patients. METHODS: The χ2 test and Fisher exact test were applied to analyze the clinical data and RNA sequencing expression data, and the association between LCN1 expression and clinicopathologic features was determined. The receiver-operating characteristic (ROC) curve of LCN1 was drawn to assess its ability as a diagnostic marker, and the optimal cutoff value was obtained from the ROC curve to distinguish groups with high and low LCN1 expression. Cox regression was used to compare both groups, and a log-rank test was applied to calculate p values and compare the -Kaplan-Meier curves. Furthermore, GEO datasets were employed for external data validation. RESULTS: Analysis of 1,104 breast cancer patients with a primary tumor revealed that LCN1 was overexpressed in breast cancer. High LCN1 expression was associated with clinicopathologic features and poor survival. Analyzing the area under the ROC curve (AUC) of LCN1, it was found that its diagnostic ability was limited. Multivariate analysis indicated that LCN1 expression is an independent predictor of survival in breast cancer patients. Through validation in GEO datasets, LCN1 expression was higher in tumor than normal tissue of the breast. High LCN1 expression was associated with poor survival in breast cancer patients. CONCLUSIONS: High LCN1 expression is an independent prognosticator of a poor prognosis in breast cancer.
Authors: Benjamin L Nicholas; Paul Skipp; Sheila Barton; Dave Singh; Dinesh Bagmane; Richard Mould; Gilbert Angco; Jon Ward; Binita Guha-Niyogi; Susan Wilson; Peter Howarth; Donna E Davies; Stephen Rennard; C David O'Connor; Ratko Djukanovic Journal: Am J Respir Crit Care Med Date: 2010-01-28 Impact factor: 21.405
Authors: Ana M Gutiérrez; Ana Montes; Cándido Gutiérrez-Panizo; Pablo Fuentes; Ernesto De La Cruz-Sánchez Journal: J Proteomics Date: 2017-12-01 Impact factor: 4.044