Identification of breast cancer recurrence risk factors based on functional pathways in tumor and normal tissues.

Xiujie Chen,Yunfeng Wang,Lei Liu,Qiuqi Liu,Qing Jin,Mengjian Li,Hongbo Xie,Denan Zhang,Diheng Zeng,Bo Liu

doi:10.18632/oncotarget.11557

Abstract

The recurrence of breast cancer (BC) is a serious therapeutic problem, and the risk factors for recurrence urgently need to be identified. In this study, we examined the functional pathways in tumor and normal tissues to more comprehensively identify biomarkers for the risk of BC recurrence. We collected tumor and normal tissue gene expression profiles of recurrent BC patients and non-recurrent BC patients from the TCGA database.We derived an expression interval (mean ± 1.96SD) based on non-recurrent patients rather than a single value, such as a mean or median. If the expression of a gene was significantly different from its normal expression interval, it was considered a differentially expressed gene. Eight pathways that significantly distinguished recurrent and non-recurrent BC patients were obtained based on 65% accuracy, and these pathways were all associated with the immune response and sensitivity to drugs. The genes in these eight pathways were also used to analyze survival, and the significance level reached 0.003 in an independent dataset (p = 0.02 in tumor and p = 0.03 in normal tissue). Our results reveal that the integration of tumor and normal tissue functional analyses can comprehensively enhance the understanding of BC prognosis.

Highlights

Breast cancer (BC) is a highly heterogeneous disease with different clinical manifestations
We identified specific genes that were only altered in subgroups and likely reflect individual recurrence risk by participating in the mechanisms of recurrence
These genes may only be differentially expressed in small groups; changes in these genes are usually less significant when compared to the mean values of background data

Summary

Introduction

Breast cancer (BC) is a highly heterogeneous disease with different clinical manifestations. The early identification of precancerous normal tissue damage may provide better prognosis biomarkers [9, 10] To this end, Ye M and Herszényi L considered the difference and uniformity between the precancerous and cancer statuses.Activated leukocyte cell adhesion molecule (ALCAM) has been identified as a novel potential molecular marker of gastric cancer. Herszényi L found that proteolytic enzymes play a major role in colorectal cancer (CRC) invasion and metastasis and in the malignant transformation of precancerous lesions into cancer [12]. This finding indicates that the precancerous and cancer statuses may www.impactjournals.com/oncotarget share common mechanisms that may influence prognosis. The utility of these genes to predict prognosis was evaluated

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Conclusion