Identification of blood protein biomarkers for breast cancer staging by integrative transcriptome and proteome analyses

Breast cancer is the most common malignancy for women. Accurate prediction of breast cancer and its pathological stages is important for treatment decision-making. Although many studies have focused on discovering circulating biomarkers of breast cancer, no such biomarkers have been reported for different stages of this disease. In this study, we identified blood protein biomarkers for each stage of breast cancer by analyzing transcriptome and proteome data from patients. Analysis of the TCGA transcriptome datasets revealed that a large number of genes were differentially expressed in tumor samples of each stage of breast cancer compared with adjacent normal tissues. Blood-secretory proteins encoded by these genes were then predicted by bioinformatics programs. Furthermore, iTRAQ-based proteomic analysis was conducted for plasma samples of breast cancer patients with different stages. A portion of predicted blood-secretory proteins could be detected and verified differentially expressed. Finally, several proteins were chosen as potential blood protein biomarkers for different stages of breast cancer due to their consistent expression patterns at both mRNA and protein levels. Overall, our data provide new insights into diagnosis and classification of breast cancer as well as selection of optimal treatments. We identified blood protein biomarkers for each stage of breast cancer by analyzing tissue-based transcriptome and blood-based proteome data from patients. To our knowledge, this is the first time to try to identify blood protein biomarkers for different stages of breast cancer via these integrative analyses. Our data may provide new insights into diagnosis and classification of breast cancer as well as selection of optimal treatment.