Plasma HSP90AA1 Predicts the Risk of Breast Cancer Onset and Distant Metastasis - Liu, Haizhou; Zhang, Zihan; Huang, Yi; Wei, Wene; Ning, Shufang; Li, Jilin; Liang, Xinqiang; Liu, Kaisheng; Zhang, Litu (Frontiers in Cell and Developmental Biology, 2021)
AIM: We aimed to develop and validate a comprehensive nomogram containing pre-treatment plasma HSP90AA1 to predict the risk of breast cancer onset and metastasis. METHODS: We assessed the expression of HSP90s in breast cancer patients using an online database. To verify the results, 677 patients diagnosed with breast cancer and 146 patients with benign breast disease between 2014 and 2019 were selected from our hospital and were divided into cancer risk and metastasis risk cohorts. We focused on HSP90AA1 to elucidate the risks of onset and metastasis in the cohorts. RESULTS: Expression levels of HSP90AA1, HSP90AA2, HSP90AB1, HSP90B1, and TRAP1 were linked to disease progression. Survival analysis using the GEPIA and OncoLnc databases indicated that the upregulation of HSP90AA1 and HSP90AB1 was related to poor overall survival. In the cancer risk cohort, carcinoembryonic antigen (CEA), carbohydrate antigen 153 (CA153), HSP90AA1, T cells %, natural killer cells %, B cells %, neutrophil count, monocyte count, and d-dimer were incorporated into the nomogram. A high Harrell's concordance index (C-index) value of 0.771(95% confidence interval [CI], 0.725–0.817) could still be reached in the interval validation. In the metastasis risk cohort, predictors contained in the prediction nomogram included the use of CEA, CA153, HSP90AA1, carbohydrate antigen 125 (CA125), natural killer cells %, B cells%, platelet count, monocyte count, and d-dimer. The C-index was 0.844 (95% CI, 0.801–0.887) and it was well-calibrated. HSP90AA1 raised net clinical benefit of breast cancer onset and metastasis risk prediction nomogram in a range of risk thresholds (5% to 92%) and (1% to 90%). CONCLUSIONS: Our study revealed that pretreatment plasma HSP90AA1 combined with other markers could conveniently predict the risk of breast cancer onset and metastasis.