Heat shock proteins create a signature to predict the clinical outcome in breast cancer.

Na bazie danych z TCGA zbudowano model predykcyjny, który przewiduje ryzyko śmierci spowodowanej przez nowotwór

Utilizing The Cancer Genome Atlas (TCGA) and KM plotter databases we identified six heat shock proteins associated with survival of breast cancer patients. The survival curves of samples with high and low expression of heat shock genes were compared by log-rank test (Mantel-Haenszel). Interestingly, patients overexpressing two identified HSPs - HSPA2 and DNAJC20 exhibited longer survival, whereas overexpression of other four HSPs - HSP90AA1, CCT1, CCT2, CCT6A resulted in unfavorable prognosis for breast cancer patients. We explored correlations between expression level of HSPs and clinicopathological features including tumor grade, tumor size, number of lymph nodes involved and hormone receptor status. Additionally, we identified a novel signature with the potential to serve as a prognostic model for breast cancer. Using univariate Cox regression analysis followed by multivariate Cox regression analysis, we built a risk score formula comprising prognostic HSPs (HSPA2, DNAJC20, HSP90AA1, CCT1, CCT2) and tumor stage to identify high-risk and low-risk cases. Finally, we analyzed the association of six prognostic HSP expression with survival of patients suffering from other types of cancer than breast cancer. We revealed that depending on cancer type, each of the six analyzed HSPs can act both as a positive, as well as a negative regulator of cancer development. Our study demonstrates a novel HSP signature for the outcome prediction of breast cancer patients and provides a new insight into ambiguous role of these proteins in cancer development.