Abstract
In current study, a bioinformatic-based network pharmacology was used to identify the osteosarcoma (OGS)-pathological targets and formononetin (FN)-treated targets before the main core predictive biotargets were screened. In addition, all core targets were selected through a number of bioinformatic databases, followed by identification of predominant biological processes and signalling pathways of FN anti-OGS. Further, top three core targets of FN anti-OGS were determined as oestrogen receptor 1 (ESR1), tumour protein p53 (TP53), receptor tyrosine-protein kinase erbB-2 (ERBB2) respectively. In clinical biochemical data, the plasma samples of OGS showed the increased trends of alkaline phosphatase, triglyceride, blood glucose, lactate dehydrogenase, high-sensitive C-reactive protein and some immune cell counts when referenced to medical criteria. In clinicopathological examination, histological OGS sections resulted in increased positive cell counts of neoplastic ESR1, TP53, ERBB2. To further validate these corn proteins in experimental study in vivo, FN-treated tumour-bearing nude mice showed intracellular reductions of ESR1, TP53, ERBB2 positive expressions, accompanied with visibly reduced tumour weights. Collectively, our bioinformatic and experimental findings disclosed main core targets, biological processes and signalling pathways of FN anti-OGS. Interestingly, the top core targets were representatively validated following FN treatment in vivo. Therefore, we reasoned that these predictive targets might be the potential biomarkers for screening and treating osteosarcoma.