Study On Drug Synergistic Mechanism Of Mitoxantrone And Its Derivatives In Cancer Treatment

Cervical cancer treatment mainly uses drugs such as cisplatin,carboplatin,paclitaxel,fluorouracil and topotecan,but these drugs are prone to drug resistance and many toxic side effects in long-term use.So drug combination chemotherapy has become a trend in cervical cancer treatment in recent years.In the treatment of cervical cancer,drug combination can reduce drug resistance,expand the therapeutic range as well as reduce drug dose and toxicity compared with individual drugs.However,the current research in drug synergy is mainly based on clinical trial methods to screen for effective combinations of drugs.This method is resource intensive.So it becomes a novel strategy to obtain effective drug combinations by deep learning prediction.Therefore,predicting effective drug combinations by deep learning has become a novel strategy for drug combination.Meanwhile,activation of PI3K/Akt/mTOR signaling pathway promotes the occurrence of cervical cancer.and inhibition of PI3K/Akt/mTOR signaling pathway is a novel strategy for cervical cancer targeted therapy.The main research approach is to use the molecular fingerprints of drugs as input variables to build deep learning twin neural network models for the prediction of potentially effective combinations of anti-tumour drugs.Among the model prediction combinations in this paper,the combination of mitoxantrone(MIT)and fludarabine(FLU)scored 0.975,which was the highest scoring group,and therefore,this combination was selected for experimental validation in this paper.In this paper,we observed the effects of the combination of MIT and FLU on the proliferation and invasion of cervical cancer cells cultured in vitro,as well as analyzed the anti-tumor effects of the combination of MIT and FLU on tumor-bearing mice in vitro,by further validating the accuracy of our prediction results.The results of this paper showed that the combination of MIT and FLU could effectively inhibit cell growth,lead to G0/G1 phase cell cycle arrest and induce apoptosis.Western blot results showed that MIT mainly decreased the expression of phosphorylated PDK1 protein,FLU mainly inhibited the expression of phosphorylated PI3 K and PDK1 proteins,and the combination of the two inhibited the phosphorylated AKT protein The effect on phosphorylated AKT protein was very significant.This paper also confirmed that the combination of MIT and FLU effectively inhibited the growth of cervical cancer cell transplanted tumors in nude mice.The results of Ki67 staining of paraffin sections of tumor tissues showed that the ki67-positive nuclei in the tumor tissues of the combined treatment group were less than those of the drugs alone,and the combination of MIT and FLU significantly reduced Ki67 expression.The expression of phosphorylated AKT was detected by immunohistochemistry.The results showed that the AKT expression in the combination group was significantly lower than that in the single drug group,which was consistent with the Western blot results.These results confirmed that the drug target of the combination was AKT protein.The experiments demonstrated that MIT and FLU have strong drug synergistic effects,confirming the validity of our predicted results.We found that the combination of MIT and FLU was useful for predicting potentially effective combinations of antitumor drugs by building a deep learning twin neural network model,among which MIT and FLU were commonly used in clinical practice.In the cellular environment of human cervical cancer cell lines,the combination of MIT and FLU effectively and specifically blocked the PI3K/Akt/mTOR pathway.Deep learning is a novel strategy to predict the combination of antitumor drugs in combination.Meanwhile,the dual-blocking PI3K/Akt/mTOR pathway approach elucidated in this study is a promising combination drug strategy for the treatment of cervical cancer.