Treatment of advanced breast cancer with a combination of highly agglutinative staphylococcin and vinorelbine-based chemotherapy

OBJECTIVE

Breast cancer is the most frequently diagnosed cancer among women in over 75% of countries worldwide accounting for one in four of all cancers in women. Highly agglutinative staphylococcin (HAS), a mixture of Staphylococcus aureus culture filtrates, has been used clinically as an immunomodifier in the treatment of a number of tumors for many years. The aim of present study is to evaluate the therapeutic effects and safety of treating advanced breast cancer patients with a combined therapy of HAS and vinorelbine-based chemotherapy compared to patients who receive standard chemotherapy alone.

PATIENTS AND METHODS

A total of 62 patients with advanced breast cancer were divided into 2 study groups. One group received intravenous injections of HAS and vinorelbine-based chemotherapy (n=31) compared to a control group assigned to receive vinorelbine-based standard chemotherapy (n=31).

RESULTS

Patients with advanced breast cancer who received HAS combined therapy showed a significantly higher overall response rate (Complete Response + Partial Response) of 67.7% compared with patients who received systemic chemotherapy alone (51.6%; p < 0.05). Overall, the occurrence of adverse effects was not significantly different between study groups. HAS was able to remedy the immunosuppressing effects of standard chemotherapy in these patients.

CONCLUSIONS

Treatment of advanced breast cancer with of HAS - in combination with vinorelbine-based chemotherapy - was generally more effective and just as safe compared to treatment with vinorelbine-based standard chemotherapy alone.

VNP: Interactive Visual Network Pharmacology of Diseases, Targets, and Drugs

In drug discovery, promiscuous targets, multifactorial diseases, and "dirty" drugs construct complex network relationships. Network pharmacology description and analysis not only give a systems-level understanding of drug action and disease complexity but can also help to improve the efficiency of target selection and drug design. Visual network pharmacology (VNP) is developed to visualize network pharmacology of targets, diseases, and drugs with a graph network by using disease, target or drug names, chemical structures, or protein sequence. To our knowledge, VNP is the first free interactive VNP server that should be very helpful for systems pharmacology research. VNP is freely available at http://cadd.whu.edu.cn/ditad/vnpsearch.