Data Mining-Based and Network Pharmacology-Based Analysis of Medication Rules and Action Mechanism of Professor Zhou Zhongying in Lung Cancer Treatment

Objective. To investigate the medication rules and mechanism of Chinese medicine for lung cancer treated by professor Zhou Zhongying. Methods. Medical records of lung cancer patients treated by Professor Zhou were obtained and analyzed by data mining methods to arrive at the core herb combination. The relevant techniques of network pharmacology were applied to obtain the effective compounds, targets and signal pathways of the herb combination. Results. A total of 457 prescriptions were selected, involving 279 herbs. The high-frequency core herbs for lung cancer treatment were Glehniae Radix (Beishashen), Cremastrae Pseudobulbus (Shancigu), Ophiopogonis Radix (Maidong), Adenophprae Radix (Nanshashen). Through association rules and cluster analysis, the core prescriptions of 4 herbs were obtained. The four herbs were screened to obtain 19 active ingredients, and 193 potential targets were related to lung cancer treatment. Core herb combination perform its function for lung cancer by regulating the targets, such as AKT1, VEGFA, IL6, MAPK3, HIV-1A, TP53.The GO analysis results showed that a total of 285 GO entries were obtained, involving inflammatory response, and apoptotic process. The KEGG analysis was involved 113 terms, which showed that the targets of core prescription for lung cancer treatment mainly focused on PI3K-Akt, MAPK, MicroRNAs in cancer, HIF-1signaling pathway, and HTLV-1 infection signaling pathways. Conclusion. This study obtained the core prescription of professor Zhou in treatment of lung cancer by data mining techniques and explored the action mechanisms of the core herb combination by network pharmacology. This article reveals the core herb combination make effects through multicomponent, multi-target, and multi-pathway, and provides reference for clinical related research.