Abstract
Lung cancer is the most common malignant cancer worldwide. Targeted therapies have emerged as a promising treatment strategy for lung cancers. To evaluate the current landscape of targets and find promising targets for future new drug discovery for lung cancers, this research identified the science-technology-clinical development pattern and mapped the interaction network of targets. Targets for cancers were classified into 3 groups based on a paper published in Nature. We searched for scientific pieces of literature, patent documents and clinical trials of targets in Group 1 and Group 2 for lung cancers. Then, a target-target interaction network of Group 1 was constructed, and the science-technology-clinical (S-T-C) development patterns of targets in Group 1 were identified. Finally, based on the cluster distribution and the development pattern of targets in Group 1, interactions between the targets were employed to predict potential targets in Group 2 for drug development. The target-target interaction (TTI) network of group 1 resulted in 3 clusters with different developmental stages. The potential targets in Group 2 are divided into 3 ranks. Level-1 is the first priority and level-3 is the last. Level-1 includes 16 targets, such as STAT3, CRKL, and PTPN11, that are mostly involved in signaling transduction pathways. Level-2 and level-3 contain 8 and 6 targets, respectively, related to various biological functions. This study will provide references for drug development in lung cancers, emphasizing that priorities should be given to targets in Level-1, whose mechanisms are worth further exploration.
Published Version
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