Background: Lung cancer is the most common malignant cancer worldwide. Targeted therapies have emerged as a promising treatment strategy for lung cancers.

Objective: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

背景：肺癌是全球最常见的恶性肿瘤。靶向治疗已成为一种很有前景的肺癌治疗策略。

目的：为了评估靶点的现状，为未来的肺癌新药发现寻找有希望的靶点，本研究确定了科学-技术-临床发展模式，并绘制了靶点相互作用网络。

方法：根据发表在《自然》杂志上的一篇论文，将癌症的靶标分为 3 组。我们检索了第 1 组和第 2 组肺癌靶点的科学文献、专利文件和临床试验。然后，构建了第1组靶点-靶点相互作用网络，确定了第1组靶点的科学-技术-临床（STC）发展模式。最后，根据第一组靶点的聚类分布和发展模式，利用靶点之间的相互作用来预测第二组药物开发的潜在靶点。

结果：第 1 组的目标-目标相互作用 (TTI) 网络产生了 3 个具有不同发展阶段的集群。第 2 组中的潜在目标分为 3 个等级。Level-1 是第一优先级，Level-3 是最后一个优先级。Level-1 包括 STAT3、CRKL 和 PTPN11 等 16 个靶点，主要参与信号转导通路。Level-2 和 level-3 分别包含 8 个和 6 个目标，与各种生物功能相关。

结论：本研究将为肺癌药物研发提供参考，强调优先关注Level-1的靶点，其作用机制值得进一步探索。