The interactions of microRNAs (miRNAs), transcription factors (TFs) and their common target long non-coding RNAs (lncRNAs) can lead to the production of TF-miRNA-lncRNA (TML) network motifs. These motifs are functional regulators that perform a wide range of biological processes, such as carcinogenesis. However, TML network motifs have not been systematically identified, and their roles in lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) are largely unknown. In the present study, a computational integration approach was performed using multiple sources in order to construct a global TML network for LUAD and LUSC. The analysis revealed several dysregulated TML network motifs, which were common between the two lung cancer subtypes or specific to a single cancer subtype. In addition, functional analysis further indicated that the TML network motifs may potentially serve as putative biomarkers in LUAD and LUSC. The associations between drug treatments and dysregulated TML network motifs were also examined. Collectively, the present study elucidated the roles of TML network motifs in LUAD and LUSC, which may be beneficial for understanding the pathogenesis of lung cancer and its potential treatment.