Background: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer (LC). However, the early-stage diagnostic rate is still low, and the 5-year overall survival (OS) rate remains poor. The present study aimed to identify critical genes as diagnostic and prognostic markers and small-molecule drugs for combating LUAD using a systematic bioinformatics analysis. Methods: Five gene expression profiling datasets were systematically integrated and analyzed. First, gene coexpression modules were identified, and differentially expressed genes (DEGs) were screened. Second, the functional changes of these DEGs were systematically investigated. Third, the protein-protein interaction network, high correlation module and key genes were identified. Fourth, prognosis and diagnostic analyses were performed. Fifth, small-molecule drugs were predicted for guiding LUAD therapy. Results: Finally, 12-gene and 2-gene signatures were identified as diagnostic and prognostic markers. The areas under the curves (AUCs) of two signatures associated with 3-year survival were 0.686 and 0.603, respectively. The AUCs of two signatures were over 95% and 94% in diagnostic model, separately. Eleven small-molecule drugs were found and irinotecan was simultaneously predicted in three drug databases. Conclusions: The present study identified some key dysregulated genes involved in LUAD and potential drugs by a comprehensive analysis, which provides novel insights into the pathological mechanism involved in LUAD and may shed light on the diagnosis, prognosis and treatment of LUAD patients.

Accumulating evidence has demonstrated that chromatin regulators (CRs) regulate immune cell infiltration and are correlated with prognoses of patients in some cancers. However, the immunological and prognostic roles of CRs in lung adenocarcinoma (LUAD) are still unclear. Here, we systematically revealed the correlations of CRs with immunological features and the survival in LUAD patients based on a cohort of gene expression datasets from the public TCGA and GEO databases and real RNA-seq data by an integrative analysis using a comprehensive bioinformatics method. Totals of 160 differentially expressed CRs (DECRs) were identified between LUAD and normal lung tissues, and two molecular prognostic subtypes (MPSs) were constructed and evaluated based on 27 prognostic DECRs using five independent datasets (p =0.016, <0.0001, =0.008, =0.00038 and =0.00055, respectively). Six differentially expressed genes (DEGs) (CENPK, ANGPTL4, CCL20, CPS1, GJB3, TPSB2) between two MPSs had the most important prognostic feature and a six-gene prognostic model was established. LUAD patients in the low-risk subgroup showed a higher overall survival (OS) rate than those in the high-risk subgroup in nine independent datasets (p <0.0001, =0.021, =0.016, =0.0099, <0.0001, =0.0045, <0.0001, =0.0038 and =0.00013, respectively). Six-gene prognostic signature had the highest concordance index of 0.673 compared with 19 reported prognostic signatures. The risk score was significantly correlated with immunological features and activities of oncogenic signaling pathways. LUAD patients in the low-risk subgroup benefited more from immunotherapy and were less sensitive to conventional chemotherapy agents. This study provides novel insights into the prognostic and immunological roles of CRs in LUAD.