Survival-based bioinformatics analysis to identify hub genes and key pathways in non-small cell lung cancer

Bioinformatics and Network Pharmacology of the First Crystal Structured Clerodin: Anticancer and Antioxidant Potential against Human Breast Carcinoma Cell

Clerodin was isolated from the medicinal plant Clerodendrum infortunatum, and CSD search showed the first crystal structure of clerodin by a single-crystal X-ray diffraction study. We checked its binding potential with target proteins by docking and conducted network pharmacology analysis, ADMET analysis, in silico pathway analysis, normal mode analysis (NMA), and cytotoxic activity studies to evaluate clerodin as a potential anticancer agent. The cell viability studies of clerodin on the human breast carcinoma cell line (MCF-7) showed toxicity on MCF-7 cells but no toxicity toward normal human lymphocyte cells (HLCs). The anticancer mechanism of clerodin was validated by its enhanced capacity to produce intracellular reactive oxygen species (ROS) and to lower the reduced glutathione content in MCF-7 cells.

Identifying the hub genes in non-small cell lung cancer by integrated bioinformatics methods and analyzing the prognostic values

BACKGROUND

Lung cancer, a malignant tumor, has the highest mortality and second most common morbidity worldwide. Non-small cell lung cancer (NSCLC) is the most common pathological subtype of lung cancer. This study aimed to identify the gene signature associated with the NSCLC prognosis using bioinformatics analysis.

MATERIALS AND METHODS

The dataset GSE103512 was utilized to construct co-expression networks using weighted gene co-expression network analysis (WGCNA). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using Database for Annotation, Visualization, and Integrated Discovery. Gene set enrichment analysis was conducted to ascertain the function of the hub genes more accurately. The relationship between the hub genes and immune infiltration was investigated using a single sample gene set enrichment analysis. Hub genes were screened and validated by other datasets and online websites.

RESULTS

The results of WGCNA demonstrated that the blue module was most significantly related to tumor progression in NSCLC. Functional enrichment analysis showed that the blue module was associated with DNA replication, cell division, mitotic nuclear division, and cell cycle. A total of five hub genes (RFC5, UBE2S, CHAF1A, FANCI, and TMEM194A) were chosen to be identified and validated at transcriptional and translational levels. Receiver operating characteristic curve verified that the mRNA levels of these five genes can excellently discriminate between normal and tumor tissues. Survival analysis was also performed. Additionally, the protein levels of these five genes were also significantly different between tumor and normal tissues. Immune infiltration analysis showed that the expression levels of the hub genes had a negative correlation with the infiltration levels of many cells related to innate immune response, antigen-presenting process, humoral immune response, or T cell-mediated immune responses.

CONCLUSIONS

We identified five hub genes associated with the NSCLC tumorigenesis. NSCLC patients with higher expressions of each hub gene had a worse prognosis than those with lower expressions. Moreover, the hub genes might serve as biomarkers and therapeutic targets for precise diagnosis, target therapy, and immunotherapy of NSCLC in the future.