Lung cancer has a complex etiology involving multiple regulatory systems. Uncertainty about the biology and evolution of lung cancer has made it difficult to improve its poor prognosis. To create efficient therapeutic targets and optimal molecular screening tools for lung cancer, the most important task seems to be to understand how it develops and progresses. The expression and regulation of GTPBP4 in non-small cell lung cancer (NSCLC) are not well understood. Using methods such as knocking down GTPBP4 in lung cancer cells and establishing a mouse lung cancer model, we found that the expression of GTPBP4 was upregulated in human lung adenocarcinoma cells and tissues, and that knocking down the expression of the GTPBP4 gene in A549 and Calu-1 lung adenocarcinoma cells can inhibit the proliferation of lung adenocarcinoma cells and reduce their invasion ability. The results of the mouse lung cancer model showed that the lung weight and the number of lung surface nodules decreased significantly in the LLC-GTPBP4 KO group. The mechanism by which GTPBP4 regulation affects the progression of lung adenocarcinoma may be related to the regulation of EMT. From this study, new research ideas emerge to explore GTPBP4 as a biomarker and therapeutic target for early diagnosis and treatment of lung cancer.

This study aimed to using bioinformatics tools, qPCR, and the immunohistochemical analysis to find out factors related to the early diagnosis and prognosis of kidney renal clear cell carcinoma (KIRC). The expression profiles of lncRNA, miRNA, and mRNA of KIRC were downloaded from The Cancer Genome Atlas database. A ceRNA regulatory network was constructed based on the interaction between these three differentially expressed genes. The CIBERSORT deconvolution algorithm was used to analyze the differential distribution of 22 types of immune cells. The Kaplan–Meier survival and Cox analyses were used to screen genes of the ceRNA network and also immune cell subtypes related to the clinical and prognostic prediction of KIRC. Co-expression regulatory relationships were found among LINC01426, LINC00894, CCNA2, L1 cell adhesion molecule (L1CAM), and T follicular helper cells, which served as potential biomarkers. The results of quantitative reverse transcriptase-polymerase chain reaction showed that LINC01426 was upregulated while L1CAM was downregulated in KIRC, but no difference was found in the expression levels of LINC00894 and CCNA2 in cancer and adjacent samples. The immunohistochemical analysis showed that T follicular helper cells were more concentrated in core tissues and metastases of KIRC. In a word, co-expression relationships were found among LINC01426, L1CAM, and T follicular helper cells, and they may serve as biomarkers for early diagnosis and prognostic evaluation of KIRC.