P1.03-24 TMPRSS4: A Novel Prognostic Biomarker and Therapeutic Target in NSCLC

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

LINC00184 plays an oncogenic role in non-small cell lung cancer via regulation of the miR-524-5p/HMGB2 axis

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. We aimed to investigate the role of LINC00184 in NSCLC. Migration, proliferation and invasion of NSCLC cells were analysed using the wound healing assay, cell counting kit-8 assay and transwell assay, respectively. Apoptosis and cell cycle were assessed using flow cytometry. Online bioinformatics tools were utilized to predict downstream microRNAs (miRNA) or genes related to LINC00184 expression. The RNA pull-down experiment and luciferase reporter assay were performed to verify the predictions thereof. LINC00184, miR-524-5p, and high mobility group 2 protein (HMGB2) expression levels in NSCLC tissues and cell lines were detected using quantitative real-time polymerase chain reaction. An NSCLC mouse model was constructed for in vivo experiments. LINC00184 overexpression was observed in NSCLC tissues and cell lines and was found to be correlated with poor prognosis. LINC00184 knockdown inhibited cell proliferation, migration and invasion, induced cell cycle arrest and accelerated apoptosis in NSCLC cell lines. LINC00184 suppressed tumour growth and proliferation in NSCLC mouse models and directly targeted the miR-524-5p/HMGB2 axis. Moreover, the expression levels of LINC00184 and HMGB2 were negatively correlated with miR-524-5p expression, whereas LINC00184 expression was positively correlated with HMGB2 expression. LINC00184 affected the cell cycle, proliferation, apoptosis, migration and invasion in NSCLC via regulation of the miR-524-5p/HMGB2 axis.