Search

Introduction: Lung cancer represents the second most diagnosed cancer worldwide (11.4% of the total cases), and the most diagnosed cancer in men (14.3%) and represents the leading cause of cancer deaths in both men and women (18%). Moreover, the majority of tumors are characterized by dynamic molecular and phenotypic changes that occur in tumor cells which influence therapy resistance and result in poor clinical outcomes. Methods: FFPE lung tumor tissue from two lung adenocarcinoma (LUAD) and two lung squamous cell carcinoma (LUSC) patients were evaluated using the lOXGenomics Visium platform. The protocol included sample preparation, preparation of slides, fixing the slides on the capture areas, HE staining, deparaffinization and imagining, decrosslinking and probe hybridization, probe extension and library preparation. Sequencing was done using the Illumina platform, FastQC and SpaceRanger were used for primary analysis. Seurat and LoupeBrowser were used for the secondary analysis. Results: Unsupervised clustering revealed six and three clusters in LUAD samples, and six and seven clusters in LUSC samples, based on the transcriptomic profile of the cells in the spots of the capture area. The top 10 upregulated genes in each cluster were identified for each sample. It was noted that differentially expressed genes in clusters include genes encoding hemoglobin, cytokines, histones, and collagens. The inquiry revealed that T cells and B cells markers appear to be more present in LUAD tissue samples than in LUSC tissue samples. Moreover, LUSC tissue samples appear to have cancer associated fibroblasts markers whose expression is spatially variable. Conclusion: given the complex tumor heterogeneity in LUAD and LUSC tissue samples, we were able to observe gene expression in the context of spatial organization lung cancer tumor tissue. [ABSTRACT FROM AUTHOR]

Background: Non-small cell lung cancer (NSCLC) is still one of the types of cancer with the highest death rates. MicroRNAs (miRNAs) play essential roles in NSCLC development. This study evaluates miRNA expression patterns and specific mechanisms in male patients with NSCLC. Methods: We report an integrated microarray analysis of miRNAs for eight matched samples of males with NSCLC compared to the study of public datasets of males with NSCLC from TCGA, followed by qRT-PCR validation. Results: For the TCGA dataset, we identified 385 overexpressed and 75 underexpressed miRNAs. Our cohort identified 54 overexpressed and 77 underexpressed miRNAs, considering a fold-change (FC) of ±1.5 and p < 0.05 as the cutoff value. The common miRNA signature consisted of eight overexpressed and nine underexpressed miRNAs. Validation was performed using qRT-PCR on the tissue samples for miR-183-3p and miR-34c-5p and on plasma samples for miR-34c-5p. We also created mRNA-miRNA regulatory networks to identify critical molecules, revealing NSCLC signaling pathways related to underexpressed and overexpressed transcripts. The genes targeted by these transcripts were correlated with overall survival. Conclusions: miRNAs and some of their target genes could play essential roles in investigating the mechanisms involved in NSCLC evolution and provide opportunities to identify potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Lung cancers are broadly divided into two categories: non-small-cell lung carcinoma (NSCLC), which accounts for 80–85% of all cancer cases, and small-cell lung carcinoma (SCLC), which covers the remaining 10–15%. Recent advances in cancer biology and genomics research have allowed an in-depth characterization of lung cancers that have revealed new therapy targets (EGFR, ALK, ROS, and KRAS mutations) and have the potential of revealing even more biomarkers for diagnostic, prognostic, and targeted therapies. A new source of biomarkers is represented by non-coding RNAs, especially microRNAs (miRNAs). MiRNAs are short non-coding RNA sequences that have essential regulatory roles in multiple cancers. Therefore, we aim to investigate the tumor microenvironment (TME) and miRNA tumor profile in a subset of 51 early-stage lung cancer samples (T1 and T2) to better understand early tumor and TME organization and molecular dysregulation. We analyzed the immunohistochemistry expression of CD4 and CD8 as markers of the main TME immune populations, E-cadherin to evaluate early-stage epithelial-to-mesenchymal transition (EMT), and p53, the main altered tumor suppressor gene in lung cancer. Starting from these 4 markers, we identified and validated 4 miRNAs that target TP53 and regulate EMT that can be further investigated as potential early-stage lung cancer biomarkers. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC) remains a problem worldwide due to its rapid progression and low rate of response to treatment. The heterogeneity of these tumors observed in histopathology exam but also in the mutational status and gene expression pattern makes this malignancy difficult to treat in clinic. The present study investigated the effect of miR-21 and let-7 family members as prognostic biomarkers in NSCLC patients based on the results published in different studies regarding this subject until March 2019. The analysis revealed that these two transcripts are steady biomarkers for prediction of patient outcome or survival. Upregulated expression of miR-21 is associated with poor outcome of patients with NSCLC [HR = 1.87, 95% CI = (1.41, 2.47), p < 0.001]. The analysis regarding let-7 family, specifically let-7a/b/e/f, revealed that downregulated expression of these transcripts predicts poor outcome for NSCLC patients [HR = 2.61, 95% CI = (1.58, 4.30), p < 0.001]. Besides, the reliability of these microRNAs is reflected in the fact that their prognostic significance is constant given the different sample types (tissue, FFPE tissue, serum, serum/plasma or exosomes) used in the selected studies. [ABSTRACT FROM AUTHOR]

Non‐small cell lung cancer (NSCLC) comprises 85% of lung cancers. NSCLC has a high incidence and mortality. The present study aimed to investigate the role of miR-28-5p and miR-708-5p and to analyze the relationship between target coding genes and their signaling pathways. The two miRs were overexpressed in a patient cohort of 32 matched paired tumor and adjacent nontumoral tissue. All biological samples were collected from stage III and IV NSCLC patients. Due to the paralog structure of the two miRNAs, we conducted the study specifically on miR-708-5p, which showed a statistical significance between tumor tissue and adjacent nontumoral tissue. MiR-28-5p also revealed a significant difference, but at a lower level. We showed the critical roles of miR-28-5p and miR-708-5p in regulating ECM-receptor interaction, adherent’s junctions and Hippo signaling in the progression of NSCLC. Additional confirmation of the overexpression of miR-708-5p was done in the male TCGA patient cohort. The analysis using the Trans-Mir program revealed that the following transcriptional factors (TFs) may control miR-708: AR, ESR1, CREBBP, EOMES, EZH2, SOX2, TCF3/4, USF2; EZH2, JMJD1c, KDM2D, CXXC1, CXXC2, SFPQ, and MED1. These processes can be interrelated, particularly during the execution of the cell cycle. To analyze these connections, we performed a bioinformatics analysis of the correlation between TFs, based on genetic interactions, co-localization, physical interactions, co-expression and common pathways. We excluded predicted correlations and common protein domains. [ABSTRACT FROM AUTHOR]

Introduction. Lung cancer represents the second most diagnosed cancer worldwide and is the leading cause of cancer death. Considering the involvement of noncoding RNAs in various cancer-related processes, the idea of an interaction between these molecules arose. This study focused on identifying a lncRNA-miRNA-mRNA network with connection to biological processes altered in lung cancer. Using this approach, we aimed to identify potential targetable molecules to improve lung cancer patients’ response to therapy and, thus, their survival rate. Materials and method. In silico analysis for identification of differentially expressed miRNAs, lncRNAs and mRNAs and subsequent survival analysis of LUAD and LUSC TCGA datasets were performed. The interconnection among these transcripts was emphasized. Correlation analysis of mRNA/miRNA/lncRNA pairs in lung cancer was performed. Validation of mRNA/miRNA/lncRNA expression using two independent cohorts of LUAD and LUSC patients in a qRT-PCR experiment was performed. Results. We identified top dysregulated mRNA/miRNA/lncRNA transcripts in LUAD and LUSC TCGA datasets. Survival analysis on TCGA datasets based on the expression of the selected dysregulated transcripts allowed the identification of potential mRNA/ miRNA/lncRNA pairs with prognostic biomarker potential. The expression pattern of the mRNA/miRNA/lncRNA in the TCGA datasets was confirmed in qRT-PCR experiments performed on LUAD and LUSC patient cohort. Conclusions. RNA networks in cancer have clinical value in various aspects of patient care, including diagnosis, prognosis, treatment stratification and monitoring. The study revealed differences in terms of molecular imbalance in the two subtypes of NSCLC. [ABSTRACT FROM AUTHOR]