Comprehensive analysis of aberrantly expressed microRNA profiles reveals potential biomarkers of human lung adenocarcinoma progression

Prognostic value of CASC15 and LINC01600 as competitive endogenous RNAs in lung adenocarcinoma: An observational study

Long noncoding RNAs (lncRNAs) can directly or indirectly regulate gene expression through interacting with microRNAs (miRNAs). Competitive endogenous RNAs render the roles of lncRNAs more complicated in the process of tumor occurrence and progression. However, the prognostic value of lncRNAs as potential biomarkers and their functional roles as competitive endogenous RNAs have not been clearly described for lung adenocarcinoma (LUAD). In the present study, the aberrant expression profiles of lncRNAs and miRNAs were analyzed at cBioPortal by interrogating LUAD dataset from The Cancer Genome Atlas (TCGA) database with 517 tissue samples. A total of 92 lncRNAs and 125 miRNAs with highly genetic alterations were identified. Further bioinformatics analysis was performed to construct a LUAD-related lncRNA-miRNA-mRNA ceRNA network, which included 24 highly altered lncRNAs, 21 miRNAs and 142 mRNAs. Some key lncRNAs in this network were subsequently identified as LUAD prognosis-related, and of those, CASC15 and LINC01600 both performed the potential prognostic characteristics with LUAD regarding OS and recurrence. Comprehensive analysis indicated that the expression of LINC01600 was significantly associated with KRAS mutation and lymph node metastasis, and CASC15 and LINC01600 were significantly tended towards co-occurrence, which may be due to the similarity of genes co-expressed by these 2 lncRNAs. Our findings provided novel insight into better understanding of ceRNA regulatory mechanisms in the pathogenesis of LUAD and facilitated the identification of potential biomarkers for prognosis.

Characterization of plasma exosomal microRNAs in responding to radiotherapy of human esophageal squamous cell carcinoma

Radiotherapy is one of the main treatment methods for esophageal squamous cell carcinoma (ESCC). Previous research has shown that plasma exosomal microRNAs (miRNAs) can predict therapeutic outcome. In the present study, to identify potential exosomal miRNAs that respond to radiotherapy, plasma exosomal miRNAs from ESCC patients undergoing radiotherapy were isolated and sequenced. Upregulated and downregulated miRNAs were detected from patients pre- and post-radiotherapy, and it was found that they play distinct roles in DNA damage process and endosomal mediated transport. Based on wound healing and Cell Counting Kit-8 assays in TE-1 human esophageal cancer cells, it was identified that representative miRNA miR-652 and miR-30a alter migration but not proliferation. The present findings identified differentially expressed miRNAs in responding to radiotherapy, and added a reference to explore non-invasive plasma biomarkers to evaluate therapeutic effects in ESCC.

MiR-30a-3p Suppresses the Growth and Development of Lung Adenocarcinoma Cells Through Modulating GOLM1/JAK-STAT Signaling

A considerable amount of people succumbs to lung adenocarcinoma (LUAD) due to its high incidence and mortality. This study attempted to reveal the impacts of GOLM1 on LUAD. This work analyzed GOLM1 expression in LUAD and normal tissue and studied its prognostic value utilizing data from The Cancer Genome Atlas. RNA and protein levels were, respectively, determined utilizing qRT-PCR and western blot. Cell-aggressive behaviors were assessed employing Cell Counting Kit-8, scratch healing, and Transwell assays. The targetting relationship between GOLM1 and miR-30a-3p was assayed by dual-luciferase method. GOLM1 up-regulation in LUAD was found in TCGA and it was also a negative factor for survival in patients. GOLM1 overexpression promoted cell progression in LUAD. Down-regulated miR-30a-3p in LUAD was an upstream regulatory miRNA of GOLM1 in terms of molecular mechanism. Further, rescue assays illustrated that miR-30a-3p overexpression attenuated the GOLM1 facilitating impacts on LUAD progression. Finally, we proved that miR-30a-3p/GOLM1 regulated progression of LUAD cells via JAK-STAT pathway. Collectively, the inhibitory impacts of miR-30a-3p on LUAD growth may be mediated by GOLM1/JAK-STAT, which may contribute to the diagnosis of LUAD therapy and the development of therapeutic tools.

Nonnegative matrix factorization-based bioinformatics analysis reveals that TPX2 and SELENBP1 are two predictors of the inner sub-consensuses of lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a heterogeneous disease. However the inner sub‐groups of LUAD have not been fully studied. Markers predicted the sub‐groups and prognosis of LUAD are badly needed.

Aims

To identify biomarkers associated with the sub‐groups and prognosis of LUAD.

Materials and Methods

Using nonnegative matrix factorization (NMF) clustering, LUAD patients from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) datasets and LUAD cell lines from Genomics of Drug Sensitivity in Cancer (GDSC) dataset were divided into different sub‐consensuses based on the gene expression profiling. The overall survival of LUAD patients in each sub‐consensus was determined by Kaplan‐Meier survival analysis. The common genes which were differentially expressed in each sub‐consensus of LUAD patients and LUAD cell lines were identified using TBtools. The predictive accuracy of TPX2 and SELENBP1 for theinner sub‐consensuses of LUAD was determined by Receiver operator characteristic (ROC) analysis. The Kaplan‐Meier survival analysis was also used to test the prognostic significance of TPX2 and SELENBP1 in LUAD patients.

Results

Using nonnegative matrix factorization clustering, LUAD patients in The Cancer Genome Atlas (TCGA), GSE30219, GSE42127, GSE50081, GSE68465, and GSE72094 datasets were divided into three sub‐consensuses. Sub‐consensus3 LUAD patients were with low overall survival and were with high TP53 mutations. Similarly, LUAD cell lines were also divided into three sub‐consensuses by NMF method, and sub‐consensus2 cell lines were resistant to EGFR inhibitors. Identification of the common genes which were differentially expressed in different sub‐consensuses of LUAD patients and LUAD cell lines revealed that TPX2 was highly expressed in sub‐consensus3 LUAD patients and sub‐consensus2 LUAD cell lines. On the contrary, SELENBP1 was highly expressed in sub‐consensus1 LUAD patients and sub‐consensus1 LUAD cell lines. The expression levels of TPX2 and SELENBP1 could distinguish sub‐consensus3 LUAD patients or sub‐consensus2 LUAD cell lines from other sub‐consensuses of LUAD patients or cell lines. Moreover, compared with normal lung tissues, TPX2 was highly expressed, while, SELENBP1 was lowly expressed in LUAD tissues. Furthermore, the higher expression levels of TPX2 were associated with the lower relapse‐free survival and the lower overall survival of LUAD patients. While, the higher expression levels of SELENBP1 were associated with the higher relapse‐free survival and higher overall survival. At last, we showed that TP53 mutant LUAD patients were with higher TPX2 and lower SELENBP1 expressions.

Discussion

Both iCluster and NMF method are proved to be robust LUAD classification systems. However, the LUAD patients in different iclusters had no significant clinical overall survival, while, sub‐consensus3 LUAD patients from NMF classification were with lower overall survival than other sub‐consensuses.

Conclusions

By integrated analysis of 1765 LUAD patients and 64 LUAD cell lines, we showed that NMF was a robust inner sub‐consensuses classification method of LUAD. TPX2 and SELENBP1 were differentially expressed in different LUAD sub‐ consensuses, and predicted the inner sub‐consensuses of LUAD with high accuracy. TPX2 was an unfavorable prognostic biomarker of LUAD which was up‐regulated in LUAD tissues and associated with the low overall survival of LUAD. SELENBP1 was a favorable prognostic biomarker of LUAD which was down‐regulated in LUAD tissues and associated with the prolonged overall survival of LUAD.

SKA3 promotes lung adenocarcinoma metastasis through the EGFR-PI3K-Akt axis

The processes that lead to lung adenocarcinoma (LUAD) metastasis are poorly characterized. Spindle and kinetochore associated complex subunit 3 (SKA3) plays a key role in cervical cancer development, but its contribution to LUAD is unknown. Here, we found that SKA3 is overexpressed in LUAD and its expression correlates with lymph node metastasis and poor prognosis. SKA3 silencing experiments identified SKA3 as an oncogene that promotes the metastasis of LUAD cell lines and tissues. SKA3 was found to induce the expression of matrix metalloproteinase (MMP)-2, -7, and -9, which activate PI3K–AKT. SKA3 was also found to bind and activate EGFR to activate PI3K–AKT. In summary, we identify a role for SKA3 in LUAD metastasis through its ability to bind EFGR and activate PI3K–AKT signaling.

Are There New Biomarkers in Tissue and Liquid Biopsies for the Early Detection of Non-Small Cell Lung Cancer?

Lung cancer is one of the most lethal malignancies worldwide, mainly due to its late diagnoses. The detection of molecular markers on samples provided from routine bronchoscopy including several liquid-based cytology tests (e.g., bronchoaspirate, bronchoalveolar lavage) and/or on easily obtained specimens such as sputum could represent a new approach to improve the sensitivity in lung cancer diagnoses. Recently growing interest has been reported for "noninvasive" liquid biopsy as a valuable source for molecular profiling. Unfortunately, a biomarker and/or composition of biomarkers capable of detecting early-stage lung cancer has yet to be discovered even if in the last few years there has been, through the use of revolutionary new technologies, an explosion of lung cancer biomarkers. Assay sensitivity and specificity need to be improved particularly when new approaches and/or tools are used. We have focused on the most important markers detected in tissue, and on several cytological specimens and liquid biopsies overall.

Changing expression profiles of mRNA, lncRNA, circRNA, and miRNA in lung tissue reveal the pathophysiological of bronchopulmonary dysplasia (BPD) in mouse model

New perinatal care technologies have improved the survival rate of preterm neonates, but the prevalence of bronchopulmonary dysplasia (BPD), one of the most intractable problems in neonatal intensive care unit (NICU), remains unchanged. In present study, high-throughput sequencing (HTS) was performed to detect the expression profiles of long noncoding RNAs (lncRNAs), messenger RNAs (mRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) in hyperoxia-induced BPD mouse model. Significant differentially expressed RNAs were selected and clustered between the BPD group and the control group. The results revealed that expressions of 1778 lncRNAs, 1240 mRNAs, 97 circRNAs, and 201 miRNAs were significantly altered in the BPD group. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to predict the potential functions of differentially expressed RNAs. lncRNA-mRNA and circRNA-miRNA coexpression networks were constructed to detect their association with the pathogenesis of BPD. Our study provides a systematic perspective on the potential function of RNAs during BPD.

miR-944 inhibits lung adenocarcinoma tumorigenesis by targeting STAT1 interaction

Lung adenocarcinoma (LAC) is a leading cause of cancer-associated mortalities, particularly in developed countries. The aberrant expression of microRNAs (miRNAs) has been proven to regulate numerous diseases in the past two decades. miRNAs have been identified in almost all human cancer types. In the present study, the role of miR-944 in LAC proliferation was examined. It was identified that miR-944 was downregulated in LAC tissues and cells, and miR-944 overexpression inhibited A549 and H1299 cell proliferation, as determined by the Cell Counting Kit-8 and colony formation assay. Signal transducer and activator of transcription 1 (STAT1) was upregulated in LAC tissues and cells. Kaplan-Meier analysis demonstrated that the 5-year overall survival in patients with high STAT1 levels was significantly reduced, compared with patients with negative and low STAT1 expression. STAT1 was the direct target of miR-944. Additionally, a miR-944 mimic inhibited A549 cell growth in vitro. Collectively, these data demonstrate that miR-944 serves a pivotal role in LAC tumor growth by targeting STAT1. The data obtained indicated that miR-944 may be a novel biomarker and could result in potential therapies for LAC.

Identification of nine microRNAs as potential biomarkers for lung adenocarcinoma

Lung cancer is a leading global cause of cancer‐related death, and lung adenocarcinoma (LUAD) accounts for ~ 50% of lung cancer. Here, we screened for novel and specific biomarkers of LUAD by searching for differentially expressed mRNAs (DEmRNAs) and microRNAs (DEmiRNAs) in LUAD patient expression data within The Cancer Genome Atlas (TCGA). The identified optimal diagnostic miRNA biomarkers were used to establish classification models (including support vector machine, decision tree, and random forest) to distinguish between LUAD and adjacent tissues. We then predicted the targets of identified optimal diagnostic miRNA biomarkers, functionally annotated these target genes, and performed receiver operating characteristic curve analysis of the respective DEmiRNA biomarkers, their target DEmRNAs, and combinations of DEmiRNA biomarkers. We validated the expression of selected DEmiRNA biomarkers by quantitative real‐time PCR (qRT‐PCR). In all, we identified a total of 13 DEmiRNAs, 2301 DEmRNAs and 232 DEmiRNA–target DEmRNA pairs between LUAD and adjacent tissues and selected nine DEmiRNAs (hsa‐mir‐486‐1, hsa‐mir‐486‐2, hsa‐mir‐153, hsa‐mir‐210, hsa‐mir‐9‐1, hsa‐mir‐9‐2, hsa‐mir‐9‐3, hsa‐mir‐577, and hsa‐mir‐4732) as optimal LUAD‐specific biomarkers with great diagnostic value. The predicted targets of these nine DEmiRNAs were significantly enriched in transcriptional misregulation in cancer and central carbon metabolism. Our qRT‐PCR results were generally consistent with our integrated analysis. In summary, our study identified nine DEmiRNAs that may serve as potential diagnostic biomarkers of LUAD. Functional annotation of their target DEmRNAs may provide information on their roles in LUAD.