Analysis of lncRNA expression profiles in non-small cell lung cancers (NSCLC) and their clinical subtypes

Overexpression of the non-coding SOX2OT variants 4 and 7 in lung tumors suggests an oncogenic role in lung cancer

Despite the advances in cancer therapy, lung cancer still remains the most leading cause of cancer death worldwide. The long non-coding RNAs (lncRNAs) are recently introduced as novel regulators of human cancers. SOX2 overlapping transcript (SOX2OT) is a cancer-associated lncRNA gene that encodes different alternatively spliced transcripts. Here, we investigated the alterations in the preferential expression of different SOX2OTs in twenty non-small cell lung cancer (NSCLC) patients by real-time quantitative reverse transcription PCR (qRT-PCR) method. We observed preferential expression of SOX2OT4 and SOX2OT7 in lung tumor tissues. The quantitative gene expression analysis revealed that >30 % of NSCLC tumors express SOX2OT4 (mean = 7.6 times) and SOX2OT7 (mean = 5.9 times) more than normal tissues, with higher expression in squamous cell carcinoma. Further, we observed overexpression of pluripotency-associated transcription factor, SOX2 in 47 % of our samples concordant with SOX2OT (R = 0.62, P value <0.05). Overexpression of OCT4A gene was also observed in 36.8 % of tumor tissues. Then, we investigated the effects of SOX2OT suppression in lung adenocarcinoma cell line, by means of RNAi. Cell characteristics of colony formation, apoptosis, 2-D mobility, and cell cycle progression were measured in control and treated A549 cells. The SOX2OT knockdown significantly reduced the colony formation ability of cancer cells; however, no alterations in the rate of apoptosis were detected. On the other hand, SOX2OT-suppressed cells had elevated accumulation in G2/M phase of cell cycle and exhibited limited mobility. Altogether, our findings support a potential oncogenic role for SOX2OT in non-small cell lung cancer tumor genesis and SOX2OT seems a promising therapeutic candidate for NSCLC.

The plasma lncRNA acting as fingerprint in non-small-cell lung cancer

Recent studies have indicated that long non-coding RNAs (lncRNAs) could act as non-invasive tumor markers in both diagnosis and predicting the prognosis. In this study, we focused to determine the expression of circulating lncRNAs in patients suffering from non-small-cell lung cancer (NSCLC), aiming to found the potential lncRNA as predictor. Twenty-one lncRNAs which previously identified were selected as candidate targets for subsequent circulating lncRNA assay. The candidate lncRNAs were validated by qRT-PCR arranged in the training and validation sets. Circulating SPRY4-IT1, ANRIL, and NEAT1 were significantly increased in plasma samples of NSCLC patients during training set and validation set. Receiver operating characteristic curve (ROC) analysis revealed that plasma ANRIL provided the highest diagnostic performance with an area under ROC curve value (AUC) of 0.798. Further combination with the three factors indicated a higher power (AUC, 0.876; sensitivity, 82.8 %; specificity, 92.3 %). The stableness detection of the three factors indicated that circulating SPRY4-IT1, ANRIL, and NEAT might serve as a predictor for the early warning of non-small-cell lung cancer.

Long Noncoding RNAs as New Architects in Cancer Epigenetics, Prognostic Biomarkers, and Potential Therapeutic Targets

Recent advances in genome-wide analysis have revealed that 66% of the genome is actively transcribed into noncoding RNAs (ncRNAs) while less than 2% of the sequences encode proteins. Among ncRNAs, high-resolution microarray and massively parallel sequencing technologies have identified long ncRNAs (>200 nucleotides) that lack coding protein function. LncRNAs abundance, nuclear location, and diversity allow them to create in association with protein interactome, a complex regulatory network orchestrating cellular phenotypic plasticity via modulation of all levels of protein-coding gene expression. Whereas lncRNAs biological functions and mechanisms of action are still not fully understood, accumulating data suggest that lncRNAs deregulation is pivotal in cancer initiation and progression and metastatic spread through various mechanisms, including epigenetic effectors, alternative splicing, and microRNA-like molecules. Mounting data suggest that several lncRNAs expression profiles in malignant tumors are associated with prognosis and they can be detected in biological fluids. In this review, we will briefly discuss characteristics and functions of lncRNAs, their role in carcinogenesis, and their potential usefulness as diagnosis and prognosis biomarkers and novel therapeutic targets.

A potential signature of eight long non-coding RNAs predicts survival in patients with non-small cell lung cancer

Background

Accumulated evidence suggests that dysregulated expression of long non-coding RNAs (lncRNAs) may play a critical role in tumorigenesis and prognosis of cancer, indicating the potential utility of lncRNAs as cancer prognostic or diagnostic markers. However, the power of lncRNA signatures in predicting the survival of patients with non-small cell lung cancer (NSCLC) has not yet been investigated.

Methods

We performed an array-based transcriptional analysis of lncRNAs in large patient cohorts with NSCLC by repurposing microarray probes from the gene expression omnibus database. A risk score model was constructed based on the expression data of these eight lncRNAs in the training dataset of NSCLC patients and was subsequently validated in other two independent NSCLC datasets. The biological implications of prognostic lncRNAs were also analyzed using the functional enrichment analysis.

Results

An expression pattern of eight lncRNAs was found to be significantly associated with overall survival (OS) of NSCLC patients in the training dataset. With the eight-lncRNA signature, patients of the training dataset could be classified into high- and low-risk groups with significantly different OS (median survival 1.67 vs. 6.06 years, log-rank test p = 4.33E−09). The prognostic power of eight-lncRNA signature was further validated in other two non-overlapping independent NSCLC cohorts, demonstrating good reproducibility and robustness of this eight-lncRNA signature in predicting OS of NSCLC patients. Multivariate regression and stratified analysis suggested that the prognostic power of the eight-lncRNA signature was independent of clinical and pathological factors. Functional enrichment analyses revealed potential functional roles of the eight prognostic lncRNAs in tumorigenesis.

Conclusions

These findings indicate that the eight-lncRNA signature may be an effective independent prognostic molecular biomarker in the prediction of NSCLC patient survival.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-015-0556-3) contains supplementary material, which is available to authorized users.

Genome-scale long noncoding RNA expression pattern in squamous cell lung cancer

In this study, we aimed to explore the long noncoding RNA expression pattern in squamous cell lung cancer (SQCC) on a genome-wide scale. Total RNAs were extracted from 16 lung SQCC patients’ normal and matched lung cancer tissues by Trizol reagent. The expression level of genome-wide scale lncRNA and mRNA was determined by microarray. qRT-PCR was used to validate the lncRNA expression level in 47 patients. Data analyses were performed using R and Bioconductor. A total of 2,748 up and 852 down regulated probes were identified to be significantly and differentially expressed in tumor tissues. The annotation result of their co-expressed mRNAs showed that the most significantly related category of GO analysis was development and differentiation, while the most significantly related pathway was cell cycle. Subgroup analysis identified that 46 and 18 probes were specifically differentially expressed in smoking and moderately differentiated tumors, respectively. Our study indicated that clusters of lncRNAs were significantly and differentially expressed in SQCC compared with normal tissues in the same subject. They may exert a significant role in lung cancer development and could be potential targets for future treatment of SQCC.

Long non-coding RNA functions in lung cancer

Numerous long non-coding RNAs (lncRNAs) have been discovered as a result of advances in sequencing methods in genomic research. Recent evidence indicates that lncRNAs may serve as gene regulators via various mechanisms, such as translational control. Dysregulation of lncRNAs contributes to the development and progression of several human diseases, notably lung cancer, which is one of the leading causes of cancer-associated death. Recent studies have identified key roles for molecules such as p53 and polycomb repressive complex 2 (PRC2) in carcinogenesis and the anti-carcinogenic action of lncRNAs. These findings point to the potential of lncRNAs as prospective diagnostic and prognostic biomarkers in lung cancer. In this review, we consider the functions of lncRNAs in translational control and discuss their involvement in lung cancer via p53, PRC2, and other pathways. We also consider the effects of modulating the levels and functions of lncRNAs. Further characterization of these lung cancer-associated lncRNAs will provide a better understanding of their potential roles as therapeutic targets.

Long non-coding RNA LINC01296 is a potential prognostic biomarker in patients with colorectal cancer

Colorectal cancer (CRC), one of the most malignant cancers, is currently the fourth leading cause of cancer deaths worldwide. Recent studies indicated that long non-coding RNAs (lncRNAs) could be robust molecular prognostic biomarkers that can refine the conventional tumor-node-metastasis staging system to predict the outcomes of CRC patients. In this study, the lncRNA expression profiles were analyzed in five datasets (GSE24549, GSE24550, GSE35834, GSE50421, and GSE31737) by probe set reannotation and an lncRNA classification pipeline. Twenty-five lncRNAs were differentially expressed between CRC tissue and tumor-adjacent normal tissue samples. In these 25 lncRNAs, patients with higher expression of LINC01296, LINC00152, and FIRRE showed significantly better overall survival than those with lower expression (P < 0.05), suggesting that these lncRNAs might be associated with prognosis. Multivariate analysis indicated that LINC01296 overexpression was an independent predictor for patients' prognosis in the test datasets (GSE24549, GSE24550) (P = 0.001) and an independent validation series (GSE39582) (P = 0.027). Our results suggest that LINC01296 could be a novel prognosis biomarker for the diagnosis of CRC.

The non-coding RNAs of the H19-IGF2 imprinted loci: a focus on biological roles and therapeutic potential in Lung Cancer

Since it was first described, the imprinted cluster 11p15.5 has been reported to be deregulated in a variety of pediatric and adult cancers including that of the lung. Both protein coding and non-coding genes functioning as oncogenes or as tumor suppressor genes reside within this cluster. Oncomirs that can function as oncogenes or as tumor suppressors have also been reported. While a complete account of the role played by the 11p15.5 imprinted cluster in lung cancer is beyond the scope of this review, we will focus on the role of the non-coding RNAs processed from the H19-IGF2 loci. A special emphasis will be given to the H19/miR-675 gene locus. Their potential diagnostic and therapeutic use in lung cancer will be described.

Functions of lncRNA HOTAIR in lung cancer

Long non-coding RNAs (lncRNAs) govern fundamental biochemical and cellular processes. lncRNA HOX transcript antisense RNA (HOTAIR) represses gene expression through recruitment of chromatin modifiers. The expression of HOTAIR is elevated in lung cancer and correlates with metastasis and poor prognosis. Moreover, HOTAIR promotes proliferation, survival, invasion, metastasis, and drug resistance in lung cancer cells. Here we review the molecular mechanisms underlying HOTAIR-mediated aggressive phenotypes of lung cancer. We also discuss HOTAIR’s potential in diagnosis and treatment of lung cancer, as well as the challenges of exploiting HOTAIR for intervention of lung cancer.