Role of BC040587 as a predictor of poor outcome in breast cancer

Non-coding RNA's prevalence as biomarkers for prognostic, diagnostic, and clinical utility in breast cancer

Noncoding RNAs (ncRNAs), which make up a significant portion of the mammalian transcriptome and plays crucial regulatory roles in expression of genes and other biological processes, have recently been found. The most extensively researched of the sncRNAs, microRNAs (miRNAs), have been characterized in terms of their synthesis, roles, and significance in the tumor development. Its crucial function in the stem cell regulation, another class of sncRNAs known as aspirRNAs, has attracted attention in cancer research. The investigations have shown that long non-coding RNAs have a crucial role in controlling developmental stages, such as mammary gland development. Additionally, it has been discovered that lncRNA dysregulation precedes the development of several malignancies, including breast cancer. The functions of sncRNAs (including miRNAs and piRNAs) and lncRNAs in the onset and development of the breast cancer are described in this study. Additionally, future perspectives of various ncRNA-based diagnostic, prognostic, and therapeutic approaches also discussed.

Circulating LncRNAs landscape as potential biomarkers in breast cancer

BACKGROUND

In Iran, the delay in diagnosis and treatment of breast cancer results in low survival rates.

AIM

It is essential to characterize new therapeutic targets and prognostic breast cancer biomarkers. The rising evidence suggested that long non-coding RNAs (lncRNAs) expression levels are deregulated in human cancers and can use as biomarkers for the rapid diagnosis of breast cancer.

METHODS

In the present study, a quantitative real-time polymerase chain reaction (qRT-PCR) technique was used to measure 20 oncogenic and tumor suppressor lncRNAs expression levels in whole blood samples of female breast cancer patients and healthy women. Receiver operating characteristic curve (ROC) was used to assess the diagnostic value of each selected lncRNA as a biomarker.

RESULTS

The results revealed that some circulating lncRNAs (MEG3, NBAT1, NKILA, GAS5, EPB41L4A-AS2, Z38, and BC040587) were significantly down-regulated in breast cancer patients compared to healthy women. In contrast, other circulating lncRNAs (H19, SPRY4-IT1, XIST, UCA1, AC026904.1, CCAT1, CCAT2, ITGB2-AS, and AK058003) were significantly up-regulated in breast cancer patients compared to controls. It was shown that the expression levels of NKILA, and NBAT1 lncRNAs were related to tumor size, and BC040587 expression level related to age, node metastasis, tumor size, and grade (p < .05). The association between H19 and SPRY4-IT1 lncRNAs with HER-2 was confirmed statistically (p < .05). ROC curves illustrated that the blood levels of SPRY4-IT1, XIST, and H19 lncRNAs have excellent potential in discriminating breast cancer from the healthy controls, showing an AUC of 1.0 (95% CI 1.0-1.0, p = .00), 0.898 (95% CI 0.815-0.981, p = .00), and 0.848 (95% CI 0.701-0.995, p = .01), respectively.

CONCLUSION

In conclusion, the expression levels of circulating H19 and SPRY4-IT1 lncRNAs in breast cancer patients could consider as the prognostic biomarkers and therapeutic targets in breast cancer, because of their excellent power in discriminating breast cancer from healthy individuals and the significant correlation of H19, and SPRY4-IT1 lncRNAs with clinicopathological traits. We also suggest the possible application of BC040587 lncRNA as a diagnostic and prognostic indicator to assess tumor progression in case of verification in larger patients' cohorts.

Long non-coding RNAs as novel prognostic biomarkers for breast cancer in Egyptian women

Breast cancer (BC), the most common type of malignant tumor, is the leading cause of death, having the highest incidence rate among women. The lack of early diagnostic tools is one of the clinical obstacles for BC treatment. The current study was designed to evaluate a panel of long non-coding RNAs (lncRNAs) BC040587, HOTAIR, MALAT1, CCAT1, CCAT2, PVT1, UCA1, SPRY4-IT1, PANDAR, and AK058003-and two mRNAs (SNCG, BDNF) as novel prognostic biomarkers for BC. This study was ethically approved by the Institutional Review Board of the National Cancer Institute, Cairo University. Our study included 75 women recently diagnosed with BC and 25 healthy women as normal controls. Patients were divided into three groups: 24 with benign breast diseases, 28 with metastatic breast cancer (MBC, stage IV), and 23 with non-metastatic breast cancer (NMBC, stage III). LncRNA and mRNA expression levels were measured in patient plasma using quantitative real-time PCR. We found that 10 lncRNAs (BCO40587, HOTAIR, PVT1, CCAT2, PANDAR, CCAT1, UCA1, SPRY4-IT1, AK058003, and MALAT1) and both mRNAs demonstrated at least a 2-fold change in expression with a more than 95% probability of significance. BCO40587 and SNCG were significantly up-regulated in MBC and NMBC patients (3.2- and 4-fold, respectively) compared with normal controls. The expression of UCA1 was repressed by 1.78-fold in MBC and NMBC patients compared with those with benign diseases. SPRY4-IT1 was down-regulated by 1.45-fold in MBC patients compared with NMBC and benign disease patients. Up-regulation of lncRNAs plays an important role in BC development. SNCG and BCO40587 may be potential prognostic markers for BC.The organization number is IORG0003381 (IRB No: IRB00004025).

MCA-Net: Multi-Feature Coding and Attention Convolutional Neural Network for Predicting lncRNA-Disease Association

With the advent of the era of big data, it is troublesome to accurately predict the associations between lncRNAs and diseases based on traditional biological experiments due to its time-consuming and subjective. In this paper, we propose a novel deep learning method for predicting lncRNA-disease associations using multi-feature coding and attention convolutional neural network (MCA-Net). We first calculate six similarity features to extract different types of lncRNA and disease feature information. Second, a multi-feature coding method is proposed to construct the feature vectors of lncRNA-disease association samples by integrating the six similarity features. Furthermore, an attention convolutional neural network is developed to identify lncRNA-disease associations under 10-fold cross-validation. Finally, we evaluate the performance of MCA-Net from different perspectives including the effects of the model parameters, distinct deep learning models, and the necessity of attention mechanism. We also compare MCA-Net with several state-of-the-art methods on three publicly available datasets, i.e., LncRNADisease, Lnc2Cancer, and LncRNADisease2.0. The results show that our MCA-Net outperforms the state-of-the-art methods on all three dataset. Besides, case studies on breast cancer and lung cancer further verify that MCA-Net is effective and accurate for the lncRNA-disease association prediction.

Long non-coding RNA LSAMP-1 is down-regulated in non-small cell lung cancer and predicts a poor prognosis

Background

Long noncoding RNAs (lncRNAs) are emerging as master regulators for gene expression and thus play a vital role in human tumorigenesis and progression. But the involvement of novel lncRNAs in non-small cell lung cancer (NSCLC) remains largely unelucidated.

Methods

A total of 170 NSCLC and their adjacent non-tumor tissues were enrolled to detect the expression of Lnc-LSAMP-1 by RT-qPCR. The effects of Lnc-LSAMP-1 on cell proliferation, migration, invasion and drug-sensitivity were determined by in vitro and in vivo experiments. The proteins that interact with Lnc-LSAMP-1were confirmed by RNA pull-down assay. RNA-sequencing were used to identify the potential targets of Lnc-LSAMP-1 in NSCLC.

Results

We found that Lnc-LSAMP-1 was significantly down-regulated in 170 cases of NSCLC tissues when compared to their adjacent non-cancerous tissues. Loss expression of Lnc-LSAMP-1 was notably correlated with unfavorable prognosis of NSCLC patients. The ectopic expression of Lnc-LSAMP-1 drastically inhibited lung cancer cell proliferation, viability, invasion and migration ability, arrested cell cycle and facilitated apoptosis. Chemotherapy sensitization experiments showed that over-expressed Lnc-LSAMP-1 enhanced the inhibition of cell proliferation induced by TKI. Mechanistically, Lnc-LSAMP-1-LSAMP formed a complex which could protect the degradation of LSAMP gene, and thus exerted crucial roles in NSCLC progression and TKI targeted treatment.

Conclusions

Consequently, our findings highlight the function and prognostic value of Lnc-LSAMP-1 in NSCLC and provide potential novel therapeutic targets and prognostic biomarkers for patients with NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02592-0.

Abnormal Long Non-Coding RNAs Expression Patterns Have the Potential Ability for Predicting Survival and Treatment Response in Breast Cancer

Abnormal long non-coding RNAs (lncRNAs) expression has been documented to have oncogene or tumor suppressor functions in the development and progression of cancer, emerging as promising independent biomarkers for molecular cancer stratification and patients’ prognosis. Examining the relationship between lncRNAs and the survival rates in malignancies creates new scenarios for precision medicine and targeted therapy. Breast cancer (BRCA) is a heterogeneous malignancy. Despite advances in its molecular classification, there are still gaps to explain in its multifaceted presentations and a substantial lack of biomarkers that can better predict patients’ prognosis in response to different therapeutic strategies. Here, we performed a re-analysis of gene expression data generated using cDNA microarrays in a previous study of our group, aiming to identify differentially expressed lncRNAs (DELncRNAs) with a potential predictive value for response to treatment with taxanes in breast cancer patients. Results revealed 157 DELncRNAs (90 up- and 67 down-regulated). We validated these new biomarkers as having prognostic and predictive value for breast cancer using in silico analysis in public databases. Data from TCGA showed that compared to normal tissue, MIAT was up-regulated, while KCNQ1OT1, LOC100270804, and FLJ10038 were down-regulated in breast tumor tissues. KCNQ1OT1, LOC100270804, and FLJ10038 median levels were found to be significantly higher in the luminal subtype. The ROC plotter platform results showed that reduced expression of these three DElncRNAs was associated with breast cancer patients who did not respond to taxane treatment. Kaplan–Meier survival analysis revealed that a lower expression of the selected lncRNAs was significantly associated with worse relapse-free survival (RFS) in breast cancer patients. Further validation of the expression of these DELncRNAs might be helpful to better tailor breast cancer prognosis and treatment.

Critical roles of long noncoding RNAs in breast cancer

Breast cancer is a major clinical challenge that affects a wide range of the female population and heavily burdens the health system. In the past few decades, attempts have been made to understand the etiology of breast cancer, possible environmental risk factors, and the genetic predispositions, pathogenesis, and molecular aberrations involved in the process. Studies have shown that breast cancer is a heterogeneous entity; each subtype has its specific set of aberrations in different cell signaling pathways, such as Notch, Wnt/β-catenin, transforming growth factor-β, and mitogen-activated protein kinase pathways. One novel group of molecules that have been shown to be inducted in the regulation of multiple cell signaling pathways is the long noncoding RNAs (lncRNAs). These molecules have important implications in the regulation of multiple signaling pathways by interacting with various genes, affecting the transcription process, and finally, playing roles in posttranslational control of these genes. There is growing evidence that lncRNAs are involved in the process of breast cancer formation by effecting the aforementioned signaling pathways, and that this involvement can have significant diagnostic and prognostic values in clinical contexts. The present review aims to elicit the significance of lncRNAs in the regulation of cell signaling pathways, and the resulting changes in cell survival, proliferation, and invasion, which are the hallmarks of breast cancer.

Research progresses in roles of LncRNA and its relationships with breast cancer

Some progresses have been made in research of long non-coding RNA (hereunder referred to as LncRNA) related to breast cancer. Lots of data about LncRNA transcription concerning breast cancer have been obtained from large-scale omics research (e.g. transcriptomes and chips). Some LncRNAs would become indices for detecting breast cancer and judging its development and prognosis. LncRNAs may affect genesis and development of breast cancer in multiple ways. Perhaps they could develop into potential targets for treating breast cancer if they are carcinogenic. Like those from other studies of breast cancer, many data gained from omics research remain to be validated by much experimental work. For instance, it is still necessary to demonstrate reliability of LncRNAs as indices for diagnosing breast cancer and judging its prognosis (particularly for various subtypes of breast cancer), effectiveness and feasibility of these genes for treating breast cancer as targets. In this paper, recent years’ literatures about LncRNAs which are related to breast cancer are summarized and sorted out to review the research progresses in relationships between LncRNAs and breast cancer.

The Impact of lncRNA Dysregulation on Clinicopathology and Survival of Breast Cancer: A Systematic Review and Meta-analysis

Dysregulation of multiple long non-coding RNAs (lncRNAs) was reported to play major roles in breast cancer (BC). Here we aimed to collect most of the relevant literature to assess the prognostic value of lncRNAs in BC. To this end, we systematically searched PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure (CNKI), and Wanfang to identify published articles on the associations of lncRNAs with clinicopathology and/or survival of BC. Via this searching, we identified 70 articles involving 9,307 BC patients and regarding 48 lncRNAs. The expression of 41 lncRNAs was related to one or more clinicopathological parameters of BC, including tumor size; lymph node metastasis; histological grade; TNM stage; and estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) statuses (p < 0.05). Dysregulation of 28 lncRNAs was associated with overall survival, and abnormal expression of 9 lncRNAs was linked to disease-free survival. Furthermore, the expression level of 3 lncRNAs was correlated with metastasis-free survival, 3 lncRNAs with relapse-free survival, and 3 lncRNAs with progression-free survival. Our analysis showed that multiple lncRNAs were significantly associated with BC clinicopathology and survival. A large-scale study is needed to verify the prognostic value of these lncRNAs in BC.

Deciphering the roles of lncRNAs in breast development and disease

Breast cancer is the second leading cause of cancer related deaths in women. It is therefore important to understand the mechanisms underlying breast cancer development as well as raises the need for enhanced, non-invasive strategies for novel prognostic and diagnostic methods. The emergence of long non-coding RNAs (lncRNAs) as potential key players in neoplastic disease has received considerable attention over the past few years. This relatively new class of molecular regulators has been shown from ongoing research to act as critical players for key biological processes. Deregulated expression levels of lncRNAs have been observed in a number of cancers including breast cancer. Furthermore, lncRNAs have been linked to breast cancer initiation, progression, metastases and to limit sensitivity to certain targeted therapeutics. In this review we provide an update on the lncRNAs associated with breast cancer and mammary gland development and illustrate the versatility of such lncRNAs in gene control, differentiation and development both in normal physiological conditions and in diseased states. We also highlight the therapeutic and diagnostic potential of lncRNAs in cancer.

Natural Antisense Transcripts: Molecular Mechanisms and Implications in Breast Cancers

Natural antisense transcripts are RNA sequences that can be transcribed from both DNA strands at the same locus but in the opposite direction from the gene transcript. Because strand-specific high-throughput sequencing of the antisense transcriptome has only been available for less than a decade, many natural antisense transcripts were first described as long non-coding RNAs. Although the precise biological roles of natural antisense transcripts are not known yet, an increasing number of studies report their implication in gene expression regulation. Their expression levels are altered in many physiological and pathological conditions, including breast cancers. Among the potential clinical utilities of the natural antisense transcripts, the non-coding|coding transcript pairs are of high interest for treatment. Indeed, these pairs can be targeted by antisense oligonucleotides to specifically tune the expression of the coding-gene. Here, we describe the current knowledge about natural antisense transcripts, their varying molecular mechanisms as gene expression regulators, and their potential as prognostic or predictive biomarkers in breast cancers.

Decoding the usefulness of non-coding RNAs as breast cancer markers

Although important advances in the management of breast cancer (BC) have been recently accomplished, it still constitutes the leading cause of cancer death in women worldwide. BC is a heterogeneous and complex disease, making clinical prediction of outcome a very challenging task. In recent years, gene expression profiling emerged as a tool to assist in clinical decision, enabling the identification of genetic signatures that better predict prognosis and response to therapy. Nevertheless, translation to routine practice has been limited by economical and technical reasons and, thus, novel biomarkers, especially those requiring non-invasive or minimally invasive collection procedures, while retaining high sensitivity and specificity might represent a significant development in this field. An increasing amount of evidence demonstrates that non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are aberrantly expressed in several cancers, including BC. miRNAs are of particular interest as new, easily accessible, cost-effective and non-invasive tools for precise management of BC patients because they circulate in bodily fluids (e.g., serum and plasma) in a very stable manner, enabling BC assessment and monitoring through liquid biopsies. This review focus on how ncRNAs have the potential to answer present clinical needs in the personalized management of patients with BC and comprehensively describes the state of the art on the role of ncRNAs in the diagnosis, prognosis and prediction of response to therapy in BC.

Current Status of Long Non-Coding RNAs in Human Breast Cancer

Breast cancer represents a major health burden in Europe and North America, as recently published data report breast cancer as the second leading cause of cancer related death in women worldwide. Breast cancer is regarded as a highly heterogeneous disease in terms of clinical course and biological behavior and can be divided into several molecular subtypes, with different prognosis and treatment responses. The discovery of numerous non-coding RNAs has dramatically changed our understanding of cell biology, especially the pathophysiology of cancer. Long non-coding RNAs (lncRNAs) are non-protein-coding transcripts >200 nucleotides in length. Several studies have demonstrated their role as key regulators of gene expression, cell biology and carcinogenesis. Deregulated expression levels of lncRNAs have been observed in various types of cancers including breast cancer. lncRNAs are involved in cancer initiation, progression, and metastases. In this review, we summarize the recent literature to highlight the current status of this class of long non-coding lncRNAs in breast cancer.

Long noncoding RNAs as novel predictors of survival in human cancer: a systematic review and meta-analysis

Background

Expression of various long noncoding RNAs (lncRNAs) may affect cancer prognosis. Here, we aim to gather and examine all evidence on the potential role of lncRNAs as novel predictors of survival in human cancer.

Methods

We systematically searched through PubMed, to identify all published studies reporting on the association between any individual lncRNA or group of lncRNAs with prognosis in human cancer (death or other clinical outcomes). Where appropriate, we then performed quantitative synthesis of those results using meta-analytic methods to identify the true effect size of lncRNAs on cancer prognosis. The reliability of those results was then examined using measures of heterogeneity and testing for selective reporting biases.

Results

Three hundred ninety-two studies were screened to eventually identify 111 eligible studies on 127 datasets. In total, these represented 16,754 independent participants pertaining to 53 individual and 6 grouped lncRNAs within a total of 19 cancer sites. Overall, 83 % of the studies we identified addressed overall survival and 32 % of the studies addressed recurrence-free survival. For overall survival, 96 % (88/92) of studies identified a statistically significant association of lncRNA expression to prognosis. Meta-analysis of 6 out of 7 lncRNAs for which three or more studies were available, identified statistically significant associations with overall survival. The lncRNA HOTAIR was by far the most broadly studied lncRNA (n = 29; of 111 studies) and featured a summary hazard ratio (HR) of 2.22 (95 % confidence interval (CI), 1.86–2.65) with modest heterogeneity (I² = 49 %; 95 % CI, 14–79 %). Prominent excess significance was demonstrated across all meta-analyses (p-value = 0.0003), raising the possibility of substantial selective reporting biases.

Conclusions

Multiple lncRNAs have been shown to be strongly associated with prognosis in diverse cancers, but substantial bias cannot be excluded in this field and larger studies are needed to understand whether these prognostic information may eventually be useful.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-016-0535-1) contains supplementary material, which is available to authorized users.

LncRNAs and cancer

Long non-coding RNAs (lncRNAs) are a group of non-coding RNAs composed of >200 nucleotides. Recent studies have revealed that lncRNAs exert an important role in the development and progression of cancer. In this review, the involvement of the most extensively investigated lncRNAs in cancers of the digestive, respiratory, reproductive, urinary and central nervous systems are discussed. LncRNAs function via molecular and biochemical mechanisms that include cis- and trans-regulation of gene expression, epigenetic modulation in the nucleus and post-transcriptional control in the cytoplasm. Although the detailed biological functions and molecular mechanisms of the majority of lncRNAs remain to be elucidated, this review aims to provide a novel insight into the diagnosis and treatment of cancer using lncRNAs.

Comprehensive transcriptome analysis identifies novel molecular subtypes and subtype-specific RNAs of triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a highly heterogeneous group of cancers, and molecular subtyping is necessary to better identify molecular-based therapies. While some classifiers have been established, no one has integrated the expression profiles of long noncoding RNAs (lncRNAs) into such subtyping criterions. Considering the emerging important role of lncRNAs in cellular processes, a novel classification integrating transcriptome profiles of both messenger RNA (mRNA) and lncRNA would help us better understand the heterogeneity of TNBC.

METHODS

Using human transcriptome microarrays, we analyzed the transcriptome profiles of 165 TNBC samples. We used k-means clustering and empirical cumulative distribution function to determine optimal number of TNBC subtypes. Gene Ontology (GO) and pathway analyses were applied to determine the main function of the subtype-specific genes and pathways. We conducted co-expression network analyses to identify interactions between mRNAs and lncRNAs.

RESULTS

All of the 165 TNBC tumors were classified into four distinct clusters, including an immunomodulatory subtype (IM), a luminal androgen receptor subtype (LAR), a mesenchymal-like subtype (MES) and a basal-like and immune suppressed (BLIS) subtype. The IM subtype had high expressions of immune cell signaling and cytokine signaling genes. The LAR subtype was characterized by androgen receptor signaling. The MES subtype was enriched with growth factor signaling pathways. The BLIS subtype was characterized by down-regulation of immune response genes, activation of cell cycle, and DNA repair. Patients in this subtype experienced worse recurrence-free survival than others (log rank test, P = 0.045). Subtype-specific lncRNAs were identified, and their possible biological functions were predicted using co-expression network analyses.

CONCLUSIONS

We developed a novel TNBC classification system integrating the expression profiles of both mRNAs and lncRNAs and determined subtype-specific lncRNAs that are potential biomarkers and targets. If further validated in a larger population, our novel classification system could facilitate patient counseling and individualize treatment of TNBC.

A brief review on long noncoding RNAs: a new paradigm in breast cancer pathogenesis, diagnosis and therapy

With the development of technologies such as microarrays and RNA deep sequencing, long noncoding RNAs (lncRNAs) have become the focus of cancer investigations. LncRNAs, nonprotein-coding RNA molecules longer than 200 nucleotides, are dysregulated in many human diseases, especially in cancers. Recent studies have demonstrated that lncRNAs play a key regulatory role in gene expression and cancer biology through diverse mechanisms, including chromosome remodeling and transcriptional and post-transcriptional modifications. The expression levels of specific lncRNAs are attributed to prognosis, metastasis, and recurrence of cancer. LncRNAs are often involved in various biological processes, such as regulation of alternative splicing of mRNA, protein activity, and epigenetic modulation or silencing of the microRNAs, via discrete mechanisms. Deregulated levels of lncRNAs are shown in diverse tumors, including breast cancer. Based on latest research data, the tissue-specific expression signature of lncRNAs may represent the potential to discriminate normal and tumor tissue or even the different stages of breast cancer, which makes them clinically beneficial as possible biomarkers in the diagnosis and prognosis or therapeutic targets. In this brief review, we summarize some recent researches in the context of lncRNAs' roles in breast cancer pathogenesis and their potential to serve as diagnostic, predictive, and prognostic biomarkers and novel targets for breast cancer treatment.

Long noncoding RNA CCAT2 promotes breast tumor growth by regulating the Wnt signaling pathway

In addition to protein-coding genes, the human genome makes a large amount of noncoding RNAs, including microRNAs and long noncoding RNAs (lncRNAs). Emerging evidence indicates that lncRNAs could have a critical role in the regulation of cellular processes such as cell growth and apoptosis as well as cancer progression and metastasis. The lncRNA CCAT2 is dysregulated in several cancers such as colon cancer, non-small cell lung cancer, esophageal squamous cell carcinoma, gastric cancer, and breast cancer; however, the contributions of CCAT2 to breast cancer remain largely unknown. In the current paper, we first confirmed the high expression level of CCAT2 in breast cancer tissues and breast cancer cell lines by reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay, and we further analyzed the relationship between CCAT2 expression and clinical prognostic factors. Also, the biological function of CCAT2 was explored and the results showed silencing of CCAT2 could suppress cell growth in vitro and tumor formation in vivo. Finally, our results revealed that the abnormal expression of CCAT2 could influence the Wnt signaling pathway. In conclusion, lncRNA CCAT2 might be considered as a novel molecule involved in breast cancer development, which provides a potential therapeutic target for breast cancer.

LncRNAs and neoplasia

Long noncoding RNAs are emerging as new mediators of tumorigenesis by virtue of their various functions and their capacity to induce different mechanisms as a result of their wide spectrum of interactions. They play critical roles in a broad range of cellular processes including regulation of gene expression, imprinting, chromatin modification, transcription and posttranslational processing. Expression and activity of lncRNAs are deregulated in several types of human cancer. Impairment of lncRNA activity may affect key components of the cellular gene regulatory networks and is associated with deregulation of a large number of cellular oncogenic pathways. LncRNAs are also being evaluated as diagnostic and prognostic biomarkers and may provide targets for potential therapeutic applications. An improved understanding of the roles played by lncRNAs in cancer will lead to more effective therapeutic strategies. In this review we summarize the current knowledge on lncRNAs and their function as mediators of tumor development.