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.

ANRIL, a long noncoding RNA (lncRNA), has recently been reported to have a direct role in recruiting polycomb repressive complexes PRC2 and PRC1 to regulate the expression of the p15/CDKN2B-p16/CDKN2A-p14/ARF gene cluster. Expression analysis of ANRIL, EZH2, SUZ12, EED, JARID2, CBX7, BMI1, p16, p15, and p14/ARF genes was evaluated in a large cohort of invasive breast carcinomas (IBC, n = 456) by qRT-PCR and immunohistochemistry (IHC) was performed on CBX7, EZH2, p14, p15, p16, H3K27me3, and H3K27ac. We observed significant overexpression in IBCs of ANRIL (19.7%) and EZH2 (77.0%) and an underexpression of CBX7 (39.7%). Correlations were identified between these genes, their expression patterns, and several classical clinical and pathologic parameters, molecular subtypes, and patient outcomes, as well as with proliferation, epithelial–mesenchymal transition, and breast cancer stem cell markers. Multivariate analysis revealed that combined EZH2/CBX7 status is an independent prognostic factor (P = 0.001). In addition, several miRNAs negatively associated with CBX7 underexpression and EZH2 overexpression. These data demonstrate a complex pattern of interactions between lncRNA ANRIL, several miRNAs, PRC2/PRC1 subunits, and p15/CDKN2B-p16/CDKN2A-p14/ARF locus and suggest that their expression should be considered together to evaluate antitumoral drugs, in particular the BET bromodomain inhibitors. Implications: This study suggests that the global pattern of expression rather than expression of individual family members should be taken into account when defining functionality of repressive Polycomb complexes and therapeutic targeting potential. Mol Cancer Res; 14(7); 623–33. ©2016 AACR.

Background: Epigenetic deregulation is considered as a new hallmark of cancer. The long non-coding RNA MALAT1 has been implicated in several cancers; however, its role in breast cancer is still little known. Methods: We used RT–PCR, in situ hybridisation, and RPPA methods to quantify (i) the full-length (FL) and an alternatively spliced variant (Δsv) of MALAT1, and (ii) a panel of transcripts and proteins involved in MALAT1 pathways, in a large series of breast tumours from patients with known clinical/pathological status and long-term outcome. Results: MALAT1 was overexpressed in 14% (63/446) of the breast tumours. MALAT1-overexpressed tumour epithelial cells showed marked diffuse nuclear signals and numerous huge nuclear speckles. Screening of the dbEST database led to the identification of Δsv-MALAT1, a major alternatively spliced MALAT1 transcript, with a very different expression pattern compared with FL-MALAT1. This alternative Δsv-MALAT1 transcript was mainly underexpressed (18.8%) in our breast tumour series. Multivariate analysis showed that alternative Δsv-MALAT1 transcript is an independent prognostic factor. Δsv-MALAT1 expression was associated with alterations of the pre-mRNAs alternative splicing machinery, and of the Drosha-DGCR8 complex required for non-coding RNA biogenesis. Alternative Δsv-MALAT1 transcript expression was associated to YAP protein status and with an activation of the PI3K-AKT pathway. Conclusions: Our results reveal a complex expression pattern of various MALAT1 transcript variants in breast tumours, and suggest that this pattern of expressions should be taken into account to evaluate MALAT1 as predictive biomarker and therapeutic target.

Reciprocal interactions between cancer cells and tumor microenvironment (TME) are crucial events in tumor progression and metastasis. Pervasive stromal reprogramming of TME modifies numerous cellular functions, including extracellular matrix (ECM) stiffness, inflammation, and immunity. These environmental factors allow selection of more aggressive cells that develop adaptive strategies associating plasticity and epithelial‐mesenchymal transition (EMT), stem‐like phenotype, invasion, immunosuppression, and resistance to therapies. EMT is a morphomolecular process that endows epithelial tumor cells with mesenchymal properties, including reduced adhesion and increased motility. Numerous studies have demonstrated involvement of noncoding RNAs (ncRNAs), such as miRNAs and lncRNAs, in tumor initiation, progression, and metastasis. NcRNAs regulate every hallmark of cancer and have now emerged as new players in induction and regulation of EMT. The reciprocal regulatory interactions between ncRNAs, TME components, and cancer cells increase the complexity of gene expression and protein translation in cancer. Thus, deeper understanding of molecular mechanisms controlling EMT will not only shed light on metastatic processes of cancer cells, but enhance development of new therapies targeting metastasis. In this review, we will provide recent findings on the role of known ncRNAs relevant to EMT and cancer metastasis and discuss the role of the interaction between ncRNAs and TME as co‐drivers of EMT. Developmental Dynamics 247:405–431, 2018.