Mitotically associated long non-coding RNA, MANCR regulates cell cycle in triple negative breast cancer cells
Ontology highlight
ABSTRACT: Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype that is difficult to treat as it is unresponsive to hormone-therapy; therefore, it is imperative to identify novel, targetable regulators of progression in TNBC. Long non-coding RNAs (lncRNAs) are important regulators in breast cancer and have great potential as therapeutic targets; however, little is known about how the majority of lncRNAs function within TNBC cells. In this study, we identify a novel lncRNA, MANCR (LINC00704), which is upregulated in TNBC cells and breast cancer patient samples. Depletion of MANCR in TNBC cells results in a significant decrease in cell proliferation and viability with a concomitant increase in DNA damage. Transcriptome-wide sequencing following MANCR knockdown reveals significant differences in the expression of >2000 genes, and gene set enrichment analysis identifies changes in multiple categories related to cell cycle regulation. Furthermore, MANCR expression is highest in mitotic cells by both RT-qPCR and RNA in situ hybridization. Consistent with a possible role in cell cycle regulation, MANCR-depleted cells have a lower mitotic index and a higher incidence of defective cytokinesis. Taken together, our data reveal a role for the novel lncRNA, MANCR (mitotically-associated long non-coding RNA), in cell cycle regulation of aggressive breast cancer, and identify it as a potential therapeutic target.
Project description:Long non-coding RNAs (lncRNAs) are involved in cancer progression. In this study, the lncRNA profiling were analyzed in chemoresistant and sensitive breast cancer cells. We found a group of dysregulated lncRNAs in chemoresistant cells. Expression of dysregulated lncRNAs are correlated with dysregulated mRNAs, and enriched in GO and KEGG pathways related with cancer progression and chemoresistance development. Within those lncRNA-mRNA interactions, some lncRNAs may cis-regulate neighboring protein coding genes and involved in chemoresistance. The lncRNA NONHSAT028712 was then validated to regulate nearby CDK2 and interfere with cell cycle and chemoresistance. Furthermore, we identified another group of lncRNAs trans-regulated gene expression via interacting with different transcription factors (TF). Whereby NONHSAT057282 and NONHSAG023333 was found to modulate chemoresistance and most likely interacted with ELF1 and E2F1 respectively. In conclusion, this study reported for the first time the lncRNA expression patterns in chemoresistant breast cancer cells, and provided a group of novel lncRNA targets in mediating chemoresistance development in both cis- and trans- action mode. MCF-7/ADM replication 3 times, MCF-7/WT replication 3 times
Project description:Long non-coding RNAs (lncRNAs) represent a novel class of anti-cancer therapeutic targets. Hypoxia-induced lncRNAs are associated with the aggressive tumor phenotypes and might serve as putative drug targets. Here, we unraveled lncRNAs whose expression is upregulated in hypoxic breast tumors. One of the hypoxia-induced lncRNA, LAS3 (LncRNA Associated to SART3), is commonly upregulated not only in all breast cancer subtypes, but also in several types of epithelial cancers. LAS3 expression is driven by the stress-induced JNK/c-JUN pathway, which is frequently activated in human cancer. By pull down of LAS3 coupled to mass spectrometry-based proteomics, we identified SART3, a component of the splicing machinery, as a LAS3-interacting partner. In a second proteomics experiment, pull down of SART3-containing complexes from MCF10A cells treated with either scramble, or LAS3-specific GapmeRs showed that LAS3 regulates splicing efficiency by triggering SART3 dissociation from the U4/U6 snRNP during the recycling phase of the spliceosome cycle. Finally, differential shotgun analysis of MDA-MB-231/tet-shLAS3 cells allowed us to quantify expression of 2,940 proteins. Here, genes with significant intron retention showed decreased protein expression levels, indicating that widespread LAS3-mediated intron retention disrupts open reading frame integrity leading to stochastic decrease of protein expression and decreased fitness of cancer cells. Together, our data show that LAS3 is essential for growth of LAS3-positive triple negative breast tumors and indicate that LAS3 inhibition might be a suitable therapeutic approach for breast cancer treatment.
Project description:We investigated the expression patterns of lncRNAs and mRNAs from TNBC tissues and matched histological normal breast tissues with Agilent Human lncRNA array V4.0 (4 × 180 K), which include 78,243 human lncRNAs and 30,215 coding transcripts. We identified 1,758 lncRNAs and 1,254 mRNAs that were differentially expressed (≥ 2-fold change), indicating that many lncRNAs are significantly upregulated or downregulated in TNBC. Among these, XR_250621.1 and NONHSAT011259 were the most unregulated and down regulated lncRNAs. qRT-PCR was employed to validate the microarray analysis findings, and results were consistent with the data from the microarrays. GO analysis and KEGG pathway analysis were applied to explore the potential lncRNAs functions, and some pathways including microtubule motor activity and DNA replication were identified in TNBC pathogenesis.
Project description:Triple-negative breast cancer (TNBC) has a relatively aggressive biological behavior and poor outcome. Our published study showed that PAI-1 could induce the migration and metastasis of TNBC cells. However, the underlying mechanism by which PAI-1 regulates TNBC metastasis has not been addressed. Using microarray analysis of lncRNA expression profiles, we identified a lncRNA SOX2-OT, which is by induced by PAI-1 and could function as an oncogenic lncRNA in TNBC.
Project description:The development of triple-negative breast cancers (TNBCs) – a subset of tumors with particularly aggressive pathogenesis – is critically regulated by certain tumor-microenvironment-associated cells called mesenchymal stem/stromal cells (MSCs), which we and others have shown promote TNBC progression by activating a multitude of signaling nodes that propagate malignant traits in neighboring cancer cells. Characterization of these signaling cascades will better our understanding of TNBC biology, and stands to bring about novel therapeutics that can eliminate the morbidity and mortality associated with advanced disease. Here, we particularly focused on an emerging family of non-coding RNAs – called long non-coding RNAs or lncRNAs – and utilized a MSC-supported TNBC progression model to identify specific lncRNAs of functional relevance to TNBC pathogenesis. We used Affymetrix arrays to identify the gene expression changes that breast cancer cells (in this case, MDA-MB-231 cells) exhibit as they interact with admixed human MSCs
Project description:Triple negative breast cancer (TNBC) represents a challenging tumor type due to their poor prognosis and limited treatment options. It is well recognize that clinical and molecular heterogeneity of TNBC is driven in part by mRNA and lncRNAs. To stratify TNBCs, we profiled mRNAs and lncRNA in 158 adjuvant TNBC tumors using an Affymetrix microarray platform. Lehmann clustering analysis allowed us to identify TNBC subtypes featuring unique lncRNA expression patterns, disease free and overall survival rates and particular gene ontology enrichments (performed with GSEA algorithm).
Project description:Triple negative breast cancer (TNBC) represents a challenging tumor type due to their poor prognosis and limited treatment options. It is well recognize that clinical and molecular heterogeneity of TNBC is driven in part by mRNA and lncRNAs. To stratify TNBCs, we profiled mRNAs and lncRNA in 158 adjuvant TNBC tumors using an Affymetrix microarray platform. Lehmann clustering analysis allowed us to identify TNBC subtypes featuring unique lncRNA expression patterns, disease free and overall survival rates and particular gene ontology enrichments (performed with GSEA algorithm).
Project description:To develop and validate novel multigene signatures to facilitate individualized treatment of TNBC patients By integrating expression profiles of messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs). We analysed 165 TNBC samples and 33 paired normal breast tissues using transcriptome microarrays. Tumor-specific mRNAs and lncRNAs were identified and correlated with patientsâ?? recurrence-free survival (RFS). Using Cox regression model, we built two multigene signatures incorporating mRNAs and lncRNAs. The prognostic and predictive accuracy of the signatures were tested in a training set of 165 TNBC patients and validated in another 101 TNBC patients.
Project description:Long non-coding RNAs (lncRNAs) are involved in cancer progression. In this study, the lncRNA profiling were analyzed in chemoresistant and sensitive breast cancer cells. We found a group of dysregulated lncRNAs in chemoresistant cells. Expression of dysregulated lncRNAs are correlated with dysregulated mRNAs, and enriched in GO and KEGG pathways related with cancer progression and chemoresistance development. Within those lncRNA-mRNA interactions, some lncRNAs may cis-regulate neighboring protein coding genes and involved in chemoresistance. The lncRNA NONHSAT028712 was then validated to regulate nearby CDK2 and interfere with cell cycle and chemoresistance. Furthermore, we identified another group of lncRNAs trans-regulated gene expression via interacting with different transcription factors (TF). Whereby NONHSAT057282 and NONHSAG023333 was found to modulate chemoresistance and most likely interacted with ELF1 and E2F1 respectively. In conclusion, this study reported for the first time the lncRNA expression patterns in chemoresistant breast cancer cells, and provided a group of novel lncRNA targets in mediating chemoresistance development in both cis- and trans- action mode.
Project description:To identify novel TNBC-relevant lncRNAs, we performed lncRNA microarray analysis using 5 TNBC tissues and their matched adjacent non-cancerous tissues by Arraystar Human LncRNA Microarray V3.0.