The lncRNA landscape of breast cancer reveals a role for DSCAM-AS1 in breast cancer progression

KHSRP has oncogenic functions and regulates the expression and alternative splicing of DNA repair genes in breast cancer MDA-MB-231 cells

Breast cancer has become the most common type of cancers worldwide. Its high prevalence and malignant features are associated with various environmental factors and molecules. The KH-type splicing regulatory protein (KHSRP) participates in the development of breast cancer, while the underlying mechanisms are largely unknown. In this study, we silenced KHSRP expression in MDA-MB-231 cells by small interfering RNA (siKHSRP), and then assessed its effects on cellular features. Finally, we performed whole transcriptome sequencing (RNA-seq) experiments to explore the downstream targets of KHSRP, and validated their changed pattern using quantitative polymerase chain reaction. We found KHSRP showed higher expression level and was associated with worse prognosis in breast cancer patients. In siKHSRP samples, the proliferation, invasion, and migration abilities were significantly repressed compared with negative control (NC) samples, while the apoptosis level was increased. By investigating the RNA-seq data, we found KHSRP globally regulates the expression and alternative splicing profiles of MDA-MB-231 cells by identifying 1632 differentially expressed genes (DEGs) and 1630 HKSRP-regulated AS events (RASEs). Functional enriched analysis of DEGs demonstrated that cilium assembly and movement and extracellular matrix organization pathways were specifically enriched in up DEGs, consistent with the repressed migration and invasion abilities in siKHSRP cells. Interestingly, the cell cycle and DNA damage and repair associated pathways were enriched in both down DEGs and RASE genes, suggesting that KHSRP may modulate cell proliferation by regulating genes in these pathways. Finally, we validated the changed expression and AS patterns of genes in cell cycle and DNA damage/repair pathways. Expression levels of BIRC5, CCNA2, CDK1, FEN1, FOXM1, PTTG1, and UHRF1 were downregulated in siKHSRP samples. The AS patterns of PARK7, ERCC1, CENPX, and UBE2A were also dysregulated in siKHSRP samples and confirmed PCR experiments. In summary, our study comprehensively explored the downstream targets and their functions of KHSRP in breast cancer cells, highlighting the molecular mechanisms of KHSRP on the oncogenic features of breast cancer. The identified molecular targets could be served as potential therapeutic targets for breast cancer in future.

LINC01806 Promotes Breast Cancer Growth and Metastasis via Sponging miR-1286 to Disinhibit ZEB1 Expression

Breast cancer (BC) is the most abundant and aggressive cancer that impacts millions of women with poorly understood mechanisms. Here, we aimed to investigate the function of LINC01806 in BC development. Human BC tissues and nearby normal specimens were taken from diagnosed BC patients. The expression levels of LINC01806, miR-1286, ZEB1, and EMT-related markers were evaluated by qRT-PCR and western blotting. FISH was used to visualize the subcellular localization of LINC01806. The viability, proliferation, migration and invasion capacities of BC cells were assessed by MTT, colony formation, and transwell assays. Interactions among LINC01806, miR-1286 and ZEB1 were validated by dual luciferase assay. The unpaired Student t-test (for two groups) or one-way ANOVA following with Tukey post-hoc test (for more than three groups) was employed for statistical analysis. LINC01806 level was elevated in BC tissues. Knockdown of LINC01806 suppressed EMT process and BC cell proliferation, migration, and invasion. LINC01806 co-localized and directly bound with miR-1286 in the cytoplasm. MiR-1286 inhibitor blocked the effects of LINC01806 knockdown on BC cell EMT, proliferation and migration. MiR-1286 targeted ZEB1 and overexpression of ZEB1 blocked the regulatory functions of miR-1286 mimics in BC. LINC01806 facilitates EMT and accelerates BC cell proliferation, migration, and invasion via acting as miR-1286 sponge to disinhibit ZEB1 expression.

Long non-coding RNA SOX2OT in tamoxifen-resistant breast cancer

Hormone receptor (HR)-positive breast cancer can become aggressive after developing hormone-treatment resistance. This study elucidated the role of long non-coding RNA (lncRNA) SOX2OT in tamoxifen-resistant (TAMR) breast cancer and its potential interplay with the tumor microenvironment (TME). TAMR breast cancer cell lines TAMR-V and TAMR-H were compared with the luminal type A cell line (MCF-7). LncRNA expression was assessed via next-generation sequencing, RNA extraction, lncRNA profiling, and quantitative RT-qPCR. SOX2OT overexpression effects on cell proliferation, migration, and invasion were evaluated using various assays. SOX2OT was consistently downregulated in TAMR cell lines and TAMR breast cancer tissue. Overexpression of SOX2OT in TAMR cells increased cell proliferation and cell invasion. However, SOX2OT overexpression did not significantly alter SOX2 levels, suggesting an independent interaction within TAMR cells. Kaplan-Meier plot analysis revealed an inverse relationship between SOX2OT expression and prognosis in luminal A and B breast cancers. Our findings highlight the potential role of SOX2OT in TAMR breast cancer progression. The downregulation of SOX2OT in TAMR breast cancer indicates its involvement in resistance mechanisms. Further studies should explore the intricate interactions between SOX2OT, SOX2, and TME in breast cancer subtypes.

Estrogen-Induced LncRNA, LINC02568, Promotes Estrogen Receptor-Positive Breast Cancer Development and Drug Resistance Through Both In Trans and In Cis Mechanisms

Endocrine therapy is the frontline treatment for estrogen receptor (ER) positive breast cancer patients. However, the primary and acquired resistance to endocrine therapy drugs remain as a major challenge in the clinic. Here, this work identifies an estrogen-induced lncRNA, LINC02568, which is highly expressed in ER-positive breast cancer and functional important in cell growth in vitro and tumorigenesis in vivo as well as endocrine therapy drug resistance. Mechanically, this work demonstrates that LINC02568 regulates estrogen/ERα-induced gene transcriptional activation in trans by stabilizing ESR1 mRNA through sponging miR-1233-5p in the cytoplasm. Meanwhile, LINC02568 contributes to tumor-specific pH homeostasis by regulating carbonic anhydrase CA12 in cis in the nucleus. The dual functions of LINC02568 together contribute to breast cancer cell growth and tumorigenesis as well as endocrine therapy drug resistance. Antisense oligonucleotides (ASO) targeting LINC02568 significantly inhibits ER-positive breast cancer cell growth in vitro and tumorigenesis in vivo. Furthermore, combination treatment with ASO targeting LINC02568 and endocrine therapy drugs or CA12 inhibitor U-104 exhibits synergistic effects on tumor growth. Taken together, the findings reveal the dual mechanisms of LINC02568 in regulating ERα signaling and pH homeostasis in ER-positive breast cancer, and indicated that targeting LINC02568 might represent a potential therapeutic avenue in the clinic.

Deciphering the mechanisms of action of progesterone in breast cancer

A practice-changing, randomized, controlled clinical study established that preoperative hydroxyprogesterone administration improves disease-free and overall survival in patients with node-positive breast cancer. This research perspective summarizes evidences from our studies that preoperative hydroxyprogesterone administration may improve disease-free and overall survival in patients with node-positive breast cancer by modulating cellular stress response and negative regulation of inflammation. Non-coding RNAs, particularly DSCAM-AS1, play a regulatory role in this process, along with the upregulation of the kinase gene SGK1 and activation of the SGK1/AP-1/NDRG1 axis. Progesterone-induced modification of the progesterone receptor and estrogen receptor genomic binding pattern is also involved in orchestrating estrogen signaling in breast cancer, preventing cell migration and invasion, and improving patient outcomes. We also highlight the role of progesterone in endocrine therapy resistance, which could lead to novel treatment options for patients with hormone receptor-positive breast cancer and for those who develop resistance to traditional endocrine therapies.

The Clinical Utility of lncRNAs and Their Application as Molecular Biomarkers in Breast Cancer

Given their tumor-specific and stage-specific gene expression, long non-coding RNAs (lncRNAs) have demonstrated to be potential molecular biomarkers for diagnosis, prognosis, and treatment response. Particularly, the lncRNAs DSCAM-AS1 and GATA3-AS1 serve as examples of this because of their high subtype-specific expression profile in luminal B-like breast cancer. This makes them candidates to use as molecular biomarkers in clinical practice. However, lncRNA studies in breast cancer are limited in sample size and are restricted to the determination of their biological function, which represents an obstacle for its inclusion as molecular biomarkers of clinical utility. Nevertheless, due to their expression specificity among diseases, such as cancer, and their stability in body fluids, lncRNAs are promising molecular biomarkers that could improve the reliability, sensitivity, and specificity of molecular techniques used in clinical diagnosis. The development of lncRNA-based diagnostics and lncRNA-based therapeutics will be useful in routine medical practice to improve patient clinical management and quality of life.

Long non‑coding RNA DSCAM‑AS1 functions as an oncogene in thyroid cancer via regulating miR‑211

Long non-coding RNA Down syndrome cell adhesion molecule-antisense 1 (DSCAM-AS1) has been reported to play key roles in the progression and initiation of several cancer types. However, the various functional roles of DSCAM-AS1 in thyroid cancer tumorigenesis remain largely elusive. In the present study, the expression of DSCAM-AS1 was examined in thyroid cancer tissues and cell lines. Cell Counting Kit-8, wound healing, Transwell and clonogenic assays were conducted to detect cell proliferation, migration, invasion and colony formation, respectively. The association of DSCAM-AS1 with microRNA 211 (miR-211) was determined by luciferase reporter assay. It was found that the expression of DSCAM-AS1 was upregulated in thyroid cancer cells and tissues. Furthermore, enhanced DSCAM-AS1 expression was positively associated with lymph node metastasis and tumor-node-metastasis stage. Functional experiments demonstrated that DSCAM-AS1 knockdown inhibited the migration, proliferation and invasion of TPC-1 cells. Mechanistically, DSCAM-AS1 could bind to miR-211. Prevention of miR-211 by a miR-211 inhibitor reversed the effect of DSCAM-AS1 depletion in thyroid cancer tumorigenesis. Briefly, the current findings suggested that knockdown of DSCAM-AS1 suppressed the tumorigenesis of thyroid cancer via regulating miR-211, suggesting that DSCAM-AS1 may be a favorable therapeutic target for thyroid cancer.

Non-Coding RNAs Modulating Estrogen Signaling and Response to Endocrine Therapy in Breast Cancer

The largest part of human DNA is transcribed into RNA that does not code for proteins. These non-coding RNAs (ncRNAs) are key regulators of protein-coding gene expression and have been shown to play important roles in health, disease and therapy response. Today, endocrine therapy of ERα-positive breast cancer (BC) is a successful treatment approach, but resistance to this therapy is a major clinical problem. Therefore, a deeper understanding of resistance mechanisms is important to overcome this resistance. An increasing amount of evidence demonstrate that ncRNAs affect the response to endocrine therapy. Thus, ncRNAs are considered versatile biomarkers to predict or monitor therapy response. In this review article, we intend to give a summary and update on the effects of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) on estrogen signaling in BC cells, this pathway being the target of endocrine therapy, and their role in therapy resistance. For this purpose, we reviewed articles on these topics listed in the PubMed database. Finally, we provide an assessment regarding the clinical use of these ncRNA types, particularly their circulating forms, as predictive BC biomarkers and their potential role as therapy targets to overcome endocrine resistance.

Screening potential lncRNA biomarkers for breast cancer and colorectal cancer combining random walk and logistic matrix factorization

Breast cancer and colorectal cancer are two of the most common malignant tumors worldwide. They cause the leading causes of cancer mortality. Many researches have demonstrated that long noncoding RNAs (lncRNAs) have close linkages with the occurrence and development of the two cancers. Therefore, it is essential to design an effective way to identify potential lncRNA biomarkers for them. In this study, we developed a computational method (LDA-RWLMF) by integrating random walk with restart and Logistic Matrix Factorization to investigate the roles of lncRNA biomarkers in the prognosis and diagnosis of the two cancers. We first fuse disease semantic and Gaussian association profile similarities and lncRNA functional and Gaussian association profile similarities. Second, we design a negative selection algorithm to extract negative LncRNA-Disease Associations (LDA) based on random walk. Third, we develop a logistic matrix factorization model to predict possible LDAs. We compare our proposed LDA-RWLMF method with four classical LDA prediction methods, that is, LNCSIM1, LNCSIM2, ILNCSIM, and IDSSIM. The results from 5-fold cross validation on the MNDR dataset show that LDA-RWLMF computes the best AUC value of 0.9312, outperforming the above four LDA prediction methods. Finally, we rank all lncRNA biomarkers for the two cancers after determining the performance of LDA-RWLMF, respectively. We find that 48 and 50 lncRNAs have the highest association scores with breast cancer and colorectal cancer among all lncRNAs known to associate with them on the MNDR dataset, respectively. We predict that lncRNAs HULC and HAR1A could be separately potential biomarkers for breast cancer and colorectal cancer and need to biomedical experimental validation.

Functional Relationships between Long Non-Coding RNAs and Estrogen Receptor Alpha: A New Frontier in Hormone-Responsive Breast Cancer Management

In the complex and articulated machinery of the human genome, less than 2% of the transcriptome encodes for proteins, while at least 75% is actively transcribed into non-coding RNAs (ncRNAs). Among the non-coding transcripts, those ≥200 nucleotides long (lncRNAs) are receiving growing attention for their involvement in human diseases, particularly cancer. Genomic studies have revealed the multiplicity of processes, including neoplastic transformation and tumor progression, in which lncRNAs are involved by regulating gene expression at epigenetic, transcriptional, and post-transcriptional levels by mechanism(s) that still need to be clarified. In breast cancer, several lncRNAs were identified and demonstrated to have either oncogenic or tumor-suppressive roles. The functional understanding of the mechanisms of lncRNA action in this disease could represent a potential for translational applications, as these molecules may serve as novel biomarkers of clinical use and potential therapeutic targets. This review highlights the relationship between lncRNAs and the principal hallmark of the luminal breast cancer phenotype, estrogen receptor α (ERα), providing an overview of new potential ways to inhibit estrogenic signaling via this nuclear receptor toward escaping resistance to endocrine therapy.

High expression of RNF169 is associated with poor prognosis in pancreatic adenocarcinoma by regulating tumour immune infiltration

Background: Pancreatic adenocarcinoma (PAAD) is a highly deadly and aggressive tumour with a poor prognosis. However, the prognostic value of RNF169 and its related mechanisms in PAAD have not been elucidated. In this study, we aimed to explore prognosis-related genes, especially RNF169 in PAAD and to identify novel potential prognostic predictors of PAAD. Methods: The GEPIA and UALCAN databases were used to investigate the expression and prognostic value of RNF169 in PAAD. The correlation between RNF169 expression and immune infiltration was determined by using TIMER and TISIDB. Correlation analysis with starBase was performed to identify a potential regulatory axis of lncRNA-miRNA-RNF169. Results: The data showed that the level of RNF169 mRNA expression in PAAD tissues was higher than that in normal tissues. High RNF169 expression was correlated with poor prognosis in PAAD. In addition, analysis with the TISIDB and TIMER databases revealed that RNF169 expression was positively correlated with tumour immune infiltration in PAAD. Correlation analysis suggested that the long non-coding RNA (lncRNA) AL049555.1 and the microRNA (miRNA) hsa-miR-324-5p were involved in the expression of RNF169, composing a potential regulatory axis to control the progression of PAAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that RNF169 plays a role in PAAD through pathways such as TNF, Hippo, JAK-STAT and Toll-like receptor signaling. Conclusion: In summary, the upregulation of RNF169 expression mediated by ncRNAs might influence immune cell infiltration in the microenvironment; thus, it can be used as a prognostic biomarker and a potential therapeutic target in PAAD.

HEGANLDA: A Computational Model for Predicting Potential Lncrna-Disease Associations Based On Multiple Heterogeneous Networks

Long non-coding RNAs (lncRNAs) play vital regulatory roles in many human complex diseases, however, the number of validated lncRNA-disease associations is notable rare so far. How to predict potential lncRNA-disease associations precisely through computational methods remains challenging. In this study, we proposed a novel method, LDVCHN (LncRNA-Disease Vector Calculation Heterogeneous Networks), and also developed the corresponding model, HEGANLDA (Heterogeneous Embedding Generative Adversarial Networks LncRNA-Disease Association), for predicting potential lncRNA-disease associations. In HEGANLDA, the graph embedding algorithm (HeGAN) was introduced for mapping all nodes in the lncRNA-miRNA-disease heterogeneous network into the low-dimensional vectors which severed as the inputs of LDVCHN. HEGANLDA effectively adopted the XGBoost (eXtreme Gradient Boosting) classifier, which was trained by the low-dimensional vectors, to predict potential lncRNA-disease associations. The 10-fold cross-validation method was utilized to evaluate the performance of our model, our model finally achieved an area under the ROC curve of 0.983. According to the experiment results, HEGANLDA outperformed any one of five current state-of-the-art methods. To further evaluate the effectiveness of HEGANLDA in predicting potential lncRNA-disease associations, both case studies and robustness tests were performed and the results confirmed its effectiveness and robustness. The source code and data of HEGANLDA are available at https://github.com/HEGANLDA/HEGANLDA.

TLSEA: a tool for lncRNA set enrichment analysis based on multi-source heterogeneous information fusion

Long non-coding RNAs (lncRNAs) play an important regulatory role in gene transcription and post-transcriptional modification, and lncRNA regulatory dysfunction leads to a variety of complex human diseases. Hence, it might be beneficial to detect the underlying biological pathways and functional categories of genes that encode lncRNA. This can be carried out by using gene set enrichment analysis, which is a pervasive bioinformatic technique that has been widely used. However, accurately performing gene set enrichment analysis of lncRNAs remains a challenge. Most conventional enrichment analysis methods have not exhaustively included the rich association information among genes, which usually affects the regulatory functions of genes. Here, we developed a novel tool for lncRNA set enrichment analysis (TLSEA) to improve the accuracy of the gene functional enrichment analysis, which extracted the low-dimensional vectors of lncRNAs in two functional annotation networks with the graph representation learning method. A novel lncRNA-lncRNA association network was constructed by merging lncRNA-related heterogeneous information obtained from multiple sources with the different lncRNA-related similarity networks. In addition, the random walk with restart method was adopted to effectively expand the lncRNAs submitted by users according to the lncRNA-lncRNA association network of TLSEA. In addition, a case study of breast cancer was performed, which demonstrated that TLSEA could detect breast cancer more accurately than conventional tools. The TLSEA can be accessed freely at http://www.lirmed.com:5003/tlsea.

Progesterone modulates the DSCAM-AS1/miR-130a/ESR1 axis to suppress cell invasion and migration in breast cancer

BACKGROUND

A preoperative-progesterone intervention increases disease-free survival in patients with breast cancer, with an unknown underlying mechanism. We elucidated the role of non-coding RNAs in response to progesterone in human breast cancer.

METHODS

Whole transcriptome sequencing dataset of 30 breast primary tumors (10 tumors exposed to hydroxyprogesterone and 20 tumors as control) were re-analyzed to identify differentially expressed non-coding RNAs followed by real-time PCR analyses to validate the expression of candidates. Functional analyses were performed by genetic knockdown, biochemical, and cell-based assays.

RESULTS

We identified a significant downregulation in the expression of a long non-coding RNA, Down syndrome cell adhesion molecule antisense DSCAM-AS1, in response to progesterone treatment in breast cancer. The progesterone-induced expression of DSCAM-AS1 could be effectively blocked by the knockdown of progesterone receptor (PR) or treatment of cells with mifepristone (PR-antagonist). We further show that knockdown of DSCAM-AS1 mimics the effect of progesterone in impeding cell migration and invasion in PR-positive breast cancer cells, while its overexpression shows an opposite effect. Additionally, DSCAM-AS1 sponges the activity of miR-130a that regulates the expression of ESR1 by binding to its 3'-UTR to mediate the effect of progesterone in breast cancer cells. Consistent with our findings, TCGA analysis suggests that high levels of miR-130a correlate with a tendency toward better overall survival in patients with breast cancer.

CONCLUSION

This study presents a mechanism involving the DSCAM-AS1/miR-130a/ESR1 genomic axis through which progesterone impedes breast cancer cell invasion and migration. The findings highlight the utility of progesterone treatment in impeding metastasis and improving survival outcomes in patients with breast cancer.

Non-Coding RNAs of Extracellular Vesicles: Key Players in Organ-Specific Metastasis and Clinical Implications

Extracellular vesicles (EVs) are heterogeneous membrane-encapsulated vesicles released by most cells. They act as multifunctional regulators of intercellular communication by delivering bioactive molecules, including non-coding RNAs (ncRNAs). Metastasis is a major cause of cancer-related death. Most cancer cells disseminate and colonize a specific target organ via EVs, a process known as "organ-specific metastasis". Mounting evidence has shown that EVs are enriched with ncRNAs, and various EV-ncRNAs derived from tumor cells influence organ-specific metastasis via different mechanisms. Due to the tissue-specific expression of EV-ncRNAs, they could be used as potential biomarkers and therapeutic targets for the treatment of tumor metastasis in various types of cancer. In this review, we have discussed the underlying mechanisms of EV-delivered ncRNAs in the most common organ-specific metastases of liver, bone, lung, brain, and lymph nodes. Moreover, we summarize the potential clinical applications of EV-ncRNAs in organ-specific metastasis to fill the gap between benches and bedsides.

Evaluate the immune-related eRNA models and signature score to predict the response to immunotherapy in thyroid carcinoma

BACKGROUND

The functional alterations of eRNAs have been reported to be correlated with tumorigenesis. However, the roles of eRNAs in thyroid cancer (THCA) remain still unclear. This study aimed to construct an immune-related eRNA prognostic signature that could effectively predict the survival and prognosis for THCA.

METHODS

The Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify THCA-specific immune-related hub genes and immune-related eRNAs were obtained using Pearson correlation analysis. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression were conducted to construct an immune-related eRNA prognostic signature in training cohort, and the predictive capability was verified in test cohort and entire cohort. Kaplan-Meier analysis, principal component analysis (PCA), receiver operating characteristic (ROC) curves, and nomogram were used to validate the risk signature. Furthermore, CIBERSORT, ESTIMATE and ssGSEA were analyzed to explore the tumor immune microenvironment (TIME) of the risk signature, and the response of potential immunotherapeutic were also discussed.

RESULTS

A total of 125 immune-related eRNAs were obtained and 16 immune-related eRNAs were significantly correlated with overall survival (OS). A 9-immune-related eRNA prognostic signature was constructed, and the risk score was identified as an independent predictor. High-risk groups were associated with a poorer OS. Immune microenvironment analysis indicated that low risk score was correlated with higher immuneScore, high immune cell infiltration, and the better response of immunotherapy. Additionally, we also detected 9 immune-related eRNA expression levels in sixty-two matched tumorous and non-tumorous tissues using qRT-PCR analysis.

CONCLUSION

Our immune-related eRNA risk signature that was an independent prognostic factor was strongly correlated with the immune microenvironment and may be promising for the clinical prediction of prognosis and immunotherapeutic responses in THCA patients.

Small extracellular vesicles: from promoting pre-metastatic niche formation to therapeutic strategies in breast cancer

Breast cancer is the most common cancer in females, and to date, the mortality rate of breast cancer metastasis cannot be ignored. The metastasis of breast cancer is a complex, staged process, and the pattern of metastatic spread is not random. The pre-metastatic niche, as an organ-specific home for metastasis, is a favourable environment for tumour cell colonization. As detection techniques improve, the role of the pre-metastatic niche in breast cancer metastasis is being uncovered. sEVs (small extracellular vesicles) can deliver cargo, which is vital for the formation of pre-metastatic niches. sEVs participate in multiple aspects of creating a distant microenvironment to promote tumour invasion, including the secretion of inflammatory molecules, immunosuppression, angiogenesis and enhancement of vascular permeability, as well as regulation of the stromal environment. Here, we discuss the multifaceted mechanisms through which breast cancer-derived sEVs contribute to pre-metastatic niches. In addition, sEVs as biomarkers and antimetastatic therapies are also discussed, particularly their use in transporting exosomal microRNAs. The study of sEVs may provide insight into immunotherapy and targeted therapies for breast cancer, and we also provide an overview of their potential role in antitumour metastasis.

Subtype and cell type specific expression of lncRNAs provide insight into breast cancer

Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer.

Finding Lung-Cancer-Related lncRNAs Based on Laplacian Regularized Least Squares With Unbalanced Bi-Random Walk

Lung cancer is one of the leading causes of cancer-related deaths. Thus, it is important to find its biomarkers. Furthermore, there is an increasing number of studies reporting that long noncoding RNAs (lncRNAs) demonstrate dense linkages with multiple human complex diseases. Inferring new lncRNA-disease associations help to identify potential biomarkers for lung cancer and further understand its pathogenesis, design new drugs, and formulate individualized therapeutic options for lung cancer patients. This study developed a computational method (LDA-RLSURW) by integrating Laplacian regularized least squares and unbalanced bi-random walk to discover possible lncRNA biomarkers for lung cancer. First, the lncRNA and disease similarities were computed. Second, unbalanced bi-random walk was, respectively, applied to the lncRNA and disease networks to score associations between diseases and lncRNAs. Third, Laplacian regularized least squares were further used to compute the association probability between each lncRNA-disease pair based on the computed random walk scores. LDA-RLSURW was compared using 10 classical LDA prediction methods, and the best AUC value of 0.9027 on the lncRNADisease database was obtained. We found the top 30 lncRNAs associated with lung cancers and inferred that lncRNAs TUG1, PTENP1, and UCA1 may be biomarkers of lung neoplasms, non-small–cell lung cancer, and LUAD, respectively.

DSCAM-AS1 Long Non-Coding RNA Exerts Oncogenic Functions in Endometrial Adenocarcinoma via Activation of a Tumor-Promoting Transcriptome Profile

Accumulating evidence suggests that lncRNA DSCAM-AS1 acts tumor-promoting in various cancer entities. In breast cancer, DSCAM-AS1 was shown to be the lncRNA being most responsive to induction by estrogen receptor α (ERα). In this study, we examined the function of DSCAM-AS1 in endometrial adenocarcinoma using in silico and different in vitro approaches. Initial analysis of open-source data revealed DSCAM-AS1 overexpression in endometrial cancer (EC) (p < 0.01) and a significant association with shorter overall survival of EC patients (HR = 1.78, p < 0.01). In EC, DSCAM-AS1 was associated with endometrial tumor promotor gene PRL and with expression of ERα and its target genes TFF1 and PGR. Silencing of this lncRNA by RNAi in two EC cell lines was more efficient in ERα-negative HEC-1B cells and reduced their growth and the expression of proliferation activators like NOTCH1, PTK2 and EGR1. DSCAM-AS1 knockdown triggered an anti-tumoral transcriptome response as revealed by Affymetrix microarray analysis, emerging from down-regulation of tumor-promoting genes and induction of tumor-suppressive networks. Finally, several genes regulated upon DSCAM-AS1 silencing in vitro were found to be inversely correlated with this lncRNA in EC tissues. This study clearly suggests an oncogenic function of DSCAM-AS1 in endometrial adenocarcinoma via activation of a tumor-promoting transcriptome profile.

TET2-mediated epigenetic reprogramming of breast cancer cells impairs lysosome biogenesis

TET2-mediated oxidation of 5-methylcytosine establishes an antiviral state and contributes to MYC-dependent down-regulation of genes involved in lysosome biogenesis and function in breast cancer cells.

Methylation and demethylation of cytosines in DNA are believed to act as keystones of cell-specific gene expression by controlling the chromatin structure and accessibility to transcription factors. Cancer cells have their own transcriptional programs, and we sought to alter such a cancer-specific program by enforcing expression of the catalytic domain (CD) of the methylcytosine dioxygenase TET2 in breast cancer cells. The TET2 CD decreased the tumorigenic potential of cancer cells through both activation and repression of a repertoire of genes that, interestingly, differed in part from the one observed upon treatment with the hypomethylating agent decitabine. In addition to promoting the establishment of an antiviral state, TET2 activated 5mC turnover at thousands of MYC-binding motifs and down-regulated a panel of known MYC-repressed genes involved in lysosome biogenesis and function. Thus, an extensive cross-talk between TET2 and the oncogenic transcription factor MYC establishes a lysosomal storage disease–like state that contributes to an exacerbated sensitivity to autophagy inducers.

Molecular and cellular functions of long non-coding RNAs in prostate and breast cancer

Long noncoding RNAs (lncRNAs) are defined as noncoding RNA transcripts with a length greater than 200 nucleotides. Research over the last decade has made great strides in our understanding of lncRNAs, especially in the biology of their role in cancer. In this article, we will briefly discuss the biogenesis and characteristics of lncRNAs, then review their molecular and cellular functions in cancer by using prostate and breast cancer as examples. LncRNAs are abundant, diverse, and evolutionarily, less conserved than protein-coding genes. They are often expressed in a tumor and cell-specific manner. As a key epigenetic factor, lncRNAs can use a wide variety of molecular mechanisms to regulate gene expression at each step of the genetic information flow pathway. LncRNAs display widespread effects on cell behavior, tumor growth, and metastasis. They act intracellularly and extracellularly in an autocrine, paracrine and endocrine fashion. Increased understanding of lncRNA's role in cancer has facilitated the development of novel biomarkers for cancer diagnosis, led to greater understanding of cancer prognosis, enabled better prediction of therapeutic responses, and promoted identification of potential targets for cancer therapy.

Non-coding RNAs as liquid biopsy biomarkers in cancer

Although non-coding RNAs have long been considered as non-functional "junk" RNAs, accumulating evidence in the past decade indicates that they play a critical role in pathogenesis of various cancers. In addition to their biological significance, the recognition that their expression levels are frequently dysregulated in multiple cancers have fueled the interest for exploiting their clinical potential as cancer biomarkers. In particular, microRNAs (miRNAs), a subclass of small non-coding RNAs that epigenetically modulate gene-transcription, have become one of the most well-studied substrates for the development of liquid biopsy biomarkers for cancer patients. The emergence of high-throughput sequencing technologies has enabled comprehensive molecular characterisation of various non-coding RNA expression profiles in multiple cancers. Furthermore, technological advances for quantifying lowly expressed RNAs in the circulation have facilitated robust identification of previously unrecognised and undetectable biomarkers in cancer patients. Here we summarise the latest progress on the utilisation of non-coding RNAs as non-invasive cancer biomarkers. We evaluated the suitability of multiple non-coding RNA types as blood-based cancer biomarkers and examined the impact of recent technological breakthroughs on the development of non-invasive molecular biomarkers in cancer.

LncRNA functional annotation with improved false discovery rate achieved by disease associations

The long non‐coding RNAs (lncRNAs) play critical roles in various biological processes and are associated with many diseases. Functional annotation of lncRNAs in diseases attracts great attention in understanding their etiology. However, the traditional co-expression-based analysis usually produces a significant number of false positive function assignments. It is thus crucial to develop a new approach to obtain lower false discovery rate for functional annotation of lncRNAs. Here, a novel strategy termed DAnet which combining disease associations with cis-regulatory network between lncRNAs and neighboring protein-coding genes was developed, and the performance of DAnet was systematically compared with that of the traditional differential expression-based approach. Based on a gold standard analysis of the experimentally validated lncRNAs, the proposed strategy was found to perform better in identifying the experimentally validated lncRNAs compared with the other method. Moreover, the majority of biological pathways (40%∼100%) identified by DAnet were reported to be associated with the studied diseases. In sum, the DAnet is expected to be used to identify the function of specific lncRNAs in a particular disease or multiple diseases.

Identification of Crucial lncRNAs for Luminal A Breast Cancer through RNA Sequencing

BACKGROUND

The growing body of evidence indicates aberrant expression of long noncoding RNAs (lncRNAs) in breast cancer. Nevertheless, a few studies have focused on identifying key lncRNAs for patients with luminal A breast cancer. In our study, we tried to find key lncRNAs and mRNAs in luminal A breast cancer.

METHODS

RNA sequencing was performed to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) in luminal A breast cancer. The protein-protein interaction (PPI), DElncRNA-DEmRNA coexpression, DElncRNA-nearby DEmRNA interaction networks, and functional annotation were performed to uncover the function of DEmRNAs. Online databases were used to validate the RNA sequencing result. The diagnostic value of candidate mRNAs was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

A total number of 1451 DEmRNAs and 272 DElncRNAs were identified. Several hub proteins were identified in the PPI network, including TUBB3, HIST2H3C, MCM2, MYOC, NEK2, LIPE, FN1, FOXJ1, S100A7, and DLK1. In the DElncRNA-DEmRNA coexpression, some hub lncRNAs were identified, including AP001528.2, LINC00968, LINC02202, TRHDE-AS1, LINC01140, AL354707.1, AC097534.1, MIR222HG, and AL662844.4. The mRNA expression result of TFF1, COL10A1, LEP, PLIN1, PGM5-AS1, and TRHDE-AD1 in the GSE98793 was consistent with the RNA sequencing result. The protein expression results of TUBB3, MCM2, MYOC, FN1, S100A7, and TFF1 were consistent with the mRNA expression result COL10A1, LEP, PLIN1, PGM5-AS1, and TRHDE-AD1 were capable of discriminating luminal A breast cancer and normal controls. Four lncRNA-nearby and coexpressed mRNA pairs of HOXC-AS3-HOXC10, AC020907.2-FXYD1, AC026461.1-MT1X, and AC132217.1-IGF2 were identified. AMPK (involved LIPE and LEP) and PPAR (involved PLIN1) were two significantly enriched pathways in luminal A breast cancer.

CONCLUSION

This study could be helpful in unraveling the pathogenesis and providing novel therapeutic strategies for luminal A breast cancer.

The Estrogen Receptor α Signaling Pathway Controls Alternative Splicing in the Absence of Ligands in Breast Cancer Cells

Background: The transcriptional activity of estrogen receptor α (ERα) in breast cancer (BC) is extensively characterized. Our group has previously shown that ERα controls the expression of a number of genes in its unliganded form (apoERα), among which a large group of RNA-binding proteins (RBPs) encode genes, suggesting its role in the control of co- and post-transcriptional events. Methods: apoERα-mediated RNA processing events were characterized by the analysis of transcript usage and alternative splicing changes in an RNA-sequencing dataset from MCF-7 cells after siRNA-induced ERα downregulation. Results: ApoERα depletion induced an expression change of 681 RBPs, including 84 splicing factors involved in translation, ribonucleoprotein complex assembly, and 3′end processing. ApoERα depletion results in 758 isoform switching events with effects on 3′end length and the splicing of alternative cassette exons. The functional enrichment of these events shows that post-transcriptional regulation is part of the mechanisms by which apoERα controls epithelial-to-mesenchymal transition and BC cell proliferation. In primary BCs, the inclusion levels of the experimentally identified alternatively spliced exons are associated with overall and disease-free survival. Conclusion: Our data supports the role of apoERα in maintaining the luminal phenotype of BC cells by extensively regulating gene expression at the alternative splicing level.

Parkinson's Disease Is Associated With Dysregulation of Circulatory Levels of lncRNAs

Long non-coding RNAs (lncRNAs) have been recently reported to be involved in the pathoetiology of Parkinson’s disease (PD). Circulatory levels of lncRNAs might be used as markers for PD. In the present work, we measured expression levels of HULC, PVT1, MEG3, SPRY4-IT1, LINC-ROR and DSCAM-AS1 lncRNAs in the circulation of patients with PD versus healthy controls. Expression of HULC was lower in total patients compared with total controls (Expression ratio (ER)=0.19, adjusted P value<0.0001) as well as in female patients compared with female controls (ER=0.071, adjusted P value=0.0004). Expression of PVT1 was lower in total patients compared with total controls (ER=0.55, adjusted P value=0.0124). Expression of DSCAM-AS1 was higher in total patients compared with total controls (ER=5.67, P value=0.0029) and in male patients compared with male controls (ER=9.526, adjusted P value=0.0024). Expression of SPRY4-IT was higher in total patients compared with total controls (ER=2.64, adjusted P value<0.02) and in male patients compared with male controls (ER=3.43, P value<0.03). Expression of LINC-ROR was higher in total patients compared with total controls (ER=10.36, adjusted P value<0.0001) and in both male and female patients compared with sex-matched controls (ER=4.57, adjusted P value=0.03 and ER=23.47, adjusted P value=0.0019, respectively). Finally, expression of MEG3 was higher in total patients compared with total controls (ER=13.94, adjusted P value<0.0001) and in both male and female patients compared with sex-matched controls (ER=8.60, adjusted P value<0.004 and ER=22.58, adjusted P value<0.0085, respectively). ROC curve analysis revealed that MEG3 and LINC-ROR have diagnostic power of 0.77 and 0.73, respectively. Other lncRNAs had AUC values less than 0.7. Expression of none of lncRNAs was correlated with age of patients, disease duration, disease stage, MMSE or UPDRS. The current study provides further evidence for dysregulation of lncRNAs in the circulation of PD patients.

Analysis of the estrogen receptor-associated lncRNA landscape identifies a role for ERLC1 in breast cancer progression

Estrogen receptor alpha (ERα) plays a vital role in the development of normal breast tissue and in breast cancer. By cross-analyzing The Cancer Genome Atlas (TCGA) database, ERα-regulated long noncoding RNA 1 (ERLC1) was identified as a long noncoding RNA exhibiting a strong association with ERα signaling and high specificity of expression in breast tissue. ERLC1 was transcriptionally activated by ERα, and ERLC1 stabilized the ESR1 transcript by sequestering miR-129 and tethering FXR1 to maintain a positive feedback loop that potentiated ERα signaling. ERLC1 was elevated in tamoxifen-resistant breast cancer cells, where ERLC1 depletion restored sensitivity to tamoxifen and increased the efficacy of palbociclib or fulvestrant therapy. Collectively, these data warrant further investigation of ERLC1 as a modulator of therapeutic response and potential therapeutic target in ER+ breast cancer.

A Review on the Carcinogenic Roles of DSCAM-AS1

Long non-coding RNAs (lncRNAs) are a group of transcripts with fundamental roles in the carcinogenesis. DSCAM Antisense RNA 1 (DSCAM−AS1) is an example of this group of transcripts which has been firstly identified in an attempt to find differentially expressed transcripts between breast tumor cells and benign breast samples. The pathogenic roles of DSCAM-AS1 have been vastly assessed in breast cancer, yet its roles are not restricted to this type of cancer. Independent studies in non-small cell lung cancer, colorectal cancer, osteosarcoma, hepatocellular carcinoma, melanoma and cervical cancer have validated participation of DSCAM-AS1 in the carcinogenic processes. miR-577, miR-122-5p, miR-204-5p, miR-136, miR−137, miR−382, miR−183, miR−99, miR-3173-5p, miR-874-3p, miR-874-3p, miR-150-5p, miR-2467-3p, miR-216b, miR-384, miR-186-5p, miR-338-3p, miR-877-5p and miR-101 are among miRNAs which interact with DSCAM-AS1. Moreover, this lncRNA has interactions with Wnt/β-catenin pathway. The current study aims at summarization of the results of studies which focused on the assessment of oncogenic role of DSCAM-AS1.

lncRNA and breast cancer: Progress from identifying mechanisms to challenges and opportunities of clinical treatment

Breast cancer is a malignant tumor that has a high mortality rate and mostly occurs in women. Although significant progress has been made in the implementation of personalized treatment strategies for molecular subtypes in breast cancer, the therapeutic response is often not satisfactory. Studies have reported that long non-coding RNAs (lncRNAs) are abnormally expressed in breast cancer and closely related to the occurrence and development of breast cancer. In addition, the high tissue and cell-type specificity makes lncRNAs particularly attractive as diagnostic biomarkers, prognostic factors, and specific therapeutic targets. Therefore, an in-depth understanding of the regulatory mechanisms of lncRNAs in breast cancer is essential for developing new treatment strategies. In this review, we systematically elucidate the general characteristics, potential mechanisms, and targeted therapy of lncRNAs and discuss the emerging functions of lncRNAs in breast cancer. Additionally, we also highlight the advantages and challenges of using lncRNAs as biomarkers for diagnosis or therapeutic targets for drug resistance in breast cancer and present future perspectives in clinical practice.

Regulation of integrin and extracellular matrix genes by HNRNPL is necessary for epidermal renewal

Stratified epithelia such as the epidermis require coordinated regulation of stem and progenitor cell proliferation, survival, and differentiation to maintain homeostasis. Integrin-mediated anchorage of the basal layer stem cells of the epidermis to the underlying dermis through extracellular matrix (ECM) proteins is crucial for this process. It is currently unknown how the expression of these integrins and ECM genes are regulated. Here, we show that the RNA-binding protein (RBP) heterogeneous nuclear ribonucleoprotein L (HNRNPL) binds to these genes on chromatin to promote their expression. HNRNPL recruits RNA polymerase II (Pol II) to integrin/ECM genes and is required for stabilizing Pol II transcription through those genes. In the absence of HNRNPL, the basal layer of the epidermis where the stem cells reside prematurely differentiates and detaches from the underlying dermis due to diminished integrin/ECM expression. Our results demonstrate a critical role for RBPs on chromatin to maintain stem and progenitor cell fate by dictating the expression of specific classes of genes.

LncRNA TCONS_00041002 improves neurological outcomes in neonatal rats with hypoxic-ischemic encephalopathy by inhibiting apoptosis and promoting neuron survival

It has been reported that Neonatal hypoxic-ischemic encephalopathy (HIE) could induce apoptosis in neonates and result in cognitive and sensory impairments, which are associated with poor developmental outcomes. Despite the improvement in neonatology, there is still no clinically effective treatment for HIE presently. Long non-coding RNAs (lncRNAs) play important roles in cellular homeostasis. Nevertheless, their effects in developing rat brains with HI is little known. Here, we established HIE model in neonate rats and explored the expression and function of lncRNAs in HI, and found the expression of 19 lncRNAs was remarkably changed in the brains of HI rats, compared to the sham group. Among them, three lncRNAs (TCONS_00041002, TCONS_00070547, TCONS_00045572) were enriched in the apoptotic process via gene ontology (GO) and pathway analysis, which were selected for the further qRT-PCR verification. Through lentivirus-mediated overexpression of these three lncRNAs, we found that overexpression of TCONS_00041002 attenuated the cell apoptosis, and increased the vitality of neurons after oxygen-glucose deprivation (OGD), therefore reduced the brain infarction and further promoted the neuron survival as well as improved the neurological disorders in the rats subjected to HIE. What's more, ceRNA network prediction and co-expression verification showed that the expression of TCONS_00041002 was positively associated with Foxe1, Pawr and Nfkbiz. Altogether, this study has exhibited that lncRNA TCONS_00041002 participates in the cell apoptosis and neuronal survival of HIE and represents a potential new target for the treatment of HIE.

Long non-coding RNA Down syndrome cell adhesion molecule-anti-sense 1 promotes gastric carcinoma cell proliferation and migration by regulating the miR-204/TPT1 axis

Background: Several recent studies have suggested that the long non-coding RNA (lncRNA) DSCAM-AS1 (Down syndrome cell adhesion molecule - anti-sense 1) is aberrantly expressed in many malignancies. Purpose: In this study, we aimed to explore the the role of DSCAM-AS1 in gastric carcinoma. Research Design: Expression of DSCAM-AS1 mRNA, miR-204, and TPT1 (Tumor Protein, Translationally-Controlled 1) were detected using quantitative real-time polymerase chain reaction (qRT-PCR). Proliferation and apoptosis of GC cells were determined using the CCK-8 cell counting assay and flow cytometry. The rate of cell migration and invasion was determined using a transwell assay. The relationships between DSCAM-AS1, miR-204, and TPT1 were predicted and confirmed using a dual-luciferase reporter assay. Expression of TPT1 protein was quantified by Western blot. Results: In this study, we found that DSCAM-AS1 was significantly overexpressed in GC tissues and cell lines. Functional experiments indicated that GC cells with DSCAM-AS1 silencing exhibited a dynamic reduction in proliferation and migration. We identified miR-204 as a target of DSCAM-AS1 and found that it targeted TPT1 in GC cells, which further led to decreased expression of miR-204 in GC tissues and cell lines. A rescue assay revealed that knocked-down DSCAM-AS1 hindered GC progression, which was reversed upon miR-204 downregulation or TPT1 overexpression. Conclusion: We conclude that DSCAM-AS1 is expressed as a tumor oncogene in GC progression, modulated via the miR-204/TPT1 axis. These findings indicate the potential of DSCAM-AS1 as a therapeutic target for GC prevention.

Transcriptome Analysis Identifies GATA3-AS1 as a Long Noncoding RNA Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients

Breast cancer is one of the leading causes of mortality in women worldwide, and neoadjuvant chemotherapy has emerged as an option for the management of locally advanced breast cancer. Extensive efforts have been made to identify new molecular markers to predict the response to neoadjuvant chemotherapy. Transcripts that do not encode proteins, termed long noncoding RNAs (lncRNAs), have been shown to display abnormal expression profiles in different types of cancer, but their role as biomarkers in response to neoadjuvant chemotherapy has not been extensively studied. Herein, lncRNA expression was profiled using RNA sequencing in biopsies from patients who subsequently showed either response or no response to treatment. The GATA3-AS1 transcript was overexpressed in the nonresponder group and was the most stable feature when performing selection in multiple random forest models. GATA3-AS1 was experimentally validated by RT-qPCR in an extended group of 68 patients. Expression analysis confirmed that GATA3-AS1 is overexpressed primarily in patients who were nonresponsive to neoadjuvant chemotherapy, with a sensitivity of 92.9%, a specificity of 75.0%, and an area under the curve of approximately 0.90, as measured by receiver operating characteristic curve analysis. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74-208.42; P = 0.001); GATA3-AS1 was established as an independent predictor of response. Thus, lncRNA GATA3-AS1 is proposed as a potential predictive biomarker of nonresponse to neoadjuvant chemotherapy.

FBXO16-mediated hnRNPL ubiquitination and degradation plays a tumor suppressor role in ovarian cancer

Heterogeneous nuclear ribonucleoprotein L (hnRNPL) is a type of RNA binding protein that highly expressed in a variety of tumors and plays a vital role in tumor progression. However, its post-translational regulation through ubiquitin-mediated proteolysis and the cellular mechanism responsible for its proteasomal degradation remains unclear. F-box proteins (FBPs) function as the substrate recognition subunits of SCF ubiquitin ligase complexes and directly bind to substrates. The aberrant expression or mutation of FBPs will lead to the accumulation of its substrate proteins that often involved in tumorigenesis. Here we discover FBXO16, an E3 ubiquitin ligase, to be a tumor suppressor in ovarian cancer, and patients with the relatively high expression level of FBXO16 have a better prognosis. Silencing or depleting FBXO16 significantly enhanced ovarian cancer cell proliferation, clonogenic survival, and cell invasion by activating multiple oncogenic pathways. This function requires the F-box domain of FBXO16, through which FBXO16 assembles a canonical SCF ubiquitin ligase complex that constitutively targets hnRNPL for degradation. Depletion of hnRNPL is sufficient to inactive multiple oncogenic signaling regulated by FBXO16 and prevent the malignant behavior of ovarian cancer cells caused by FBXO16 deficiency. FBXO16 interacted with the RRM3 domain of hnRNPL via its C-terminal region to trigger the proteasomal degradation of hnRNPL. Failure to degrade hnRNPL promoted ovarian cancer cell proliferation in vitro and tumor growth vivo, phenocopying the deficiency of FBXO16 in ovarian cancer.

The lncRNA HMS recruits RNA-binding protein HuR to stabilize the 3'-UTR of HOXC10 mRNA

Long noncoding RNAs (lncRNAs) have been reported to drive key cancer pathways but the functions of majority of lncRNAs are unknown making a case for comprehensive functional evaluation of lncRNAs. With an aim to identify lncRNAs dysregulated in human cancers, we analyzed the cancer patient database of lung adenocarcinoma (LUAD), which revealed an upregulated lncRNA, LINC02381 (renamed HOXC10mRNA stabilizing factor or HMS in this study), whose depletion results in proliferation defects and inhibition of colony formation of human cancer cells. In order to identify the binding targets of HMS, we screened for cis-genes and discovered that HOXC10, an oncogene, is downregulated in the absence of HMS. Depletion of HMS does not affect the HOXC10 promoter activity but inhibits the HOXC10 3′-UTR-linked luciferase reporter activity. Since lncRNAs have been known to associate with RNA-binding proteins (RBPs) to stabilize mRNA transcripts, we screened for different RBPs and discovered that HuR, an ELAV family protein, stabilizes HOXC10 mRNA. Using RNA pull-down and deletion mapping experiments, we show that HuR physically interacts with the cytosine-rich stretch of HMS and HOXC10 3′-UTR to stabilize HOXC10 mRNA. HOXC10 is overexpressed in many human cancers, and our discovery highlights that lncRNA HMS sustains the HOXC10 mRNA levels to maintain the invasive phenotypes of cancer cells.

From Micro to Long: Non-Coding RNAs in Tamoxifen Resistance of Breast Cancer Cells

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer mortality among women. Two thirds of patients are classified as hormone receptor positive, based on expression of estrogen receptor alpha (ERα), the main driver of breast cancer cell proliferation, and/or progesterone receptor, which is regulated by ERα. Despite presenting the best prognosis, these tumors can recur when patients acquire resistance to treatment by aromatase inhibitors or antiestrogen such as tamoxifen (Tam). The mechanisms that are involved in Tam resistance are complex and involve multiple signaling pathways. Recently, roles for microRNAs and lncRNAs in controlling ER expression and/or tamoxifen action have been described, but the underlying mechanisms are still little explored. In this review, we will discuss the current state of knowledge on the roles of microRNAs and lncRNAs in the main mechanisms of tamoxifen resistance in hormone receptor positive breast cancer. In the future, this knowledge can be used to identify patients at a greater risk of relapse due to the expression patterns of ncRNAs that impact response to Tam, in order to guide their treatment more efficiently and possibly to design therapeutic strategies to bypass mechanisms of resistance.

Benchmarking and Testing Machine Learning Approaches with BARRA:CuRDa, a Curated RNA-Seq Database for Cancer Research

RNA-seq is gradually becoming the dominating technique employed to access the global gene expression in biological samples, allowing more flexible protocols and robust analysis. However, the nature of RNA-seq results imposes new data-handling challenges when it comes to computational analysis. With the increasing employment of machine learning (ML) techniques in biomedical sciences, databases that could provide curated data sets treated with state-of-the-art approaches already adapted to ML protocols, become essential for testing new algorithms. In this study, we present the Benchmarking of ARtificial intelligence Research: Curated RNA-seq Database (BARRA:CuRDa). BARRA:CuRDa was built exclusively for cancer research and is composed of 17 handpicked RNA-seq data sets for Homo sapiens that were gathered from the Gene Expression Omnibus, using rigorous filtering criteria. All data sets were individually submitted to sample quality analysis, removal of low-quality bases and artifacts from the experimental process, removal of ribosomal RNA, and estimation of transcript-level abundance. Moreover, all data sets were tested using standard approaches in the field, which allows them to be used as benchmark to new ML approaches. A feature selection analysis was also performed on each data set to investigate the biological accuracy of basic techniques. Results include genes already related to their specific tumoral tissue a large amount of long noncoding RNA and pseudogenes. BARRA:CuRDa is available at http://sbcb.inf.ufrgs.br/barracurda.

Identification and Roles of miR-29b-1-3p and miR29a-3p-Regulated and Non-Regulated lncRNAs in Endocrine-Sensitive and Resistant Breast Cancer Cells

Despite improvements in the treatment of endocrine-resistant metastatic disease using combination therapies in patients with estrogen receptor α (ERα) primary tumors, the mechanisms underlying endocrine resistance remain to be elucidated. Non-coding RNAs (ncRNAs), including microRNAs (miRNA) and long non-coding RNAs (lncRNA), are targets and regulators of cell signaling pathways and their exosomal transport may contribute to metastasis. Previous studies have shown that a low expression of miR-29a-3p and miR-29b-3p is associated with lower overall breast cancer survival before 150 mos. Transient, modest overexpression of miR-29b1-3p or miR-29a-3p inhibited MCF-7 tamoxifen-sensitive and LCC9 tamoxifen-resistant cell proliferation. Here, we identify miR-29b-1/a-regulated and non-regulated differentially expressed lncRNAs in MCF-7 and LCC9 cells using next-generation RNA seq. More lncRNAs were miR-29b-1/a-regulated in LCC9 cells than in MCF-7 cells, including DANCR, GAS5, DSCAM-AS1, SNHG5, and CRND. We examined the roles of miR-29-regulated and differentially expressed lncRNAs in endocrine-resistant breast cancer, including putative and proven targets and expression patterns in survival analysis using the KM Plotter and TCGA databases. This study provides new insights into lncRNAs in endocrine-resistant breast cancer.

Integrated analysis of long non-coding RNAs and mRNAs associated with malignant transformation of gastrointestinal stromal tumors

Malignant transformation of gastrointestinal stromal tumors (GISTs) is correlated with poor prognosis; however, the underlying biological mechanism is not well understood. In the present study, low-risk (LR) GISTs, GISTs categorized as high-risk based on tumor size (HBS), and on mitotic rate (HBM) were collected for RNA sequencing. Candidate hub lncRNAs were selected by Oncomine analysis. Expression of a selected hub lncRNA, DNM3OS, and its correlation with patients’ prognosis were analyzed using FISH staining, followed with the determination of function and underlying mechanism. Our results revealed a series of key pathways and hub lncRNAs involved in the malignant transformation of GISTs. Oncomine analysis revealed a tight association between clinical signatures and DNM3OS and suggested that DNM3OS is a hub lncRNA that is involved in the Hippo signaling pathway. In addition, DNM3OS was upregulated in HBS, HBM, and HBS/M GIST and correlated with worse prognosis in patients with GISTs. In addition, DNM3OS promoted GIST cell proliferation and mitosis by regulating the expression of GLUT4 and CD36. Collectively, these results improve our understanding of the malignant transformation of GISTs and unveil a series of hub lncRNAs in GISTs.

Extracellular Vesicles Carry lncRNA SNHG16 to Promote Metastasis of Breast Cancer Cells via the miR-892b/PPAPDC1A Axis

Breast cancer (BC) represents the most commonly diagnosed malignancy among women. Long non-coding RNAs (lncRNAs) can be transferred by extracellular vesicles (EVs) to participate in BC progression. This study demonstrated that SNHG16 expression was significantly increased in BC tissues and cells. Overexpression of SNHG16 promoted the migration, invasion, and epithelial-mesenchymal transition (EMT) of BC cells. SNHG16 was carried by EVs. Bioinformatics analysis predicted that SNHG16 regulated PPAPDC1A expression by sponging miR-892b, which was confirmed by RNA-fluorescence in situ hybridization (FISH), RT-qPCR, dual-luciferase gene reporter assay, and RNA immunoprecipitation (RIP). MDA-MB-157 and HS578T cells were transfected with pcDNA3.1-SNHG16, miR-892b-mimic, or si-PPAPDC1A for functional rescue experiments in vitro, and the cells were treated with MDA-MB-231 cell-derived EVs. The results confirmed that enhanced miR-892b expression partially eliminated the increase of migration, invasion, and EMT of BC cells mediated by SNHG16 or EVs. The lung metastasis model in nude mice was established by injecting HS578T cells via tail vein. The results showed that si-SNHG16 reduced the metastatic nodules and decreased the vimentin expression. In conclusion, EVs derived from BC cells transferred SNHG16 via the miR-892b/PPAPDC1A axis, thus promoting EMT, migration, and invasion of BC.

Pan-cancer characterization of lncRNA modifiers of immune microenvironment reveals clinically distinct de novo tumor subtypes

The emerging field of long noncoding RNA (lncRNA)-immunity has provided a new perspective on cancer immunity and immunotherapies. The lncRNA modifiers of infiltrating immune cells in the tumor immune microenvironment (TIME) and their impact on tumor behavior and disease prognosis remain largely uncharacterized. In the present study, a systems immunology framework integrating the noncoding transcriptome and immunogenomics profiles of 9549 tumor samples across 30 solid cancer types was used, and 36 lncRNAs were identified as modifier candidates underlying immune cell infiltration in the TIME at the pan-cancer level. These TIME lncRNA modifiers (TIL-lncRNAs) were able to subclassify various tumors into three de novo pan-cancer subtypes characterized by distinct immunological features, biological behaviors, and disease prognoses. Finally, a TIL-lncRNA-derived immune state index (TISI) that was reflective of immunological and oncogenic states but also predictive of patients' prognosis was proposed. Furthermore, the TISI provided additional prognostic value for existing tumor immunological and molecular subtypes. By applying the TISI to tumors from different clinical immunotherapy cohorts, the TISI was found to be significantly negatively correlated with immune-checkpoint genes and to have the ability to predict the effectiveness of immunotherapy. In conclusion, the present study provided comprehensive resources and insights for future functional and mechanistic studies on lncRNA-mediated cancer immunity and highlighted the potential of the clinical application of lncRNA-based immunotherapeutic strategies in precision immunotherapy.

Functional interplay between long non-coding RNAs and the Wnt signaling cascade in osteosarcoma

Osteosarcoma is a common and highly malignant bone tumor among children, adolescents and young adults. However, the underlying molecular mechanisms remain largely unexplored. LncRNAs are transcripts with no or limited protein-coding capacity in human genomes, and have been demonstrated to play crucial functions in initiation, progression, therapeutic resistance, recurrence and metastasis of tumor. Considerable studies revealed a dysregulated lncRNA expression pattern in osteosarcoma, which may act as oncogenes or suppressors to regulate osteosarcoma progression. Wnt signaling pathway is an important cascade in tumorigenesis by modulation of pleiotropic biological functions including cell proliferation, apoptosis, differentiation, stemness, genetic stability and chemoresistance. Hyperactivation or deficiency of key effectors in Wnt cascade is a common event in many osteosarcoma patients. Recently, increasing evidences have suggested that lncRNAs could interplay with component of Wnt pathway, and thereby contribute to osteosarcoma onset, progression and dissemination. In this review, we briefly summarize Wnt signaling-related lncRNAs in osteosarcoma progression, aiming to gain insights into their underlying crosstalk as well as clinical application in osteosarcoma therapeutic modalities.

Global investigation of estrogen-responsive genes regulating lipid metabolism in the liver of laying hens

BACKGROUND

Estrogen plays an essential role in female development and reproductive function. In chickens, estrogen is critical for lipid metabolism in the liver. The regulatory molecular network of estrogen in chicken liver is poorly understood. To identify estrogen-responsive genes and estrogen functional sites on a genome-wide scale, we determined expression profiles of mRNAs, lncRNAs, and miRNAs in estrogen-treated ((17β-estradiol)) and control chicken livers using RNA-Sequencing (RNA-Seq) and studied the estrogen receptor α binding sites by ChIP-Sequencing (ChIP-Seq).

RESULTS

We identified a total of 990 estrogen-responsive genes, including 962 protein-coding genes, 11 miRNAs, and 17 lncRNAs. Functional enrichment analyses showed that the estrogen-responsive genes were highly enriched in lipid metabolism and biological processes. Integrated analysis of the data of RNA-Seq and ChIP-Seq, identified 191 genes directly targeted by estrogen, including 185 protein-coding genes, 4 miRNAs, and 2 lncRNAs. In vivo and in vitro experiments showed that estrogen decreased the mRNA expression of PPARGC1B, which had been reported to be linked with lipid metabolism, by directly increasing the expression of miR-144-3p.

CONCLUSIONS

These results increase our understanding of the functional network of estrogen in chicken liver and also reveal aspects of the molecular mechanism of estrogen-related lipid metabolism.

Uncovering the roles of microRNAs/lncRNAs in characterising breast cancer subtypes and prognosis

Background

Accurate prognosis and identification of cancer subtypes at molecular level are important steps towards effective and personalised treatments of breast cancer. To this end, many computational methods have been developed to use gene (mRNA) expression data for breast cancer subtyping and prognosis. Meanwhile, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have been extensively studied in the last 2 decades and their associations with breast cancer subtypes and prognosis have been evidenced. However, it is not clear whether using miRNA and/or lncRNA expression data helps improve the performance of gene expression based subtyping and prognosis methods, and this raises challenges as to how and when to use these data and methods in practice.

Results

In this paper, we conduct a comparative study of 35 methods, including 12 breast cancer subtyping methods and 23 breast cancer prognosis methods, on a collection of 19 independent breast cancer datasets. We aim to uncover the roles of miRNAs and lncRNAs in breast cancer subtyping and prognosis from the systematic comparison. In addition, we created an R package, CancerSubtypesPrognosis, including all the 35 methods to facilitate the reproducibility of the methods and streamline the evaluation.

Conclusions

The experimental results show that integrating miRNA expression data helps improve the performance of the mRNA-based cancer subtyping methods. However, miRNA signatures are not as good as mRNA signatures for breast cancer prognosis. In general, lncRNA expression data does not help improve the mRNA-based methods in both cancer subtyping and cancer prognosis. These results suggest that the prognostic roles of miRNA/lncRNA signatures in the improvement of breast cancer prognosis needs to be further verified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04215-3.

LINC00894 Enhances the Progression of Breast Cancer by Sponging miR-429 to Regulate ZEB1 Expression

PURPOSE

Long non-coding RNAs (lncRNAs) are known to regulate tumorigenesis. Although breast cancer tissues show a high expression of LINC00894, its specific biological role in breast cancer progression is still unknown. In this study, lncRNA microarray was used to analyze the lncRNA expression in breast cancer tissues, and LINC00894 was selected for further analysis.

MATERIALS AND METHODS

Expression of LINC00894 in 45 pairs of breast cancer tissues and normal tissues obtained from patients with breast cancer was assessed by quantitative reverse transcription-PCR, while proliferation and invasion of breast cancer cells were assessed using a Cell Counting Kit-8 (CCK-8), EdU assay, colony formation experiment, and transwell assays. A dual-luciferase reporter gene assay and bioinformatics analysis were employed to detect potential targets of LINC00894. Additionally, RNA Binding Protein Immunoprecipitation (RIP) and Western blot assays were utilized to clarify its interaction and roles in the regulation of breast cancer progression.

RESULTS

High expression of LINC00894 was observed in breast cancer cells, and its overexpression significantly expedited cell proliferation and invasion. Moreover, LINC00894 positively regulated the expression of ZEB1 by competitively binding to miR-429.

CONCLUSION

Taken together, these results suggest that LINC00894 competitively binds to miR-429 to mediate ZEB1 expression; consequently, it is implicated to play a role in the progression of breast cancer.

LncRNA PCIR Is an Oncogenic Driver via Strengthen the Binding of TAB3 and PABPC4 in Triple Negative Breast Cancer

Long non-coding RNAs (LncRNA) as the key regulators in all stages of tumorigenesis and metastasis. However, the underlying mechanisms are largely unknown. Here, we report a lncRNA RP11-214F16.8, which renamed Lnc-PCIR, is upregulated and higher RNA level of Lnc-PCIR was positively correlated to the poor survival of patients with triple negative breast cancer (TNBC) tissues. Lnc-PCIR overexpression significantly promoted cell proliferation, migration, and invasion in vitro and in vivo. RNA pulldown, RNA immunoprecipitation (RIP) and RNA transcriptome sequencing technology (RNA-seq) was performed to identify the associated proteins and related signaling pathways. Mechanistically, higher Lnc-PCIR level of blocks PABPC4 proteasome-dependent ubiquitination degradation; stable and highly expressed PABPC4 can further increase the stability of TAB3 mRNA, meanwhile, overexpression of Lnc-PCIR can disrupt the binding status of TAB3 and TAB2 which lead to activate the TNF-α/NF-κB pathway in TNBC cells. Our findings suggest that Lnc-PCIR promotes tumor growth and metastasis via up-regulating the mRNA/protein level of TAB3 and PABPC4, activating TNF-α/NF-κB signaling pathway in TNBC.

Gain of LINC00624 Enhances Liver Cancer Progression by Disrupting the Histone Deacetylase 6/Tripartite Motif Containing 28/Zinc Finger Protein 354C Corepressor Complex

BACKGROUND AND AIMS

Long noncoding RNAs (lncRNAs) are involved in almost every stage of tumor initiation and progression. Here, we have identified an antisense lncRNA, LINC00624, that arises from the antisense strand of chromo-domain-helicase-DNA-binding protein 1-like (CHD1L), located on chr1q21.1, with significant copy number gain and transcriptional activation of CHD1L and B-cell CLL/lymphoma 9 protein (BCL9), in hepatocellular carcinoma (HCC).

APPROACH AND RESULTS

Overexpression of LINC00624 enhances tumor growth and metastasis in vitro and in vivo. Mechanistically, higher levels of LINC00624 strengthen the interaction between histone deacetylase 6 (HDAC6) and tripartite motif containing 28 (TRIM28), which accelerates HDAC6 ubiquitination and degradation. Moreover, LINC00624 binds to the RBCC domain of TRIM28, inhibits trimer formation, and weakens the interaction between TRIM28 and zinc finger protein 354C (ZNF354C). Thus, LINC00624 overexpression disrupts the formation of the HDAC6-TRIM28-ZNF354C transcriptional corepressor complex, resulting in the dissociation of the complex from the promoter of CHD1L and BCL9, thereby removing transcription inhibition.

CONCLUSIONS

Our findings suggest that LINC00624 acts as a molecular decoy that sequesters the HDAC6-TRIM28-ZNF354C transcriptional corepressor complex away from the specific genomic loci, and that it can potentially be a therapeutic target in HCC.

Enhancer RNAs Mediate Estrogen-Induced Decommissioning of Selective Enhancers by Recruiting ERα and Its Cofactor

The function of enhancer RNAs (eRNAs) in transcriptional regulation remains obscure. By analyzing the genome-wide nascent transcript profiles in breast cancer cells, we identify a special group of eRNAs that are essential for estrogen-induced transcriptional repression. Using eRNAs of TM4SF1 and EFEMP1 as the paradigms, we find that these RNA molecules not only stabilize promoter-enhancer interactions but also recruit liganded estrogen receptor α (ERα) to particular enhancer regions, facilitate the formation of a functional transcriptional complex, and cause gene silencing. Interestingly, ERα is shown to directly bind with eRNAs by its DNA-binding domain. These eRNAs help with the formation of a specific ERα-centered transcriptional complex and promote the association of the histone demethylase KDM2A, which dismisses RNA polymerase II from designated enhancers and suppresses the transcription of target genes. Our work demonstrates a complete mechanism underlying the action of eRNAs in modulating and refining the locus-specific transcriptional program.

Yang et al. identified a group of eRNAs that are essential for estrogen-induced transcriptional repression by assisting with the chromatin recruitment of ERα through binding to its DNA-binding domain and facilitating the interaction of ERα with its cofactors, which leads to the dismissal of RNA polymerase II.