Long noncoding RNA expression signatures of bladder cancer revealed by microarray

Exosomal LINC00853 promotes progression of gastric cancer via the MAP17/PDZK1/AKT signaling pathway

Although rare, there is ongoing research into biomarkers that predict the onset and recurrence of gastric cancer, particularly focusing on substances found in exosomes. Long non-coding RNAs (lncRNAs) have garnered attention for their potential in diagnosing gastric cancer. This study investigates the role of lncRNAs in gastric cancer, focusing on their presence in exosomes as potential biomarkers for the disease's onset and recurrence. We utilized the ArrayStar Human LncRNA array 2.0 to analyze lncRNA expression in tissues from early-stage gastric cancer patients. Our analysis highlighted LINC00853, which was significantly upregulated in cancer tissues and implicated in promoting epithelial-mesenchymal transition via the MAP17/PDZK1/AKT pathway. Functional studies on AGS and MKN74 gastric cancer cell lines demonstrated that LINC00853 facilitates cell proliferation, invasion, and migration. Additionally, RNA immunoprecipitation and electrophoretic mobility shift assays confirmed LINC00853 interaction with MAP17. Importantly, LINC00853 was also detected in exosomes from both patient samples and cell lines, and its downregulation led to decreased tumorigenicity in AGS cells. These findings suggest that both cellular and exosomal LINC00853 contribute to gastric cancer pathogenesis and may serve as valuable biomarkers for the disease.

RPI-EDLCN: An Ensemble Deep Learning Framework Based on Capsule Network for ncRNA-Protein Interaction Prediction

Noncoding RNAs (ncRNAs) play crucial roles in many cellular life activities by interacting with proteins. Identification of ncRNA-protein interactions (ncRPIs) is key to understanding the function of ncRNAs. Although a number of computational methods for predicting ncRPIs have been developed, the problem of predicting ncRPIs remains challenging. It has always been the focus of ncRPIs research to select suitable feature extraction methods and develop a deep learning architecture with better recognition performance. In this work, we proposed an ensemble deep learning framework, RPI-EDLCN, based on a capsule network (CapsuleNet) to predict ncRPIs. In terms of feature input, we extracted the sequence features, secondary structure sequence features, motif information, and physicochemical properties of ncRNA/protein. The sequence and secondary structure sequence features of ncRNA/protein are encoded by the conjoint k-mer method and then input into an ensemble deep learning model based on CapsuleNet by combining the motif information and physicochemical properties. In this model, the encoding features are processed by convolution neural network (CNN), deep neural network (DNN), and stacked autoencoder (SAE). Then the advanced features obtained from the processing are input into the CapsuleNet for further feature learning. Compared with other state-of-the-art methods under 5-fold cross-validation, the performance of RPI-EDLCN is the best, and the accuracy of RPI-EDLCN on RPI1807, RPI2241, and NPInter v2.0 data sets was 93.8%, 88.2%, and 91.9%, respectively. The results of the independent test indicated that RPI-EDLCN can effectively predict potential ncRPIs in different organisms. In addition, RPI-EDLCN successfully predicted hub ncRNAs and proteins in Mus musculus ncRNA-protein networks. Overall, our model can be used as an effective tool to predict ncRPIs and provides some useful guidance for future biological studies.

Mysterious long noncoding RNAs and their relationships to human disease

Increasingly studies have shown that the formation mechanism of many human diseases is very complex, which is determined by environmental factors and genetic factors rather than fully following Mendel's genetic law of inheritance. Long non-coding RNA (lncRNA) is a class of endogenous non-protein coding RNA with a length greater than 200 nt, which has attracted much attention in recent years. Studies have shown that lncRNAs have a wide range of biological functions, such as roles in gene imprinting, cell cycle progression, apoptosis, senescence, cell differentiation, and stress responses, and that they regulate the life processes of mammals at various levels, such as epigenetic transcription, processing, modification, transport, translation and degradation. Analyzing the characteristics of lncRNAs and revealing their internal roles can not only deepen our understanding of human physiological and pathological processes, but also provide new ideas and solutions for the diagnosis, prevention and treatment of some diseases. This article mainly reviews the biological characteristics of lncRNAs and their relationship with some diseases, so as to provide references for the related research of lncRNAs.

Construction and analysis of a lncRNA–miRNA–mRNA competing endogenous RNA network from inflamed and normal synovial tissues after anterior cruciate ligament and/or meniscus injuries

Background: Despite ample evidence demonstrating that anterior cruciate ligament (ACL) and meniscus tears are associated with posttraumatic osteoarthritis (PTOA) development, the contributing factors remain unknown. Synovial inflammation has recently been recognized as a pivotal factor in the pathogenesis of OA. However, there is a lack of data on synovial profiles after ACL or meniscus injuries, which may contribute to PTOA.

Methods: Twelve patients with ACL tears and/or meniscus injuries were recruited. During surgery, synovial tissues were obtained from the injured knees. The inflammation status of the synovium was characterized according to macroscopic criteria and histological synovitis grades. Then the synovial tissues were classified as control group or inflamed group. High-throughput RNA sequencing of the synovial samples (3 vs. 3) was conducted to identify differentially expressed (DE) RNAs. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein–protein interaction (PPI) analyses were performed to investigate DE mRNAs. Next, competing endogenous RNA (ceRNA) networks were constructed based on bioinformatics analyses. Associations of the identified DE genes (DEGs) with infiltrating immune cells were explored using Pearson correlation analysis.

Results: The results showed that 2793 mRNAs, 3392 lncRNAs and 211 miRNAs were significantly DE between two groups. The top 3 significantly upregulated GO terms and KEGG pathways were immune response, adaptive immune response and immune system process, systemic lupus erythematosus, haematopoietic cell lineage and cytokine–cytokine receptor interaction, respectively. In PPI networks, the top 10 hub genes were IL6, CCR7, C3, CCR5, CXCR3, CXCL8, IL2, CCR3, CCR2 and CXCL1. Seven mRNAs (EPHA5, GSN, ORC1, TLN2, SOX6, NKD2 and ADAMTS19), 4 lncRNAs (MIR4435-2HG, TNXA, CEROX1 and TMEM92-AS1) and 3 miRNAs (miR-486-5p, miR-199a-3p and miR-21-3p) were validated by quantitative real-time polymerase chain reaction and sub-networks were constructed. In correlation analysis, MMP9 correlated positively with M0 macrophages and plasma cells, NKD2 positively with CD8 T cells, and CCR7 and IL2RB positively with naive B cells.

Conclusion: Our study provides foundational synovial inflammation profiles following knee trauma. The ceRNA and PPI networks provide new insight into the biological processes and underlying mechanisms of PTOA. The differential infiltration profiles of immune cells in synovium may contribute to PTOA development. This study also highlights immune-related DEGs as potential PTOA treatment biomarkers.

Anti-cancer effect of LINC00478 in bladder cancer correlates with KDM1A-dependent MMP9 demethylation

Accumulating evidence has highlighted the important roles of long intergenic non-coding RNAs (lincRNAs) during cancer progression. However, the involvement of LINC00478 in bladder cancer remains largely unclear. Accordingly, the current study sought to investigate the function of LINC00478 on malignant phenotypes of bladder cancer cells as well as the underlying mechanism. By integrating data from in silico analysis, we uncovered that LINC00478 was differentially expressed in bladder cancer. We further analyzed the expression of LINC00478 and matrix metalloprotein 9 (MMP9) in bladder cancer tissues and cell lines and observed a significant decline in LINC00478 expression and an elevation in MMP9 expression. In addition, chromatin immunoprecipitation, RNA-binding protein immunoprecipitation, and RNA pull-down assays predicted and validated that LINC00478 targeted lysine-specific demethylase-1 (KDM1A) and down-regulated the expression of MMP9 by decreasing the monomethylation on lysine 4 of histone H3 (H3K4me1) of MMP9 promoter. Treatment with KDM1A inhibitor tranylcypromine (TCP) also led to an increase in the enrichment of H3K4me1 in the MMP9 promoter region. Through gain- and loss-of-function approaches, we found that LINC00478 up-regulation diminished the malignant phenotype of bladder cancer cells in vitro, and further inhibited xenograft tumor growth and metastasis in vivo by repressing MMP9. Collectively, our findings unraveled a LINC00478-mediated inhibitory mechanism in bladder cancer via the recruitment of histone demethylation transferase KDM1A to the MMP9 promoter region, which can provide potential implications for novel therapeutic targets against bladder cancer.

LncRNA KRT19P3 Is Involved in Breast Cancer Cell Proliferation, Migration and Invasion

Long non-coding RNAs (LncRNAs) have already been taken as critical regulatory molecules in breast carcinoma (BC). Besides, the progression of BC is closely associated with the immune system. However, the relationship between lncRNAs and the tumor immune system in BC has not been fully studied. LncRNA KRT19P3 has been reported to inhibit the progression of gastric cancer. In the present study, we first discovered that KRT19P3 was downregulated in BC tissues compared with para cancer tissue. Then we showed that KRT19P3 could be used as a marker to differentiate BC from para cancer tissue. Increased expression of KRT19P3 markedly inhibited the proliferation, migration, and invasion rate of BC cells in vitro and tumor growth of BC in vivo. Conversely, KRT19P3 knockdown by siRNA markedly promoted the proliferation, migration, and invasion rate of BC cells after being transfected. Comparison of clinical parameters showed an inverse relationship between the expression of KRT19P3 and pathological grade. Furthermore, immunohistochemistry (IHC) was applied to reveal the positive rate of the expression of Ki-67, programmed death-ligand 1 (PD-L1), and CD8 in BC tissues. Correlation analysis showed that Ki-67 and PD-L1 were inversely proportional to KRT19P3 but CD8 was directly proportional to KRT19P3. In conclusion, this study demonstrated that lncRNA KRT19P3 inhibits BC progression, and may affect the expression of PD-L1 in BC, which in turn affects CD8⁺ T (CD8 positive Cytotoxic T lymphocyte) cells in the immune microenvironment.

NPI-RGCNAE: Fast predicting ncRNA-protein interactions using the Relational Graph Convolutional Network Auto-Encoder

- ncRNAs play important roles in a variety of biological processes by interacting with RNA-binding proteins. Therefore, identifying ncRNA-protein interactions is important to understanding the biological functions of ncRNAs. Since experimental methods to determine ncRNA-protein interactions are always costly and time-consuming, computational methods have been proposed as alternative approaches. We developed a novel method NPI-RGCNAE (predicting ncRNA-Protein Interactions by the Relational Graph Convolutional Network Auto-Encoder). With a reliable negative sample selection strategy, we applied the Relational Graph Convolutional Network encoder and the DistMult decoder to predict ncRNA-protein interactions in an accurate and efficient way. By using the 5-fold cross-validation, we found that our method achieved a comparable performance to all state-of-the-art methods. Our method requires less than 10% training time of all state-of-the-art methods. It is a more efficient choice with large datasets in practice. All datasets and source codes of NPI-RGCNAE have been deposited in a public Github repository (https://github.com/Angelia0hh/NPI-RGCNAE).

RPARP-AS1/miR125a-5p Axis Promotes Cell Proliferation, Migration and Invasion in Colon Cancer

Background

It was reported that long-noncoding RNAs (lncRNAs) had been identified as a novel class of regulators related to various cancers. RPARP-AS1, a differentially-expressed gene, was found in analysis of the gene expression profile of CRC from GEO database. However, its function has not been clear.

Methods

RPARP-AS1 expression was determined by qPCR and Startbase3 analysis. Knockdown of RPARP-AS1 in CRC cell lines was performed by RNAi technology, named si-RPARP-AS1 HCT116 and si-RPARP-AS1 LoVo. Cell proliferation was examined by CCK8 and colony formation assay. RNA pull-down and Luciferase reporter assay were performed to confirm the interaction between RPARP-AS1 and miR-125a-5p.

Results

In the study, we found that the expression of RPARP-AS1 was significantly up-regulated in CRC tissues and multiple CRC cell lines, which was closely related to poor prognosis of CRC patients. Loss-of-function studies indicated that knockdown of RPARP-AS1 inhibited CRC cell proliferation, migration and invasion in HCT116 and LoVo cell lines. Results of research on the mechanisms showed that RPARP-AS1 functioned as a competitive endogenous RNA (ceRNA) to sponge miR-125a-5p, therefore promoting CRC procession.

Conclusion

In summary, these results indicated that RPARP-AS1/miR-125a-5p axis played a positive role in promoting cell proliferation, migration and invasion in CC. It may be as a biomarker used to evaluate CRC prognosis.

The role of noncoding RNAs in pituitary adenoma

Pituitary adenomas (PAs) are common cranial tumors that affect the quality of life in patients. Early detection of PA is beneficial for avoiding clinical complications of this disease and increasing the quality of life. Noncoding RNAs, including long noncoding RNA, miRNA and circRNA, regulate protein expression, mostly by inhibiting the translation process. Studies have shown that dysregulation of noncoding RNAs is associated with PA. Hence understanding the expression pattern of noncoding RNAs can be considered a promising method for developing biomarkers. This article reviews data on the expression pattern of dysregulated noncoding RNAs involved in PA. Possible molecular mechanisms by which the dysregulated noncoding RNA could possibly induce PA are also described.

Characterization of the small RNA transcriptomes of cell protrusions and cell bodies of highly metastatic hepatocellular carcinoma cells via RNA sequencing

Increasing evidence suggest that hepatocellular carcinoma (HCC) HCCLM3 cells initially develop pseudopodia when they metastasize, and microRNAs (miRNAs/miRs) and circular RNAs (circRNAs) have been demonstrated to serve important roles in the development, progression and metastasis of cancer. The present study aimed to isolate the cell bodies (CBs) and cell protrusions (CPs) from HCCLM3 cells, and screen the miRNAs and circRNAs associated with HCC infiltration and metastasis in CBs and CPs. The Boyden chamber assay has been confirmed to effectively isolate the CBs and CPs from HCCLM3 cells via observation of microtubule immunofluorescence, DAPI staining and nuclear protein H3 western blotting. Following high-throughput sequencing of the successfully isolated CBs and CPs, 64 pairs of miRNAs, including 23 pairs of upregulated genes and 41 pairs of downregulated genes, and 260 sets of circRNAs, including 127 upregulated genes and 133 downregulated genes, were significantly differentially expressed, using the following criteria: HP/HB ratio, fold change ≥|1.5|, P<0.05). PCR analysis verified that changes in the expression levels of hsa-let-7a-5p, hsa-let-7c-3p, hsa-miR-30c-5p, hsa_circ_0059580, hsa_circ_0067475, hsa_circ_0002100 and hsa_circ_00072309 were consistent with the sequencing results. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to analyze the functions and roles of the differentially expressed miRNAs and circRNAs. The interaction maps between miRNAs and circRNAs were constructed, and signaling pathway maps were analyzed to determine the molecular mechanism and regulation of the differentially expressed miRNAs and circRNAs. Taken together, the results of the present study suggest that the Boyden chamber assay can be used to effectively isolate the somatic CBs and CPs of HCC, which can be used to screen the miRNAs and circRNAs associated with invasion and metastasis of HCC.

LncRNA GATA3‑AS1‑miR‑30b‑5p‑Tex10 axis modulates tumorigenesis in pancreatic cancer

Long noncoding RNAs (lncRNAs) have been widely recognized to play an important role in a variety of diseases. Abnormal regulation of lncRNA GATA3-antisense RNA 1 (AS1) occurs in several cancers, but whether it is involved in the progression of pancreatic cancer (PC) remains unknown. The present study aimed to investigate the biological effects of GATA3-AS1 in PC and to explore the underlying molecular mechanisms. Upregulation of GATA3-AS1 was revealed in PC tissues and cell lines. Knockdown of GATA3-AS1 in PANC-1 or AsPC-1 cells markedly reduced cell viability, cell proliferation, and cell invasion abilities, while cell apoptosis was increased. In addition, GATA3-AS1 knockdown suppressed the stemness of PANC-1 and AsPC-1 cells by decreasing the spheroid formation ability. A tumor xenograft in vivo assay demonstrated that GATA3-AS1 knockdown inhibited tumorigenicity of AsPC-1 cells. Furthermore, the microRNA (miR)-30b-5p downregulation and GATA3-AS1 upregulation were revealed in PC tissues and cell lines. Negative correlations were present between GATA3-AS1 and miR-30b-5p and between miR-30b-5p and testis-expressed protein 10 (Tex10) in the PC tissues, while GATA3-AS1 and Tex10 were positively correlated. GATA3-AS1 was then revealed to act as a competing endogenous RNA (ceRNA) for miR-30b-5p in regulating Tex10 expression. Moreover, the miR-30b-5p-Tex10 axis was confirmed to be involved in the regulation of biological effects of GATA3-AS1, including cell viability, cell proliferation, cell invasion, cell apoptosis, and cell stemness, as well as Wnt1/β-catenin signaling. Collectively, these data indicated that the GATA3-AS1-miR-30b-5p-Tex10 axis modulates tumorigenesis in PC, which may be associated with the Wnt/β-catenin signaling pathway.

EDLMFC: an ensemble deep learning framework with multi-scale features combination for ncRNA-protein interaction prediction

Background

Non-coding RNA (ncRNA) and protein interactions play essential roles in various physiological and pathological processes. The experimental methods used for predicting ncRNA–protein interactions are time-consuming and labor-intensive. Therefore, there is an increasing demand for computational methods to accurately and efficiently predict ncRNA–protein interactions.

Results

In this work, we presented an ensemble deep learning-based method, EDLMFC, to predict ncRNA–protein interactions using the combination of multi-scale features, including primary sequence features, secondary structure sequence features, and tertiary structure features. Conjoint k-mer was used to extract protein/ncRNA sequence features, integrating tertiary structure features, then fed into an ensemble deep learning model, which combined convolutional neural network (CNN) to learn dominating biological information with bi-directional long short-term memory network (BLSTM) to capture long-range dependencies among the features identified by the CNN. Compared with other state-of-the-art methods under five-fold cross-validation, EDLMFC shows the best performance with accuracy of 93.8%, 89.7%, and 86.1% on RPI1807, NPInter v2.0, and RPI488 datasets, respectively. The results of the independent test demonstrated that EDLMFC can effectively predict potential ncRNA–protein interactions from different organisms. Furtherly, EDLMFC is also shown to predict hub ncRNAs and proteins presented in ncRNA–protein networks of Mus musculus successfully.

Conclusions

In general, our proposed method EDLMFC improved the accuracy of ncRNA–protein interaction predictions and anticipated providing some helpful guidance on ncRNA functions research. The source code of EDLMFC and the datasets used in this work are available at https://github.com/JingjingWang-87/EDLMFC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04069-9.

LncRNA ZNF503-AS1 acts as a tumor suppressor in bladder cancer by up-regulating Ca2+ concentration via transcription factor GATA6

PURPOSE

Ca2+ homeostasis plays a pivotal role in regulating proliferation and apoptosis during cancer development. This study intended to examine the potential tumor-suppressing role of ZNF503 antisense RNA 1 (ZNF503-AS1) in bladder cancer, which may be implicated in the regulation of Ca2+ homeostasis.

METHODS

Differentially expressed long non-coding RNAs (lncRNAs) related to bladder cancer were identified using microarray analysis, followed by the verification of transcription factors to which they bind. The relationship between ZNF503-AS1, GATA6 and SLC8A1 was assessed using dual luciferase reporter, RIP and ChIP assays. The expression levels of ZNF503-AS1, GATA6 and SLC8A1 were modulated to examine their effects on the tumorigenic potential, intracellular Ca2+ concentration and Ca2+-ATPase activity in bladder cancer cells. The in vivo tumorigenic ability was validated in nude mice.

RESULTS

Microarray-based expression profile analysis of the GEO GSE61615 dataset revealed that the expression of ZNF503-AS1 was decreased in bladder cancer. Subsequently, we found that ZNF503-AS1 can bind to the transcription factor GATA6 to up-regulate the expression of SLC8A1. ZNF503-AS1 and SLC8A1 were found to be down-regulated in both primary bladder cancer tissues and cells. Exogenous overexpression of ZNF503-AS1 or SLC8A1 attenuated bladder cancer cell proliferation, invasion and migration, but promoted their apoptosis, accompanied by decreased Ca2+-ATPase activities and increased intracellular Ca2+ concentrations. Additional in vivo experiments validated the inhibitory effect of ZNF503-AS1 overexpression on the tumorigenic capacity of bladder cancer cells in nude mice.

CONCLUSION

ZNF503-AS1 can recruit transcription factor GATA6 to up-regulate SLC8A1 expression, thereby increasing the intracellular Ca2+ concentration and repressing the proliferation, invasion and migration, and enhancing the apoptosis of bladder cancer cells.

LncRNA HCP5 Promotes Cell Invasion and Migration by Sponging miR-29b-3p in Human Bladder Cancer

BACKGROUND

Bladder cancer (BC) is one of the most common malignant tumors in the urinary system. In this study, the roles of lncRNA HCP5 (human major histocompatibility complex p5) and miR-29b-3p in human BC were investigated. Their regulations involved in cell invasion and migration were also evaluated.

METHODS

Luciferase reporter assay was performed to detect the binding between miR-29b-3p and HCP5 or high-mobility group box 1 (HMGB1). Cell viability, migration, invasion and apoptosis were assessed by CCK-8, colony formation, transwell assay and flow cytometry, respectively. Expression levels of HMGB1/toll-like receptor 4 (TLR4) proteins were measured by Western blot. Xenograft model was built, and tumor volumes and weights were calculated.

RESULTS

The results revealed dysregulation of HCP5 and miR-29b-3p in BC samples and cells. HCP5 negatively regulated the expression of miR-29b-3p and enhanced cell viability, migration and invasion. MiR-29b-3p mediated the effect of HCP5 on cell viability, proliferation, migration and invasion in RT4 cells. In addition, miR-29b-3p could regulate the expression of HMGB1 through interaction with HMGB1.

CONCLUSION

The findings in this study supported that lncRNA HCP5 could promote cell invasion and migration by sponging miR-29b-3p in human BC.

DDX11-AS1exacerbates bladder cancer progression by enhancing CDK6 expression via suppressing miR-499b-5p

PURPOSE

We investigated DDX11-AS1 effects on bladder cancer (BLCA) progression to identify a new potential therapeutic target for BLCA.

METHODS

BLCA cases (n = 108) were enrolled. SW780 and J82 cells were transfected. Cell counting kit-8 (CCK-8) assay, wound healing assay and transwell migration assay was conducted. Cell cycle and apoptosis was detected by flow cytometry. Luciferase reporter assay was performed. DDX11-AS1, miR-499b-5p and CDK6 mRNA expression in tissues/cells was determined by quantitative real-time polymerase chain reaction (qRT-PCR). In vivo experiment was performed using nude mice. CDK6 and Ki67 proteins expression in cells and xenograft tumors were researched by Western blot and immunohistochemistry.

RESULTS

Overexpressed DDX11-AS1 in BLCA was associated with poor outcome of patients. Compared with siCtrl group, SW780 and J82 cells of siDDX11-AS1 group had lower OD450 value (P < 0.01), less cells in S phase, more apoptosis cells (P < 0.05), higher relative wound width (P < 0.05) and less invasive cell number (P < 0.01). DDX11-AS1 promoted CDK6 expression via inhibiting miR-499b-5p. Compared with oe-DDX11-AS1 group, SW780 cells of oe-DDX11-AS1 + miR-499b-5p mimic group and oe-DDX11-AS1 + siCDK6 group had lower OD450 value (P < 0.01), less cells in S phrase, more apoptosis cells (P < 0.01), higher relative wound width (P < 0.05) and less invasive cell numbers (P < 0.01). DDX11-AS1 knockdown inhibited SW780 cells growth in vivo and suppressed CDK6 and Ki67 expression in xenograft tumors.

CONCLUSION

DDX11-AS1 exacerbates BLCA progression by enhancing CDK6 expression via suppressing miR-499b-5p.

Evaluation of C5orf66-AS1 as a Potential Biomarker for Predicting Early Gastric Cancer and Its Role in Gastric Carcinogenesis

Background

Long non-coding RNAs (lncRNAs) participate in a series of pathological processes in tumorigenesis. Reports show that C5orf66-AS1, an antisense lncRNA, is expressed in various tumors. However, the role of C5orf66-AS1 in gastric cancer (GC) has not been fully clarified. The study focused on the expression patterns and serum level of C5orf66-AS1 in GC to explore its potential application in GC screening and diagnosis. The effects of C5orf66-AS1 on GC cells were also analyzed.

Methods

Tissue and serum samples were used for RNA isolation. Expression levels of C5orf66-AS1 in GC tissues, serum, and cell lines were detected using quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). CCK-8, transwell, and wound healing assays were performed to determine the effects of C5orf66-AS1 on GC cell behavior.

Results

C5orf66-AS1 expression was downregulated in GC cells compared to that in adjacent normal tissues. Serum C5orf66-AS1 levels were significantly lower in GC patients than in superficial gastritis (GS) and atrophic gastritis (GA) patients. Low serum expression of C5orf66-AS1 was associated with an increased risk of gastric dysplasia (GD) and GC. Receiver operating characteristic curve results showed that the area under curve (AUC) for GC was 0.688, with a sensitivity and specificity of 77.5% and 53.6%, respectively. For the GD + early gastric cancer (ECG) group, the AUC was 0.789, with a sensitivity and specificity of 85.15% and 62.86%, respectively. Correlation analyses of clinicopathological parameters showed that serum C5orf66-AS1 was predominantly associated with Lauren type, TNM stages, pTNM stages, and vessel tumor emboli. Additionally, in vitro overexpression of C5orf66-AS1 in AGS cells inhibited cell proliferation, migration, and invasion.

Conclusion

Decreased expression levels of serum C5orf66-AS1 can be utilized for diagnosis of GC, especially for early diagnosis. The low level of serum C5orf66-AS1 indicated poor biological behavior of tumors in GC patients. In addition, C5orf66-AS1 can inhibit GC cell proliferation, migration, and invasion.

Long Noncoding RNA GATA3-AS1 Promotes Cell Proliferation and Metastasis in Hepatocellular Carcinoma by Suppression of PTEN, CDKN1A, and TP53

BACKGROUND

Long noncoding RNAs (lncRNAs) have been known to play important roles in the progression of various types of human cancer. LncRNA GATA3 antisense RNA 1, GATA3-AS1, has been reported to be associated with T-cell development and differentiation. However, the expression pattern and function of GATA3-AS1 in hepatocellular carcinoma (HCC) remain unknown.

METHODS

Real-time quantitative PCR (RT-qPCR) assay was conducted to detect GATA3-AS1 expression levels in 80 cases of pairs HCC tissues and matched normal tissues. Chi-squared (χ ²) test was used to analyze the correlation between GATA3-AS1 expression and clinicopathologic variables. Survival curves were plotted using the Kaplan-Meier method and were compared via the log-rank test. The cell counting kit-8 (CCK-8) and wound scratch assays were applied to detect the effect of GATA3-AS1 knockdown and overexpression on cell growth and migration of HCC. RT-qPCR was performed for the detection of the phosphatase and tensin homolog (PTEN), cyclin-dependent kinase inhibitor 1A (CDKN1A), and tumor protein p53 (TP53) expression in HCC cells after GATA3-AS1 knockdown and overexpression.

RESULTS

GATA3-AS1 was significantly upregulated in HCC tissues compared with matched normal tissues. The high expression of GATA3-AS1 was significantly correlated with larger tumor size, advanced TNM stage, and more lymph node metastasis. High GATA3-AS1 expression was markedly correlated with shorter overall survival times of HCC patients. Furthermore, knockdown of GATA3-AS1 obviously inhibited Hep3B and HCCLM3 cell growth and migration, whereas overexpression of GATA3-AS1 had the opposite effects. In addition, GATA3-AS1 knockdown resulted in upregulated expression levels of tumor-suppressive genes, PTEN, CDKN1A, and TP53, in Hep3B and HCCLM3 cells, while restoration of GATA3-AS1 decreased PTEN, CDKN1A, and TP53 expression levels.

CONCLUSION

Our data suggested that GATA3-AS1 promotes cell proliferation and metastasis of HCC by suppression of PTEN, CDKN1A, and TP53.

Long non-coding RNA KRT19P3 suppresses proliferation and metastasis through COPS7A-mediated NF-κB pathway in gastric cancer

Long non-coding RNAs (lncRNAs) have emerged as critical regulators in gastric cancer (GC). LncRNA expression microarray data indicate that KRT19P3 (Keratin 19 Pseudogene 3) is downregulated in GC samples. However, the expression pattern and molecular mechanism of KRT19P3 in GC have not been characterized. The present study confirmed the downregulation of KRT19P3 in GC tissues and cells. Decreased expression of KRT19P3 was correlated with larger tumor size, advanced TNM stage, Lauren's classification, positive lymph node metastasis, and poor prognosis. Enforced expression of KRT19P3 significantly inhibited cell proliferation, migration, and invasion in vitro, as well as tumorigenesis and metastasis in vivo. Conversely, KRT19P3 knockdown had opposite effects. Mechanistically, RNA pull-down and RNA immunoprecipitation assay revealed that KRT19P3 could directly bind COPS7A. KRT19P3 enhanced COPS7A protein stability in GC cells, and KRT19P3 suppressed GC cell proliferation and metastasis partly through regulation of COPS7A expression. COPS7A could promote deubiquitinylation of IκBα, which was executed by CSN-associated deubiquitinylase USP15, and then KRT19P3 inactivated nuclear factor kappa-B (NF-κB) signaling pathway in a COPS7A-dependent manner. For the first time, we revealed that KRT19P3 could suppress tumor growth and metastasis through COPS7A-mediated NF-κB pathway, which may serve as potential targets for treatment of GC in the future.

Recognition of early and late stages of bladder cancer using metabolites and machine learning

INTRODUCTION

Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its rate of occurrence increases with age. The current method of BCa diagnosis includes a cystoscopy and biopsy. This process is expensive, unpleasant, and may have severe side effects. Recent growth in the power and accessibility of machine-learning software has allowed for the development of new, non-invasive diagnostic methods whose accuracy and sensitivity are uncompromising to function.

OBJECTIVES

The goal of this research was to elucidate the biomarkers including metabolites and corresponding genes for different stages of BCa, show their distinguishing and common features, and create a machine-learning model for classification of stages of BCa.

METHODS

Sets of metabolites for early and late stages, as well as common for both stages were analyzed using MetaboAnalyst and Ingenuity^® Pathway Analysis (IPA^®) software. Machine-learning methods were utilized in the development of a binary classifier for early- and late-stage metabolites of BCa. Metabolites were quantitatively characterized using EDragon 1.0 software. The two modeling methods used are Multilayer Perceptron (MLP) and Stochastic Gradient Descent (SGD) with a logistic regression loss function.

RESULTS

We explored metabolic pathways related to early-stage BCa (Galactose metabolism and Starch and sucrose metabolism) and to late-stage BCa (Glycine, serine, and threonine metabolism, Arginine and proline metabolism, Glycerophospholipid metabolism, and Galactose metabolism) as well as those common to both stages pathways. The central metabolite impacting the most cancerogenic genes (AKT, EGFR, MAPK3) in early stage is D-glucose, while late-stage BCa is characterized by significant fold changes in several metabolites: glycerol, choline, 13(S)-hydroxyoctadecadienoic acid, 2'-fucosyllactose. Insulin was also seen to play an important role in late stages of BCa. The best performing model was able to predict metabolite class with an accuracy of 82.54% and the area under precision-recall curve (PRC) of 0.84 on the training set. The same model was applied to three separate sets of metabolites obtained from public sources, one set of the late-stage metabolites and two sets of the early-stage metabolites. The model was better at predicting early-stage metabolites with accuracies of 72% (18/25) and 95% (19/20) on the early sets, and an accuracy of 65.45% (36/55) on the late-stage metabolite set.

CONCLUSION

By examining the biomarkers present in the urine samples of BCa patients as compared with normal patients, the biomarkers associated with this cancer can be pinpointed and lead to the elucidation of affected metabolic pathways that are specific to different stages of cancer. Development of machine-learning model including metabolites and their chemical descriptors made it possible to achieve considerable accuracy of prediction of stages of BCa.

Emerging Roles of p53 Related lncRNAs in Cancer Progression: A Systematic Review

p53 is the major mediator of the tumor suppressor response. It participates in apoptosis and senescence and can respond to DNA damage. As a crucial sequence-specific transcription factor, p53 regulates the expression of many genes, such as small noncoding RNAs (ncRNAs), microRNAs, and long ncRNAs (lncRNAs). Given the emergence of novel and high-throughput sequencing technologies, many lncRNAs have been discovered. LncRNAs may function as vital gene regulators in a variety of biological processes through extensive mechanisms. Recently, lncRNAs have been demonstrated to be associated with the p53 regulatory pathway. In this review, we discuss the current and fast growing knowledge about the influence of lncRNAs to the p53 signaling pathway, the different mechanisms by which they affect gene expression in cancer. Our findings show that p53-associated lncRNAs may be used as biomarkers for cancer diagnosis or targets for disease therapy.

RPITER: A Hierarchical Deep Learning Framework for ncRNA⁻Protein Interaction Prediction

Non-coding RNAs (ncRNAs) play crucial roles in multiple fundamental biological processes, such as post-transcriptional gene regulation, and are implicated in many complex human diseases. Mostly ncRNAs function by interacting with corresponding RNA-binding proteins. The research on ncRNA⁻protein interaction is the key to understanding the function of ncRNA. However, the biological experiment techniques for identifying RNA⁻protein interactions (RPIs) are currently still expensive and time-consuming. Due to the complex molecular mechanism of ncRNA⁻protein interaction and the lack of conservation for ncRNA, especially for long ncRNA (lncRNA), the prediction of ncRNA⁻protein interaction is still a challenge. Deep learning-based models have become the state-of-the-art in a range of biological sequence analysis problems due to their strong power of feature learning. In this study, we proposed a hierarchical deep learning framework RPITER to predict RNA⁻protein interaction. For sequence coding, we improved the conjoint triad feature (CTF) coding method by complementing more primary sequence information and adding sequence structure information. For model design, RPITER employed two basic neural network architectures of convolution neural network (CNN) and stacked auto-encoder (SAE). Comprehensive experiments were performed on five benchmark datasets from PDB and NPInter databases to analyze and compare the performances of different sequence coding methods and prediction models. We found that CNN and SAE deep learning architectures have powerful fitting abilities for the k-mer features of RNA and protein sequence. The improved CTF coding method showed performance gain compared with the original CTF method. Moreover, our designed RPITER performed well in predicting RNA⁻protein interaction (RPI) and could outperform most of the previous methods. On five widely used RPI datasets, RPI369, RPI488, RPI1807, RPI2241 and NPInter, RPITER obtained A U C of 0.821, 0.911, 0.990, 0.957 and 0.985, respectively. The proposed RPITER could be a complementary method for predicting RPI and constructing RPI network, which would help push forward the related biological research on ncRNAs and lncRNAs.

Overexpression of long non‑coding RNA n346372 in bladder cancer tissues is associated with a poor prognosis

Accumulating evidence has confirmed that dysregulated long non-coding RNAs (lncRNAs) participate in the initiation and progression of a number of solid tumors and have potential applications for early diagnosis, targeted therapy, and the prognosis of patients with bladder cancer. In the present study, via high-throughput sequencing technology and bioinformatics analysis, a total of 169 lncRNAs with significantly differential expression between bladder cancer tissues and paired adjacent normal tissues (n=10) were initially identified by screening. Reverse-transcription-quantitative polymerase chain reaction was carried out to validate the expression levels of lncRNA-n346372 in 60 pairs of tissue samples from bladder cancer patients. The results indicated that lncRNA-n346372 was upregulated in bladder cancer tissues compared with the matched adjacent normal tissues (P<0.05). In addition, the results of fluorescence in situ hybridization analysis of bladder cancer cells and tissues demonstrated that lncRNA-n346372 is located in the cytoplasm, and the expression of lncRNA-n346372 in bladder cancer tissues was significantly increased compared with the paired normal tissues. Following a χ² test with common clinical variables among the patients, the expression level of lncRNA-n346372 was demonstrated to be positively associated with advanced tumor stage and poor histological differentiation of bladder cancer. Kaplan-Meier survival analysis revealed that patients with high expression of n346372 were more likely to have a poor prognosis compared with patients with low n346372 expression. Finally, univariate and multivariate analyses indicated that the relative level of n346372, apart from tumor stage and histological grade, may serve as an independent prognostic factor of bladder cancer. To the best of the authors' knowledge, this is the first study to verify the dysregulated expression of lncRNA-n346372 in bladder cancer; an association of this lncRNA with overall survival of bladder cancer patients was also uncovered in the present study, suggesting that lncRNA-n346372 may contribute to the initiation and/or progression of bladder cancer with potential applications in the clinic.

Aberrant methylation-mediated downregulation of long noncoding RNA C5orf66-AS1 promotes the development of gastric cardia adenocarcinoma

As a long non-coding RNA, C5orf66-AS1 is located at 5q31.1. Downregulation and aberrant hypermethylation of C5orf66-AS1 have been detected in a limited several tumors. However, the biological role and distribution of methylated CpG sites of C5orf66-AS1 in gastric cardia adenocarcinoma (GCA) development and prognosis are poorly clarified. The present study was to investigate the expression status and function of C5orf66-AS1 in GCA, and to detect the distribution of methylated CpG sites within the three CpG islands of the promoter and gene body of C5orf66-AS1, further to clarify its prognostic value in GCA patients. C5orf66-AS1 was significantly downregulated in GCA tissues and cell lines, and the expression level was associated with TNM stage, pathological differentiation, lymph node metastasis, and distant metastasis or recurrence. The expression level of C5orf66-AS1 was significantly increased in cancer cells after treated with 5-Aza-dC. Further methylation analysis demonstrated that the aberrant hypermethylation of the regions around the transcription start site of C5orf66-AS1 was more tumor specific and was associated with its expression. Moreover, Sp1 may upregulate C5orf66-AS1 expression and CpG sites hypermethylation within the binding sites may abrogate Sp1 binding. In addition, C5orf66-AS1 inhibited gastric cancer cell proliferation and invasion, and the dysregulation and hypermethylation of the regions around the transcription start site of C5orf66-AS1 were associated with poorer GCA patients' survival. These findings suggest that aberrant hypermethylation-mediated downregulation of C5orf66-AS1 may play important roles in GCA tumorigenesis and C5orf66-AS1 may serve as a potential prognostic marker in predicting GCA patients' survival.

Identification and functional characterization of long non-coding RNAs in human gastric cancer

Abnormal regulation of long non-coding RNAs (lncRNAs) appears to be a primary feature of numerous types of human cancer. However, the association between the dysregulation of lncRNAs and functional alterations in gastric cancer (GC) remains unclear. In previous studies, we applied microarray and bioinformatics analyses to screen for key lncRNAs from the tumor tissues and matched adjacent non-tumor tissues of 10 patients with GC. There were seven key lncRNAs demonstrated to be significantly different between carcinoma tissues and adjacent non-tumor tissues. In the present study, the expression of these seven selected lncRNAs were validated in 82 patients with GC to further investigate the association between lncRNAs and GC clinical characterization. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) results demonstrated that RP5-919F19, MCPH1 antisense RNA 1 (CTD-2541M15) and urothelial carcinoma-associated 1 (UCA1) exhibited consistent upregulation in cancer compared with adjacent non-tumor tissues, whereas AP000459, LOC101928316, tumor suppressor candidate 8 (LINC01071) and maternally expressed 3 (MEG3) showed consistent downregulation. The results from the microarray and RT-qPCR experiments achieved 100% agreement. A correlation analysis indicated that RP5-919F19, LOC101928316 and MEG3 were significantly associated with tumor differentiation degree, RP5-919F19, UCA1 and MEG3 were significantly associated with lymph node metastasis, and RP5-919F19, CTD-2541M15 and UCA1 were significantly associated with tumor-node-metastasis stage (P<0.05). In addition, it was identified that the differential expression of LINC01071 and LOC101928316 significantly correlated with the age and gender of the GC patients, respectively (P<0.05). The results suggest that the lncRNAs RP5-919F19, LOC101928316, CTD-2541M15, UCA1 and MEG3 are closely associated with the invasion and metastasis of GC, which reveals these indicators as potential specificity biomarkers for the diagnosis, prognosis and classification of GC. Thus, these lncRNAs merit further study as novel candidate biomarkers for the clinical diagnosis of GC and as potential targets for therapy.

Identification of long non-coding RNAs that stimulate cell survival in bladder cancer

For many years, research on the biology underlying bladder cancer focused on protein-coding genes which cover only about 3% of the human genome. Recently, it was discovered that a large part of the human genome is actively transcribed as long non-coding RNAs (lncRNAs). LncRNAs are master regulators of gene expression and several lncRNAs were shown to play a role in bladder cancer development and progression. Here, we analyzed lncRNA expression in muscle-invasive bladder cancer (MIBC) using the MiTranscriptome database of cancer lncRNA expression profiles, and we studied their function in bladder cancer-derived tumor cells. Analysis of the MiTranscriptome lncRNA expression data revealed four MIBC subgroups, which partially overlapped with the four mRNA clusters identified by The Cancer Genome Atlas consortium. Up-regulation of three lncRNAs CAT266, CAT1297, and CAT1647 in bladder cancer, in comparison to normal urothelium, was confirmed in an independent series of normal, non-muscle invasive (NMIBC) and MIBC tissue samples. Furthermore, expression levels of CAT1297 were found to be correlated with disease-free and overall survival in MIBC. Knockdown of CAT266, CAT1297, and CAT1647 decreased cell viability and colony formation, due to the induction of apoptosis. In conclusion, our data show that lncRNAs expression is de-regulated in MIBC and three aberrantly expressed transcripts regulate proliferation and apoptosis. Our data indicate that lncRNAs play an important role in MIBC development and progression and are a treasure chest for the discovery of new biomarkers.

Aberrant methylation-mediated silencing of lncRNA CTC-276P9.1 is associated with malignant progression of esophageal squamous cell carcinoma

Downregulation and aberrant hypermethylation of long non-coding RNA CTC-276P9.1 have been detected in limited tumors. However, the distribution of methylated CpG sites and biological role of CTC-276P9.1 in esophageal squamous cell carcinoma (ESCC) progression and prognosis have not been fully clarified. The present study was to investigate the expression status and the distribution of methylated CpG sites within the three CpG islands of CTC-276P9.1, further to clarify its functional role and prognostic value in ESCC development and prognosis. Significant downregulation of CTC-276P9.1 was detected in esophageal cancer cells and ESCC tissues, and the expression of CTC-276P9.1 in ESCC tissues was associated with TNM stage, pathological differentiation, lymph node metastasis, and distant metastasis or recurrence. The expression level of CTC-276P9.1 in esophageal cancer cells was significantly reversed by treatment with 5-Aza-dC and TSA. The aberrant hypermethylation of the regions around the transcription start site was more tumor specific and associated with the expression levels of CTC-276P9.1. Moreover, histone modification may also participate in the regulation of CTC-276P9.1. Furthermore, over-expression of CTC-276P9.1 inhibited esophageal cancer cells proliferation and invasion in vitro, decreased the expression of proliferative markers and inhibited esophageal cancer cells invasion probably by regulating EMT. In addition, the dysregulation and hypermethylation of the regions around the transcription start site of CTC-276P9.1 were associated with poorer ESCC patients' survival. These findings suggest that CTC-276P9.1 may act as a tumor suppressor and may be employed as a new prognostic factor and therapeutic target for ESCC.

Comprehensive analysis of differentially expressed profiles of lncRNAs and circRNAs with associated co-expression and ceRNA networks in bladder carcinoma

Accumulating evidences indicate that long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) play important roles in tumorigenesis. However, the mechanisms remain largely unknown. To explore lncRNAs and circRNAs expression profiling and their biological functions in bladder cancer, we surveyed the lncRNA/circRNA and mRNA expression profiles of bladder cancer and para-cancer tissues using microarray for four patients. Thousands of significantly changed lncRNAs and mRNAs as well as hundreds of circRNAs were identified. Five dysregulated lncRNAs and four mRNAs were confirmed by quantitative real-time PCR in 30 pairs of samples. GO and KEGG pathway enrichment analyses were executed to determine the principal functions of the significantly deregulated genes. Further more, we constructed correlated expression networks including coding-noncoding co-expression (CNC), competing endogenous RNAs (ceRNA), cis regulation, lncRNAs-transcription factor (TF)-mRNA with bioinformatics methods. Co-expression analysis showed lncRNA APLP2 expression is correlated with apoptosis-related genes, including PTEN and TP53INP1. CeRNA network inferred that lncRNA H19 and circRNA MYLK could bind competitively with miRNA-29a-3p increasing target gene DNMT3B, VEGFA and ITGB1 expressions. Moreover, the nearby genes pattern displayed that overexpressing ADAM2 and C8orf4 are cis-regulated by lncRNA RP11-359E19.2, involving in progression of bladder cancer. In addition, lncRNAs-TF-mRNA diagram indicated that lncRNA BC041488 could trans-regulate CDK1 mRNA expression through SRF transcription factor. Taken together, these results suggested lncRNAs and circRNAs could implicate in the pathogenesis and development of bladder cancer. Our findings provide a novel perspective on lncRNAs and circRNAs and lay the foundation for future research of potential roles of lncRNAs and circRNAs in bladder carcinoma.

Comprehensive analysis of aberrantly expressed profiles of lncRNAs and miRNAs with associated ceRNA network in muscle-invasive bladder cancer

Although initially thought to be transcriptional noise, long noncoding RNAs (lncRNAs) are gaining increased attention in human cancers as its diversity function. At present, lncRNAs are regarded as the main part of competing endogenous RNA (ceRNA) network due to its regulation on protein-coding gene expression by acting as miRNA sponges. However, functional roles of lncRNA-mediated ceRNAs in muscle-invasive bladder cancer remain unclear. To clarify relevant potential mechanisms, here we comprehensively compared the expression profiles of mRNAs, lncRNAs and miRNAs between 322 muscle-invasive bladder cancer tissues and 19 non-tumor bladder tissues, based on the Cancer Genome Atlas (TCGA). A total of 22 lncRNAs were identified as aberrantly expressed and had correlations with tumorigenesis and/or progression of muscle-invasive bladder cancer (|log2FoldChange| > 1.5, corrected P value < 0.01). 6 out of the 22 dysregulated lncRNAs functioned as prognostic biomarkers for patients with muscle-invasive bladder cancer according to the overall survival analysis (P value < 0.05). Finally, a dysregulated lncRNA-associated ceRNA network was successfully constructed, which inculdes five muscle-invasive bladder cancer-specific lncRNAs, nine miRNAs and 32 mRNAs. In summary, our study identified novel lncRNAs as candidate prognostic biomarkers and potential therapeutic targets for muscle-invasive bladder cancer, based on large-scale sample size. More importantly, the newly identified ceRNA network will be beneficial for improving the understanding of lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of muscle-invasive bladder cancer.

Role of Non-Coding RNAs in the Etiology of Bladder Cancer

According to data of the International Agency for Research on Cancer and the World Health Organization (Cancer Incidence in Five Continents, GLOBOCAN, and the World Health Organization Mortality), bladder is among the top ten body locations of cancer globally, with the highest incidence rates reported in Southern and Western Europe, North America, Northern Africa and Western Asia. Males (M) are more vulnerable to this disease than females (F), despite ample frequency variations in different countries, with a M:F ratio of 4.1:1 for incidence and 3.6:1 for mortality, worldwide. For a long time, bladder cancer was genetically classified through mutations of two genes, fibroblast growth factor receptor 3 (FGFR3, for low-grade, non-invasive papillary tumors) and tumor protein P53 (TP53, for high-grade, muscle-invasive tumors). However, more recently scientists have shown that this disease is far more complex, since genes directly involved are more than 150; so far, it has been described that altered gene expression (up- or down-regulation) may be present for up to 500 coding sequences in low-grade and up to 2300 in high-grade tumors. Non-coding RNAs are essential to explain, at least partially, this ample dysregulation. In this review, we summarize the present knowledge about long and short non-coding RNAs that have been linked to bladder cancer etiology.

Knockdown of DUXAP10 inhibits proliferation and promotes apoptosis in bladder cancer cells via PI3K/Akt/mTOR signaling pathway

DUXAP10 is a member of long non-coding RNAs (lncRNAs) and has been reported to be upregulated in bladder cancer (BC) tissues. However, the biological functions of DUXAP10 in BC are largely unknown. The present study detected the expression of DUXAP10 in human normal bladder cell SV‑HUC‑1 and BC cell lines. Subsequently, cell proliferation, cell cycle, and apoptosis were analyzed by knockdown of the DUXAP10 expression. Results suggested that the expression level of DUXAP10 was significantly enhanced in cancer cells. After knockdown of DUXAP10, cell proliferation was inhibited, cell cycle was arrested at G0/G1 phase, and apoptosis was increased in T24 and 5637 cells. Western blot analysis detected that knockdown of DUXAP10 decreased the expression of Bcl-xL, cyclin D and CDK4. This increased the expression of Bad, cleaved caspase‑3, cleaved caspase-9, and p27. Further studies indicated that knockdown of DUXAP10 inhibited PI3K/Akt/mTOR signaling pathway. Combining these results, our study suggests that DUXAP10 plays an important role in BC and DUXAP10 inhibition is a potential therapeutic target for BC.

Downregulated long non-coding RNA TCONS_00068220 upregulates apoptosis in gastric cancer cells

Long non-coding RNAs (lncRNAs) are emerging as a fundamental class of biological effect or molecules that perform pivotal functions in the regulation of the genome. With advances in bioinformatics and genomics, extensive identification and characterization of lncRNAs is now possible. They regulate cellular growth, differentiation and apoptosis. Dysregulation of lncRNAs has been associated with numerous types of human cancer. In the present study, the expression profile of differentially expressed genes (DEGs) and lncRNAs in gastric cancer (GC) samples and normal tissue samples was evaluated with bioinformatics. The biological functions of the predicted lncRNA TCONS_00068220 were focused on; the DEGs co-expressed with TCONS_00068220 were enriched in cancer-associated pathways. TCONS_00068220 was demonstrated to be upregulated in GC tissues and cell lines compared with normal controls. In addition, an increased rate of apoptosis was observed in NCI-N87 cells following transfection with small interfering RNA against TCONS_00068220. These data suggest that TCONS_00068220 may be associated with the pathogenesis of GC, and it may serve as a potential therapeutic target.

Knockdown of long non-coding RNA prostate cancer-associated ncRNA transcript 1 inhibits multidrug resistance and c-Myc-dependent aggressiveness in colorectal cancer Caco-2 and HT-29 cells

The long non-coding RNA (lncRNA) prostate cancer-associated ncRNA transcript 1 (PCAT-1) has been shown to promote prostate cancer cell proliferation through c-Myc and is associated with the poor prognosis of CRC patients. In the current study, it was hypothesized that the effect of PCAT-1 on the aggressiveness of CRC cells was dependent on the function of c-Myc. Human CRC cell lines Caco-2 and HT-29 were transfected with specific PCAT-1 shRNAs, and cell migration, invasiveness, and resistance to 5-fluorouracil were measured. To elucidate the role of c-Myc in PCAT-1 function, c-Myc was overexpressed in PCAT-1-silenced CRC cells and the effect of c-Myc overexpression on the aggressiveness of PCAT-1-silenced cells was detected. The results showed that knockdown of PCAT-1 in CRC cells suppressed cell motility and invasiveness, and sensitized the cells to 5-fluorouracil, as evidenced by the reduced viability and induced apoptosis in PCAT-1-silenced cells compared to the parental cells in response to 5-fluorouracil treatment. The expression of c-Myc in PCAT-1-silenced CRC cells was down-regulated, and forced expression of c-Myc partially restored the invasiveness in PCAT-1-silenced cells. In summary, the findings outlined in the current study suggest that PCAT-1 regulates the invasiveness and drug resistance in CRC cells and that PCAT-1 may promote CRC cell invasion by modulating the expression of c-Myc.

Long non-coding RNA C5orf66-AS1 is downregulated in pituitary null cell adenomas and is associated with their invasiveness

Pituitary null cell adenoma is a challenging clinical condition, and its pathogenesis remains to be elucidated. We performed this study to determine the roles of C5orf66-AS1, NORAD, and TINCR in the pathogenesis and invasion of pituitary null cell adenomas. Expression of the three long non-coding RNAs in pituitary null cell adenoma tissues of 11 patients and normal pituitary tissues from four donors was examined by performing quantitative reverse transcription-polymerase chain reaction. We found that C5orf66-AS1 expression was lower in pituitary null cell adenoma tissues than in normal pituitary tissues. Moreover, C5orf66-AS1 expression level was significantly lower in invasive pituitary null cell adenomas than in non-invasive ones. After transfection of C5orf66-AS1 into pituitary adenoma cells, assessment of cell viability and invasion suggested that overexpressed C5orf66-AS1 inhibited cell viability and cell invasion. In silico algorithms predicted several cis- and trans-acting target genes of C5orf66-AS1, including PITX1 and SCGB3A1. In addition, expression of some of the predicted target genes was determined using microarray data of another cohort with pituitary null cell adenomas. It showed that some of these target genes were differentially expressed between pituitary null cell adenoma tissues and normal pituitary tissues as well as between invasive and non-invasive tumors. Co-expression analysis in RNA sequencing data showed that PAQR7 was the most correlated gene of C5orf66-AS1 and that several predicted trans-acting target genes, including SCGB3A1, were highly correlated with C5orf66-AS1. NORAD and TINCR expression was not statistically significant in the complete cohort; however, a negative correlation was observed between NORAD expression and maximum tumor diameter in some subgroups. These results indicate that C5orf66-AS1 suppresses the development and invasion of pituitary null cell adenomas. However, our results do not provide enough statistical evidence to support the roles of NORAD and TINCR in the development and invasion of pituitary null cell adenomas.

Long noncoding RNAs in the p53 network

The tumor-suppressor protein p53 is activated in response to numerous cellular stresses including DNA damage. p53 functions primarily as a sequence-specific transcription factor that controls the expression of hundreds of protein-coding genes and noncoding RNAs, including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). While the role of protein-coding genes and miRNAs in mediating the effects of p53 has been extensively studied, the physiological function and molecular mechanisms by which p53-regulated lncRNAs act is beginning to be understood. In this review, we discuss recent studies on lncRNAs that are directly or indirectly regulated by p53 and how they contribute to the biological outcomes of p53 activation. WIREs RNA 2017, 8:e1410. doi: 10.1002/wrna.1410 For further resources related to this article, please visit the WIREs website.

Bioinformatic identification of candidate genes induced by trichostatin A in BGC-823 gastric cancer cells

The aim of the present study was to identify the candidate genes induced by trichostatin A (TSA) in BGC-823 gastric cancer (GC) cells and to explore the possible inhibition mechanism of TSA in GC. Gene expression data were obtained through chip detection, and differentially expressed genes (DEGs) between GC cells treated with TSA and untreated GC cells (control group) were identified. Gene ontology analysis of the DEGs was performed using the database for annotation, visualization and integrated discovery. Then sub-pathway enrichment analysis was performed and a microRNA (miRNA) regulatory network was constructed. We selected 76 DEGs, among which 43 were downregulated genes and 33 were upregulated genes. By sub-pathway enrichment analysis of the DEGs, the propanoate metabolism pathway was selected as the sub-pathway. By constructing a miRNA regulatory network, we identified that DKK1 and KLF13 were the top hub nodes. The propanoate metabolism pathway and the genes DKK1 and KLF13 may play significant roles in the inhibition of GC induced by TSA. These genes may be potential therapeutic targets for GC. However, further experiments are still required to confirm our results.

Long non-coding RNA LOC572558 inhibits bladder cancer cell proliferation and tumor growth by regulating the AKT-MDM2-p53 signaling axis

Long non-coding RNAs (lncRNAs) have been suggested to play important roles in the progression of many cancers such as bladder cancer. However, the detailed mechanism has not been fully understood. We have previously identified a collection of aberrantly expressed lncRNAs in bladder cancer using microarray gene profiling assay. In the current study, we aim to further explore the expression profile and the function of LOC572558, one of the most deregulated lncRNAs in bladder cancer. A large cohort of human bladder cancer tissue samples with benign controls, as well as established human bladder cancer cell lines, has been examined for the expression of LOC572558. The biological functions of LOC572558 were examined by CCK-8 assay, flow cytometry analysis, and wound healing and transwell assays. Using a high-throughput phospho-proteome array, we identified proteins that were ectopic phosphorylated in bladder cancer cells where LOC572558 expression was upregulated. We demonstrated that LOC572558 expression was markedly decreased in bladder cancer tissues and bladder cancer cell lines. Moreover, ectopic expression of LOC572558 inhibited cell proliferation and motility, induced S phase arrest of the cell cycle and promoted cell apoptosis in T24 and 5637 bladder cancer cell lines. We further verified that overexpression of LOC572558 was associated with dephosphorylation of AKT, MDM2 and phosphorylation of p53 protein. Our data clearly demonstrated that LOC572558 is a tumor suppressor and regulates the p53 signaling pathway in bladder cancer. Thus, it may serve as a promising new diagnostic marker and therapeutic target in bladder cancer.

[Epigenetics in urothelial cancer: Pathogenesis, improving diagnostics and developing novel treatment options]

Urothelial carcinoma of the bladder is a common tumor for which improvements in diagnostic markers and new therapy approaches, in addition to or combined with standard chemotherapy, are urgently required. Epigenetic alterations could provide both novel diagnostic markers and therapeutic targets as they are emerging as crucial factors in the development and progression of this tumor type, likely contributing to altered differentiation and metastatic potential. These alterations affect DNA methylation, histone modifications, chromatin remodeling, long noncoding RNAs, and microRNAs. Factors involved in histone modifications and chromatin remodeling appear to be particularly frequently inactivated by mutations. Thus, histone-modifying enzymes may represent good targets for rational new therapeutic approaches, although thorough investigation of their complex functions is a prerequisite. DNA methylation changes and altered miRNA expression provide promising biomarkers for diagnosis and prognosis that need further validation in comprehensive and well-standardized studies.

Differential expression profiles of long non-coding RNAs reveal potential biomarkers for identification of human gastric cancer

Gastric cancer (GC) is one of the most lethal malignancies worldwide. To reduce its high mortality, sensitive and specific biomarkers for early detection are urgently needed. Recent studies have reported that tumor-specific long non-coding RNAs (lncRNAs) seem to be potential biomarkers for the early diagnosis and treatment of cancer. In the present study, lncRNA and mRNA expression profiling of GC specimens and their paired adjacent non-cancerous tissues was performed. Differentially expressed lncRNAs and mRNAs were identified through microarray analysis. The function of differential mRNA was determined by gene ontology and pathway analysis and the functions of lncRNAs were studied by constructing a co-expression network to find the relationships with corresponding mRNAs. We connected the co-expression network, mRNA functions, and the results of the microarray profile differential expression and selected 14 significantly differentially expressed key lncRNAs and 21 key mRNAs. Quantitative RT-PCR (qRT-PCR) was conducted to verify these key RNAs in 50 newly diagnosed GC patients. The data showed that RP5-919F19, CTD-2541M15 and UCA1 was significantly higher expressed. AP000459, LOC101928316, RP11-167N4 and LINC01071 expression was significantly lower in 30 advanced GC tumor tissues than adjacent non-tumor tissues P<0.05. Then, we further validated the above significant differential expression candidate lncRNAs in 20 early stage GC patients. Results showed that CTD-2541M15 and UCA1 were significantly higher expressed, AP000459, LINC01071 and MEG3 expression was significantly lower in 20 early stage GC patient tumor tissues than adjacent non-tumor tissues (P<0.05). In addition, expression of these lncRNAs shows gradual upward trend from early stage GC to advanced GC. Furthermore, conditional logistic regression analysis revealed the aberrant expression of CTD-2541M15, UCA1 and MEG3 closely linked with GC. There is a set of differentially expressed lncRNAs in GC which may be associated with the progression and development of GC. The differential expression profiles of lncRNAs in GC may be promising biomarkers for the early detection and early screening of high‑risk populations.

Role of long noncoding RNAs in malignant disease (Review)

Long noncoding RNAs (lncRNAs) are endogenous transcribed RNA molecules without protein-coding potential, ranging between 200 and 100,000 nt in length. LncRNAs regulate the expression of specific genes in several ways, including guiding chromatin-remodeling, and affecting splicing, transcription or translation. The mutations and dysregulation of lncRNAs have been found to be important in various human diseases, but particularly in human cancer. Previous studies have demonstrated that changes to lncRNAs are closely associated with tumorigenesis, metastasis, prognosis and diagnosis. The current review aims to present a brief overview of the associated reports of lncRNAs in malignant neoplasms, including breast cancer, prostate cancer and hematological malignancies. LncRNAs may be evaluated as novel markers in disease diagnosis, and as prospective therapeutic targets for the prevention and treatment of human diseases.

C-Myc-activated long noncoding RNA CCAT1 promotes colon cancer cell proliferation and invasion

Recently, more and more evidence are rapidly accumulating that long noncoding RNAs (lncRNAs) are involved in human tumorigenesis and misregulated in many cancers, including colon cancer. LncRNA could regulate essential pathways that contribute to tumor initiation and progression with their tissue specificity, which indicates that lncRNA would be valuable biomarkers and therapeutic targets. Colon cancer-associated transcript 1 (CCAT1) is a 2628 nucleotide-lncRNA and located in the vicinity of a well-known transcription factor c-Myc. CCAT1 has been found to be upregulated in many cancers, including gastric carcinoma and colonic adenoma-carcinoma. However, its roles in colon cancer are still not well documented and need to be investigated. In this study, we aim to investigate the prognostic value and biological function of CCAT1 and discover which factors may contribute to the deregulation of CCAT1 in colon cancer. Our results revealed that CCAT1 was significantly overexpressed in colon cancer tissues when compared with normal tissues, and its increased expression was correlated with patients' clinical stage, lymph nodes metastasis, and survival time after surgery. Moreover, c-Myc could promote CCAT1 transcription by directly binding to its promoter region, and upregulation of CCAT1 expression in colon cancer cells promoted cell proliferation and invasion. These data suggest that c-Myc-activated lncRNA CCAT1 expression contribute to colon cancer tumorigenesis and the metastatic process and could predict the clinical outcome of colon cancer and be a potential target for lncRNA direct therapy.