Integrated analysis of a competing endogenous RNA network reveals key long noncoding RNAs as potential prognostic biomarkers for hepatocellular carcinoma

An extensive overview of the role of lncRNAs generated from immune cells in the etiology of cancer

Long non-coding RNAs (lncRNAs) are involved in the control of critical tumor-suppressor and oncogenic pathways in cancer. These types of non-coding RNAs could affect both immune and cancer cells. The thorough analysis of lncRNAs derived from immune cells and the incorporation of new findings significantly advance our understanding of the complex role of lncRNAs in the context of cancer. This work highlights the promise of lncRNAs for translational therapeutic approaches while also establishing a solid foundation for comprehending the complex link between lncRNAs and cancer through a coherent narrative. The main findings of this article are that types of lncRNAs derived from immune cells, such as MM2P and MALAT1, can affect the behaviors of cancer cells, like invasion, angiogenesis, and proliferation. As research in this area grows, the therapeutic potential of targeting these lncRNAs offers promising opportunities for expanding our understanding of cancer biology and developing cutting-edge, precision-based therapies for cancer therapy.

Expression analysis of novel long non-coding RNAs for invasive ductal and invasive lobular breast carcinoma cases

AIM

Long non-coding RNAs (LncRNAs) serve as important regulatory molecules of gene expression and protein functionality at multiple biological levels, and their deregulation plays a key role in tumorigenesis including in breast cancer metastasis. Therefore, in this study, we aim to compare the expression of novel lncRNAs in the landscape of invasive ductal carcinoma (IDC) and invasive lobular (ILC) carcinoma of breast.

MAIN METHODS

We have designed an in-silico approach to find the lncRNAs that regulate the breast cancer. Then, we used the clinical samples to carry out the verification of our in silico finding. In the present study, the tissues of breast cancer were deparaffinized. RNA was extracted by the TRIzole method. After synthesizing cDNA from the extracted RNA, expression levels of lncRNAs were analyzed by qPCR using primers specifically designed and validated for the targeted lncRNAs. In this study, breast biopsy materials from 41 female patients with IDC and 10 female patients with ILC were examined histopathological and expression changes of candidate lncRNAs were investigated in line with the findings. The results were analyzed using IBM SPSS Statistics 25 version.

RESULTS

The mean age of the cases was 53.78 ± 14.96. The minimum age was 29, while the maximum age was 87. While 27 of the cases were pre-menopausal, 24 cases were post-menopausal. The number of hormone receptor-positive cases was found to be 40, 35, and 27 for ER, PR, and cerb2/neu, respectively. While the expressions of LINC00501, LINC00578, LINC01209, LINC02015, LINC02584, ABCC5-AS1, PEX5L-AS2, SHANK2-AS3 and SOX2-OT showed significant differences (p < 0.05), the expressions of LINC01206, LINC01994, SHANK2-AS1, and TPRG1-AS2 showed no significant differences (p > 0.05). In addition, it was determined that the regulation of all lncRNAs could be able to involve in the development of cancer such as the NOTCH1, NFKB, and estrogen receptor signalings.

CONCLUSION

As a result, it was thought that the discovery of novel lncRNAs might be an important player in the diagnosis, prognosis and therapeutic development of breast cancer.

A novel prognostic related lncRNA signature associated with amino acid metabolism in glioma

Background

Glioma is one of the deadliest malignant brain tumors in adults, which is highly invasive and has a poor prognosis, and long non-coding RNAs (lncRNAs) have key roles in the progression of glioma. Amino acid metabolism reprogramming is an emerging hallmark in cancer. However, the diverse amino acid metabolism programs and prognostic value remain unclear during glioma progression. Thus, we aim to find potential amino-related prognostic glioma hub genes, elaborate and verify their functions, and explore further their impact on glioma.

Methods

Glioblastoma (GBM) and low-grade glioma (LGG) patients' data were downloaded from TCGA and CCGA datasets. LncRNAs associated with amino acid metabolism were discriminated against via correlation analysis. LASSO analysis and Cox regression analysis were conducted to identify lncRNAs related to prognosis. GSVA and GSEA were performed to predict the potential biological functions of lncRNA. Somatic mutation data and CNV data were further built to demonstrate genomic alterations and the correlation between risk scores. Human glioma cell lines U251 and U87-MG were used for further validation in vitro experiments.

Results

There were eight amino-related lncRNAs in total with a high prognostic value that were identified via Cox regression and LASSO regression analyses. The high risk-score group presented a significantly poorer prognosis compared with the low risk-score group, with more clinicopathological features and characteristic genomic aberrations. Our results provided new insights into biological functions in the above signature lncRNAs, which participate in the amino acid metabolism of glioma. LINC01561 is one of the eight identified lncRNAs, which was adopted for further verification. In in vitro experiments, siRNA-mediated LINC01561 silencing suppresses glioma cells' viability, migration, and proliferation.

Conclusion

Novel amino-related lncRNAs associated with the survival of glioma patients were identified, and a lncRNA signature can predict glioma prognosis and therapy response, which possibly has vital roles in glioma. Meanwhile, it emphasized the importance of amino acid metabolism in glioma, particularly in providing deeper research at the molecular level.

Identification of lncRNA biomarkers in hepatocellular carcinoma by comprehensive analysis of the lncRNA-mediated ceRNA network

Growing evidence implicates that miRNAs can interact with long non-coding RNAs (lncRNAs) to regulate target mRNAs through competitive interactions. However, this mechanism that regulate tumorigenesis and cancer progression remains largely unexplored. Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs), which play a significant role in regulating gene expression. The purpose of our study was to determine potential lncRNA biomarkers to predict the prognosis of HCC by comprehensive analysis of a ceRNA network. The edgeR package was used to obtain the differentially expressed RNA datasets by analyzing 370 HCC tissues and 50 adjacent non-HCC tissues from The Cancer Genome Atlas (TCGA). Through investigating the differentially expressed between HCC tissues and adjacent non-HCC tissues, a total of 947 lncRNAs, 52 miRNAs, and 1,650 mRNAs were obtained. The novel constructed ceRNA network incorporated 99 HCC-specific lncRNAs, four miRNAs, and 55 mRNAs. Survival analysis identified 22 differentially expressed mRNAs, four miRNAs, and nine lncRNAs which were associated with overall survival (OS) time in HCC (p &lt; 0.05), and further exploration was performed to assess the correlation of these differentially expressed genes with tumor stage. The Interpretation of the potential functions of these differentially expressed genes in HCC was realized by Gene ontology (GO) and KEGG pathway enrichment analyses. Seven lncRNAs were confirmed based on univariate Cox regression analysis, lasso COX regression analysis and multivariate Cox regression analysis to construct a predictive model in HCC patients which were related to the prognosis of OS. In summary, ceRNAs contributed to explore the mechanism of tumorigenesis and development, and a model with seven lncRNAs might be potential biomarker to predict the prognosis of HCC. These findings supported the need to studies on the mechanisms involved in the regulation of HCC by ceRNAs.

A somatic mutation-derived LncRNA signatures of genomic instability predicts the prognosis and tumor microenvironment immune characters in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is an aggressive carcinoma with genome instability. Long non-coding RNAs (LncRNAs) have been functionally associated with genomic instability in cancers. However, the identification and prognostic value of lncRNAs related to genome instability have not been explored in hepatocellular carcinoma. In this study, we aim to identify a genomic instability-related lncRNA signature for predicting prognosis and the efficacy of immunotherapy in HCC patients.

METHODS

According to the somatic mutation and transcript data of 364 patients with HCC, we determined differentially expressed genome instability-related lncRNAs (GInLncRNAs). Gene ontology (GO) enrichment analyses and Kyoto Encyclopedia of genes and genomes enrichment analyses revealed the potential functions of genes co-expressed with those lncRNAs involved in cancer development and immune function. We further determined a genome instability-related lncRNA signature (GInLncSig) through Cox regression analysis and LASSO regression analysis. Thereafter, we performed correlation analyses with mutations, clinical stratification analyses, and survival analyses to evaluate GInLncSig predictive function. Subsequently, we construct a nomogram model for prognostic assessments of patients with HCC. Finally, we performed Immunocytes infiltration analysis, gene set enrichment analysis (ssGSEA) of immunity circle-associated pathways, and T cell-inflamed score to explore GInLncSig's potential value in guiding immunotherapy.

RESULTS

We identified 11 independent prognosis-associated GInLncRNAs (AC002511.2, LINC00501, LINC02055, LINC02714, LINC01508, LOC105371967, RP11_96A15.1, RP11_305F18.1, RP11_342M1.3, RP11_432J24.3, U95743.1) to construct a GInLncSig. According to the risk score calculated by GInLncSig, the high-risk group was characterized by a higher somatic mutation count, significantly poorer clinical prognosis, higher T cell-inflamed score, and specific tumor immune infiltration status compared to the low-risk group. Furthermore, we constructed a nomogram model to improve the reliability and clinical utility of predicting the prognosis of patients with HCC.

CONCLUSION

Our study established a reliable prognostic prediction signature that could be a tool for prognosis prediction and a promising predictive biomarker of immunotherapy in hepatocellular carcinoma.

Long non‑coding RNA PART1: dual role in cancer

Increasing evidence has shown that long non-coding RNAs (lncRNAs), which are non-coding endogenous single-stranded RNAs, play an essential role in various physiological and pathological processes through transcriptional interference, post-transcriptional regulation, and epigenetic modification. Moreover, lncRNAs, as oncogenes or tumor suppressor genes, play an important role in the occurrence and development of human cancers. Prostate androgen-regulated transcript 1 (PART1) was initially identified as a carcinogenic lncRNA in prostate adenomas. The upregulated expression of PART1 plays a tumor-promoting role in liver, prostate, lung cancers, and other tumors. In contrast, the expression of PART1 is downregulated in esophageal squamous cell carcinoma, glioma, and other tumors, which may inhibit the tumor. PART1 plays a dual role in cancer and regulates cell proliferation, apoptosis, invasion, and metastasis through a variety of potential mechanisms. These findings suggest that PART1 is a promising tumor biomarker and therapeutic target. This article reviews the biological functions, related mechanisms, and potential clinical significance of PART1 in a variety of human cancers.

LncRNA TSPEAR-AS1 predicts poor prognosis in patients with hepatitis B virus-associated hepatocellular carcinoma and promotes metastasis via miR-1915-5p

BACKGROUND

Hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) will contribute to more than half of the liver deaths worldwide. This study aimed to investigate the prognostic value of TSPEAR-AS1 in HBV-HCC and its role in the HBV-HCC progression.

METHODS

HBV-HCC tissue and adjacent non-cancerous tissues (ANT) were detected to figure out the expression level of TSPEAR-AS1 using real-time quantitative PCR. The relationship between TSPEAR-AS1 expression and each important clinical characteristic was evaluated. And the prognostic significance of TSPEAR-AS1 was assessed by Kaplan-Meier curve and Cox regression analysis. CCK-8 and Transwell assays were performed to observe the effects of TSPEAR-AS1 on HBV-HCC cell proliferation, migration, and invasion.

RESULTS

The TSPEAR-AS1 expression was downregulated in HBV-HCC tissues, as well as in HBV-HCC cell lines. The downregulation of TSPEAR-AS1 showed a significant association with TNM stage, clinical stage, and vascular invasion and predicted poor prognosis of HBV-HCC patients. Overexpression of TSPEAR-AS1 inhibited HBV-HCC cell ability of proliferation, migration, and invasiveness. TSPEAR-AS1 may bind to miR-1915-5p in HCC.

CONCLUSION

TSPEAR-AS1 expression was downregulated in HBV-HCC and may serve as a potential prognostic factor. TSPEAR-AS1 might exert a suppressor role in HBV-HCC through inhibiting tumor cell proliferation, migration, and invasion.

Construction and Comprehensive Analysis of ceRNA Networks and Tumor-Infiltrating Immune Cells in Hepatocellular Carcinoma With Vascular Invasion

Background: Hepatocellular carcinoma (HCC) is a common malignant cancer. Metastasis plays a critical role in tumor progression, and vascular invasion is considered one of the most crucial factors for HCC metastasis. However, comprehensive analysis focusing on competitive endogenous RNA (ceRNA) and immune infiltration in the vascular invasion of HCC is lacking.

Methods: The gene expression profiles of 321 samples, including 210 primary HCC cases and 111 HCC cases with vascular invasion, were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma project, and used in identifying significant differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs). The RNAs associated with vascular invasion were used in constructing a ceRNA network. A multigene-based risk signature was constructed using the least absolute shrinkage and selection operator algorithm. We detected the fractions of 28 immune cell types in HCC through single-sample gene set enrichment analysis (ssGSEA). Finally, the relationship between the ceRNA network and immune cells was determined through correlation analysis and used in clarifying the potential mechanism involved in vascular invasion.

Results: Overall, 413 DElncRNAs, 27 DEmiRNAs, and 397 DEmRNAs were recognized in HCC. A specific ceRNA network based on the interaction among 3 lncRNA–miRNA pairs and 24 miRNA–mRNA pairs were established. A ceRNA-based prognostic signature was constructed and used in dividing samples into high- and low-risk subgroups. The signature showed significant efficacy; its 3- and 5-year areas under the receiver operating characteristic curves were 0.712 and 0.653, respectively. ceRNA and ssGSEA integration analysis demonstrated that PART1 (p = 0, R = −0.33) and CDK5R2 (p = 0.01, R = −0.15) were negatively correlated to natural killer cells.

Conclusion: This study demonstrated that vascular invasion in HCC might be related to PART1, and its role in regulating CDK5R2 and NK cells. A nomogram was developed to predict the prognosis of patients with HCC and demonstrated the value of the ceRNA network and tumor-infiltrating immune cells value in improving personalized management.

Construction of an HCC recurrence model based on the investigation of immune-related lncRNAs and related mechanisms

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in immune regulation. Growing evidence suggests that immune-related genes and lncRNAs can serve as markers to predict the prognosis of patients with cancers, including hepatocellular carcinoma (HCC). This study aimed to contract an immune-related lncRNA (IR-lncRNA) signature for prospective assessment to predict early recurrence of HCC. A total of 319 HCC samples under radical resection were randomly divided into a training cohort (161 samples) and a testing cohort (158 samples). In the training dataset, univariate, lasso, and multivariate Cox regression analyses identified a 9-IR-lncRNA signature closely related to disease-free survival. Kaplan-Meier analysis, principal component analysis, gene set enrichment analysis, and nomogram were used to evaluate the risk model. The results were further confirmed in the testing cohort. Furthermore, we constructed a competitive endogenous RNA regulatory network. The results of the present study indicated that this 9-IR-lncRNA signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in HCC patients. These IR-lncRNAs and regulated genes may be potential biomarkers associated with the prognosis of HCC.

Comprehensive analysis of competitive endogenous RNAs networks reveals potential prognostic biomarkers associated with epithelial ovarian cancer

Ovarian cancer (OC) is a major health threat to females, as it has high morbidity and mortality. Evidence has increasingly demonstrated that long non-coding RNAs (lncRNAs) regulate OC progression and they may have value as early diagnostic biomarkers, prognostic biomarkers and/or therapeutic targets. In the present study, the regulatory mechanisms and prognosis associated with cancer-specific lncRNAs and their related competing endogenous (ce)RNA network in OC were investigated. The differential expression profiles and prognostic significance of lncRNAs and mRNAs were systematically explored based on data from 359 OC cases from The Cancer Genome Atlas and 180 healthy individuals from the Genotype-Tissue Expression database. Functional enrichment analyses, RNA-RNA interactome prediction, ceRNA network analysis, correlation analysis and survival analysis were utilized to identify hub lncRNAs and biomarkers associated with OC diagnosis or prognosis. A total of 1,049 differentially expressed lncRNAs and 6,516 differentially expressed mRNAs between OC and healthy tissues were detected. An lncRNA-micro (mi)RNA-mRNA regulatory network in OC was further established, containing 91 lncRNAs, 23 miRNAs and 179 mRNAs. After survival analysis based on the expression of the RNAs in the ceRNA network, 8 lncRNAs, 4 miRNAs and 11 mRNAs that were significantly associated with OC patient survival (P<0.05) were obtained. Using least absolute shrinkage and selection operator-penalized Cox regression, an eight-lncRNA risk score model was generated, which was able to readily discriminate between OC and healthy individuals and predict the survival of patients with OC. In addition, the differential expression of several key lncRNAs and mRNAs was verified by reverse transcription-quantitative PCR and western blot analysis. The current study presents a novel lncRNA-miRNA-mRNA network, which provides insight into the potential pathogenesis of OC and allows the identification of prognostic biomarkers and treatment strategies for OC.

Silencing of long noncoding RNA MYLK-AS1 suppresses nephroblastoma via down-regulation of CCNE1 through transcription factor TCF7L2

Nephroblastoma, a pediatric kidney cancer, caused by pluripotent embryonic renal precursors. Long noncoding RNAs (lncRNAs) are commonly abnormal expressed in many cancers. In the present study, we fousced on one newly discrovered lncRNA, MYLK Antisense RNA 1 (MYLK-AS1), and its functional role in proliferation and cycle distribution of nephroblastoma cells. Micorarray-based analysis revealed the highly expressed Cyclin E1 (CCNE1) and MYLK-AS1 in nephroblastoma. After nephroblastoma tissue sample collection, RT-qPCR confirmed the upregulated expression of MYLK-AS1 and CCNE1 in nephroblastoma tissues and cells. Kaplan-Meier curve exhibited that patients with elevated CCNE1 had lower overall survival rate in follow-up study. RNA binding protein immunoprecipitation, chromatin immunoprecipitation, and dual-luciferase reporter gene assay were employed to determine the relationship among MYLK-AS1, TCF7L2, and CCNE1, which validated that transcription factor 7-like 2 (TCF7L2) could specifically bind to MYLK-AS1 and TCF7L2 could positively promote CCNE1. After gain- and loss-of function assays, the conclusion that silencing of MYLK-AS1 could inhibit expression of CCNE1 through the transcription factor TCF7L2 to regulate the cell proliferation and cell cycle distribution of nephroblastoma cells was obtained. Subsequently, the subcutaneous tumor formation ability of nephroblastoma cell in nude mice was observed and the silencing of MYLK-AS1 exerts suppressive role in the tumorigenic ability of nephroblastoma cells in vivo. Taken together, MYLK-AS1 constitutes a promising biomarker for the early detection and treatment of nephroblastoma.

The Role of Tumor-related LncRNA PART1 in cancer

BACKGROUND

As we all know, long non-coding RNA (lncRNA) affects tumor progression, which has caused a great upsurge in recent years. It can also affect the growth, migration, and invasion of tumors. When we refer to the abnormal expression of lncRNA, we will find it associated with malignant tumors. In addition, lncRNA has been proved to be a key targeted gene for the treatment of some diseases. PART1, a member of lncRNA, has been reported as a regulator in the process of tumor occurrence and development. This study aims to reveal the biological functions, specific mechanisms, and clinical significance of PART1 in various tumor cells.

METHODS

Through the careful search of PUBMED, the mechanisms of the effect of PART1 on tumorigenesis and development are summarized.

RESULTS

On the one hand, the up-regulated expression of PART1 plays a tumor-promoting role in tumors, including lung cancer, prostate cancer, bladder cancer and so on. On the other hand, PART1 is down-regulated in gastric cancer, glioma and other tumors to play a tumor inhibitory role. In addition, PART1 regulates tumor growth mainly by targeting microRNA such as miR-635, directly regulating the expression of proteins such as FUS/EZH2, affecting signal pathways such as the Toll-like receptor pathway, or regulating immune cells.

CONCLUSION

PART1 is closely related to tumors by regulating a variety of molecular mechanisms. In addition, PART1 can be used as a clinical marker for the early diagnosis of tumors and plays an important role in tumor-targeted therapy.

Development and validation of ferroptosis-related lncRNAs signature for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors throughout the world. However, there is no research to establish a ferroptosis-related lncRNAs (FRlncRNAs) signature for the patients with HCC. Therefore, this study was designed to establish a novel FRlncRNAs signature to predict the survival of patients with HCC.

Method

The expression profiles of lncRNAs were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. FRlncRNAs co-expressed with ferroptosis-related genes were utilized to establish a signature. Cox regression was used to construct a novel three FRlncRNAs signature in the TCGA cohort, which was verified in the GEO validation cohort.

Results

Three differently expressed FRlncRNAs significantly associated with prognosis of HCC were identified, which composed a novel FRlncRNAs signature. According to the FRlncRNAs signature, the patients with HCC could be divided into low- and high-risk groups. Patients with HCC in the high-risk group displayed shorter overall survival (OS) contrasted with those in the low-risk group (P < 0.001 in TCGA cohort and P = 0.045 in GEO cohort). This signature could serve as a significantly independent predictor in Cox regression (multivariate HR > 1, P < 0.001), which was verified to a certain extent in the GEO cohort (univariate HR > 1, P < 0.05). Meanwhile, it was also a useful tool in predicting survival among each stratum of gender, age, grade, stage, and etiology,etc. This signature was connected with immune cell infiltration (i.e., Macrophage, Myeloid dendritic cell, and Neutrophil cell, etc.) and immune checkpoint blockade targets (PD-1, CTLA-4, and TIM-3).

Conclusion

The three FRlncRNAs might be potential therapeutic targets for patients, and their signature could be utilized for prognostic prediction in HCC.

The REASON score: an epigenetic and clinicopathologic score to predict risk of poor survival in patients with early stage oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a capricious cancer with poor survival rates, even for early-stage patients. There is a pressing need to develop more precise risk assessment methods to appropriately tailor clinical treatment. Genome-wide association studies have not produced a viable biomarker. However, these studies are limited by using heterogeneous cohorts, not focusing on methylation although OSCC is a heavily epigenetically-regulated cancer, and not combining molecular data with clinicopathologic data for risk prediction. In this study we focused on early-stage (I/II) OSCC and created a risk score called the REASON score, which combines clinicopathologic characteristics with a 12-gene methylation signature, to predict the risk of 5-year mortality.

METHODS

We combined data from an internal cohort (n = 515) and The Cancer Genome Atlas (TCGA) cohort (n = 58). We collected clinicopathologic data from both cohorts to derive the non-molecular portion of the REASON score. We then analyzed the TCGA cohort DNA methylation data to derive the molecular portion of the risk score.

RESULTS

5-year disease specific survival was 63% for the internal cohort and 86% for the TCGA cohort. The clinicopathologic features with the highest predictive ability among the two the cohorts were age, race, sex, tobacco use, alcohol use, histologic grade, stage, perineural invasion (PNI), lymphovascular invasion (LVI), and margin status. This panel of 10 non-molecular features predicted 5-year mortality risk with a concordance (c)-index = 0.67. Our molecular panel consisted of a 12-gene methylation signature (i.e., HORMAD2, MYLK, GPR133, SOX8, TRPA1, ABCA2, HGFAC, MCPH1, WDR86, CACNA1H, RNF216, CCNJL), which had the most significant differential methylation between patients who survived vs. died by 5 years. All 12 genes have already been linked to survival in other cancers. Of the genes, only SOX8 was previously associated with OSCC; our study was the first to link the remaining 11 genes to OSCC survival. The combined molecular and non-molecular panel formed the REASON score, which predicted risk of death with a c-index = 0.915.

CONCLUSIONS

The REASON score is a promising biomarker to predict risk of mortality in early-stage OSCC patients. Validation of the REASON score in a larger independent cohort is warranted.

Integrative analysis of the gastric cancer long non-coding RNA-associated competing endogenous RNA network

Gastric cancer (GC) is a common type of cancer, and identification of novel diagnostic biomarkers associated with this disease is important. The present study aimed to identify novel diagnostic biomarkers associated with the prognosis of GC, using an integrated bioinformatics approach. Differentially expressed long non-coding RNAs (lncRNAs) associated with GC were identified using Gene Expression Omnibus datasets (GSE58828, GSE72305 and GSE99416) and The Cancer Genome Atlas database. A competing endogenous RNA network that incorporated five lncRNAs [long intergenic non-protein coding RNA 501 (LINC00501), LINC00365, SOX21 antisense divergent transcript 1 (SOX21-AS1), GK intronic transcript 1 (GK-IT1) and DLEU7 antisense RNA 1 (DLEU7-AS1)], 29 microRNAs and 114 mRNAs was constructed. Gene Ontology and protein-protein interaction network analyses revealed that these lncRNAs may be involved in 'biological regulation', 'metabolic process', 'cell communication', 'developmental process', 'cell proliferation', 'reproduction' and the 'cell cycle'. The results of receiver operating characteristic curve analysis demonstrated that LINC00501 (AUC=0.819), LINC00365 (AUC=0.580), SOX21-AS1 (AUC=0.736), GK-IT1 (AUC=0.823) and DLEU7-AS1 (AUC=0.932) had the potential to become valuable diagnostic biomarkers for GC. Associations with clinicopathological characteristics demonstrated that LINC00501 expression was significantly associated with sex (P=0.015) and tumor grade (P=0.022). Furthermore, LINC00365 expression was significantly associated with lymph node metastasis (P=0.025). Gene set enrichment analysis revealed that LINC00501, LINC00365 and SOX21-AS1 were enriched in signaling pathways associated with GC. Reverse transcription-quantitative PCR analysis demonstrated that LINC00501 expression (P=0.043) was significantly upregulated in GC tissues, whereas the expression levels of LINC00365 (P=0.033) and SOX21-AS1 (P=0.037) were significantly downregulated in GC tissues. Taken together, the results of the present study suggest that LINC00501, LINC00365, SOX21-AS1, GK-IT1 and DLEU7-AS1 may be used as novel diagnostic biomarkers for GC, and may be functionally associated with GC development and progression.

Construction of a ceRNA Network and a Prognostic lncRNA Signature associated with Vascular Invasion in Hepatocellular Carcinoma based on Weighted Gene Co-Expression Network Analysis

Background: Understanding risk factors for vascular invasion (VI) is crucial for assessing the risk of recurrence and overall prognosis of hepatocellular carcinoma (HCC). This study aimed to construct a prognostic long non-coding RNA (lncRNA) signature and a ceRNA Network associated with vascular invasion in HCC. Methods: Differentially expressed genes (DEGs) of HCC patients associated with VI were identified by analyzing data from TCGA. Weighted gene co-expression network analysis (WGCNA) was used to identify associations between gene expression modules and clinical features. A VI-related prognostic lncRNA signature was then established using univariate, LASSO and multivariate Cox proportional hazards regression analyses. Based on the hub modules identified by the WGCNA, we constructed a VI-related lncRNA-miRNA-mRNA ceRNA network and screened hub lncRNAs for further research. Finally, we conducted in vitro and in vivo experiments to determine the biological roles of the identified hub gene BBOX1-AS1. Results: The key module related to VI and OS was identified using WGCNA, after which a prognostic model consisting of eight lncRNAs was established, and verified using time-dependent receiver operating characteristic (ROC) curve analysis. BBOX1-AS1 was confirmed to be highly expressed in HCC tissues, and its expression was significantly correlated with a poor prognosis. Silencing BBOX1-AS1 in vitro significantly suppressed the proliferation, migration and invasion of HCC cells. In vivo experiments demonstrated that knocking down of BBOX1-AS1 could result in significant decrease of tumor volume and tumor weight. Conclusions: The VI-related lncRNA signature established in this study can be used to predict the clinical outcomes of HCC patients. In addition, we constructed a VI-related lncRNA-miRNA-mRNA ceRNA network and demonstrated that BBOX1-AS1 might be a novel biomarker associated with VI in HCC.

Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

Background

Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.

Methods

We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.

Results

With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.

Conclusions

In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08173-0.

Identification of METTL3 as an Adverse Prognostic Biomarker in Hepatocellular Carcinoma

INTRODUCTION

N6-methyladenosine (m6A), the most prominent mRNA modification, plays a critical role in many physiological and pathological processes. However, the roles of m6A RNA modification in hepatocellular carcinoma (HCC) remain largely unknown.

MATERIALS AND METHODS

We investigated the mRNA expression and clinical significance of m6A-related genes using data from The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma cohort. Mutation, copy number variation (CNV), methylation, differential expression, and gene ontology analyses, gene set enrichment analysis and the construction of a competing endogenous RNA (ceRNA) regulatory network were performed to investigate the underlying mechanisms of the aberrant expression of m6A-related genes.

RESULTS

m6A-related genes were frequently dysregulated in cancers but with a cancer-specific pattern. METTL3, YTHDF2, and ZC3H13 were found to be independent prognostic factors of overall survival (OS); however, only METTL3 was found to be an independent prognostic factor of recurrence-free survival (RFS). Joint effects analysis showed the predictive capacity of combining METTL3, YTHDF2, and ZC3H13 for HCC OS. Then the potential mechanisms of METTL3 were further explored due to its prognostic role in both OS and RFS. CNV and DNA methylation, but not somatic mutations, might contribute to the abnormal upregulation of METTL3 in HCC. Significantly altered genes, microRNAs, and lncRNAs were identified, and a ceRNA regulatory network was constructed to explain the upregulation of METTL3 in HCC.

CONCLUSIONS

Our study identified several m6A-related genes, especially METTL3, that could be potential prognostic biomarkers in HCC.

Construction of a disease-specific lncRNA-miRNA-mRNA regulatory network reveals potential regulatory axes and prognostic biomarkers for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with a high incidence and poor prognosis. Exploration of the underlying mechanisms and effective prognostic indicators is conducive to clinical management and optimization of treatment. The RNA‐seq and clinical phenotype data of HCC were retrieved from The Cancer Genome Atlas (TCGA), and differential expression analysis was performed. Then, a differential lncRNA‐miRNA‐mRNA regulatory network was constructed, and the key genes were further identified and validated. By integrating this network with the online tool‐based ceRNA network, an HCC‐specific ceRNA network was obtained, and lncRNA‐miRNA‐mRNA regulatory axes were extracted. RNAs associated with prognosis were further obtained, and multivariate Cox regression models were established to identify the prognostic signature and nomogram. As a result, 198 DElncRNAs, 120 DEmiRNAs, and 2827 DEmRNAs were identified, and 30 key genes identified from the differential network were enriched in four cancer‐related pathways. Four HCC‐specific lncRNA‐miRNA‐mRNA regulatory axes were extracted, and SNHG11, CRNDE, MYLK‐AS1, E2F3, and CHEK1 were found to be related with HCC prognosis. Multivariate Cox regression analysis identified a prognostic signature, comprised of CRNDE, MYLK‐AS1, and CHEK1, for overall survival (OS) of HCC. A nomogram comprising the prognostic signature and pathological stage was established and showed some net clinical benefits. The AUC of the prognostic signature and nomogram for 1‐year, 3‐year, and 5‐year survival was 0.777 (0.657‐0.865), 0.722 (0.640‐0.848), and 0.630 (0.528‐0.823), and 0.751 (0.664‐0.870), 0.773 (0.707‐0.849), and 0.734 (0.638‐0.845), respectively. These results provided clues for the study of potential biomarkers and therapeutic targets for HCC. In addition, the obtained 30 key genes and 4 regulatory axes might also help elucidate the underlying mechanism of HCC.

LncRNA MYLK-AS1 facilitates tumor progression and angiogenesis by targeting miR-424-5p/E2F7 axis and activating VEGFR-2 signaling pathway in hepatocellular carcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs) are crucial in the invasion, angiogenesis, progression, and metastasis of hepatocellular carcinoma (HCC). The lncRNA MYLK-AS1 promotes the growth and invasion of HCC through the EGFR/HER2-ERK1/2 signaling pathway. However, the clinical significance of MYLK-AS1 in HCC still needs to be further determined.

METHODS

Bioinformatic analysis was performed to determine the potential relationship among MYLK-AS1, miRNAs and mRNAs. A total of 156 samples of normal liver and paired HCC tissues from HCC patients were used to evaluate MYLK-AS1 expression by qRT-PCR. Human HCC cell lines were used to evaluate the colony formation, cell proliferation, migration, invasion, cell cycle and apoptosis after transfection of lentiviral short-hairpin RNAs (shRNAs) targeting MYLK-AS1 or MYLK-AS1 vectors. The competitive endogenous RNA (ceRNA) mechanism was clarified using fluorescence in situ hybridization (FISH), Western blotting, qPCR, RNA binding protein immunoprecipitation (RIP), and dual luciferase reporter analysis.

RESULTS

MYLK-AS1 up-regulation was detected in the HCC tumor tissues and cell lines associated with the enhancement of the angiogenesis and tumor progression. The down-regulation of MYLK-AS1 reversed the effects on angiogenesis, proliferation, invasion and metastasis in the HCC cells and in vivo. MYLK-AS1 acted as ceRNA, capable of regulating the angiogenesis in HCC, while the microRNA miR-424-5p was the direct target of MYLK-AS1. Promoting the angiogenesis and the tumor proliferation, the complex MYLK-AS1/miR-424-5p activated the VEGFR-2 signaling through E2F7, whereas the specific targeting of E2F transcription factor 7 (E2F7) by miR-424-5p, was indicated by the mechanism studies.

CONCLUSIONS

MYLK-AS1 and E2F7 are closely related to some malignant clinicopathological features and prognosis of HCC, thus the MYLK-AS1/ miR-424-5p/E2F7 signaling pathway might represent a promising treatment strategy to combat HCC.

LncRNA PART1 Exerts Tumor-Suppressive Functions in Tongue Squamous Cell Carcinoma via miR-503-5p

Background

Tongue squamous cell carcinoma (TSCC) accounts for one-third of oral cancers. Previous studies had reported that lncRNA/miRNA regulated the biological behaviors of different cancer cells. However, the mechanisms of PART1 in regulating tumorigenesis and TSCC development via targeting miR-503-5p had not been studied.

Methods

The expressions of PART1 and miR-503-5p in tissues and cultured cell lines were detected by qRT-PCR. StarBase 3.0 was used to predict the binding sites of PART1, then dual-luciferase assay and RNA pull-down assay were executed to confirm whether miR-503-5p was a target of PART1. TSCC cells were co-transfected with PART1-overexpressed plasmid or miR-503-5p mimics in vitro, and the transfection efficiency was evaluated through qRT-PCR. Western blot was performed to assess the expressions of EMT-related proteins. CCK-8 and clone formation assays were conducted to detect cell proliferation, TUNEL assay was used to detect apoptosis, and transwell assay was executed to test migration and invasion.

Results

The low PART1 expression and high miR-503-5p expression were found in TSCC tissues and cell lines (CAL-27 and SCC9). PART1 expression was positively correlated with patients’ prognosis. The targeting and binding relationship between PART1 and miR-503-5p was confirmed, and overexpressed PART1 diminished the expression of miR-503-5p as well. Moreover, PART1 facilitated apoptosis, inhibited proliferation, invasion and migration of TSCC cells, and these influences were impeded by miR-503-5p overexpression.

Conclusion

LncRNA PART1 played a cancer-suppressing role in TSCC by targeting miR-503-5p, which provided a potential target for TSCC treatment.

Long Noncoding RNA PART1 Promotes Hepatocellular Carcinoma Progression via Targeting miR-590-3p/HMGB2 Axis

Introduction

In East Asia, hepatocellular carcinoma (HCC) is one of the most commonly diagnosed cancer types. Long noncoding RNA (lncRNA) prostate androgen-regulated transcript 1 (PART1) was reported to play crucial roles in regulating cancer progression. However, roles and mechanisms of action of PART1 in hepatocellular carcinoma (HCC) still remain unknown.

Methods

Quantitative real-time polymerase chain reaction (RT-qPCR) method was used to detect the PART1 expression level in HCC cells. Cell proliferation, colony formation, and transwell invasion assays were performed to investigate the biological roles of PART1 on HCC cell behaviors. Bioinformatic analysis methods were performed to analyze connections of microRNA-590-3p (miR-590-3p) with PART1 or high mobility group box 2 (HMGB2) in HCC. Moreover, expression levels of PART1, miR-590-3p, and HMGB2 in HCC tissues and normal tissues were analyzed at ENCORI.

Results

PART1 expression was found to be significantly upregulated in HCC tissues and cells. Functionally, silencing of PART1 significantly suppressed HCC cell proliferation, colony formation and invasion in vitro, while forcing PART1 exerts opposite biological effects. Mechanically, miR-590-3p/HMGB2 axis was downstream target of PART1, and silencing of miR-590-3p or forcing of HMGB2 could rescue the stimulation effects of PART1 overexpression on HCC cell behaviors.

Discussion

Our results provided evidence that PART1 serves as oncogenic lncRNA through sponging miR-590-3p to upregulate HMGB2 expression in HCC.

Risk Scoring System based on lncRNA Expression for Predicting Survival in Hepatocellular Carcinoma with Cirrhosis

Objective:

This study aims to explore the roles of long non-coding RNAs (lncRNAs) for predicting survival in hepatocellular carcinoma (HCC) patients with cirrhosis.

Methods:

A set of lncRNAs differentially expressed between HCC patients with or without cirrhosis was identified using expression profiles of The Cancer Genome Atlas database, and these lncRNAs were screened for their risk scoring system to predict recurrence-free survival (RFS) or overall survival (OS). Predictive ability of risk scoring systems was confirmed using uni- and multivariate Cox analyses while adjusting for clinical features. Predictive lncRNAs were analyzed by functional enrichment analysis.

Results:

Our screen identified 22 lncRNAs that were upregulated in the presence of cirrhosis and 59 that were downregulated. To predict OS of HCC patients with cirrhosis, a risk scoring system was developed with four lncRNAs (LINC02086, LINC00880, LINC01549 and AC136475.3); to predict RFS in these patients, the risk scoring system contained five lncRNAs (SH3RF3-AS1, AC104117.3, AC136475.3, LINC00239 and MRPL23-AS1). All risk scoring systems were associated with an area under the receiver operating characteristic curve > 0.7. Based on uni- and multivariate Cox analyses, the risk scoring system could serve as a significant independent predictor for OS in HCC patients with cirrhosis. Functional enrichment analysis suggested that the lncRNAs in the risk scoring systems are involved primarily in the pathway of Wnt signal and cytokine-cytokine receptor interaction.

Conclusion:

Risk scoring systems based on lncRNAs can effectively predict OS of HCC patients with cirrhosis. The system should be further developed and validated in larger, preferably multi-site patient populations.

Long Non-Coding RNA PART1 Promotes Proliferation, Migration and Invasion of Hepatocellular Carcinoma Cells via miR-149-5p/MAP2K1 Axis

Background

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy worldwide. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been identified as effective markers for the detection of multiple cancers. This study aimed to illuminate the mechanism of prostate androgen regulated transcript 1 (PART1) in HCC.

Materials and Methods

The levels of PART1, miR-149-5p and mitogen-activated protein kinase 1 (MAP2K1) mRNA were detected by quantitative real-time polymerase chain reaction (qRT-PCR) assay. Cell proliferation was assessed by Cell Counting Kit-8 (CCK-8) assay, and cell migration and invasion were evaluated by transwell assay. Dual-luciferase reporter assay was carried out to examine the relationship among PART1, miR-149-5p and MAP2K1. Western blot assay was conducted to measure the protein expression of MAP2K1.

Results

PART1 and MAP2K1 expression were greatly increased and miR-149-5p level was decreased in HCC tissues. Functional analysis revealed that the si-PART1 inhibited proliferation, migration and invasion of HCC cells. PART1 directly bound to miR-149-5p and miR-149-5p level was down-regulated by PART1. Moreover, restoration experiment demonstrated that the effect of PART1 knockdown on HCC cell progression could be partially rescued by miR-149-5p depletion. MiR-149-5p was predicted to target MAP2K1 and MAP2K1 expression was negatively modulated by miR-149-5p. Also, MAP2K1 rescued the inhibitory effects of miR-149-5p overexpression on proliferation, migration and invasion in HCC cells. Besides, the inhibition of miR-149-5p weakened the impact on MAP2K1 expression mediated by PART1 repression.

Conclusion

PART1 promoted proliferation, migration and invasion of HCC cells by regulating miR-149-5p/MAP2K1 axis.

CircRNA_103809 Suppresses the Proliferation and Metastasis of Breast Cancer Cells by Sponging MicroRNA-532-3p (miR-532-3p)

Breast cancer has become one of the most serious disease threatening mankind health in the world. Accumulating studies indicated that circRNAs played an important role in the occurrence and progression of breast cancer, however, the roles of circRNA_103809 in breast cancer progression remain unclear. Therefore, in this study, we aimed to clarify the potential role and regulatory mechanism of circRNA_103809 in the development of breast cancer. Firstly, the expression level of circRNA_103809 and microRNA-532-3p (miR-532-3p) in breast cancer tissues and normal tissues were detected with the quantitative real-time polymerase chain reaction (RT-qPCR). In addition, the cell proliferation ability, metastasis ability and related pathways were identified by Cell Counting Kit-8 (CCK-8), flow cytometry, and western blot, respectively. Furthermore, the connection between circRNA_103809 and miR-532-3p was detected by dual-luciferase reporter assay. Then, our data showed that circRNA_103809 was down-regulated in breast cancer tissues in contrast to adjacent non-tumor tissues, and the relative expression level of circRNA_103809 was closely associated with distant metastasis size, TNM stage, HER-2 status and overall survival time. In addition, our in vitro assays showed that the overexpression of circRNA_103809 could significantly inhibit epithelial-mesenchymal transition (EMT) pathway, then suppress breast cancer cell proliferation and metastasis ability. Moreover, we also found that the antitumor effect induced by circRNA_103809 could be reversed with the addition of miR-532-3p mimics. Taken together, this study showed that circRNA_103809 could inhibit cell proliferation and metastasis in breast cancer by sponging miR-532-3p, and circRNA_103809 might be a prospective target of breast cancer therapy.

Dysregulation of CircRNA_0001946 Contributes to the Proliferation and Metastasis of Colorectal Cancer Cells by Targeting MicroRNA-135a-5p

This study was aimed to evaluate the potential function of circ-0001946 in the progression of colorectal cancer (CRC) and the related regulatory mechanism. First, the expression levels of circRNA_0001946 and microRNA-135a-5p (miR-135a-5p) in normal and CRC tissues were measured by quantitative real-time polymerase chain reaction (RT-qPCR). In addition, cell proliferation was assessed by the Cell Counting Kit-8 (CCK-8) assay, cell migration and invasion were evaluated by Transwell assays, and the cell cycle patterns were determined by flow cytometry. The relationship between the expression levels of circ_0001946 and miR-135a-5p was determined by dual-luciferase reporter assays. Our data showed that the expression of circ_0001946 was upregulated in CRC tissues, which was negatively correlated with tumor size, histologic grade, lymphatic metastasis, and TMN stage, and patients with circ_0001946 overexpression were more likely to have a poor prognosis. In addition, in vitro experiments showed that silencing circ_0001946 inhibited the epithelial–mesenchymal transition (EMT) pathway and markedly suppressed CRC cell growth, migration, and invasion. Furthermore, we discovered that the transfection of miR-135a-5p mimics could reverse the antitumor effects of circRNA_0001946 downregulation. To summarize, this study revealed that circRNA_0001946 might act as a tumor promoter by activating the miR-135a-5p/EMT axis and may be a promising treatment target for CRC.

Genome-wide analysis of prognostic-related lncRNAs, miRNAs and mRNAs forming a competing endogenous RNA network in lung squamous cell carcinoma

PURPOSE

As a type of cancer with the highest morbidity and mortality, lung squamous cell carcinoma (LUSC) has a very poor prognosis. Long-non-coding RNA (lncRNA) has recently attracted attentions because it can play the role of competing endogenous RNA (ceRNA) to inhibit microRNA (miRNA) functions. In this study, we aimed to find prognosis-related lncRNAs, miRNAs and mRNAs and construct a prognosis-related ceRNA network.

METHODS

The original LUSC RNA-sequencing data and miRNA profiles data were downloaded from the cancer genome atlas (TCGA) database. Differentially expressed lncRNAs, miRNAs and mRNAs were then identified between patients with lymph node metastasis and no lymph node metastasis. Univariate Cox regression analysis was performed to find the survival-associated lncRNAs, miRNAs and mRNAs. Subsequently, prognostic-related ceRNA network was established. By multivariate Cox regression analysis, three lncRNA signatures and three mRNA signatures were developed and used for predicting LUSC patients' survival.

RESULTS

A total of 224 lncRNAs, 160 miRNAs, 913 mRNAs were identified between samples with lymph node metastasis and no lymph node metastasis. Univariate Cox regression analysis showed that, among them, 28 lncRNAs, 8 miRNAs, 105 mRNAs were significantly associated with patients' overall survival time. Further pathway and enrichment analysis suggested that these mRNAs were associated with the regulation of transmembrane transport, regulation of blood circulation, plasma lipoprotein particle organization. Then we constructed a survival-related ceRNA network including 9 lncRNAs, 8 miRNAs and 23 mRNAs. Additionally, a multivariate Cox regression analysis demonstrated that three lncRNAs (AL161431.1, LINC02389, APCDD1L.DT) and three mRNAs (KLK6, SLITRK5, CCDC177) had a significant prognostic value. Risk score indicated that lncRNA signature and mRNA signature could independently predict overall survival in LUSC patients.

CONCLUSION

The current study provided a better understanding of the ceRNA network in the progression of LUSC and laid a theoretical foundation for LUSC prognosis.

Long noncoding RNA MYLK-AS1 promotes growth and invasion of hepatocellular carcinoma through the EGFR/HER2-ERK1/2 signaling pathway

The epidermal growth factor receptor (EGFR) family members EGFR and HER2 play pivotal roles in oncogenesis and tumor progression. Anticancer drugs targeting EGFR and HER2 have been developed. Long noncoding RNAs (lncRNAs) have been reported to regulate cancer development and progression through signaling pathways. However, lncRNAs that regulate EGFR and HER2 expression remain unknown. Here, we show that lncRNA myosin light chain kinase-antisense RNA 1 (MYLK-AS1) promotes EGFR and HER2 expression and activates their downstream signaling pathway. MYLK-AS1 increases hepatocellular carcinoma (HCC) cell proliferation, migration, and invasion in vitro. Consistently, MYLK-AS1 knockdown hinders tumor growth in vivo. Mechanistically, MYLK-AS1 enhances HCC cell proliferation, migration, and invasion through stimulating the EGFR/HER2-extracellular signal-regulated kinase 1/2 (ERK1/2) signaling pathway. In addition, MYLK-AS1 is overexpressed in HCC patients and negatively correlated with HCC prognosis. Thus, MYLK-AS1 is an upstream regulator of EGFR/HER2, and acts as an oncogene, suggesting an additional target for cancer therapeutics.

Identification of a Novel Eight-lncRNA Prognostic Signature for HBV-HCC and Analysis of Their Functions Based on Coexpression and ceRNA Networks

Studies have demonstrated the prognosis potential of long noncoding RNAs (lncRNAs) for hepatocellular carcinoma (HCC), but specific lncRNAs for hepatitis B virus- (HBV-) related HCC have rarely been reported. This study was aimed at identifying a lncRNA prognostic signature for HBV-HCC and exploring their underlying functions. The sequencing dataset was collected from The Cancer Genome Atlas database as the training set, while the microarray dataset was obtained from the European Bioinformatics Institute database (E-TABM-36) as the validation set. Univariate and multivariate Cox regression analyses identified that eight lncRNAs (TSPEAR-AS1, LINC00511, LINC01136, MKLN1-AS, LINC00506, KRTAP5-AS1, ZNF252P-AS1, and THUMPD3-AS1) were significantly associated with overall survival (OS). These eight lncRNAs were used to construct a risk score model. The Kaplan-Meier survival curve results showed that this risk score can significantly differentiate the OS between the high-risk group and the low-risk group. Receiver operating characteristic curve analysis demonstrated that this risk score exhibited good prediction effectiveness (area under the curve (AUC) = 0.990 for the training set; AUC = 0.903 for the validation set). Furthermore, this lncRNA risk score was identified as an independent prognostic factor in the multivariate analysis after adjusting other clinical characteristics. The crucial coexpression (LINC00511-CABYR, THUMPD3-AS1-TRIP13, LINC01136-SFN, LINC00506-ANLN, and KRTAP5-AS1/TSPEAR-AS1/MKLN1-AS/ZNF252P-AS1-MC1R) or competing endogenous RNA (THUMPD3-AS1-hsa-miR-450a-TRIP13) interaction axes were identified to reveal the possible functions of lncRNAs. These genes were enriched into cell cycle-related biological processes or pathways. In conclusion, our study identified a novel eight-lncRNA prognosis signature for HBV-HCC patients and these lncRNAs may be potential therapeutic targets.

LncRNA FENDRR Upregulation Promotes Hepatic Carcinoma Cells Apoptosis by Targeting miR-362-5p Via NPR3 and p38-MAPK Pathway

Background: Abnormal long noncoding RNA FOXF1 adjacent noncoding developmental regulatory RNA (FENDRR) expression has been discovered in multiple human cancers pathogenesis, but its role in hepatocellular carcinoma (HCC) cells is rarely reported. Its effects on HCC cells are covered in this study. Materials and Methods: MiR-362-5p and NPR3 expressions in HCC tissues and cell were detected by quantitative real-time polymerase chain reaction and Western blot as needed. Cell viability and apoptosis were detected by MTT assay and flow cytometry, respectively. Target gene and potential binding sites of FENDRR, miR-362-5p, and NPR3 were predicted and confirmed by TargetScan and Starbase, and dual-luciferase reporter assay. Results: FENDRR expression was downregulated while miR-362-5p expression was upregulated in HCC tissues and cells. FENDRR upregulation inhibited HCC cells viability yet induced apoptosis, which was reversed by miR-362-5p. In addition, miR-362-5p resulted in p38-mitogen-activated protein kinase (MAPK) pathway activation and NPR3 expression decrease in HCC cells, which was reversed by FENDRR. Conclusion: FENDRR inhibited HCC cells viability yet promoted apoptosis by targeting miR-362-5p by promoting NPR3 and deactivating p38-MAPK pathway, thus exerting its anticarcinogenic effects in HCC cells.

Exploring prognostic potential of long noncoding RNAs in colorectal cancer based on a competing endogenous RNA network

BACKGROUND

Colorectal cancer (CRC) is one of the most prevalent tumors worldwide. Recently, long noncoding RNAs (lncRNAs) have been shown to influence tumorigenesis and tumor progression by acting as competing endogenous RNAs (ceRNAs). It is difficult to extract prognostic lncRNAs and useful bioinformation from most ceRNA networks constructed previously.

AIM

To construct a prognostic related ceRNA regulatory network and lncRNA related signature based on risk score in CRC.

METHODS

RNA transcriptome profile and clinical information of 506 CRC patients were downloaded from the Cancer Genome Atlas database. R packages and Perl program were used for data processing. Cox regression analysis was used for prognostic model construction. Quantitative real-time polymerase chain reaction was used to detect the expression of lncRNAs.

RESULTS

A prognostic-related ceRNA network was constructed, including 9 lncRNAs, 44 mRNAs, and 30 miRNAs. In addition, a four-lncRNA model was constructed using multivariate Cox regression analysis, which could be an independent prognostic model in CRC. The risk score for each patient was calculated, and the 506 patients were divided into high and low-risk groups (253 for each group) based on the median risk score. The results of the survival analysis showed that patients with a high-risk score had a poor survival rate. Furthermore, the predictive value of the four-lncRNA model was evaluated in GSE38832. Patient survival probabilities could be better predicted when combing the risk score and clinical features. Gene Set Enrichment Analysis results verified that a number of cancer-related signaling pathways were enriched with a high-risk score in CRC. Finally, we validated a novel lncRNA (LINC00488) using quantitative real-time polymerase chain reaction in 22 paired CRC patient tumor tissues compared to adjacent non-tumor tissues.

CONCLUSION

The four-lncRNA model could give better predictive value for CRC patients. Our understanding of the lncRNA-related ceRNA regulatory mechanism could provide a potential diagnostic indicator for CRC patients.

Long Non-Coding RNA PART1 Exerts Tumor Suppressive Functions in Glioma via Sponging miR-190a-3p and Inactivation of PTEN/AKT Pathway

Background

Glioma is the most commonly diagnosed primary brain tumor. Dysregulation of long non-coding RNA (lncRNA) is associated with initiation and development of various cancer types including glioma.

Methods

The relative expression of lncRNA was analyzed by real time-quantitative polymerase chain reaction (RT-qPCR). Cell counting kit (CCK-8) and flow cytometry analysis were applied to explore the role of prostate androgen-regulated transcript 1 (PART1) in glioma cell lines. Luciferase reporter assay, Western blotting and RT-qPCR were used to investigate the association between PART1, miR-190a-3p and phosphatase and tensin homolog deleted on chromosome ten (PTEN) in glioma cell lines.

Results

In the present study, we elucidated a pivotal role and molecular mechanism of lncRNA PART1 in glioma cell lines. It was found that PART1 was significantly downregulated in glioma tissues compared to normal tissues according to TCGA data and our RT-qPCR results. The cell-based assays showed that PART1 suppressed cell proliferation and triggered cell apoptosis in glioma cell lines. PART1 inactivated PI3K/AKT cascade in glioma cell lines. Transfection of constitutively activated AKT (Myr-AKT) reversed PART1 induced cell apoptosis and cell growth arrest. The bioinformatic analysis suggested that miR-190a-3p might bind to PART1. In the dual luciferase reporter assay, we validated that PART1 directly bound to miR-190a-3p in glioma cell lines. Furthermore, there was a reciprocal repression between PART1 and miR-190-3p. In addition, PART1 upregulated PTEN and inactivated PI3K/AKT pathway in glioma cell lines. Moreover, silencing of PTEN reversed PART1 overexpression induced cell growth arrest and apoptosis. In glioma tissues, the Pearson Correlation analysis showed that there was a strong-positive correlation between PART1 level and PTEN mRNA level.

Conclusion

Taken together, the current study revealed a PART1/miR-190a-3p/PTEN/PI3K/AKT axis in glioma and provided novel insights for understanding the complex lncRNA-miRNA network in glioma.

Comprehensive RNA Sequencing in Adenoma-Cancer Transition Identified Predictive Biomarkers and Therapeutic Targets of Human CRC

Specific molecular biomarkers for predicting the transition from colorectal adenoma to cancer have been identified, however, circular RNA (circRNA)-related signatures remain to be clarified. We carried out high-throughput RNA sequencing to determine the expression profiles of circRNAs, microRNAs (miRNAs), and mRNAs in human colorectal cancer (CRC), adenoma, and adjacent normal tissues. We identified 84 circRNAs, 41 miRNAs, and 398 mRNAs that were commonly differentially expressed in CRC and adenoma tissues compared with normal tissues. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) analyses identified numerous cancer-related hub genes that might serve as potential therapeutic targets in CRC. Competing endogenous RNA (ceRNA) networks, including three circRNAs, three miRNAs, and 28 mRNAs were constructed, suggesting their potential role in cancer progression. Representative differentially expressed RNAs were validated by the Cancer Genome Atlas (TCGA) database and real-time PCR experiments. Receiver operating characteristic (ROC) curve analysis identified three circRNAs (hsa_circ_0049487, hsa_circ_0066875, and hsa_circ_0007444) as possible novel biomarkers predicting the transition from colonic adenoma to cancer. Overall, our findings may provide novel perspectives to clarify the mechanisms of the transition from premalignant adenoma to cancer and identify specific circRNA-related signatures with possible applications for the early diagnosis of and as potential therapeutic targets in CRC.