Identification of a six lncRNAs signature as novel diagnostic biomarkers for cervical cancer

A new marker constructed from immune-related lncRNA pairs can be used to predict clinical treatment effects and prognosis: in-depth exploration of underlying mechanisms in HNSCC

BACKGROUND

Long non-coding RNA (lncRNA) plays a vital role in tumor proliferation, migration, and treatment. Since it is challenging to standardize the gene expression levels detected by different platforms, the signatures composed of many immune-related single lncRNAs are still inaccurate. Utilizing a gene pair formed of two immune-related lncRNAs and strategically assigning values can effectively meet the demand for a higher-accuracy dual biomarker combination.

METHODS

Co-expression and differential expression analyses were performed on immune genes and lncRNAs data from The Cancer Genome Atlas and the ImmPort database to obtain differentially expressed immune-related lncRNAs for pairwise pairing. The prognostic-related differentially expressed immune-related lncRNAs (PR-DE-irlncRNAs) pairs were then identified by univariate Cox regression and used for lasso regression to construct a prognostic model. Various methods were used to validate the predictive prognostic performance of the model. Additionally, we explored the potential guiding value of the model in immunotherapy and chemotherapy and constructed a nomogram suitable for efficient prognosis prediction. Mechanistic exploration of anti-tumor immunity and mutational perspectives are also included. We also analyzed the correlation between the model and immune checkpoint inhibitors (ICIs)-related, N6-methyadenosine (m6A)-related, and multidrug resistance genes.

RESULTS

We used a total of 20 pairs of PR-DE-irlncRNAs to create a prognosis model. Quantitative real-time polymerase chain reaction experiments further verified the abnormal expression of 11 lncRNAs in HNSCC cells. Various methods have confirmed the excellent performance of the model in predicting patient prognosis. We reasoned that lncRNAs/TP53 mutation might play a positive/negative anti-tumor role through the immune system by multi-perspective analyses. Finally, it was found that the prognostic model was closely related to immunotherapy and chemotherapy as well as the expression of ICIs/m6A/multidrug resistance-related genes.

CONCLUSION

The prognostic model performs excellently in predicting the prognosis of patients and provides the potential value of practical guidance for treatment.

Long non-coding RNAs as promising biomarkers and therapeutic targets in cervical cancer

Cervical cancer is the second most common cancer in women. The detection of oncopathologies in the early stages of development is a paramount task of modern medicine, which can be solved only by improving modern diagnostic methods. The use of screening for certain tumor markers could complement modern tests such as testing for oncogenic types of human papillomavirus (HPV), cytology, colposcopy with acetic acid and iodine solutions. Such highly informative biomarkers can be long noncoding RNAs (lncRNAs) that are highly specific compared to the mRNA profile and are involved in the regulation of gene expression. LncRNAs are a class of non-coding RNAs molecules that are typically over 200 nucleotides in length. LncRNAs may be involved in the regulation of all major cellular processes, including proliferation and differentiation, metabolism, signaling pathways, and apoptosis. LncRNAs molecules are highly stable due to their small size, which is also their undoubted advantage. The study of individual lncRNAs as regulators of the expression of genes involved in the mechanisms of oncogenesis cervical cancer can be not only of great diagnostic value, but, as a result, of therapeutic significance in cervical cancer patients. This review article will present the characteristics of lncRNAs that allow them to be used as accurate diagnostic and prognostic tools, as well as to consider them as effective therapeutic targets in cervical cancer.

Role of noncoding RNAs with emphasis on long noncoding RNAs as cervical cancer biomarkers

Cervical cancer is a significant public health problem in developing countries, as most cases present at an advanced stage. This review aimed to analyze the role of noncoding RNAs as diagnostic and prognostic biomarkers in cervical cancers. Published studies on specific microRNA signatures in body fluids and cervical cancer tissues are highly heterogeneous, and there are no validated assays. The precision of the various immune-associated long noncoding (lncRNA) signatures should be assessed in clinical samples. Even though lncRNAs are tissue and cancer-specific, safe and appropriate methods for delivery to tumor tissues, toxicities and side effects are to be explored. Few studies have evaluated deregulated lncRNA expression levels with clinicopathological factors in a limited number of clinical samples. Prospective studies assessing the diagnostic and prognostic roles of circulating lncRNAs and P-Element-induced wimpy testis interacting PIWI RNAs (Piwil RNAs) in cervical cancer cases are essential. For the clinical application of lnc-RNA-based biomarkers, comprehensive research is needed as the impact of noncoding transcripts on molecular pathways is complex. The standardization and validation of deregulated ncRNAs in noninvasive samples of cervical cancer cases are needed.

Abnormally Expressed lncRNAs as Potential Biomarkers for Gastric Cancer Risk: A Diagnostic Meta-Bioinformatics Analysis

Background and Aims

Abnormal expression of lncRNAs is relevant to the occurrence and development of gastric cancer (GC), but the significance remains inconclusive. We performed a diagnostic meta-bioinformatics analysis to elucidate the association between lncRNA expression and GC risk.

Methods

Published datasets were selected from PubMed, Embase, CNKI, and Web of Science, up to 1st December 2021. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated to evaluate the diagnostic value. RNA sequencing data were downloaded for validation.

Results

54 studies with 4671 patients and 4652 matched controls were included in the meta-analysis. The pooled SEN, SPE, PLR, NLR, DOR, and AUC were 0.71, 0.76, 2.9, 0.39, 8, and 0.79, respectively. Subgroup analyses showed that the DOR and AUC of intergenic lncRNAs, circulating lncRNAs, larger sample size (>200), and high-quality (NOS score ≥ 7) groups were superior to antisense lncRNAs, tissue lncRNAs, smaller sample size (≤200), and low-quality (NOS score < 7) groups, respectively. However, only circulating lncRNAs had significantly higher diagnostic utility than that tissue lncRNAs. Nine differentially expressed lncRNAs in the meta-analysis were verified in TCGA-STAD. PVT1 was the most effective single lncRNA, with AUC of 0.949, SEN of 0.808, and SPE of 0.969, while PVT1 and C5orf66-AS1 were the most effective combination, with AUC of 0.972, SEN of 0.941, and SPE of 0.937.

Conclusion

Abnormally expressed lncRNAs, especially circulating lncRNAs, might be potential diagnostic biomarkers for GC risk. A novel combined model of lncRNAs might achieve better GC diagnosis performance.

Testing lncRNAs signature as clinical stage–related prognostic markers in gastric cancer progression using TCGA database

LncRNA expression can be conducive to gastric cancer (GC) prognosis. The objective of this study is to ascertain five specific lncRNAs involved in tumor progression of GC and their role as prognostic markers to diagnose clinical stage-wise GC. High-throughput RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) database and performed genome-wide lncRNA expression analysis using edgeR package, Bioconductor.org , and R-statistical computing to analyze differentially expressed lncRNA analysis. Cutoff parameters were FDR < 0.05 and |Log2FC| > 2. Total 351 tumor samples with differentially expressed lncRNAs were divided into group-1 lncRNAs such as AC019117.2 and LINC00941, and group-2 lncRNAs such as LINC02410, AC012317.2, and AC141273.1 by 2:1. The Spearman correlation coefficients ( p < 0.05) and correlation test function (cor.test ()) were performed for lncRNAs as per clinical stage. Cytoscape software was used to construct lncRNA–mRNA interaction networks. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway ( p < 0.05) analysis were conducted using the clusterProfiler package. Kaplan–Meier survival analysis was performed to determine the overall survival of patients based on the expression of five lncRNAs in different clinical stages of GC. AC019117.2 and LINC00941 of group 1 inferred a positive correlation with clinical stages of stage I to stage IV, and their expressions were higher in tumor tissues than normal tissues. On the contrary, LINC02410, AC012317.2, and AC141273.1 of group 2 exhibited a negative correlation with clinical stage, and they exhibited more expression in normal tissues compared to tumor tissues. GO and KEGG pathway analysis reported that AC019117.2 may interact with LINC00941 via ITGA3 and trophoblast glycoprotein (TPBG) to foster tumor progression. Tumor-specific group-1 lncRNAs were conducive to the poor overall survival and exhibited a positive correlation with the clinical stages of stage I to stage IV in GC as per the lncRNA–mRNA networking analysis. These five lncRNAs could be considered as clinically useful lncRNA-based prognostic markers to predict clinical stage-wise GC progression.

Analysis of differentially expressed long non‑coding RNAs revealed a pro‑tumor role of MIR205HG in cervical cancer

Cervical cancer is the fourth most common female malignancy for both incidence and mortality worldwide and is one of the major threats to women's health. The role of long non‑coding RNAs (lncRNAs) in cervical cancer remains largely unknown. In the present study, the differentially expressed lncRNAs in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tissues were retrieved form The Cancer Genome Atlas (TCGA) and were analyzed. The expression analysis of related genes was performed with GEPIA. The proliferation and migratory and invasive abilities of MIR205HG knockdown CESC cells were analyzed using Cell Counting Kit‑8 and transwell assays. The expression of Ki‑67 and p16 was detected by immunofluorescence. A total of 203 differentially expressed lncRNAs were identified. The results demonstrated that MIR205HG was overexpressed in CESC tissues. Furthermore, the genes related to MIR205HG were enriched in cancer‑related pathways. MIR205HG knockdown significantly decreased the proliferation and migratory and invasive abilities of CESC cells. In addition, silencing of MIR205HG significantly decreased the expression of p16 in C‑33 A cells. The expression of fibroblast growth factor receptor 3, thymidine phosphorylase and GTPase HRas was downregulated in MIR205HG knockdown CESC cells. These findings revealed some potential lncRNA candidates for cervical cancer research and suggested that MIR205HG may have a pro‑tumor role in CESC.

Long noncoding RNA HOXA-AS2 accelerates cervical cancer by the miR-509-3p/BTN3A1 axis

OBJECTIVES

Cervical cancer is an aggressive malignant tumour and causes high mortality in women. LncRNA HOXA-AS2 is a tumour promoter in many cancers. The current work was designed to elucidate the functions of HOXA-AS2 in cervical cancer and the underlying regulatory mechanism.

METHODS

qRT-PCR was conducted to reveal RNA levels. A FISH assay was conducted for the identification of the subcellular location of HOXA-AS2. MTT, EdU, Transwell and tube formation were used for detection of cell growth, migration and angiogenesis, respectively. In-vivo studies were conducted to reveal the role of HOXA-AS2 on transplanted tumour growth in mice.

KEY FINDINGS

The HOXA-AS2 level was found high in tissues and cells of cervical cancer. Silencing of HOXA-AS2 restrained cell proliferation, migration and invasion. Angiogenesis of HUVECs was restrained after silencing HOXA-AS2. Additionally, HOXA-AS2 upregulated the BTN3A1 by interaction with miR-509-3p. BTN3A1 overexpression rescues the inhibitory effect of silenced HOXA-AS2 on cell phenotypes in cervical cancer. Moreover, xenograft tumour growth in mice was suppressed by HOXA-AS2 depletion and was facilitated by BTN3A1 overexpression.

CONCLUSIONS

HOXA-AS2 accelerates cellular progression in cervical cancer by the miR-509-3p/BTN3A1 axis.

Using lncRNA Sequencing to Reveal a Putative lncRNA-mRNA Correlation Network and the Potential Role of PCBP1-AS1 in the Pathogenesis of Cervical Cancer

Background/Aims

Long non-coding RNAs (lncRNAs) play important roles in many diseases and participate in posttranscriptional regulatory networks in tumors. However, the functions of major lncRNAs in cervical cancer are unclear. Therefore, the aim of this study was to construct a lncRNA-mRNA coexpression functional network and analyze lncRNAs that might contribute to the pathogenesis of cervical cancer.

Methods

Differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between three pairs of cervical cancer tissues and adjacent mucosa were identified by lncRNA microarray analysis. LncRNA-mRNA correlation analysis and functional enrichment were performed on the DEGs. From the correlation network, PCBP1-AS1 was selected as a candidate for further analysis. PCBP1-AS1 expression was examined by qPCR, and Kaplan-Meier survival, clinicopathology, GSEA, and immune infiltration analysis of PCBP1-AS1 were performed. The immune responses of PCBP1-AS1 expression in cervical cancer were analyzed using TIMER and western blot. PCBP1-AS1 was knocked down and overexpressed to evaluate its role in cell proliferation, migration, and invasion.

Results

A total of 130 lncRNAs were significantly differentially expressed in cervical cancer patient samples compared with control samples. Differentially expressed mRNAs in the lncRNA-mRNA interaction network were involved in the EMT process. Combined with the Kaplan-Meier survival analyses, the coexpression network revealed that PCBP1-AS1 was significantly associated with OS and clinicopathological parameters in cervical cancer patients. Moreover, PCBP1-AS1 expression was not only significantly increased in cervical cancer specimens but also associated with tumor stage, TNM, and invasion. GSEA revealed that PCBP1-AS1 is closely correlated with cell biological function via the p53 and notch signaling pathways. TIMER analysis revealed that the numbers of NK cells and M2 macrophages decreased when PCBP1-AS1 expression was high, which was consistent with the western blot results in clinical samples. Furthermore, in vitro experiments showed that high expression of PCBP1-AS1 promoted cell proliferation, migration, and invasion.

Conclusions

Transcriptomic and lncRNA-mRNA correlation analyses revealed that PCBP1-AS1 plays a key role as an independent prognostic factor in patients with cervical cancer. The identification of PCBP1-AS1 as a new biomarker for cervical cancer could help explain how changes in the immune environment promote cervical cancer development.

Identification of an immune-based mRNA-lncRNA signature for overall survival in cervical squamous cell carcinoma

Aim: To better predict the survival of cervical squamous cell carcinoma (CESC) patients, we aimed to construct a signature according to different immune infiltration. Methods: We downloaded the RNA sequences of CESC patients from the Cancer Genome Atlas database. By using single-sample gene set enrichment analysis, we separated the samples into high- and low-immunity groups. Then we separated the samples into training and testing datasets and performed the following analyses: univariate, least absolute shrinkage and selection operator analysis, multivariate Cox regression analyses and weighted gene coexpression network analysis using R software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes studies were performed using the Database for Annotation, Visualization and Integrated Discovery website. Results & conclusion: We finally identified a signature with three mRNAs and two lncRNAs: ADGRG5, HSH2D, ZMAT4, RBAKDN and LINC00200. In short, our study constructed an mRNA-lncRNA signature related to immune infiltration to better predict the survival of CESC patients.

Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients

Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.

LncRNA LINC01305 promotes cervical cancer progression through KHSRP and exosome-mediated transfer

Cervical cancer (CC) is one of the deadliest female malignancies worldwide. Long non-coding RNAs (lncRNAs) are essential regulators for cancer progression. This study aimed to elucidate the role of lncRNA LINC01305 in the progression of CC. We found where LINC01305 was expressed in CC tissues and its correlation with the survival rate of CC patients. Functional experiments were performed to elucidate the effect of LINC01305 on CC. The results showed that LINC01305 was increased in CC tumor tissues and was correlated with a lower survival rate. The overexpression and knockdown of LINC01305 enhanced and inhibited the progression of CC, respectively. Additionally, the upregulation of LINC01305 promoted tumor growth in xenograft mice. Moreover, the effect of LINC01305 on CC was mediated through interacting with the RNA-binding protein, KHSRP. Furthermore, LINC01305 was mainly distributed in exosomes and was transferred to recipient cells to enhance CC progression. Lastly, LINC01305 may participate in the regulation of the stemness of CC. Taken together, the results suggest that LINC01305 promotes the progression of CC through KHSRP and that LINC01305 is released through exosomes and is involved in the stemness of CC. This study sheds light on the molecular mechanism underlying the progression of CC.

Eight-lncRNA signature of cervical cancer were identified by integrating DNA methylation, copy number variation and transcriptome data

BACKGROUND

Copy number variation (CNV) suggests genetic changes in malignant tumors. Abnormal expressions of long non-coding RNAs (lncRNAs) resulted from genomic and epigenetic abnormalities play a driving role in tumorigenesis of cervical cancer. However, the role of lncRNAs-related CNV in cervical cancer remained largely unclear.

METHODS

The data of messenger RNAs (mRNAs), DNA methylation, and DNA copy number were collected from 292 cervical cancer specimens. The prognosis-related subtypes of cervical cancer were determined by multi-omics integration analysis, and protein-coding genes (PCGs) and lncRNAs with subtype-specific expressions were identified. The CNV pattern of the subtype-specific lncRNAs was analyzed to identify the subtype-specific lncRNAs. A prognostic risk model based on lncRNAs was established by least absolute shrinkage and selection operator (LASSO).

RESULTS

Multi-omics integration analysis identified three molecular subtypes incorporating 617 differentially expressed lncRNAs and 1395 differentially expressed PCGs. The 617 lncRNAs were found to intersect with disease-related lncRNAs. Functional enrichment showed that 617 lncRNAs were mainly involved in tumor metabolism, immunity and other pathways, such as p53 and cAMP signaling pathways, which are closely related to the development of cervical cancer. Finally, according to CNV pattern consistent with differential expression analysis, we established a lncRNAs-based signature consisted of 8 lncRNAs, namely, RUSC1-AS1, LINC01990, LINC01411, LINC02099, H19, LINC00452, ADPGK-AS1, C1QTNF1-AS1. The interaction of the 8 lncRNAs showed a significantly poor prognosis of cervical cancer patients, which has also been verified in an independent dataset.

CONCLUSION

Our study expanded the network of CNVs and improved the understanding on the regulatory network of lncRNAs in cervical cancer, providing novel biomarkers for the prognosis management of cervical cancer patients.

Roles and Mechanisms of the Long Noncoding RNAs in Cervical Cancer

Cervical cancer (CC) continues to be one of the leading causes of death for women across the world. Although it has been determined that papillomavirus infection is one of the main causes of the etiology of the disease, genetic and epigenetic factors are also required for its progression. Among the epigenetic factors are included the long noncoding RNAs (lncRNAs), transcripts of more than 200 nucleotides (nt) that generally do not code for proteins and have been associated with diverse functions such as the regulation of transcription, translation, RNA metabolism, as well as stem cell maintenance and differentiation, cell autophagy and apoptosis. Recently, studies have begun to characterize the aberrant regulation of lncRNAs in CC cells and tissues, including Homeobox transcript antisense RNA (HOTAIR), H19, Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), Cervical Carcinoma High-Expressed 1 (CCHE1), Antisense noncoding RNA in the inhibitors of cyclin-dependent kinase 4 (ANRIL), Growth arrest special 5 (GAS5) and Plasmacytoma variant translocation 1 (PVT1). They have been associated with several disease-related processes such as cell growth, cell proliferation, cell survival, metastasis and invasion as well as therapeutic resistance, and are novel potential biomarkers for diagnosis and prognosis in CC. In this review, we summarize the current literature regarding the knowledge we have about the roles and mechanisms of the lncRNAs in cervical neoplasia.

Long Non-Coding RNA LINC00511 Accelerates Proliferation and Invasion in Cervical Cancer Through Targeting miR-324-5p/DRAM1 Axis

Purpose

Cervical cancer is the second most prevalent female malignance, and human papillomavirus (HPV) infection is the main pathogenic factor of cervical cancer. Emerging evidence has revealed that a number of long non-coding RNAs (lncRNAs) play critical roles in the tumorigenesis and progression of cervical cancer. The aim of this study was to further investigate the precise role of lncRNA LINC00511 in HPV-negative and HPV-positive cervical cancer cells and explore the potential regulatory mechanism.

Methods

The expression of LINC00511 in cervical cancer and cell lines was examined by RT-PCR. Fluorescence in situ hybridization analysis (FISH) assay was performed to detect the localization of LINC00511 in cervical cancer cells. Loss-of-function experiments of LINC00511 by siRNA interference were performed to assess its effects on HPV-negative and HPV-positive cervical cancer cells. Dual-luciferase reporter and RNA immunoprecipitation (RIP) assays were used to identify the target of LINC00511. Relative expression of related proteins was detected using Western blot.

Results

Herein, the results showed that LINC00511 was significantly up-regulated in cervical cancer and cell lines and mainly distributed in the cytoplasm of cervical cancer cells. Loss-of-function experiments indicated that silencing of LINC00511 inhibited the proliferation and invasion of both HPV-negative and HPV-positive cervical cancer cells, as well as promoted apoptosis by regulating the Bcl-2/Bax axis and Caspase 3 activation. Bioinformatic analysis, dual-luciferase reporter, and RIP assays showed that LINC00511 was a target of miR-324-5p, while DRAM1 was a direct target of miR-324-5p. The expression of miR-324-5p was down-regulated in cervical cancer, while the expression of DRAM1 was up-regulated. Moreover, the expression of LINC00511 was negatively correlated with miR-324-5p expression in cervical cancer tissues and positively correlated with DRAM1. Further, DRAM1 overexpression promoted both HPV-negative and HPV-positive cervical cancer cell proliferation and invasion, which could be reversed by miR-324-5p mimics or si-LINC00511.

Conclusion

Collectively, these results suggest that LINC00511 functions as a competing endogenous RNA (ceRNA) to regulate the miR-324-5p/DRAM1 axis, leading to HPV-negative and HPV-positive cervical cancer aggravation.

A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer

Cervical cancer is the fourth most common cancer in women worldwide. The current approaches still have limitations in predicting the therapy outcome of each individual because of cancer heterogeneity. The goal of this study was to establish a gene expression signature that could help when choosing the right therapeutic method for the treatment of advanced-stage cervical cancer. The 666 patients were collected from four independent datasets. The 70-gene expression signature was established using univariate Cox proportional hazard regression analysis. The 70-gene signature was significantly different between low- and high-risk groups in the training dataset (p = 4.24e-6) and in the combined three validation datasets (p = 4.37e-3). Treatment of advanced-stage cancer patients in the high-risk group with molecular-targeted therapy combined with chemoradiotherapy yielded a better survival rate than with only chemoradiotherapy (p = 0.0746). However, treatment of the patients in the low-risk group with the combined therapy resulted in significantly lower survival (p = 0.00283). Functional classification of 70 genes revealed involvement of the angiogenesis pathway, specifically phosphatidylinositol 3-kinase signaling (p = 0.040), extracellular matrix organization (p = 0.0452), and cell adhesion (p = 0.011). The 70-gene signature could predict the prognosis and indicate an optimal therapeutic modality in molecular-targeted therapy or chemotherapy for advanced-stage cervical cancer.

OIP5-AS1/miR-137/ZNF217 Axis Promotes Malignant Behaviors in Epithelial Ovarian Cancer

Background

Long non-coding RNAs (lncRNAs) have been reported to play crucial regulatory roles in cellular activities and are associated with the carcinogenesis of various diseases. OIP5-AS1, as a novel lncRNA, function in epithelial ovarian cancer (EOC) still remains unclear.

Material and Methods

qRT-PCR and Western blot analyses were performed to measure relevant expression, as needed. A series of functional experiments were performed to determine the role of OIP5-AS1 in EOC cells. Luciferase report, RNA pull down and RIP assays were performed to testify the interaction between relevant RNAs.

Results

We found that OIP5-AS1 was significantly overexpressed in EOC. Knockdown of OIP5-AS1 inhibited cell proliferation, migration, invasion and epithelial–mesenchymal transition (EMT) process, yet facilitated apoptosis in vitro. OIP5-AS1 functioned as a competing endogenous RNA (ceRNA) to elevate ZNF217 expression through sponging miR-137. Furthermore, miR-137 inhibition and ZNF217 upregulation can reverse the effects of silencing OIP5-AS1 on the cellular activities of ovarian cancer cells. Also, depleted OIP5-AS1 hindered tumor growth and metastasis in vivo.

Conclusion

OIP5-AS1 regulated ovarian cancer progression via modulating miR-137/ZNF217 signaling, suggesting that targeting OIP5-AS1 could be conducive to EOC clinical treatment.

Long noncoding RNA PVT1 promotes tumor cell proliferation, invasion, migration and inhibits apoptosis in oral squamous cell carcinoma by regulating miR‑150‑5p/GLUT‑1

Oral squamous cell carcinoma (OSCC) is a cancer with high morbidity and mortality. Research has demonstrated that long non-coding RNAs (lncRNAs) are critical for tumor initiation and development. In the present study, we aimed to ascertain the functions and potential mechanisms of lncRNA plasmacytoma variant translocation 1 (PVT1) in OSCC. Firstly, we found that the expression of PVT1 was increased in human OSCC tumor tissues and it was related to reduced survival of the patients. Furthermore, miR-150-5p expression was downregulated in OSCC tumor tissues and it was negatively related with PVT1. Moreover, GLUT-1 protein expression was upregulated in human OSCC tumor tissues. In addition, cell proliferation capacity was measured by CCK-8 assay and cell invasion and migration were measured by Transwell assay. PVT1 overexpression promoted cell proliferation, invasion and migration, while these effects were abrogated by PVT1 downregulation. In addition, luciferase gene reporter assay verified the miR-150-5p directly binds with PVT1, which regulates the biological functions of OSCC. Additionally, luciferase gene reporter assay confirmed that GLUT-1 was a target for miR-150-5p. The promotion of cell proliferation, invasion and migration in LV-PVT1-transfected cells was eliminated following miR-150-5p overexpression. Finally, in vivo nude mouse xenograft model further verified that PVT1 knockdown inhibited tumor growth, formation, invasion and migration. According to the results, PVT1 is increased in human OSCC tumor tissues, and is related to the poor prognosis of human OSCC patients. We uncovered a previously unappreciated PVT1/miR-150-5p/GLUT-1 signaling axis that promotes cell proliferation, invasion, migration and inhibits apoptosis in OSCC cell lines and in vivo, which suggests that this axis could be a target for the treatment of OSCC.

Analysis of exosomal lncRNA, miRNA and mRNA expression profiles and ceRNA network construction in endometriosis

Aim: To investigate exosomal RNAs (long noncoding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs)) profiling and their related networks in endometriosis (EMs). Materials & methods: RNA sequence was performed in exosomes from ovarian endometriomas (EC), eutopic endometria (EU) and normal endometria (Control) stromal cells. The bioinformatics algorithms evaluated competing endogenous RNA (ceRNA) networks. The top-ranked ceRNA networks were confirmed by RT-PCR. Results: Overlapped differentially expressed 938 lncRNAs, 39 miRNAs and 1449 mRNAs were identified. 13 co-expression modules and 61 ceRNA networks were constructed. Conclusion: This study for the first time shows exosomal RNA biomarkers and lncRNA-related networks in EMs, which reveals a novel molecular mechanism of EMs and provides new resources for EM diagnosis and treatment.

Identification Hub Genes in Colorectal Cancer by Integrating Weighted Gene Co-Expression Network Analysis and Clinical Validation in vivo and vitro

Colorectal cancer (CRC) is the third leading cause of death in the world. However, the key roles of most molecules in CRC remain unclear. This study aimed to identify key modules and hub genes associated with the progression of CRC. The data of the patients with CRC were obtained from the Gene Expression Omnibus (GEO) database and assessed by weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses performed in R. by WGCNA, several hub genes that regulate the mechanism of tumorigenesis in CRC were identified, which were associated with clinical traits. Next, we screened hub genes related to the progression of CRC authenticated by The Cancer Genome Atlas (TCGA) and Oncomine databases. Three hub genes (HCLS1, EVI2B, and CD48) were identified, and survival analysis was further performed. Moreover, the results of qPCR and immunohistochemistry staining revealed that HCLS1, EVI2B, and CD48 are tumor suppressor genes. Further, the functional study verified that over-expression of HCLS1, EVI2B, and CD48 can reduce the proliferation, migration, and invasion ability of CRC cells and significantly suppress CRC tumor growth in vivo. In summary, we identified three hub genes that were associated with the progression of CRC that can be applied in treatment.