Comprehensive analysis of five long noncoding RNAs expression as competing endogenous RNAs in regulating hepatoma carcinoma

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 RNAs as Novel Biomarkers in the Clinical Management of Papillary Renal Cell Carcinoma Patients: A Promise or a Pledge?

Papillary renal cell carcinoma (pRCC) represents the second most common subtype of renal cell carcinoma, following clear cell carcinoma and accounting for 10–15% of cases. For around 20 years, pRCCs have been classified according to their mere histopathologic appearance, unsupported by genetic and molecular evidence, with an unmet need for clinically relevant classification. Moreover, patients with non-clear cell renal cell carcinomas have been seldom included in large clinical trials; therefore, the therapeutic landscape is less defined than in the clear cell subtype. However, in the last decades, the evolving comprehension of pRCC molecular features has led to a growing use of target therapy and to better oncological outcomes. Nonetheless, a reliable molecular biomarker able to detect the aggressiveness of pRCC is not yet available in clinical practice. As a result, the pRCC correct prognosis remains cumbersome, and new biomarkers able to stratify patients upon risk of recurrence are strongly needed. Non-coding RNAs (ncRNAs) are functional elements which play critical roles in gene expression, at the epigenetic, transcriptional, and post-transcriptional levels. In the last decade, ncRNAs have gained importance as possible biomarkers for several types of diseases, especially in the cancer universe. In this review, we analyzed the role of long non-coding RNAs (lncRNAs) in the prognosis of pRCC, with a particular focus on their networking. In fact, in the competing endogenous RNA hypothesis, lncRNAs can bind miRNAs, resulting in the modulation of the mRNA levels targeted by the sponged miRNA, leading to additional regulation of the target gene expression and increasing complexity in the biological processes.

Long Non-Coding RNAs (lncRNAs) in Response and Resistance to Cancer Immunosurveillance and Immunotherapy

Long non-coding RNAs (lncRNAs) are critical regulatory elements in cellular functions in states of both normalcy and disease, including cancer. LncRNAs can influence not only tumorigenesis but also cancer features such as metastasis, angiogenesis and resistance to chemo-and immune-mediated apoptotic signals. Several lncRNAs have been demonstrated to control directly or indirectly the number, type and activities of distinct immune cell populations of adaptive and innate immunities within and without the tumor microenvironment. The disruption of lncRNA expression in both cancer and immune cells may reflect alterations in tumor responses to cancer immunosurveillance and immunotherapy, thus providing new insights into lncRNA biomarker-based prognostic and therapeutic cancer assessment. Here we present an overview on lncRNAs’ functions and underlying molecular mechanisms related to cancer immunity and conventional immunotherapy, with the expectation that any elucidations may lead to a better understanding and management of cancer immune escape and response to current and future immunotherapeutics.

lnc-NLC1-C inhibits migration, invasion and autophagy of glioma cells by targeting miR-383 and regulating PRDX-3 expression

Long non-coding RNAs (lncRNAs) serve an important role in tumor progression, and their abnormal expression is associated with tumor development. The lncRNA narcolepsy candidate region 1 gene C (lnc-NLC1-C) is involved in numerous types of cancer, but its biological function in glioma remains unknown. In the present study, lnc-NLC1-C expression was detected using reverse transcription-quantitative (RT-q)PCR in U251, SHG44, U87MG and U118MG glioma cells. U87MG cells were transfected with lnc-NLC1-C overexpression or interference vectors. Cell proliferation was detected using a Cell Counting Kit-8 assay. Cell migration and invasion were examined using a Transwell assay, while apoptosis, cell cycle and reactive oxygen species production were evaluated using flow cytometry, and the expression levels of lnc-NLC1-C, microRNA (miR)-383 and peroxiredoxin 3 (PRDX-3) were measured using western blotting and RT-qPCR. Rescue experiments were performed to verify the function of the lnc-NLC1-C/miR-383/PRDX-3 axis. The highest expression levels of lnc-NLC1-C were identified in U87MG glioma cells. Overexpression of lnc-NLC1-C expression promoted cell proliferation, G1 phase blocking, migration and invasion, while inhibiting apoptosis and autophagy in U87MG cells. Mechanistically, miR-383 could bind to lnc-NLC1-C to regulate PRDX-3 expression and improve its oncogenic effect. Rescue experiments confirmed that the lnc-NLC1-C/miR-383/PRDX-3 axis was involved in the molecular mechanism of glioma progression. Therefore, lnc-NLC1-C may be a tumor promoter that affects multiple biological functions, such as migration, invasion and autophagy, in glioma cells.

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.

LINC00200 contributes to the chemoresistance to oxaliplatin of gastric cancer cells via regulating E2F1/RAD51 axis

The goal of this research was to decipher the biological functions and mechanism of long intergenic non-protein coding RNA 200 (LINC00200) in gastric cancer (GC). In this study, our data confirmed that LINC00200 expression was up-regulated in GC tissues and its high expression was correlated with the poor differentiation of GC tissues and lymph node metastasis of the patients. In vitro experiments indicated that, the overexpression of LINC00200 facilitated the proliferation of GC cells, constrained their apoptosis, and increased the IC₅₀ of oxaliplatin (Oxa), whereas knockdown of LINC00200 exhibited the opposite effects. Additionally, we demonstrated that LINC00200 could bind to E2F transcription factor 1 (E2F1), and the up-regulation of LINC00200 expression enhanced the binding between E2F1 and RAD51 promoter, hence promoting RAD51 transcription, while knockdown of LINC00200 inhibited the transcription of RAD51. In conclusion, LINC00200 may recruit E2F1 to the RAD51 recombinase (RAD51) promoter region, thereby up-regulating the expression of RAD51 and enhancing the chemoresistance of GC cells to Oxa. Our data suggested that LINC00200 could probably be a promising target for treating GC.

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.

Integrated Analysis of a Competing Endogenous RNA Network Reveals a Prognostic Signature in Kidney Renal Papillary Cell Carcinoma

The kidney renal papillary cell carcinoma (KIRP) is a relatively rare type of renal cell carcinoma (RCC). Currently, most kidney cancer studies primarily focus on RCC, and there has been no investigation to find a robust signature to predict the survival outcome of KIRP patients. In this study, we constructed a competing endogenous RNA (ceRNA) network, including 1,251 lncRNA-miRNA-mRNA interactions. Eight differentially expressed genes (IGF2BP3, PLK1, LINC00200, NCAPG, CENPF, miR-217, GAS6-As1, and LRRC4) based on the TCGA database were selected. The prognostic signature was established by combining the univariate Cox regression method and a stepwise regression method, with its predictive value validated by time-dependent receiver operating characteristic (ROC) curves. In conclusion, we identified eight prognostic signatures with using ceRNA networks. Our study provided a global view and a systematic dissection on KIRP prognosis biomarkers, and the eight identified genes might be used as new and important prognostic factors involved in KIRP pathogenesis.

Downregulation of Long Noncoding RNA LUCAT1 Suppresses the Migration and Invasion of Bladder Cancer by Targeting miR-181c-5p

Purpose

The long noncoding RNA LUCAT1 (lung cancer-associated transcript 1) has been reported to be highly expressed in bladder cancer samples, but its role and molecular mechanisms need to be elucidated.

Methods

Bioinformatics methods show that miR-181c-5p is a target of LUCAT1. Here, we aimed to reveal whether LUCAT1 participates in the development of bladder cancer via targeting miR-181c-5p. The expression levels of LUCAT1 and miR-181c-5p were detected by RT-PCR technology in bladder cells and tissues. The effects of the LUCAT1/miR-181c-5p axis on cell proliferation, migration, invasion, and apoptosis were tested by CCK-8, wound healing, Transwell chambers, and flow cytometry assays. The expressions of apoptosis/migration-related proteins were detected by western blotting assays.

Results

The results demonstrated that LUCAT1 was overexpressed in bladder cancer tissue and cells, while miR-181c-5p showed a low expression pattern as compared to normal bladder cells and tissues. Cell proliferation, migration, and invasion capacities were significantly impaired, and cell apoptosis was enhanced when LUCAT1 was silenced in UM-UC-3 and T24 cell lines, but this effect was abolished by miR-181c-5p downregulation. In addition, miR-181c-5p downregulation impaired LUCAT1 downregulation which mediated the decreased expressions of Bcl2 and N-cadherin and the increased expressions of Bax and E-cadherin. Moreover, we found that KRAS was a direct target of miR-181c-5p and was under the positive regulation of LUCAT1.

Conclusion

Collectively, this study reveals that knockdown of LUCAT1 inhibits the migration and invasion of bladder cancer cells in a miR-181c-5p-dependent manner, which may be related to KRAS downregulation.

LINC00501 Inhibits the Growth and Metastasis of Lung Cancer by Mediating miR-129-5p/HMGB1

Background

The function of LINC00501, a long-non-coding RNA (lncRNA), is unclear at present. According to the Cancer Genome Atlas (TCGA), LINC00501 is highly expressed in lung cancer (LC), but whether it can be adopted as a potential therapy target for LC still needs further research.

Methods

The expression of LINC00501 in LC was analyzed based on the TCGA, and a real-time fluorescent quantitative PCR assay was carried out to quantify LINC00501 in non-small-cell lung cancer (NSCLC). Additionally, bioinformatics analysis, luciferase reporter gene technique, and RNA immunoprecipitation (RIP) were employed to analyze the direct interaction between LINC00501 and miR-129-5p, and CCK-8 and Transwell assays and flow cytometry were employed to analyze the effects of LINC00501 on cell proliferation, invasion, and apoptosis. Furthermore, a Western blot assay was carried out to determine the protein level of HMGB1.

Results

LINC00501 was highly expressed in LC according to the database, and it was found that LINC00501 was upregulated in NSCLC specimens and cells, and the up-regulation indicated an unfavorable prognosis. Besides, knockdown of LINC00501 hindered the proliferation and invasion of NSCLC cells and intensified their apoptosis, and LINC00501 could be adopted as competitive endogenous RNA to regulate HMGB1 and tumorigenesis through miR-129-5p.

Conclusion

LINC00501 is overexpressed in LC and the overexpression indicates poor prognosis of patients. In addition, LINC00501 can inhibit the invasion and migration of LC by mediating miR-129-5p/HMGB1.

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Colon Adenocarcinoma Metastasis

BACKGROUND

Colon adenocarcinoma (COAD) is a malignant and lethal tumor in digestive system and distance metastasis lead to poor prognosis. The metastasis-specific ceRNAs (competitive endogenous RNAs) and tumor-infiltrating immune cells might associate with tumor prognosis and distance metastasis. Nonetheless, few studies have concentrated on ceRNAs and Immune cells in COAD.

METHODS

The gene expression profile and clinical information of COAD were downloaded from TCGA and divided into two groups: primary tumors with or without distance metastasis. We applied comprehensive bioinformatics methods to analyze differential expression genes (DEGs) related to metastasis and establish the ceRNA networks. The Cox analysis and Lasso regression were utilized to screen the pivotal genes and prevent overfitting. Based on them, the prognosis prediction nomograms were established. The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was then applied to screen significant tumor immune-infiltrating cells associated with COAD metastasis and established another prognosis prediction model. Ultimately, co-expression analysis was applied to explore the relationship between key genes in ceRNA networks and significant immune cells. Multiple databases and preliminary clinical specimen validation were used to test the expressions of key biomarkers at the cellular and tissue levels.

RESULTS

We explored 1 significantly differentially expressed lncRNA, 1 significantly differentially expressed miRNA, 8 survival-related immune-infiltrating cells, 5 immune cells associated with distance metastasis. Besides, 3 pairs of important biomarkers associated with COAD metastasis were also identified: T cells follicular helper and hsa-miR-125b-5p (R = -0.200, P < 0.001), Macrophages M0 and hsa-miR-125b-5p (R = 0.170, P < 0.001) and Macrophages M0 and FAS (R = -0.370, P < 0.001). Multidimensional validation and preliminary clinical specimen validation also supported the results.

CONCLUSION

In this research, we found some significant ceRNAs (FAS and hsa-miR-125b-5p) and tumor-infiltrating immune cells (T cells follicular helper and Macrophages M0) might related to distance metastasis and prognosis of COAD. The nomograms could assist scientific and medical researchers in clinical management.

A novel molecular-clinicopathologic nomogram to improve prognosis prediction of hepatocellular carcinoma

BACKGROUND

Emerging evidence suggests that long non-coding RNA (lncRNA) plays a crucial part in the development and progress of hepatocellular carcinoma (HCC). The objective was to develop novel molecular-clinicopathological prediction methods for overall survival (OS) and recurrence of HCC.

RESULTS

An 8-lncRNA-based classifier for OS and a 14-lncRNA-based classifier for recurrence were developed by LASSO COX regression analysis, both of which had high accuracy. The tdROC of OS-nomogram and recurrence-nomogram indicates the satisfactory accuracy and predictive power. The classifiers and nomograms for predicting OS and recurrence of HCC were validated in the Test and GEO cohorts.

CONCLUSIONS

These two lncRNA-based classifiers could be independent prognostic factors for OS and recurrence. The molecule-clinicopathological nomograms based on the classifiers could increase the prognostic value.

METHODS

HCC lncRNA expression profiles from the cancer genome atlas (TCGA) were randomly divided into 1:1 training and test cohorts. Based on least absolute shrinkage and selection operator method (LASSO) COX regression model, lncRNA-based classifiers were established to predict OS and recurrence, respectively. OS-nomogram and recurrence-nomogram were developed by combining lncRNA-based classifiers and clinicopathological characterization to predict OS and recurrence, respectively. The prognostic value was accessed by the time-dependent receiver operating characteristic (tdROC) and the concordance index (C-index).

Construction of a competing endogenous RNA network using differentially expressed lncRNAs, miRNAs and mRNAs in non‑small cell lung cancer

The competing endogenous RNA (ceRNA) network is crucial for the development and progression of tumors, including non-small cell lung cancer (NSCLC). However, what type of ceRNA network regulates NSCLC has not been clarified. The present study aimed to elucidate the long non-coding RNA (lncRNA)/microRNA (miRNA)/mRNA ceRNA network in NSCLC, particularly for the significance of lncRNAs in NSCLC. NSCLC-specific differentially expressed lncRNAs, miRNAs and mRNAs in the Cancer Genome Atlas (TCGA) were analyzed and their relationship was analyzed by a ceRNA network. Their potential functions of differentially expressed mRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the expression levels of four selected lncRNAs in TCGA were determined and their associated survival of patients was examined. In addition, the expression profiles of these four lncRNAs in 48 NSCLC specimens and cell lines, their cellular distribution and associated clinical parameters were examined. We successfully constructed a ceRNA network, including 113 lncRNAs, 12 miRNAs and 36 mRNAs differentially expressed between NSCLC and non-tumor tissues. LINC00525, MED4-AS1, STEAP2-AS1 and SYNPR-AS1 lncRNAs were selected and validated for their association with the survival of NSCLC patients. The expression of these lncRNAs was upregulated in 48 NSCLC tissues and was varying in NSCLC cells. While LINC00525 was mainly expressed in the cytoplasm, MED4-AS1 was in both the nucleus and cytoplasm of A549 cells. In addition, the expression of LINC00525 was significantly associated with smoking history (P<0.05); MED4-AS1 was significantly associated with women, poor differentiation and lymph node metastasis (P<0.05); STEAP2-AS1 was significantly associated with women (P<0.01); and SYNPR-AS1 was significantly associated with women and adenocarcinoma (P<0.05). These lncRNAs may be valuable biomarkers for prognosis of NSCLC and the ceRNA network may provide new insights in the pathogenesis of NSCLC.

Comprehensive analysis of five long noncoding RNAs expression as competing endogenous RNAs in regulating hepatoma carcinoma

Liver cancer is the most common cancer and is the epitome of a recalcitrant cancer. Increasing evidence shown that long noncoding RNAs (lncRNA) were associated with cancer‐related death and could function as a competing endogenous RNA (ceRNA). To explore regulatory roles and potential prognostic biomarkers of lncRNA for liver cancer, RNA‐sequencing expression data were downloaded from the TCGA database and GEO database. A total of 357 patients were randomly divided into a discovery group and a validation group, of which 313 patients can obtain clinical data. In discovery phrase, 58 lncRNAs, 16 miRNAs, and 34 mRNAs were screened to construct the ceRNA network based on 252 patients employed from discovery group. Univariate and multivariate Cox hazard regression analysis model revealed that five lncRNAs (AATK‐AS1, C10orf91, LINC00162, LINC00200, and LINC00501) from 58 lncRNAs were formulated to predict the overall survival (OS). We used the value of gene expression and regression coefficients to construct a risk score based on the five lncRNAs. Next, we validated our model in the GSE116174 dataset (n = 64) and the validation group (n = 94) from TCGA database. Subgroup analysis suggest that the five lncRNAs played critical parts in early stage in cancer from both discovery and validation groups. The five lncRNAs were also found to be associated with immune cells infiltration including CD4⁺ memory activated, NK cells activated and mast cells activated, then the results were also validated according to the validation group. Furthermore, KEGG pathway enrichment analysis showed that these nine coexpressed modules using the method of WGCNA, and many of these pathways are associated with the development and progression of disease. At last, the transcription factor binding sites (TFBS) of the five lncRNAs were predicted, which help us to understand the potential mechanism that the TFBS adjusted the ceRNA network. In summary, the ceRNA regulatory network may contribute to a better understanding of liver cancer mechanism and provide potential prognostic biomarkers and therapeutic targets.