The downregulation of lncRNA EMX2OS might independently predict shorter recurrence-free survival of classical papillary thyroid cancer

Progress in long non-coding RNAs as prognostic factors of papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is generally recognized as a slow-growing tumor. However, a small subset of patients may still experience relapse or metastasis shortly after therapy, leading to a poor prognosis and raising concerns about excessive medical treatment. One major challenge lies in the inadequacy of effective biomarkers for accurate risk stratification. Long non-coding RNAs (lncRNAs), which are closely related to malignant characteristics and poor prognosis, play a significant role in the genesis and development of PTC through various pathways. The objective of this review is to provide a comprehensive summary of the biological functions of lncRNAs in PTC, identify prognosis-relevant lncRNAs, and explore their potential mechanisms in drug resistance to BRAF kinase inhibitors, tumor dedifferentiation, and lymph node metastasis. By doing so, this review aims to offer valuable references for both basic research and the prediction of PTC prognosis.

The function of lncRNA EMX2OS/miR-653-5p and its regulatory mechanism in lung adenocarcinoma

This study aimed to evaluate the significance of EMX2OS in lung adenocarcinoma (LUAD) prognosis and development and its potential molecular mechanism. Paired tissue samples were collected from 117 LUAD patients. The EMX2OS expression level was detected by PCR and correlated with patients' clinicopathological features by a series of statistical analyses. The function of EMX2OS in cell proliferation and metastasis was evaluated by CCK8 and Transwell assay. In mechanism, the interaction between EMX2OS and miR-653-5p was assessed by the dual-luciferase reporter assay, and the regulatory effect of miR-653-5p on EMX2OS tumor suppressor role was also estimated. Significant downregulation of EMX2OS and its negative correlation with miR-653-5p was observed in LUAD tissues. A significant relationship was revealed in EMX2OS with TNM stage, lymph node metastasis, and differentiation of LUAD patients, and associated with the poor prognosis of patients. EMX2OS suppressed the proliferation and metastasis of LUAD cells and negatively regulated the expression of miR-653-5p. The overexpression of miR-653-5p could reverse the inhibitory effect of EMX2OS on LUAD cells. In conclusion, EMX2OS served as a biomarker in LUAD that indicated patients' prognosis and regulated cellular processes via regulating miR-653-5p.

Cuproptosis-related lncRNA signatures predict prognosis and immune relevance of kidney renal papillary cell carcinoma

Kidney renal papillary cell carcinoma (KIRP) has a high mortality rate and a poor prognosis. Cu concentrations differed significantly between renal cancer tissues and adjacent normal tissues. Cuproptosis is a newly identified cell death. Long non-coding RNAs (lncRNAs) play a crucial role in the progression of KIRP. In this study, we focused on constructing and validating cuproptosis-related lncRNA signatures to predict the prognosis of KIRP patients and their immune correlation. We created prognosis models using Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. We found that patients in the high-risk group had poorer overall survival (OS) and progression-free survival (PFS) and higher mortality. Risk score and stage are prognosis factors independent of other clinical features. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and C-index curves showed that cuproptosis-related lncRNA signatures could more accurately predict the prognosis of patients. Functional enrichment analysis suggests that the function of differentially expressed genes (DEGs) is associated with KIRP development and immunity. In immune-related function analysis, we found a significant difference in parainflammation responses between high-risk and low-risk groups. The mutation frequencies of TTN, MET, KMT2C, PKHD1, SETD2, and KMT2D genes in the high-risk group were higher than those in the low-risk group, but the mutation frequencies of MUC16, KIAA109, CUBN, USH2A, DNAH8 and HERC2 genes were significantly lower than those in the low-risk group. Survival analysis of tumor mutation burden (TMB) and combined TMB-risk showed better OS in patients with high TMB. Immune infiltration and immune checkpoint analysis assessed the immune association of six high mutation frequency genes (TTN, MET, KMT2C, PKHD1, SETD2, and KMT2D) with KIRP. Finally, we performed a drug sensitivity analysis and screened 15 potential drugs that differed between high-risk and low-risk patients. In this study, we constructed and validated cuproptosis-related lncRNA signatures that can more accurately predict the prognosis of KIRP patients and provide new potential therapeutic targets and prognosis markers for KIRP patients.

Comprehensive analysis of necroptosis-related long noncoding RNA to predict prognosis, immune status, and immunotherapeutic response in clear cell renal cell carcinoma

Background

Necroptosis has been found to be associated with tumorigenesis and tumor progression. However, the prognostic effect of long noncoding RNAs (lncRNAs) associated with necroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear.

Methods

Pearson correlation analysis was used to identify necroptosis-related genes and lncRNAs obtained from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression analyses were used to identify a novel necroptosis-associated lncRNAs signature that significantly correlated with survival of ccRCC. Next, single sample gene set enrichment analysis (ssGSEA) was employed to assess the extent of infiltration with immune cells. Analyses to predict the half-maximal inhibitory concentration (IC50) of patients in different risk groups were also conducted. Moreover, follow-up data of an immunotherapy cohort were used to test for differences in the immunotherapeutic efficiency between two risk groups. Finally, patients with ccRCC were divided into two groups based on 6 prognostic lncRNAs.

Results

We developed a signature of necroptosis-related lncRNAs, which was verified as an independent prognostic factor that can predict prognosis up to 7 years. Patients with higher risk scores were shown to have higher immune suppressive cell infiltration levels and expression of immune checkpoint genes, which suggests that these patients were in a state of immunosuppression. Patients in the low-risk group were found to have an increased response to immunotherapy. A prognostic prediction nomogram was conducted to predict long-term survival of patients. Cluster A tumors were considered hot tumors, since they were correlated with higher levels of immune infiltration and were more sensitive to immunotherapy.

Conclusions

A comprehensive bioinformatics analysis was conducted, which found that the necroptosis-associated lncRNA signature might be a potent prognostic factor for patients with ccRCC, which could contribute to improved prognosis of these patients.

A Potential Nine-lncRNAs Signature Identification and Nomogram Diagnostic Model Establishment for Papillary Thyroid Cancer

The purpose of our current study was to establish a long non-coding RNA(lncRNA) signature and assess its prognostic and diagnostic power in papillary thyroid cancer (PTC). LncRNA expression profiles were obtained from the Cancer Genome Atlas (TCGA). The key module and hub lncRNAs related to PTC were determined by weighted gene co-expression network analysis (WGCNA) and LASSO Cox regression analyses, respectively. Functional enrichment analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis were implemented to analyze the possible biological processes and signaling pathways of hub lncRNAs. Associations between key lncRNA expressions and tumor-infiltrating immune cells were identified using the TIMER website, and proportions of immune cells in high/low risk score groups were compared. Kaplan-Meier Plotter was used to evaluate the prognostic significance of hub genes in PTC. A diagnostic model was conducted with logistic regression analysis, and its diagnostic performance was assessed by calibration/receiver operating characteristic curves and principal component analysis. A nine-lncRNAs signature (SLC12A5-AS1, LINC02028, KIZ-AS1, LINC02019, LINC01877, LINC01444, LINC01176, LINC01290, and LINC00581) was established in PTC, which has significant diagnostic and prognostic power. Functional enrichment analyses elucidated the regulatory mechanism of the nine-lncRNAs signature in the development of PTC. This signature and expressions of nine hub lncRNAs were correlated with the distributions of tumor infiltrating immune cells. A diagnostic nomogram was also established for PTC. By comparing with the published models with less than or equal to nine lncRNAs, our signature showed a preferable performace for prognosis prediction. In conclusion, our present research established an innovative nine-lncRNAs signature and a six-lncRNAs nomogram that might act as a potential indicator for PTC prognosis and diagnosis, which could be conducive to the PTC treatment.

miRNA and lncRNA Expression Networks Modulate Cell Cycle and DNA Repair Inhibition in Senescent Prostate Cells

Cellular senescence is a state of permanent growth arrest that arises once cells reach the limit of their proliferative capacity. It creates an inflammatory microenvironment favouring the initiation and progression of various age-related diseases, including prostate cancer. Non-coding RNAs (ncRNAs) have emerged as important regulators of cellular gene expression. Nonetheless, very little is known about the interplay of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and how deregulation of ncRNA networks promotes cellular senescence. To investigate this, human prostate epithelial cells were cultured through different passages until senescent, and their RNA was extracted and sequenced using RNA sequencing (RNAseq) and microRNA sequencing (miRNA-seq) miRNAseq. Differential expression (DE) gene analysis was performed to compare senescent and proliferating cells with Limma, miRNA-target interactions with multiMiR, lncRNA-target interactions using TCGA data and network evaluation with miRmapper. We found that miR-335-3p, miR-543 and the lncRNAs H19 and SMIM10L2A all play central roles in the regulation of cell cycle and DNA repair processes. Expression of most genes belonging to these pathways were down-regulated by senescence. Using the concept of network centrality, we determined the top 10 miRNAs and lncRNAs, with miR-335-3p and H19 identified as the biggest hubs for miRNAs and lncRNA respectively. These ncRNAs regulate key genes belonging to pathways involved in cell senescence and prostate cancer demonstrating their central role in these processes and opening the possibility for their use as biomarkers or therapeutic targets to mitigate against prostate ageing and carcinogenesis.

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.

Identification of circulating biomarkers for differentiating patients with papillary thyroid cancers from benign thyroid tumors

BACKGROUND

This study aimed to identify the potential circulating biomarkers of protein, mRNAs, and long non-coding RNAs (lncRNAs) to differentiate the papillary thyroid cancers from benign thyroid tumors.

METHODS

The study population of 100 patients was classified into identification (10 patients with papillary thyroid cancers and 10 patients with benign thyroid tumors) and validation groups (45 patients with papillary thyroid cancers and 35 patients with benign thyroid tumors). The Sengenics Immunome Protein Array-combined data mining approach using the Open Targets Platform was used to identify the putative protein biomarkers, and their expression validated using the enzyme-linked immunosorbent assay. Next-generation sequencing by Illumina HiSeq was used for the detection of dysregulated mRNAs and lncRNAs. The website Timer v2.0 helped identify the putative mRNA biomarkers, which were significantly over-expressed in papillary thyroid cancers than in adjacent normal thyroid tissue. The mRNA and lncRNA biomarker expression was validated by a real-time polymerase chain reaction.

RESULTS

Although putative protein and mRNA biomarkers have been identified, their serum expression could not be confirmed in the validation cohorts. In addition, seven lncRNAs (TCONS_00516490, TCONS_00336559, TCONS_00311568, TCONS_00321917, TCONS_00336522, TCONS_00282483, and TCONS_00494326) were identified and validated as significantly downregulated in patients with papillary thyroid cancers compared to those with benign thyroid tumors. These seven lncRNAs showed moderate accuracy based on the area under the curve (AUC = 0.736) of receiver operating characteristic in predicting the occurrence of papillary thyroid cancers.

CONCLUSIONS

We identified seven downregulated circulating lncRNAs with the potential for predicting the occurrence of papillary thyroid cancers.

EMX2OS plays a prognosis-associated enhancer RNA role in gastric cancer

Enhancer RNAs (eRNAs), a subclass of lncRNAs, are derived from enhancer regions. The function of eRNAs has been reported by many previous studies. However, the role of eRNAs in gastric cancer, especially the prognosis-associated eRNAs, has not been studied yet.In this study, we have used a novel approach to screened key eRNAs in gastric cancer. Kaplan-Meier correlation analysis and Co-expression analysis were used to find the most significant survival-associated eRNAs. Enrichment analysis is applied to explore the key functions and pathways of screened eRNAs. The correlation and survival analysis are used to evaluate targeted genes in the pan-cancer analysisA total of 63 prognostic-associated eRNAs in gastric cancer were identified, the top 6 eRNAs were LINC01714, ZNF192P1, AC079760.2, LINC01645, EMX2OS, and AC114489.2. The correlation analysis demonstrated the top 10 screened eRNAs and their targeted genes. The results demonstrated that EMX2OS was ranked as the top eRNA according to the results of the Kaplan-Meier analysis. The correlation analysis demonstrated that eRNA EMX2OS is correlated with age, grade, stage, and cancer status. The pan-cancer analysis demonstrated that EMX2OS was associated with poor survival outcomes in adrenocortical carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney renal clear cell carcinoma, stomach adenocarcinoma, and uveal melanoma.In this study, survival-related eRNAs were screened and the correlation between survival-related eRNAs and their targeted genes was demonstrated. EMX2OS plays a prognosis-associated eRNA role in gastric cancer, which might be a novel therapeutic target in clinical practice.

Up-regulation of FOXN3-AS1 in invasive ductal carcinoma of breast cancer patients

Oncogenic and tumor-suppressive roles of long non-coding RNA make them an appropriate target for expression analysis in cancer studies. In this study, we selected two lncRNAs (EMX2OS and FOXN3-AS1) that are resided near the GWAS-identified SNPs for breast cancer (rs2901157 and rs141061110). These transcripts have been identified in different cancer types as either oncogenes or tumor suppressors. In the present investigation, we aimed to quantify the expression level of EMX2OS and FOXN3-AS1 in 44 breast cancer samples and normal adjacent tissues (ANCTs). The FOXN3-AS1 expression level was significantly increased in breast cancer samples compared with ANCTs (P value = 0.02), Also its amounts could distinguish two sets of samples with an accuracy of 70% (P value = 0.009). We have found an association between FOXN3-AS1 expression and tumor size (P value = 0.02). On the other hand, no significant differences were found in the EMX2OS expression level between two sets of samples (P value = 0.44); however, EMX2OS expression level has a significant association with the age of the patients (P value = 0.03). According to our result, FOXN3-AS1 can be demonstrated as a probable diagnostic marker in breast cancer so we suggest further functional studies to find the precise role of these lncRNAs in breast cancer progression.

SFPQ promotes an oncogenic transcriptomic state in melanoma

The multifunctional protein, splicing factor, proline- and glutamine-rich (SFPQ) has been implicated in numerous cancers often due to interaction with coding and non-coding RNAs, however, its role in melanoma remains unclear. We report that knockdown of SFPQ expression in melanoma cells decelerates several cancer-associated cell phenotypes, including cell growth, migration, epithelial to mesenchymal transition, apoptosis, and glycolysis. RIP-seq analysis revealed that the SFPQ-RNA interactome is reprogrammed in melanoma cells and specifically enriched with key melanoma-associated coding and long non-coding transcripts, including SOX10, AMIGO2 and LINC00511 and in most cases SFPQ is required for the efficient expression of these genes. Functional analysis of two SFPQ-enriched lncRNA, LINC00511 and LINC01234, demonstrated that these genes independently contribute to the melanoma phenotype and a more detailed analysis of LINC00511 indicated that this occurs in part via modulation of the miR-625-5p/PKM2 axis. Importantly, analysis of a large clinical cohort revealed that elevated expression of SFPQ in primary melanoma tumours may have utility as a prognostic biomarker. Together, these data suggest that SFPQ is an important driver of melanoma, likely due to SFPQ-RNA interactions promoting the expression of numerous oncogenic transcripts.

Identification of a Four Hypoxia-Associated Long Non-Coding RNA Signature and Establishment of a Nomogram Predicting Prognosis of Clear Cell Renal Cell Carcinoma

To identify novel hypoxia-associated long non-coding RNAs (lncRNAs) as potential biomarkers, we developed a risk stratification signature and constructed a prognosis prediction nomogram of clear cell renal cell carcinoma (ccRCC). Hypoxia-related lncRNAs were identified through Pearson correlation analysis between the expression profiles of hypoxia-related differentially expressed genes and lncRNAs from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Then, a signature of four key lncRNAs (COMETT, EMX2OS, AC026462.3, and HAGLR) was developed. The four lncRNAs were downregulated in high-grade, advanced stage, and high-risk ccRCC. The signature had an independent and long-standing prognosis prediction ability up to a 10-year follow-up. Notably, the risk score was significantly positively correlated with the infiltration abundances of six immune cells from the Tumor IMmune Estimation Resource (TIMER). The gene set enrichment analysis (GSEA) also suggested that the signature was involved in metabolism and tumorigenesis, which were closely related to the hypoxic tumor microenvironment. Ultimately, a nomogram of signature, age, stage, and grade, was built to predict the individual long-term survival possibility. Finally, the expressions of four lncRNAs were validated by quantitative real-time PCR (qRT-PCR). Our study identified a four-lncRNA signature and established a prognostic nomogram that reliably predicts survival in ccRCC. The findings may be beneficial to therapeutic customization and medical decision-making.

Comparison of thermal ablation and routine surgery for the treatment of papillary thyroid microcarcinoma: a systematic review and Meta-analysis

BACKGROUND

Thermal ablation (TA), as an alternative to surgery, has shown some benefits in the treatment of papillary thyroid microcarcinoma (PTMC) patients, especially for those who are at high risk for surgery or refuse surgery. We performed a systematic review and meta-analysis to evaluate the efficiency, safety, and economy of TA, compared with those of routine surgery (RS), for the treatment of PTMC.

METHODS

PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP databases were retrieved from inception to 10 January 2020 to identify relevant original studies on comparison of TA and RS for treatment of PTMC. The recurrence rate, recurrence-free survival (RFS), complication rate, operation time, postoperative length of stay, and cost during the perioperative period were extracted as main indices. The pooled standardized mean difference (SMD) or odds ratio (OR) with 95% confidence intervals (CI) were calculated and analyzed. Chi-square test and I ² statistic were applied to determine the heterogeneity among studies. The sensitivity analysis was applied to explore the origin of heterogeneity, and the publication bias was evaluated by Egger's test.

RESULTS

Seven retrospective studies with a total of 867 patients met the eligibility criteria and were included in the final meta-analysis. Our study demonstrated that TA showed significant reduction in complication with a pooled OR 0.24 (95% CI 0.13 to 0.43), postoperative length of stay with a pooled SMD -3.14 (95% CI -4.77 to -1.51) and cost during the perioperative period with a pooled SMD of -1.69 (95% CI -3.18 to -0.20). It also demonstrated that both TA and RS had similar pooled proportion of recurrence of OR 0.93 (95% CI 0.38 to 2.30) and recurrence-free survive (RFS). The sensitivity analysis showed that each included study had no significant effect on the results and the results were stable and reliable. The Egger's test demonstrated publication bias was acceptable.

CONCLUSIONS

TA may not be oncologically inferior to RS, and it is a relatively safe and economical alternative for the treatment of PTMC.

A long non-coding RNAs expression signature to improve prognostic prediction of Wilms tumor in children

BACKGROUND

Wilms tumor (WT) is the most frequent malignancy of the kidney in children, and a subset of patients remains with a poor prognosis. This study aimed to identify key long non-coding RNAs (lncRNAs) related to prognosis and establish a genomic-clinicopathologic nomogram to predict survival in children with WT.

METHODS

Clinical data of 124 WT patients and the relevant RNA sequencing data including lncRNAs expression signature of primary WT samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) Data Matrix. Then, lncRNAs associated with overall survival (OS) were identified through univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. The risk scores of 124 participants were calculated, and survival analyses were performed between low- and high-risk groups. A genomic-clinicopathologic nomogram was then developed and evaluated by time-dependent receiver operating characteristic (ROC) curves, including the area under the curve (AUC), calibration curve, and decision curve analysis. Subsequently, bioinformatics analyses were performed to explore the potential molecular mechanisms that affect the prognosis of WT. The package "DESeq2" was used to identify differentially expressed protein-coding genes (DEPCGs) between groups. Gene Set Enrichment Analysis (GSEA) was applied to explore the differences in pathways enrichment. The analytical tools CIBERSORTx and ESTIMATE were used to investigate the discrepancies of the immune microenvironment.

RESULTS

A total of 10 lncRNAs were selected as independent predictors associated with OS (P<0.05). Participants in the high-risk group had a significantly worse OS and event-free survival (EFS) than those in the low-risk group (P<2E-16 and P=2.03E-04, respectively). The risk score and 3 clinicopathological features (gender, cooperative group protocol, and stage) were identified to construct the nomogram (combined model) (P=5.11E-17). The combined model (1-year AUC: 0.9272, 3-year AUC: 0.9428, 5-year AUC: 0.9259) and risk score model (1-year AUC: 0.9285, 3-year AUC: 0.9399, 5-year AUC: 0.9266) displayed higher predictive accuracy than that of the other models. Subsequently, 105 DEPCGs were identified. The GSEA revealed 4 significant pathways. Analysis with CIBERSORTx demonstrated that monocytes, macrophages M1, activated dendritic cells, and resting mast cells had significant infiltration differences between groups.

CONCLUSIONS

This study constructed a genomic-clinicopathologic nomogram, which might present a novel and efficient method for treating patients with WT.

Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune-related lncRNAs (IRLs) of CC has never been reported. This study is aimed at establishing an IRL signature for patients with CC. A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson correlation analysis between the immune score and lncRNA expression (p < 0.01). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values (p < 0.05) were identified which demonstrated an ability to stratify patients into the low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group in the training set, valid set, and total set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four-IRL signature in predicting the one-, two-, and three-year survival rates was larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four IRLs in the development of CC were ascertained preliminarily.

Identification of 12 immune-related lncRNAs and molecular subtypes for the clear cell renal cell carcinoma based on RNA sequencing data

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma (RCC). Despite the existing extensive research, the molecular and pathogenic mechanisms of ccRCC are elusive. We aimed to identify the immune-related lncRNA signature and molecular subtypes associated with ccRCC. By integrating 4 microarray datasets from Gene Expression Omnibus database, we identified 49 immune-related genes. The corresponding immune-related lncRNAs were further identified in the TCGA dataset. 12-lncRNAs prognostic and independent signature was identified through survival analysis and survival difference between risk groups was further identified based on the risk score. Besides, we identified 3 molecular subtypes and survival analysis result showed that cluster 2 has a better survival outcome. Further, ssGSEA enrichment analysis for the immune-associated gene sets revealed that cluster 1 corresponded to a high immune infiltration level. While cluster 2 and cluster 3 corresponded to low and medium immune infiltration level, respectively. In addition, we validated the 12-lncRNA prognostic signature and molecular subtypes in an external validation dataset from the ICGC database. In summary, we identified a 12-lncRNA prognostic signature which may provide new insights into the molecular mechanisms of ccRCC and the molecular subtypes provided a theoretical basis for personalized treatment by clinicians.

LncRNA EMX2OS, Regulated by TCF12, Interacts with FUS to Regulate the Proliferation, Migration and Invasion of Prostate Cancer Cells Through the cGMP-PKG Signaling Pathway

Background

LncRNA EMX2OS (EMX2 opposite strand/antisense RNA) is notably downregulated in prostate cancer (PCa) tissues and may be regarded as a potential molecular biomarker for diagnosis and prognosis. However, its exact role in regulating the development of PCa is obscure.

Methods

The EMX2OS expression was assessed in PCa tissues, paracancer tissues, PCa cells and normal prostate epithelial cells by qPCR. Gain- and loss-of-function experiments were performed to investigate the role of EMX2OS and FUS in cGMP-PKG (cyclic guanosine monophosphate-dependent protein kinase)-mediated proliferation, invasion, and migration in human PCa cell lines DU145 and PC3. Then, the interaction of transcription factor 12 (TCF12) with EMX2OS promoter was confirmed by using the dual-luciferase reporter and chromatin immunoprecipitation (ChIP) assays. RNA binding protein immunoprecipitation and RNA pull-down assays were used to verify the interaction between EMX2OS and FUS protein. Finally, the role of EMX2OS and FUS in tumor growth in vivo was validated in a xenograft nude mouse model.

Results

TCF12 and EMX2OS were both downregulated in PCa tissues and cells, and they negatively regulated cell proliferation, migration and invasion, and activated cGMP-PKG pathway in DU145 and PC3 cells. TCF12 was a transcription factor of EMX2OS. TCF12 and EMX2OS overexpression both down-regulated cell proliferation, migration and invasion, and activated cGMP-PKG pathway in DU145 and PC3 cells. Furthermore, EMX2OS directly bound with FUS protein and had a synergy effect with FUS protein on cGMP-PKG-mediated cell functions, which could be suppressed by (D)-DT-2 (a cGMP-PKG inhibitor). In addition, the overexpression of FUS or EMX2OS individually markedly decreased the volume and weight of tumors in vivo, and co-overexpression of them further inhibited tumor growth.

Conclusion

EMX2OS, transcriptionally regulated by TCF12, played a synergy role with FUS protein in regulating the proliferation, migration and invasion of PCa cells by activating the cGMP-PKG pathway.

Long non-coding RNA BRM promotes proliferation and invasion of papillary thyroid carcinoma by regulating the microRNA-331-3p/SLC25A1 axis

Long non-coding RNA BRM (lncBRM) was first identified in liver cancer stem cells and was reported to promote multiple cancer types. However, the function of lncBRM in papillary thyroid carcinoma (PTC) remains unclear. The primary focus of the present study was to determine the biological role of lncBRM in PTC. Reverse transcription-quantitative PCR assays revealed that lncBRM was upregulated in PTC tissues and cells. Cell Counting Kit-8, Transwell invasion and colony-formation assays were performed to assess cell proliferation, invasion and migration, respectively. Furthermore, high expression of lncBRM was associated with poor overall survival time in patients with PTC. lncBRM knockout significantly suppressed cell proliferation, migration and invasion. lncBRM was predicted to bind to microRNA (miR)-331-3p and targets SLC25A1. Overexpression of miR-331-3p or inhibition of SLC25A1 resulted in significantly suppressed proliferation, migration and invasion of PTC cells. Rescue assays demonstrated that inhibition of miR-331-3p significantly abrogated the effects of lncBRM knockout on PTC cell proliferation, migration and invasion. In conclusion, the present study suggests that lncBRM promotes PTC by regulating miR-331-3p and targeting SLC25A1.

The Role of High-Risk Human Papillomavirus-Related Long Non-Coding RNAs in the Prognosis of Cervical Squamous Cell Carcinoma

Cervical cancer (CC) is a malignant tumor that could seriously endanger women's life and health, of which cervical squamous cell carcinoma (CESC) accounts for more than 80%. High-risk human papillomavirus (HR-HPV) infection is the primary cause of CC. The 5-year survival rate is low due to poor prognosis. We need to explore the pathogenesis of CC and seek effective biomarkers to improve prognosis. The purpose of this research is to construct an HR-HPV-related long non-coding RNA (lncRNA) signature for predicting the survival and finding the biomarkers related to CC prognosis. First, we downloaded the CESC data from The Cancer Genome Atlas (TCGA) database to find HR-HPV-related lncRNAs in CC. Then, the differentially expressed lncRNAs were analyzed by univariate and multivariate Cox regression. Six lncRNAs were found to be associated with the prognosis and can be used as independent prognostic factors. Next, based on these prognostic genes, we established a risk score model, which showed that patients with higher score had poorer prognosis and higher mortality. Moreover, the Kaplan-Meier curve of the model indicated that the model was statistically significant (p < 0.05). The survival-receiver operating characteristic curve showed that the model could also predict the survival of CC patients (the area under the curve, AUC = 0.65). More importantly, nomogram was drawn with clinical features and risk score, which verified the above conclusion, and its calibration curve and c-index index fully demonstrated that the prediction model could predict the progress of CC. We also validated the risk score model in head and neck cancer, and the results indicated that the model had obvious prognostic ability. Finally, we analyzed the correlation between clinical features and survival, and found that neoplasm cancer (p < 0.000) and risk score (p < 0.000) were independent prognostic factors for CC. In conclusion, the study established HR-HPV-related lncRNA signature, which provided a reliable prognostic tool, and was of great significance for finding the biomarkers related to HR-HPV infection in CC.

Identifying 4 Novel lncRNAs as Potential Biomarkers for Acute Rejection and Graft Loss of Renal Allograft

Acute rejection (AR) after kidney transplant is one of the major obstacles to obtain ideal graft survival. Reliable molecular biomarkers for AR and renal allograft loss are lacking. This study was performed to identify novel long noncoding RNAs (lncRNAs) for diagnosing AR and predicting the risk of graft loss. The several microarray datasets with AR and nonrejection specimens of renal allograft downloaded from Gene Expression Omnibus database were analyzed to screen differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). Univariate and multivariate Cox regression analyses were used to identify optimal prognosis-related DElncRNAs for constructing a risk score model. 39 common DElncRNAs and 185 common DEmRNAs were identified to construct a lncRNA-mRNA regulatory relationship network. DElncRNAs were revealed to regulate immune cell activation and proliferation. Then, 4 optimal DElncRNAs, ATP1A1-AS1, CTD-3080P12.3, EMX2OS, and LINC00645, were selected from 17 prognostic DElncRNAs to establish the 4-lncRNA risk score model. In the training set, the high-risk patients were more inclined to graft loss than the low-risk patients. Time-dependent receiver operating characteristics analysis revealed the model had good sensitivity and specificity in prediction of 1-, 2-, and 3-year graft survival after biopsy (AUC = 0.891, 0.836, and 0.733, respectively). The internal testing set verified the result well. Gene set enrichment analysis which expounded NOD-like receptor, the Toll-like receptor signaling pathways, and other else playing important role in immune response was enriched by the 4 lncRNAs. Allograft-infiltrating immune cells analysis elucidated the expression of 4 lncRNAs correlated with gamma delta T cells and eosinophils, etc. Our study identified 4 novel lncRNAs as potential biomarkers for AR of renal allograft and constructed a lncRNA-based model for predicting the risk of graft loss, which would provide new insights into mechanisms of AR.

The role of long non-coding RNAs in the pathogenesis of thyroid cancer

Long noncoding RNAs (lncRNAs) as prominent regulators of gene expression are involved in different layers of expression regulation. These transcripts participate in carcinogenesis of several human malignancies including thyroid cancer. Availability of high throughput techniques such as RNA sequencing and microarray has facilitated identification of lncRNAs whose dysregulation affect tumorigenesis process. Moreover, assessment of differentially expressed lncRNAs between resistant and sensitive cells has led to recognition of biomarkers for therapeutic response. One elucidated aspect of lncRNAs functions is their role in sponging miRNAs. Several miRNA-lncRNA-mRNA triplets have been recognized till now. Any of these triplets is a putative target of interfering with the evolution of cancer. In the current study, we have summarized recent data in the fields of biology of lncRNAs, their role in thyroid cancer and their potential as biomarker or treatment target.

Bioinformatic analysis of the prognostic value and potential regulatory network of FOXF1 in papillary thyroid cancer

FOXF1 belongs to the forkhead family of transcription factors. In this study, we aimed to explore the expression profile of FOXF1 in papillary thyroid cancer (PTC) and corresponding adjacent normal tissues, by using data from The Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA) and The Genotype-Tissue Expression (GTEx) project. Also, we studied its prognostic significance in PTC and its potential regulatory network. Results showed that FOXF1 expression was significantly lower in PTC tissues compared with adjacent normal tissues. Subgroup analysis only confirmed the downregulation in classical histological variant, but not in tall-cell and follicular variants. FOXF1 downregulation was associated with advanced T stages, positive nodal invasion, and advanced pathological stages of the classical variants. FOXF1 expression might be a fair prognostic marker in terms of recurrence, which independently predicted favorable RFS (HR:0.114, 95%CI: 0.045-0.289, p < .001). We examined FOXF1 somatic mutations, gene-level copy number alterations (CNAs) and the methylation status of 57 CpG sites in more than 350 classical PTC cases. However, no expression-related genetic and epigenetic alterations were identified. Based on 20,048 genes with RNA-seq data, we identified 16 genes that showed strongly positive co-expression (Pearson's r ≥ 0.6) with FOXF1. Available evidence showed that some of the genes have well-characterized tumor suppressive effects. We hypothesized that some of these genes might be the upstream regulators or downstream effectors of FOXF1 in classical PTC. In conclusion, FOXF1 mRNA was typically downregulated in classical PTC. Its expression might be a specific and independent prognostic biomarker in terms of RFS in classical PTC patients.

Prediction of Recurrence in Cervical Cancer Using a Nine-lncRNA Signature

Background and Objective

As a common cancer type in women, cervical cancer remains one of the leading causes of cancer-associated mortalities word wide. Recent evidence has demonstrated the regulatory role of a large number of long non-coding RNAs (lncRNAs) in cervical cancer. Here, we aimed to identify new biomarkers that related with the recurrence through comprehensive bioinformatics analysis.

Methods

Firstly, we collected online lncRNA expression data of cervical cancer patients which were divided into training, validation, and test set. Then we developed a nine-lncRNA signature from training set by conducting LASSO Cox regression model along with 10-fold cross validation. The prognostic value of this risk score was validated in all the three sets using Kaplan–Meier analysis, C-index, time-dependent ROC curves and dynamic AUC. Biological function of these lncRNAs in cervical cancer cells were evaluated by performing gene ontology biological process enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathways analysis.

Results

According to the results, a higher predict accuracy was observed in the nine-lncRNA signature than that of FIGO stage in all the three sets. Stratified analysis also demonstrated that the nine-lncRNA signature can predict the recurrence of cervical cancer within FIGO stage. The potential mechanisms underlying the nine-lncRNAs from the signature were also identified according to the gene enrichment analysis.

Conclusion

In the present article, we provided a reliable prognostic tool to facilitate the individual management of patients with cervical cancer after treatment.

FMO1 gene expression independently predicts favorable recurrence-free survival of classical papillary thyroid cancer

Aim: To examine the expression profile of FMO1 in papillary thyroid cancer (PTC) and its prognostic value in recurrence-free survival (RFS). Methods: A retrospective analysis was performed using data from the Cancer Genome Atlas and Human Protein Atlas. Results: The most frequent variants of PTC had decreased FMO1 expression compared with their respective adjacent normal tissues. However, even under the best cut-off model, high FMO1 expression was only significantly associated with better RFS in classical PTC (p < 0.001), but not in other two variants. High FMO1 expression independently predicted favorable RFS (hazard ratio: 0.202; 95% CI: 0.084-0.487; p < 0.001) in classical PTC. Conclusion: High FMO1 expression might serve as a biomarker that independently predicts favorable RFS in classical PTC patients.