A nomogram combining long non-coding RNA expression profiles and clinical factors predicts survival in patients with bladder cancer

Long non-coding RNA GRASLND links melanoma differentiation and interferon-gamma response

Melanoma is a highly malignant tumor, that stands as the most lethal form of skin cancer and is characterized by notable phenotypic plasticity and intratumoral heterogeneity. Melanoma plasticity is involved in tumor growth, metastasis and therapy resistance. Long non-coding RNAs (lncRNAs) could influence plasticity due to their regulatory function. However, their role and mode of action are poorly studied. Here, we show a relevance of lncRNA GRASLND in melanoma differentiation and IFNγ signaling. GRASLND knockdown revealed switching of differentiated, melanocytic melanoma cells towards a dedifferentiated, slow-proliferating and highly-invasive cell state. Interestingly, GRASLND is overexpressed in differentiated melanomas and associated with poor prognosis. Accordingly, we found GRASLND expressed in immunological "cold" tumors and it negatively correlates with gene signatures of immune response activation. In line, silencing of GRASLND under IFNγ enhanced the expression of IFNγ-stimulated genes, including HLA-I antigen presentation, demonstrating suppressive activity of GRASLND on IFNγ signaling. Our findings demonstrate that in differentiated melanomas elevated expression of GRASLND interferes with anti-tumor effects of IFNγ, suggesting a role of GRASLND in tumor immune evasion.

The Role of Long Non-Coding RNF144A-AS1 in Cancer Progression

RNAs transcribing more than 200 nucleotides without encoding proteins are termed long non-coding RNAs (LncRNAs). LncRNAs can be used as decoy molecules, signal molecules, scaffolds, and guide molecules. Long non-coding RNAs can interact with DNA, chromatin-modifying complexes, and transcriptional regulatory proteins, regulating gene expression in the cell nucleus. It is distributed in cytoplasm; they also participate in mRNA degradation and translational regulation via miRNAs, other transcription products, and proteins. They play a significant role in the development of various diseases, including tumors. Cancer seriously threatens human life and health. Regretfully, a great deal of newly diagnosed cancer patients found to have metastasized. RNF144A-AS1, also referred to as GRASLND, was initially recognized for its regulation of chondrogenic differentiation in MSCs. Focusing on RNF144A-AS1, this review summarizes and discusses the latest progress of RNF144A-AS1 in bladder cancer, glioblastoma, papillary renal cell carcinoma, gastric cancer, osteosarcoma, head and neck squamous cell carcinoma, and ovarian cancer. RNF144A-AS1 has good potential in tumor treatment and diagnosis.

CircACTR2 promotes bladder cancer progression through IKBKB-mediated NF-κB signaling pathway activation

Background

Circular RNAs (circRNAs) have significant roles in tumor progression. The role of circRNA derived from ARP2 actin-related protein 2 homolog (circACTR2) has been reported in various human diseases. However, the functions and regulatory mechanisms of circACTR2 in Bladder Cancer (BCa) remain unknown.

Objectives

This study aims to explore the biological role and regulatory mechanism of circACTR2 in BCa.

Methods

We analyzed the effects of circACTR2 on BCa through bioinformatics analyses, RT-qPCR, and cell function assays.

Results

We observed the upregulation of circACTR2 in BCa tissues and validated its circular structure. Loss-of-function assays demonstrated that silencing circACTR2 suppressed the proliferation, invasion, and migration of BCa cells. Mechanistic investigation revealed that circACTR2 sponges miR-219a-2-3p to elevate the expression of the inhibitor of nuclear factor kappa B kinase subunit beta (IKBKB). This induced upregulation of IKKβ protein promoted the nuclear translocation of p65, thereby activating the NF-κB signaling pathway.

Conclusions

Our findings indicate that circACTR2 promotes BCa cell proliferation, migration, and invasion by activating the NF-κB signaling pathway via the miR-219a-2-3p/IKBKB axis, potentially unveiling a new therapeutic target for BCa.

Establishment and validation of a nomogram based on coagulation parameters to predict the prognosis of pancreatic cancer

BACKGROUND

In recent years, multiple coagulation and fibrinolysis (CF) indexes have been reported to be significantly related to the progression and prognosis of some cancers.

OBJECTIVE

The purpose of this study was to comprehensively analyze the value of CF parameters in prognosis prediction of pancreatic cancer (PC).

METHODS

The preoperative coagulation related data, clinicopathological information, and survival data of patients with pancreatic tumor were collected retrospectively. Mann Whitney U test, Kaplan-Meier analysis, and Cox proportional hazards regression model were applied to analyze the differences of coagulation indexes between benign and malignant tumors, as well as the roles of these indexes in PC prognosis prediction.

RESULTS

Compared with benign tumors, the preoperative levels of some traditional coagulation and fibrinolysis (TCF) indexes (such as TT, Fibrinogen, APTT, and D-dimer) were abnormally increased or decreased in patients with pancreatic cancer, as well as Thromboelastography (TEG) parameters (such as R, K, α Angle, MA, and CI). Kaplan Meier survival analysis based on resectable PC patients showed that the overall survival (OS) of patients with elevated α angle, MA, CI, PT, D-dimer, or decreased PDW was markedly shorter than other patients; moreover, patients with lower CI or PT have longer disease-free survival. Further univariate and multivariate analysis revealed that PT, D-dimer, PDW, vascular invasion (VI), and tumor size (TS) were independent risk factors for poor prognosis of PC. According to the results of modeling group and validation group, the nomogram model based on independent risk factors could effectively predict the postoperative survival of PC patients.

CONCLUSION

Many abnormal CF parameters were remarkably correlated with PC prognosis, including α Angle, MA, CI, PT, D-dimer, and PDW. Furthermore, only PT, D-dimer, and PDW were independent prognostic indicators for poor prognosis of PC, and the prognosis prediction model based on these indicators was an effective tool to predict the postoperative survival of PC.

Identification and validation of the pyroptosis-related long noncoding rna signature to predict the prognosis of patients with bladder cancer

Bladder cancer ranked the second most frequent tumor among urological malignancies. This work investigated bladder cancer prognosis, including the relevance of pyroptosis-related long noncoding RNA (lncRNA) in it and its potential roles. The Cancer Genome Atlas database offered statistics on lncRNAs and clinical data from 411 bladder cancer patients. Pearson correlation analysis was used to evaluate pyroptosis-related lncRNAs. To explore prognosis-associated lncRNAs, we performed univariate Cox regression, least absolute shrinkage and selection operator regression analyses, as well as the Kaplan-Meier method. Multivariate Cox analysis was leveraged to establish the risk score model. Afterward, a nomogram was constructed according to the risk score and clinical variables. Finally, to investigate the potential functions of pyroptosis-related lncRNAs, gene set enrichment analysis was employed. Eleven pyroptosis-related lncRNAs were screened to be closely associated with patients prognosis. On this foundation, a risk score model was created to classify patients into high and low risk groups. The signature was shown to be an independent prognostic factor (P < .001) with an area under the curve of 0.730. Then a nomogram was established including risk scores and clinical characteristics. The nomogram prediction effect is excellent, with a concordance index of 0.86. The 11-lncRNAs signature was associated with the supervision of oxidative stress, epithelial-mesenchymal transition, cell adhesion, TGF-β, and Wingless and INT-1 signaling pathway, according to the gene set enrichment analysis. Our findings indicate that pyroptosis-related lncRNAs, which may affect tumor pathogenesis in many ways, might be exploited to assess the prognosis of bladder cancer patients.

Nomograms for predicting the prognosis of patients with penoscrotal extramammary Paget’s disease: A retrospective study in the SEER database and two medical centers

Background

Extramammary Paget’ s disease (EMPD) is a rare cutaneous malignant tumor, and the prognostic factors associated with penoscrotal EMPD remains unclear. The purpose of this study is to investigate prognostic factors and construct nomograms to predict the outcome of patients with EMPD located in the penis or scrotum.

Methods

From the Surveillance, Epidemiology and End Results (SEER) database, we extracted 95 patients with primary EMPD located in the penis or scrotum as the training cohort. Forty-nine penoscrotal EMPD patients were included from two medical centers as the external validation cohort. Univariate and multivariate Cox regression model were applied to investigating risk factors of cancer-specific survival (CSS) and overall survival (OS). Based on the results of multivariate Cox regression analysis, the nomograms were constructed for predicting CSS and OS of patients with penoscrotal EMPD. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were applied to evaluate the practicability and accuracy of the nomograms.

Results

In the training cohort, multivariate Cox regression analysis showed that marital status and tumor stage were independent factors of CSS, and marital status, tumor stage and surgery are associated with OS independently in patients with penoscrotal EMPD. Based on these results, we developed nomograms to predict CSS and OS respectively. The C-index values were 0.778 for CSS, and 0.668 for OS in the training set, which displayed the good discriminations. In the external validation set, the C-index values were 0.945 for CSS, and 0.703 for OS. The areas under the curve (AUC) values of nomogram predicting 1-, 3-, and 5-year CSS were 0.815, 0.833, and 0.861 respectively, and 0.839, 0.654, and 0.667 for nomogram predicting 1-, 3-, and 5-year OS respectively. In the validation set, the AUC values of nomogram predicting 1-, 3-, and 5-year CSS were 0.944, 0.896, and 0.896 respectively, and 0.777, 0.762 and 0.692 for nomogram predicting 1-, 3-, and 5-year OS respectively. Additionally, the internal calibration curves also proved that our nomograms have good accuracy.

Conclusions

By incorporating marital status, tumor stage and/or surgery, our nomograms can efficiently predict CSS and OS of patients with penoscrotal EMPD.

Mortality prediction models after radical cystectomy for bladder tumour: A systematic review and critical appraisal

INTRODUCTION

To identify risk-predictive models for bladder-specific cancer mortality in patients undergoing radical cystectomy and assess their clinical utility and risk of bias.

METHODS

Systematic review (CRD42021224626:PROSPERO) in Medline and EMBASE (from their creation until 31/10/2021) was screened to include articles focused on the development and internal validation of a predictive model of specific cancer mortality in patients undergoing radical cystectomy. CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) and Prediction model Risk Of Bias ASsessment Tool (PROBAST) were applied.

RESULTS

Nineteen observational studies were included. The main predictors were sociodemographic variables, such as age (18 studies, 94.7%) and sex (17, 89.5% studies), tumour characteristics (TNM stage (18 studies, 94.7%), histological subtype/grade (15 studies, 78.9%), lymphovascular invasion (10 studies, 52.6%) and treatment with chemotherapy (13 studies, 68.4%). C-index values were presented in 14 studies. The overall risk of bias assessed using PROBAST led to 100% of studies being classified as high risk (the analysis domain was rated to be at high risk of bias in all the studies), and 52.6% showed low applicability. Only 5 studies (26.3%) included an external validation and 2 (10.5%) included a prospective study design.

CONCLUSIONS

Using clinical predictors to assess the risk of bladder-specific cancer mortality is a feasibility alternative. However, the studies showed a high risk of bias and their applicability is uncertain. Studies should improve the conducting and reporting, and subsequent external validation studies should be developed.

Positive feedback regulation of lncRNA TPT1-AS1 and ITGB3 promotes cell growth and metastasis in pancreatic cancer

Emerging evidence has indicated that long noncoding RNAs (lncRNAs) are potential biomarkers and play crucial roles in cancer development. However, the functions and underlying mechanisms of lncRNA TPT1-AS1 in pancreatic ductal adenocarcinoma (PDAC) remain elusive. RNAseq data of PDAC tissues and normal tissues were analyzed, and lncRNAs which were associated with PDAC prognosis were identified. The clinical relevance of TPT1-AS1 for PDAC patients was explored, and the effects of TPT1-AS1 in PDAC progression were investigated in vitro and in vivo. LncRNA TPT1-AS1 was highly expressed in PDAC, and high TPT1-AS1 levels predicted a poor prognosis. Moreover, functional experiments revealed that TPT1-AS1 promoted pancreatic cancer cell proliferation, migration, invasion, and epithelial-to-mesenchymal transition (EMT) process in vitro and in vivo. Mechanistically, TPT1-AS1 functioned as an endogenous sponge for miR-30a-5p, which increased integrin β3 (ITGB3) level in pancreatic cancer cells. Conversely, our data revealed that ITGB3 could activate the transcription factor signal transducer and activator of transcription 3 (STAT3), which in turn bound directly to the TPT1-AS1 promoter and affected the expression of TPT1-AS1, thus forming a positive feedback loop with TPT1-AS1. Taken together, our results uncovered a reciprocal loop of TPT1-AS1 and ITGB3 which contributed to pancreatic cancer growth and development, and indicated that TPT1-AS1 might serve as a novel potential diagnostic biomarker and therapeutic target for PDAC patients.

Nomograms predicting cancer-specific survival for stage IV colorectal cancer with synchronous lung metastases

This study aimed to establish a nomogram for the prediction of cancer-specific survival (CSS) of CRC patients with synchronous LM. The final prognostic nomogram based on prognostic factors was evaluated by concordance index (C-index), time-dependent receiver operating characteristic curves, and calibration curves. In the training and validation groups, the C-index for the nomogram was 0.648 and 0.638, and the AUC was 0.793 and 0.785, respectively. The high quality of the calibration curves in the nomogram models for CSS at 1-, 3-, and 5-year was observed. The nomogram model provided a conventional and useful tool to evaluate the 1-, 3-, and 5-year CSS of CRC patients with synchronous LM.

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.

A model for predicting the overall survival of gastroenteropancreatic neuroendocrine neoplasms after surgery

BACKGROUND

The increase in the incidence of gastroenteropancreatic neuroendocrine tumors (GEP-NENs) and refined morphological imaging techniques have led to a rise in the number of patients undergoing surgery. However, there is still a paucity of objective, clinically reliable and personalized tools to evaluate patient prognosis.

MATERIALS AND METHODS

We identified patients from the Surveillance, Epidemiology, and End Results (SEER) database who underwent surgery for GEP-NEN from 1975 to 2018. The predictors associated with OS were investigated by Multivariate Cox proportional hazards (PHs) regression analysis in the primary cohort; a prognostic nomogram was then built based on the multivariate analysis results. The performance of the nomogram was assessed by Harrell's concordance index (C-index) and calibration curve and compared with the eighth edition of the American Joint Committee on Cancer (AJCC) staging system.

RESULTS

A total of 45,889 patients were enrolled in our study; 32,321 were included in the primary cohort, and 13,568 were included in the validation cohort. A nomogram incorporating Age, Differentiation, M staging, and AJCC staging was subsequently built based on the multivariate analysis. The C-index (0.833 for the primary cohort and 0.845 for the validation cohort) and calibration curves indicated good discriminative ability and calibration of the nomogram. Further analysis demonstrated that the nomogram had superior discriminatory ability than the AJCC staging system (C-index= 0.706).

CONCLUSION

The proposed nomogram showed excellent prediction with good calibration and discrimination, which can be used to make well-informed and individualized clinical decisions regarding the clinical management of GEP-NENs.

Long noncoding RNA endogenous bornavirus-like nucleoprotein acts as an oncogene by regulating microRNA-655-3p expression in T-cell acute lymphoblastic leukemia

Acute lymphocytic leukemia (ALL) is the most common malignant tumor in children with T-cell ALL (T-ALL), accounting for approximately 15% of all cases. Long noncoding RNAs (lncRNAs) are involved in the pathogenesis and progression of T-ALL. The present study aimed to explore the role and mechanism of action of lncRNA EBLN3P in T-ALL. We used quantitative reverse transcription-PCR (qRT-PCR) to determine the expression of lncRNA endogenous bornavirus-like nucleoprotein (EBLN3P), microRNA (miR)-655-3p, and the transcription level of matrix metalloproteinase-9 (MMP-9), and Western blot assay to quantify the protein expression level of cleaved-caspase3, caspase3, proliferating cell nuclear antigen (PCNA), and MMP-9. The potential binding sites between lncRNA EBLN3P and miR-655-3p were predicted using StarBase, and the interaction was further verified by dual-luciferase reporter assay and RNA pull-down assay. The proliferation ability of Jurkat cells was detected using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay, and their invasion and migration ability using transwell assay. Cell apoptosis was determined using flow cytometry (FCM) assay. The expression of lncRNA EBLN3P was upregulated while that of miR-655-3p was downregulated in human T-ALL cell lines and lncRNA EBLN3P negatively regulated miR-655-3p. LncRNA EBLN3P knockdown significantly inhibited proliferation, invasion, and migration of Jurkat cells and induced their apoptosis. Downregulating miR-655-3p reversed the effects of lncRNA EBLN3P knockdown on Jurkat cells. In conclusion, we confirmed for the first time that lncRNA EBLN3P is dysregulated in T-ALL cell lines, and lncRNA EBLN3P knockdown inhibited the malignant biological behaviors of T-ALL cells by up-regulating miR-655-3p.

Development and validation of a novel nomogram for predicting survival rate in pancreatic neuroendocrine neoplasms

BACKGROUND

Over the past decades, the incidence and prevalence of pancreatic neuroendocrine neoplasms (pNENs) have steadily increased. However, accurate prediction of the prognosis and treatment of this condition are currently challenging. This study aims to develop and validate a personalized nomogram to predict the survival of patients with pNENs.

MATERIALS AND METHODS

A total of 9739 patients with pNENs were downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Subsequently, the patients were randomly assigned to a derivation cohort (n = 6874) and a validation cohort (n = 2865). The survival of patients was assessed using the Cox proportional hazards (PHs) regression analysis. Then, the nomogram that predicted 3-and 5-year survival rates were developed in the derivation cohort. Further, the predictive performance of the nomogram was evaluated through discrimination and calibration.

RESULTS

The Cox regression analysis revealed that age, differentiation, the extent of tumor, M staging, and surgery were independent prognostic predictors for pNENs. The nomogram showed superior discrimination capability than AJCC staging in both derived and validation cohorts (C-index: 0.874 versus 0.721 and 0.833 versus 0.721). The calibration curves showed that the practical and predicted survival rates effectively coincided, specifically for the 3-year survival rate.

CONCLUSION

Our nomogram is a valuable tool for the prediction of the survival rate for patients with pNENs; this may promote individualized prognostic evaluation and treatment.

A Novel Risk Signature with Seven Pyroptosis-Related Genes for Prognosis Prediction in Glioma

BACKGROUND

Increasing evidence indicates that pyroptosis is closely linked to the occurrence and progression of cancer. However, the expression and prognostic role of most pyroptosis-related genes in glioma have not been fully elucidated.

METHODS

Herein, we explored the expression profiles and prognostic value of 33 pyroptosis-related genes in glioma. LASSO regression analysis was then used to construct a risk signature to predict glioma outcomes in The Cancer Genome Atlas (TCGA) cohort. Furthermore, we constructed a nomogram based on independent prognostic factors and performed external validation. Finally, functional enrichment analysis was performed to explore the potential biological role of the pyroptosis-related signature in glioma.

RESULTS

The expression of most pyroptosis-related genes (31/33) was significantly different between normal brain and glioma tissue. By univariate Cox regression analysis, 24 genes were found to be significantly correlated with glioma overall survival (OS). Subsequently, we constructed a 7-gene risk signature in the TCGA training cohort, which demonstrated good performance in predicting glioma survival through multidatabase validation. Moreover, a nomogram was established based on independent prognostic factors (age, WHO grade, IDH status and signature) and confirmed to be more effective and accurate through internal evaluation and external validation. Finally, functional enrichment analyses suggested that the signature might be related to invasion ability and immune function.

CONCLUSIONS

The risk signature based on seven pyroptosis-related genes can effectively predict the clinical outcomes of glioma patients. Our study provides novel insights for further understanding the association between pyroptosis-related genes and glioma prognosis.

Identification of a Six-Gene Prognostic Signature Characterized by Tumor Microenvironment Immune Profiles in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is widely acknowledged to be extremely sensitive to immunotherapy, emphasizing the tremendous impacts on which the tumor microenvironment (TME) has shown. However, the molecular subgroups characterized by the TME features scarcely serve as the risk stratification guides in clinical practice for survival outcomes and immunotherapy response prediction. This study generated fresh insights into a novel TME-related prognostic signature derived from The Cancer Genome Atlas database using integrated bioinformatics analyses. Subsequently, Kaplan–Meier survival analysis, receiver operating characteristic analysis, and univariate and multivariate Cox regression analysis were performed to evaluate and validate the efficacy and the accuracy of the signature in ccRCC prognosis. Furthermore, we discovered that the risk score presented an increased likelihood of correlation with miscellaneous clinicopathological characteristics, natural killer cell-mediated cytotoxicity, immune cell infiltration levels, and immune checkpoint expression. These findings highlighted the notion that the six-gene signature characterized by the TME features may have implications on the risk stratification for personalized and precise immunotherapeutic management.

A novel risk signature with 6 RNA binding proteins for prognosis prediction in patients with glioblastoma

Recent studies suggested that RNA binding proteins (RBPs) were related to the tumorigenesis and progression of glioma. This study was conducted to identify prognostic RBPs of glioblastoma (GBM) and construct an RBP signature to predict the prognosis of GBM.Univariate Cox regression analysis was carried out to identify the RBPs associated with overall survival of GBM in the The Cancer Genome Atlas (TCGA), GSE16011, and Repository for Molecular Brain Neoplasia data (Rembrandt) datasets, respectively. Overlapping RBPs from the TCGA, GSE16011, and Rembrandt datasets were selected. The biological role of prognostic RBPs was assessed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses. Least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to construct an RBP-related risk signature. The prognostic value of RBP signature was measured by Kaplan-Meier method and time-dependent receiver operating characteristic curve. A nomogram based on independent prognostic factors was established to predict survival for GBM. The CGGA cohort was used as the validation cohort for external validation.This study identified 27 RBPs associated with the prognosis of GBM and constructed a 6-RPBs signature. Kaplan-Meier curves suggested that high-risk score was associated with a poor prognosis. Area under the curve of 1-, 3-, and 5-year overall survival was 0.618, 0.728, and 0.833 for TCGA cohort, 0.655, 0.909, and 0.911 for GSE16011 cohort, and 0.665, 0.792, and 0.781 for Rembrandt cohort, respectively. A nomogram with 4 parameters (age, chemotherapy, O6-methylguanine-DNA methyltransferase promoter status, and risk score) was constructed. The calibration curve showed that the nomogram prediction was in good agreement with the actual observation.The 6-RBPs signature could effectively predict the prognosis of GBM, and our findings supplemented the prognostic index of GBM to a certain extent.

A novel prognostic cancer-related lncRNA signature in papillary renal cell carcinoma

Background

Papillary renal cell carcinoma (pRCC) ranks second in renal cell carcinoma and the prognosis of pRCC remains poor. Here, we aimed to screen and identify a novel prognostic cancer-related lncRNA signature in pRCC.

Methods

The RNA-seq profile and clinical feature of pRCC cases were downloaded from TCGA database. Significant cancer-related lncRNAs were obtained from the Immlnc database. Differentially expressed cancer-related lncRNAs (DECRLs) in pRCC were screened for further analysis. Cox regression report was implemented to identify prognostic cancer-related lncRNAs and establish a prognostic risk model, and ROC curve analysis was used to evaluate its precision. The correlation between RP11-63A11.1 and clinical characteristics was further analyzed. Finally, the expression level and role of RP11-63A11.1 were studied in vitro.

Results

A total of 367 DECRLs were finally screened and 26 prognostic cancer-related lncRNAs were identified. Among them, ten lncRNAs (RP11-573D15.8, LINC01317, RNF144A-AS1, TFAP2A-AS1, LINC00702, GAS6-AS1, RP11-400K9.4, LUCAT1, RP11-63A11.1, and RP11-156L14.1) were independently associated with prognosis of pRCC. These ten lncRNAs were incorporated into a prognostic risk model. In accordance with the median value of the riskscore, pRCC cases were separated into high and low risk groups. Survival analysis indicated that there was a significant difference on overall survival (OS) rate between the two groups. The area under curve (AUC) in different years indicated that the model was of high efficiency in prognosis prediction. RP11-63A11.1 was mainly expressed in renal tissues and it correlated with the tumor stage, T, M, N classifications, OS, PFS, and DSS of pRCC patients. Consistent with the expression in pRCC tissue samples, RP11-63A11.1 was also down-regulated in pRCC cells. More importantly, up-regulation of RP11-63A11.1 attenuated cell survival and induced apoptosis.

Conclusions

Ten cancer-related lncRNAs were incorporated into a powerful model for prognosis evaluation. RP11-63A11.1 functioned as a cancer suppressor in pRCC and it might be a potential therapeutic target for treating pRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02247-6.

RNF144A-AS1, a TGF-β1- and hypoxia-inducible gene that promotes tumor metastasis and proliferation via targeting the miR-30c-2-3p/LOX axis in gastric cancer

Background

Although recent molecular analyses have improved our knowledge regarding gastric cancer (GC) biology, the molecular mechanisms that confer metastatic potential to GC remain poorly understood. In this study, we intend to explore the function and characterize the underlying mechanism of long noncoding RNA RNF144A-AS1 in GC metastasis and outgrowth.

Methods

The expression of RNF144A-AS1, miR-30c-2-3p, and Lysyl oxidase (LOX) was detected by quantitative real-time PCR assay. Fluorescence in situ hybridization and subcellular fractionation assay determined the cellular localization of RNF144A-AS1. Cell counting kit 8 assay, transwell assay, and tube formation assay were performed to detect the effect on cell proliferation, migration, invasion, and angiogenesis, respectively. Animal models were also applied to verify the effect on tumor metastasis, outgrowth, and angiogenesis. Bioinformatic analysis, luciferase reporter assay, and RNA immunoprecipitation (RIP) assay explored the interactions among RNF144A-AS1, miR-30c-2-3p, and LOX. Gene regulation was further validated by knockdown of Dicer or mutating the miRNA binding sites on RNF144A-AS1 and LOX 3ʹUTR. Cells were treated with recombinant human TGF-β1 (Transforming Growth Factor β1) to explore the effect of TGF-β1 on RNF144A-AS1. Western blot and immunohistochemistry were used to detect protein expression.

Results

The expression of RNF144A-AS1 was significantly upregulated in GC tissues and was associated with poor prognosis and later-stage diseases. Hypoxia stimulated the expression of RNF144A-AS1 in a HIF-1α-independent manner. Additionally, RNF144A-AS1 was also induced by TGF-β1. Loss and gain of function assays revealed that RNF144A-AS1 promoted tumor metastasis, angiogenesis, and proliferation. Mechanism exploration indicated RNF144A-AS1 served as a microRNA decoy of miR-30c-2-3p to release LOX. Gene Set Enrichment Analysis further suggested LOX and RNF144A-AS1 were enriched in the same gene sets, emphasizing the internal mechanism connection between these two genes.

Conclusions

TGF-β1- and hypoxia-inducible RNF144A-AS1 promoted tumor metastasis, angiogenesis, and proliferation through targeting the miR-30c-2-3p/LOX axis in GC, highlighting the value of the RNF144A-AS1/miR-30c-2-3p/LOX axis in therapeutic interventions of GC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-021-00689-z.

Development of Nomograms for Predicting Lymph Node Metastasis and Distant Metastasis in Newly Diagnosed T1-2 Non-Small Cell Lung Cancer: A Population-Based Analysis

Background

For different lymph node metastasis (LNM) and distant metastasis (DM), the diagnosis, treatment and prognosis of T1-2 non-small cell lung cancer (NSCLC) are different. It is essential to figure out the risk factors and establish prediction models related to LNM and DM.

Methods

Based on the surveillance, epidemiology, and end results (SEER) database from 1973 to 2015, a total of 43,156 eligible T1-2 NSCLC patients were enrolled in the retrospective study. Logistic regression analysis was used to determine the risk factors of LNM and DM. Risk factors were applied to construct the nomograms of LNM and DM. The predictive nomograms were discriminated against and evaluated by Concordance index (C-index) and calibration plots, respectively. Decision curve analysis (DCAs) was accepted to measure the clinical application of the nomogram. Cumulative incidence function (CIF) was performed further to detect the prognostic role of LNM and DM in NSCLC-specific death (NCSD).

Results

Eight factors (age at diagnosis, race, sex, histology, T-stage, marital status, tumor size, and grade) were significant in predicting LNM and nine factors (race, sex, histology, T-stage, N-stage, marital status, tumor size, grade, and laterality) were important in predicting DM(all, P< 0.05). The calibration curves displayed that the prediction nomograms were effective and discriminative, of which the C-index were 0.723 and 0.808. The DCAs and clinical impact curves exhibited that the prediction nomograms were clinically effective.

Conclusions

The newly constructed nomograms can objectively and accurately predict LNM and DM in patients suffering from T1-2 NSCLC, which may help clinicians make individual clinical decisions before clinical management.

Upregulation of 15 Antisense Long Non-Coding RNAs in Osteosarcoma

The human genome encodes thousands of natural antisense long noncoding RNAs (lncRNAs); they play the essential role in regulation of gene expression at multiple levels, including replication, transcription and translation. Dysregulation of antisense lncRNAs plays indispensable roles in numerous biological progress, such as tumour progression, metastasis and resistance to therapeutic agents. To date, there have been several studies analysing antisense lncRNAs expression profiles in cancer, but not enough to highlight the complexity of the disease. In this study, we investigated the expression patterns of antisense lncRNAs from osteosarcoma and healthy bone samples (24 tumour-16 bone samples) using RNA sequencing. We identified 15 antisense lncRNAs (RUSC1-AS1, TBX2-AS1, PTOV1-AS1, UBE2D3-AS1, ERCC8-AS1, ZMIZ1-AS1, RNF144A-AS1, RDH10-AS1, TRG-AS1, GSN-AS1, HMGA2-AS1, ZNF528-AS1, OTUD6B-AS1, COX10-AS1 and SLC16A1-AS1) that were upregulated in tumour samples compared to bone sample controls. Further, we performed real-time polymerase chain reaction (RT-qPCR) to validate the expressions of the antisense lncRNAs in 8 different osteosarcoma cell lines (SaOS-2, G-292, HOS, U2-OS, 143B, SJSA-1, MG-63, and MNNG/HOS) compared to hFOB (human osteoblast cell line). These differentially expressed IncRNAs can be considered biomarkers and potential therapeutic targets for osteosarcoma.

TINCR inhibits the proliferation and invasion of laryngeal squamous cell carcinoma by regulating miR-210/BTG2

Background

Terminal differentiation-induced ncRNA (TINCR) plays an essential role in epidermal differentiation and is involved in the development of various cancers.

Methods

qPCR was used to detect the expression level of TINCR in tissues and cell lines of laryngeal squamous cell carcinoma (LSCC). The potential targets of TINCR were predicted by the bioinformation website. The expression of miR-210 and BTG2 genes were detected by qPCR, and the protein levels of BTG2 and Ki-67 were evaluated by western blot. CCK-8 assay, scratch test, and transwell chamber were used to evaluate the proliferation, invasion, and metastasis ability of LSCC cells. The relationships among TINCR, miR-210, and BTG2 were investigated by bioinformatics software and luciferase reporter assay. The in vivo function of TINCR was accessed on survival rate and tumor growth in nude mice.

Results

We used qRT-PCR to detect the expression of TINCR in laryngeal squamous cell carcinoma (LSCC) tissues and cells and found significantly lower levels in cancer tissues compared with adjacent tissues. Additionally, patients with high TINCR expression had a better prognosis. TINCR overexpression was observed to inhibit the proliferation and invasion of LSCC cells. TINCR was shown to exert its antiproliferation and invasion effects by adsorbing miR-210, which significantly promoted the proliferation and invasion of laryngeal squamous cells. Overexpression of miR-210 was determined to reverse the tumour-suppressive effects of TINCR. BTG2 (anti-proliferation factor 2) was identified as the target gene of miR-210, and BTG2 overexpression inhibited the proliferation and invasion of LSCC cells. BTG2 knockdown relieved the inhibitory effects of TINCR on the proliferation and invasion of LSCC. Finally, TINCR upregulation slowed xenograft tumour growth in nude mice and significantly increased survival compared with control mice.

Conclusion

The results of this study suggest that TINCR inhibits the proliferation and invasion of LSCC by regulating the miR-210/BTG2 pathway, participates in cell cycle regulation, and may become a target for the treatment of LSCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08513-0.

Identification of a nomogram based on an 8-lncRNA signature as a novel diagnostic biomarker for childhood acute lymphoblastic leukemia

Childhood acute lymphoblastic leukemia (cALL) still represents a major cause of disease-related death in children. This study aimed to explore the prognostic value of long non-coding RNAs (lncRNAs) in cALL. We downloaded lncRNA expression profiles from the TARGET and GEO databases. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to identify lncRNA-based signatures. We identified an eight-lncRNA signature (LINC00630, HDAC2-AS2, LINC01278, AL356599.1, AC114490.1, AL132639.3, FUT8.AS1, and TTC28.AS1), which separated the patients into two groups with significantly different overall survival rates. A nomogram based on the signature, BCR ABL1 status and white blood cell count at diagnosis was developed and showed good accuracy for predicting the 3-, 5- and 7-year survival probability of cALL patients. The C-index values of the nomogram in the training and internal validation set reached 0.8 (95% CI, 0.757 to 0.843) and 0.806 (95% CI, 0.728 to 0.884), respectively. The nomogram proposed in this study objectively and accurately predicted the prognosis of cALL. In vitro experiments suggested that LINC01278 promoted the proliferation of leukemic cells and inhibited leukemic cell apoptosis by targeting the inhibition of miR-500b-3p in cALL, and LINC01278 may be a biological target for the treatment of cALL in the future.

Bioinformatics Profiling of Five Immune-Related lncRNAs for a Prognostic Model of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), one of the most common tumors worldwide, has the fifth highest mortality rate, which is increasing every year. At present, many studies have revealed that immunotherapy has an important effect on many malignant tumors. The main purpose of our research was to verify and establish a new immune-related lncRNA model and to explore the potential immune mechanisms. We analysed the pathways and mechanisms of immune-related lncRNAs by bioinformatics analysis, screened key lncRNAs based on Cox regression analysis, and determined the characteristics of the immune-related lncRNAs. On this basis, a predictive model was established. Through a comparison of specificity and sensitivity, we found that the constructed model was superior to the known markers of HCC. Then, the cell types were identified by the relative subgroup (CIBERSORT) algorithm for RNA transcripts. A signature model was eventually constructed, and we proved that it was a survival factor for HCC. Moreover, five kinds of immune cells were significantly positively correlated with the signature. The results indicated that these five kinds of lncRNAs may be related to the immune infiltration of hepatocellular carcinoma. To verify these findings, we selected the top coexpressed lncRNA, AC099850.3, for further study. We found that AC099850.3 could promote the migration and proliferation of hepatocellular carcinoma cells in vitro. RT-PCR experiments found that AC099850.3 could promote the expression of the cell cycle molecules BUB1, CDK1, PLK1, and TTK, and western blotting to prove that the expression of the molecules CD155 and PD-L1 was inhibited in the interference group. In conclusion, we used five kinds of immune-related lncRNAs to construct prognostic signatures to explore the mechanism, which provides a new way to study therapies for HCC.

Five long non-coding RNAs establish a prognostic nomogram and construct a competing endogenous RNA network in the progression of non-small cell lung cancer

BACKGROUND

Accumulating evidence has revealed that long non-coding RNAs (lncRNAs) play vital roles in the progression of non-small cell lung cancer (NSCLC). But the relationship between lncRNAs and survival outcome of NSCLC remains to be explored. Therefore, we attempt to figure out their survival roles and molecular connection in NSCLC.

METHODS

By analyzing the transcriptome profiling of NSCLC from TCGA databases, we divided patients into three groups, and identified differentially expressed lncRNAs (DELs) of each group. Next, we explored the prognostic roles of common DELs by univariate and multivariate Cox analysis, Lasson, and Kaplan-Meier analysis. Additionally, we assessed and compared the prognostic accuracy of 5 lncRNAs through ROC curves and AUC values. Ultimately, we detected their potential function by enrichment analysis and molecular connection through establishing a competing endogenous RNA (ceRNA) network.

RESULTS

One hundred ninety-seven common DELs were spotted. And we successfully screened out 5 lncRNAs related to the patient's survival, including LINC01833, AC112206.2, FAM83A-AS1, BANCR, and HOTAIR. Combing with age and AJCC stage, we constructed a nomogram that prognostic prediction was superior to the traditional parameters. Furthermore, 275 qualified mRNAs related to 5 lncRNAs were spotted. Functional analysis indicates that these lncRNAs act key roles in the progression of NSCLC, such as P53 and cell cycle signaling pathway. And ceRNA network also suggests that these lncRNAs are tightly connected with tumor progression.

CONCLUSIONS

A nomogram and ceRNA network based on 5 lncRNAs indicate that there can effectively predict the overall survival of NSCLC and potentially serve as a therapeutic guide for NSCLC.

Identification of crucial long non-coding RNAs and mRNAs along with related regulatory networks through microarray analysis in esophageal carcinoma

Esophageal carcinoma (EC) is a tremendous threat to human health and life worldwide. Long non-coding RNAs (lncRNAs) have been identified as crucial players in carcinomas including EC. An in-depth understanding on regulatory networks of lncRNAs contributes to the better management of EC. In this text, 2052 lncRNAs and 3240 mRNAs were found to be differentially expressed in 5 EC tumor tissues versus adjacent normal tissues by microarray analysis. Moreover, 297 carcinoma-related genes were screened out according to pathway and disease annotation analyses. In addition, 410 potential lncRNA-mRNA cis-regulation pairs and 395 lncRNA-mRNA trans-regulation pairs were screened out. Among these genes, 14 trans-regulated and 19 cis-regulated genes were found to be related with carcinomas. Additionally, 42 possible lncRNA-mRNA trans-regulation pairs and 26 cis-regulation pairs were found to be related with carcinomas. Also, 4 differentially expressed transcription factors in EC and lncRNAs possibly regulated by these transcription factors were screened out. Moreover, plenty of common upregulated or downregulated lncRNAs and mRNAs in EC were identified by comparative analysis for our microarray outcomes and previous high-throughput data. Furthermore, we demonstrated that ENST00000437781.1 knockdown inhibited cell proliferation and facilitated cell apoptosis by downregulating SIX homeobox 4 (SIX4) and ENST00000524987.1 knockdown had no influence on anoctamin 1 calcium activated chloride channel (ANO1) expression in EC cells. In conclusion, we identified some crucial lncRNAs and genes along with potential regulatory networks of lncRNAs/genes, deepening our understanding on pathogenesis of EC.

Identification of a ten-long noncoding RNA signature for predicting the survival and immune status of patients with bladder urothelial carcinoma based on the GEO database: a superior machine learning model

Bladder urothelial carcinoma (BLCA) is recognized to be immunogenic and tumorigenic. This study identified a novel long noncoding RNA (lncRNA) signature for predicting survival for patients with BLCA. A univariate Cox regression model and the random survival forest-variable hunting (RSF-VH) algorithm were employed to achieve variable selection. Ten lncRNAs (LOC105375787, CYTOR, URB1-AS1, C21orf91-OT1, CASC15, LOC101928433, FLJ45139, LINC00960, HOTAIR and TTTY19) with the highest prognostic values were identified to establish the prognostic model. The nomogram integrating the signature and clinical factors showed high concordance index values of 0.94, 0.7 and 0.90 in the three datasets, and the calibration curves showed concordance between the predicted and observed 3- and 5-year survival rates. The risk score based on the 10-lncRNA signature accurately distinguished high- and low-risk BLCA patients with different disease-specific survival(DSS) or overall survival(OS) outcomes, which were stratified according to clinical factors, including T stage and tumour grade. Gene set enrichment analysis identified BLCA-specific biological pathways and enriched functional categories, such as the cell cycle, DNA repair and immune system. Furthermore, the increased infiltration of immune cells in the high-risk group indicated that lncRNA-related inflammation may reduce the survival of BLCA patients.

Identification of a novel immune microenvironment signature predicting survival and therapeutic options for bladder cancer

Few studies have investigated the potential of tumor immune microenvironment genes as indicators of urinary bladder cancer. Here, we sought to establish an immune-related gene signature for determining prognosis and treatment options. We developed a ten-gene tumor immune microenvironment signature and evaluated its prognostic capacity on internal and external cohorts. Multivariate Cox regression and nomogram analyses revealed the prognostic risk model as an independent and effective indicator of prognosis. We observed lower proportions of CD8+ T cells, dendritic cells, regulatory T cells, higher proportions of macrophages and neutrophils in high UBC risk group. UBC tissues with high-risk score tend to exhibit high TP53 and RB1 mutation rates, high PD1/PD-L1 expression and poor-survival basal squamous subtypes, while those with low-risk score tend to have high FGFR3 mutation rates and luminal papillary subtypes. Unexpectedly, we found a highly significant positive correlation between glycolytic genes and risk score, highlighting metabolic competition in tumor ecosystem and potential therapeutic avenues. Our study thus revealed a tumor immune microenvironment signature for predicting prognostic and response to immune checkpoint inhibitors against bladder cancer. Prospective studies are required to further test the predictive capacity of this model.

Identification of immune-related LncRNA for predicting prognosis and immunotherapeutic response in bladder cancer

Long noncoding RNAs (lncRNAs) have multiple functions in the cancer immunity response and the tumor microenvironment. To investigate the immune-related lncRNA (IRlncRNA) signature for predicting prognosis and immunotherapeutic response in bladder cancer (BLCA), we extracted BLCA data from The Cancer Genome Atlas (TCGA) database. Finally, a total of 405 cases were enrolled and 8 prognostic IRlncRNAs (MIR181A2HG, AC114730.3, LINC00892, PTPRD-AS1, LINC01013, MRPL23-AS1,LINC01395, AC002454.1) were identified in the training set. Risk scores were calculated to divide patients into high-risk and low-risk groups, and the high-risk patients tended to have a poor overall survival (OS). Multivariate Cox regression analysis confirmed that the IRlncRNA signature could be an independent prognostic factor. The results were subsequently confirmed in the validating set. Additionally, this 8-IRlncRNA classifier was related to recurrence free survival (RFS) of BLCA. Functional characterization revealed this signature mediated immune-related phenotype. This signature was also associated with immune cell infiltration (i.e., macrophages M0, M2, Tregs, CD8 T cells, and neutrophils) and immune checkpoint inhibitors (ICIs) immunotherapy-related biomarkers [mismatch repair (MMR) genes, tumor mutation burden (TMB) and immune checkpoint genes]. The present study highlighted the value of the 8-IRlncRNA signature as a predictor of prognosis and immunotherapeutic response in BLCA.

LncRNA RNF144A-AS1 Promotes Bladder Cancer Progression via RNF144A-AS1/miR-455-5p/SOX11 Axis

Background

Bladder cancer (BC) is the most commonly occurring malignant tumor of the urinary system worldwide. Long non-coding RNAs (lncRNAs), including lncRNA RNF144A-AS1 (RNF144A-AS1), perform an oncogenic role in BC progression. However, how RNF144A-AS1 is regulated in BC has not been fully investigated, and its role in BC is mostly obscure. In this study, we explore its role in BC progression.

Materials and Methods

The expression level of RNF144A-AS1 in BC tissues was explored via bioinformatics analysis and quantitative real-time PCR (qRT-PCR). We used RNF144A-AS1 siRNA (si-RNF144A-AS1) to inhibit the RNF144A-AS1 level in BC cell lines (J82 and 5637 cells). A series of experimental studies in vitro (CCK-8 assay, colony formation assay and Transwell assay) was performed to explore the role of si-RNF144A-AS1 on the proliferation, migration and invasion of J82 and 5637 cells. A BC xenograft model was established, and the effect of si-RNF144A-AS1 on xenograft growth was explored in vivo. The interactions among RNF144A-AS1, miR-455-5p and SOX11 were predicted by bioinformatics miRanda and Targetscan database, and verified by the luciferase reporter assay and RNA pull-down assay. Finally, miR-455-5p inhibitor and si-RNF144A-AS1 were cotransfected into J82 and 5637 cells.

Results

RNF144A-AS1 is overexpressed in BC tumors and cells, and its overexpression is correlated with poor prognosis. Knockdown of RNF144A-AS1 markedly suppressed the proliferation, migration and invasion of J82 and 5637 cells and significantly inhibited xenograft growth in nude mice, compared to si-NC. We found that RNF144A-AS1 serves as a sponge for miR-455-5p. Furthermore, a binding site of miR-455-5p was found in 3ʹ UTR of SOX11 gene, and overexpression of miR-455-5p suppressed SOX11 levels. RNF144A-AS1 knockdown markedly decreased SOX11 expression levels, while miR-455-5p inhibitor restored this repressive effect. Restoration of SOX11 could reverse this repressive effect of RNF144A-AS1 on cell proliferation, migration and invasion abilities.

Conclusion

Overall, our findings underline the critical role of RNF144A-AS1 in BC development, and our study reveals for the first time that RNF144A-AS1 promotes BC progression via the RNF144A-AS1/miR-455-5p/SOX11 axis.

Identification of a nomogram based on an 8-lncRNA signature as a novel diagnostic biomarker for head and neck squamous cell carcinoma

Long noncoding RNAs (lncRNAs) have been proposed as diagnostic or prognostic biomarkers of head and neck squamous carcinoma (HNSCC). The current study aimed to develop a lncRNA-based prognostic nomogram for HNSCC. LncRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. After the reannotation of lncRNAs, the differential analysis identified 253 significantly differentially expressed lncRNAs in training set TCGA-HNSC (n = 300). The prognostic value of each lncRNA was first estimated in univariate Cox analysis, and 41 lncRNAs with P < 0.05 were selected as seed lncRNAs for Cox LASSO regression, which identified 11 lncRNAs. Multivariate Cox analysis was used to establish an 8-lncRNA signature with prognostic value. Patients in the high-signature score group exhibited a significantly worse overall survival (OS) than those in the low-signature score group, and the area under the receiver operating characteristic (ROC) curve for 3-year survival was 0.74. Multivariable Cox regression analysis among the clinical characteristics and signature scores suggested that the signature is an independent prognostic factor. The internal validation cohort, external validation cohort, and 102 HNSCC specimens quantified by qRT-PCR successfully validate the robustness of our nomogram.

Identification of the Six-RNA-Binding Protein Signature for Prognosis Prediction in Bladder Cancer

RNA-binding proteins (RBPs) are a kind of gene regulatory factor that presents a significant biological effect in the initiation and development of various tumors, including bladder cancer (BLCA). However, the RBP-based prognosis signature for BLCA has not been investigated. In this study, we attempted to develop an RBP-based classifier to predict overall survival (OS) for BLCA based on transcriptome analysis. We extracted data of BLCA patients from The Cancer Genome Atlas database (TCGA) and UCSC Xena. Finally, a total of 398 cases without missing clinical data were enrolled and six RBPs (FLNA, HSPG2, AHNAK, FASTKD3, POU5F1, and PCSK9) associated with OS of BLCA were identified through univariate and multivariate Cox regression analysis. Online analyses and immunohistochemistry validated the prognostic value and expression of six RBPs. Risk scores were calculated to divide patients into high-risk and low-risk level, and patients in the high-risk group tended to have a poor prognosis. In addition, the receiver operating characteristic (ROC) curve analysis was performed to assess the prognostic value of RBPs, and the area under the curve (AUC) values were 0.711 and 0.706, respectively, in the training set and validating set. The findings were further validated in an external validation set. Subsequently, the 6-RBP-based signature and pathological stage were used to construct the nomogram to predict the 3- and 5-years OS of BLCA patients. Also, this 6-RBP-based signature was highly related to recurrence-free survival of BLCA. Weighted co-expression network analysis (WGCNA) combined with functional enrichment analysis contributed to study the potential pathways of six RBPs, including keratinocyte differentiation, RHO GTPases activate PNKs, epithelial tube morphogenesis, establishment or maintenance of cell polarity, and so on. In summary, the 6-RBP-based signature holds the potentiality to serve as a novel prognostic predictor of OS for BLCA.

Long Non-Coding RNA NEAT1 Promotes the Proliferation, Migration, and Metastasis of Human Breast-Cancer Cells by Inhibiting miR-146b-5p Expression

Background

Breast cancer (BC) is the most commonly diagnosed cancer in women. Tumor recurrence and metastasis are the key causes of death in BC patients. Long non-coding RNA (lncRNA) is closely associated with BC progression. lncRNA nuclear-enriched abundant transcript (NEAT)1 has been reported to regulate the proliferation and mobility of several types of cancer cells. However, how lncRNA NEAT1 affects the proliferation and invasion of BC cells is not known.

Methods

Quantitative real time-polymerase chain reaction (qRT-PCR) was used to measure expression of lncRNA NEAT1 and microRNA (miR)-146b-5p in BC tissues and cell lines. Cell Counting Kit (CCK)-8, cell colony-formation, wound-healing, and Transwell™ assays were undertaken to determine the effects of lncRNA NEAT1 and miR-146b-5p on progression of BC cells. The interaction between lncRNA NEAT1 and miR-146b-5p was examined by luciferase reporter, RNA-binding protein immunoprecipitation (RIP), and RNA-pulldown assays.

Results

Expression of lncRNA NEAT1 was upregulated in BC tissues and cell lines. High expression of lncRNA NEAT1 predicted poor overall survival in BC patients. Silencing of expression of lncRNA NEAT1 inhibited epithelial–mesenchymal transition (EMT) and suppressed the proliferation, migration and invasion of BC cells. Ectopic expression of lncRNA NEAT1 induced EMT and promoted BC progression. Mechanistic investigations revealed that miR-146b-5p was a direct target of lncRNA NEAT1, and its expression was correlated negatively with expression of lncRNA NEAT1 in BC tissues.

Conclusion

lncRNA NEAT1 could (i) serve as a novel prognostic marker for BC and (ii) be a potential therapeutic target for BC.

Long Noncoding RNA CAR10 Contributes to Melanoma Progression By Suppressing miR-125b-5p to Induce RAB3D Expression

Background

Melanoma is a very malignant skin cancer with high mortality and unsatisfactory prognosis. Many long noncoding RNAs (lncRNAs) have been reported to be aberrantly expressed in melanoma. How lncRNA regulates melanoma progression is poorly defined. LncRNA CAR10 has been shown to regulate the progression of several cancers and its role in melanoma remains unclear. This study aims to determine the role and mechanism of lncRNA CAR10 in the regulation of melanoma progression.

Methods

qRT-PCR was utilized to analyze CAR10 in melanoma human tissues and cell lines while Kaplan–Meier curve was used to examine the survival rate. CCK8 assay and EdU assay were used to assess cell proliferation when Transwell assay was conducted to determine migration and invasion. And tumor xenograft assay was performed to evaluate tumor growth in vivo. Additionally, luciferase assay and RNA pulldown assay were performed to analyze the interactions among CAR10, miR-125b-5p and RAB3D.

Results

LncRNA CAR10 was upregulated in melanoma tissues and cell lines. Upregulation of CAR10 predicted a poor prognosis in patients with melanoma. CAR10 knockdown suppressed proliferation, migration and invasion of melanoma cells in vitro. CAR10 silencing attenuated tumor growth in vivo. CAR10 inhibited miR-125b-5p activity to upregulate RAB3D expression. And miR-125b-5p/RAB3D signaling is crucial for CAR10-dependent melanoma progression.

Conclusion

Our work suggests that lncRNA CAR10 promotes melanoma growth and metastasis through modulating miR-125b-5p/RAB3D axis.