Downregulation of enhancer RNA EMX2OS is associated with poor prognosis in kidney renal clear cell carcinoma

Exosome-related lncRNA score: A value-based individual treatment strategy for predicting the response to immunotherapy in clear cell renal cell carcinoma

BACKGROUND

Exosomes play a crucial role in intercellular communication in clear cell renal cell carcinoma (ccRCC), while the long non-coding RNAs (lncRNAs) are implicated in tumorigenesis and progression.

AIMS

The purpose of this study is to construction a exosomes-related lncRNA score and a ceRNA network to predict the response to immunotherapy and potential targeted drug in ccRCC.

METHODS

Data of ccRCC patients were obtained from the TCGA database. Pearson correlation analysis was used to identify eExosomes-related lncRNAs (ERLRs) from Top10 exosomes-related genes that have been screened. The entire cohort was randomly divided into a training cohort and a validation cohort in equal scale. LASSO regression and multivariate cox regression was used to construct the ERLRs-based score. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and drug susceptibility between the high- and low-risk groups were also investigated. Finally, the relevant ceRNA network was constructed by machine learning to analyze their potential targets in immunotherapy and drug use of ccRCC patients.

RESULTS

A score consisting of 4ERLRs was identified, and patients with higher ERLRs-based score tended to have a worse prognosis than those with lower ERLRs-based score. ROC curves and multivariate Cox regression analysis demonstrated that the score could be considered as a risk factor for prognosis in both training and validation cohorts. Moreover, patients with high scores are predisposed to experience poor overall survival, a larger prevalence of advanced stage (III-IV), a greater tumor mutational burden, a higher infiltration of immunosuppressive cells, and a greater likelihood of responding favorably to immunotherapy. The importance of EMX2OS was determined by mechanical learning, and the ceRNA network was constructed, and EMX2OS may be a potential therapeutic target, possibly exerting its function through the EMX2OS/hsa-miR-31-5p/TLN2 axis.

CONCLUSIONS

Based on machine learning, a novel ERLRs-based score was constructed for predicting the survival of ccRCC patients. The ERLRs-based score is a promising potential independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics. Meanwhile, we screened out key lncRNAEMX2OS and identified the EMX2OS/hsa-miR-31-5p/TLN2 axis, which may provide new clues for the targeted therapy of ccRCC.

Genes Selectively Expressed in Rat Organs

Background

Understanding organic functions at a molecular level is important for scientists to unveil the disease mechanism and to develop diagnostic or therapeutic methods.

Aims

The present study tried to find genes selectively expressed in 11 rat organs, including the adrenal gland, brain, colon, duodenum, heart, ileum, kidney, liver, lung, spleen, and stomach.

Materials and Methods

Three normal male Sprague-Dawley (SD) rats were anesthetized, their organs mentioned above were harvested, and RNA in the fresh organs was extracted. Purified RNA was reversely transcribed and sequenced using the Solexa high-throughput sequencing technique. The abundance of a gene was measured by the expected value of fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM). Genes in organs with the highest expression level were sought out and compared with their median value in organs. If a gene in the highest expressed organ was significantly different (p < 0.05) from that in the medianly expressed organ, accompanied by q value < 0.05, and accounted for more than 70% of the total abundance, the gene was assumed as the selective gene in the organ.

Results & Discussion

The Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) pathways were enriched by the highest expressed genes. Based on the criterion, 1,406 selective genes were screened out, 1,283 of which were described in the gene bank and 123 of which were waiting to be described. KEGG and GO pathways in the organs were partly confirmed by the known understandings and a good portion of the pathways needed further investigation.

Conclusion

The novel selective genes and organic functional pathways are useful for scientists to unveil the mechanisms of the organs at the molecular level, and the selective genes' products are candidate disease markers for organs.

Identification of enhancer RNA AC005515.1 as a novel biomarker for prognosis in esophageal cancer and predictors of immunotherapy response

Background

The enhancer RNA (eRNA) signature shows excellent promise in the prognostic role of many malignancies, but its value has not been fully explored in esophageal cancer (ESCA).

Methods

We comprehensively analyzed 33 oncogene expression matrices and clinical data from The Cancer Genome Atlas (TCGA) and identified ESCA prognostic-related key eRNAs by Kaplan-Meier and co-expression analysis. We also investigated the prognostic role of the key eRNA using a series of bioinformatics approaches, including immune infiltration, immune function, immune subtypes, and the tumor microenvironment. Finally, the tumor immune dysfunction and exclusion (TIDE) score was used to predict the immune response to immune checkpoint blockade (ICB) therapy.

Results

We identified eRNA AC005515.1, AC012368.1, AP003469.2, Clorf61, and WDFY3-AS2 were associated with the prognosis of ESCA. AC005515.1 is a critical prognostic-related eRNA in ESCA and was significantly co-expressed with immune checkpoint genes (CTLA4, CD274, etc.). In the pan-cancer analysis, AC005515.1 was also associated with the prognosis of seven cancers, including kidney renal papillary cell carcinoma and low-grade brain glioma. It was also found to be co-expressed with immune checkpoint genes in these tumors. Moreover, high expression of AC005515.1 was associated with CD8+ T cells and M1 macrophages infiltration, and the AC005515.1 high-expression group had a higher TIDE score in ESCA.

Conclusions

Overall, eRNA AC005515.1 is associated with the local immune environment of ESCA and may become a new biomarker of ESCA prognosis and immunotherapy response.

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.

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.

Emerging Role of Enhancer RNAs as Potential Diagnostic and Prognostic Biomarkers in Cancer

Enhancers are distal cis-acting elements that are commonly recognized to regulate gene expression via cooperation with promoters. Along with regulating gene expression, enhancers can be transcribed and generate a class of non-coding RNAs called enhancer RNAs (eRNAs). The current discovery of abundant tissue-specific transcription of enhancers in various diseases such as cancers raises questions about the potential role of eRNAs in disease diagnosis and therapy. This review aimed to demonstrate the current understanding of eRNAs in cancer research with a focus on the potential roles of eRNAs as prognostic and diagnostic biomarkers in cancers.

Construction and Characterization of n6-Methyladenosine-Related lncRNA Prognostic Signature and Immune Cell Infiltration in Kidney Renal Clear Cell Carcinoma

Background. Kidney renal clear cell carcinoma (KIRC) lacks effective prognostic biomarkers and the role and mechanism of N6-methyladenosine (m6A) modification of long noncoding RNAs (lncRNAs) in KIRC remain unclear. Methods. We extracted standard mRNA-sequencing and clinical data from the TCGA database. The prognostic risk model was obtained by Lasso regression and Cox regression. We randomly divided the samples into training and test sets, each taking half of the cases. Based on Lasso regression and Cox regression for training set, the prognostic risk signature was constructed; risk scores were calculated with the R package “glmnet.” Based on the median value of the prognostic risk score, risk scores were calculated for each patient and we divided all KIRC samples into high-risk and low-risk groups. Then, high- and low-risk subtypes were established and their prognosis, clinical features, and immune infiltration microenvironment were evaluated in test set and the entire sampled data set. The reliability of the prognostic model was confirmed by receiver operating characteristic curve analysis. Results. We found 28 prognostic m6A-related lncRNAs and established a m6A-related lncRNAs prognostic signature. $\text{Risk\hspace{0.17em}score}=AC015813.1\ast \left(0.0086\right)+EMX2OS\ast \left(-0.0101\right)+LINC00173\ast \left(0.0309\right)+PWAR5\ast \left(-0.0146\right)+SNHG1\ast \left(0.0043\right).$ The signature showed a better predictive ability than other clinical indicators, including tumor node metastasis classification (TNM), histological, and pathological stages. In the high-risk group, M0 macrophages, CD8+ T cells, and regulatory T cells had significantly higher scores. Contrarily, in the low-risk group, activated dendritic cells, M1 macrophages, mast resting cells, and monocytes had significantly higher scores. In the high-risk group, LSECtin was overexpressed. In the low-risk group, PD-L1 was overexpressed. Moreover, high-risk patients may benefit more from AZ628. Conclusions. In conclusion, prognosis prediction of patients with KIRC and new insights for immunotherapy are provided by the m6A-related lncRNA prognostic signature.

RNA-Seq Analysis of UPM-Exposed Epithelium Co-Cultivated with Macrophages and Dendritic Cells in Obstructive Lung Diseases

Background. Elevated concentrations of airborne pollutants are correlated with an enlarged rate of obstructive lung disease morbidity as well as acute disease exacerbations. This study aimed to analyze the epithelium mRNA profile in response to airborne particulate matter in the control, asthma, and COPD groups. Results. A triple co-culture of nasal epithelium, monocyte-derived macrophages, and monocyte-derived dendritic cells obtained from the controls, asthma, and COPD were exposed to urban particulate matter (UPM) for 24 h. RNA-Seq analysis found differences in seven (CYP1B1, CYP1B1-AS1, NCF1, ME1, LINC02029, BPIFA2, EEF1A2), five (CYP1B1, ARC, ENPEP, RASD1, CYP1B1-AS1), and six (CYP1B1, CYP1B1-AS1, IRF4, ATP1B2, TIPARP, CCL22) differentially expressed genes between UPM exposed and unexposed triple co-cultured epithelium in the control, asthma, and COPD groups, respectively. PCR analysis showed that mRNA expression of BPIFA2 and ENPEP was upregulated in both asthma and COPD, while the expression of CYP1B1-AS1 and TIPARP was increased in the epithelium from COPD patients only. Biological processes changed in UPM exposed triple co-cultured epithelium were associated with epidermis development and epidermal cell differentiation in asthma and with response to toxic substances in COPD. Conclusions. The biochemical processes associated with pathophysiology of asthma and COPD impairs the airway epithelial response to UPM.

Identification of prognostic candidate signatures by systematically revealing transcriptome characteristics in lung adenocarcinoma with differing tumor microenvironment immune phenotypes

Accumulated evidence shows that tumor microenvironment plays crucial roles in predicting clinical outcomes of lung adenocarcinoma (LUAD). The current study aimed to identify some potentially prognostic signatures by systematically revealing the transcriptome characteristics in LUADs with differing immune phenotypes. LUAD gene expression data were retrieved from the public TCGA and GEO databases, and the transcriptome characteristics were systematically revealed using a comprehensive bioinformatics method including single-sample gene set enrichment analysis, differentially expressed gene (DEG) analysis, protein and protein interaction (PPI) network construction, competitive endogenous RNA (ceRNA) network construction, weighted gene coexpression network analysis and prognostic model establishment. Finally, 1169 key DEGs associated with LUAD immune phenotype, including 88 immune DEGs, were excavated. Five essential and eight immune essential DEGs were separately identified by constructing two PPI networks based on the above DEGs. Totals of 1085 key DElncRNAs and 45 key DEmiRNAs were excavated and one ceRNA network consisting of 26 DEmRNAs, 3 DEmiRNAs and 57 DElncRNAs were established. The most significant gene coexpression module (cor=0.63 and p=3e-55) associated with LUAD immune phenotypes and three genes (FGR, BTK, SPI1) related to the immune cell infiltration were identified. Three robust prognostic signatures including a 9-lncRNA, an 8-lncRNA and an 8-mRNA were established. The areas under the curves of 5-year correlated with overall survival rate were separately 0.7319, 0.7228 and 0.713 in the receiver operating characteristic curve. The findings provide novel insights into the immunological mechanism in LUAD biology and in predicting the prognosis of LUAD patients.

Prognostic significance of AP-2α/γ targets as cancer therapeutics

Identifying genes with prognostic importance could improve cancer treatment. An increasing number of reports suggest the existence of successful strategies based on seemingly "untargetable" transcription factors. In addition to embryogenesis, AP-2 transcription factors are known to play crucial roles in cancer development. Members of this family can be used as prognostic factors in oncological patients, and AP-2α/γ transcription factors were previously investigated in our pan-cancer comparative study using their target genes. The present study investigates tumors that were previously found similar with an emphasis on the possible role of AP-2 factors in specific cancer types. The RData workspace was loaded back to R environment and 3D trajectories were built via Monocle3. The genes that met the requirement of specificity were listed using top_markers(), separately for mutual and unique targets. Furthermore, the candidate genes had to meet the following requirements: correlation with AP-2 factor (through Correlation AnalyzeR) and validated prognostic importance (using GEPIA2 and subsequently KM-plotter or LOGpc). Eventually, the ROC analysis was applied to confirm their predictive value; co-dependence of expression was visualized via BoxPlotR. Some similar tumors were differentiated by AP-2α/γ targets with prognostic value. Requirements were met by only fifteen genes (EMX2, COL7A1, GRIA1, KRT1, KRT14, SLC12A5, SEZ6L, PTPRN, SCG5, DPP6, NTSR1, ARX, COL4A3, PPEF1 and TMEM59L); of these, the last four were excluded based on ROC curves. All the above genes were confronted with the literature, with an emphasis on the possible role played by AP-2 factors in specific cancers. Following ROC analysis, the genes were verified using immunohistochemistry data and progression-related signatures. Staining differences were observed, as well as co-dependence on the expression of e.g. CTNNB1, ERBB2, KRAS, SMAD4, EGFR or MKI67. In conclusion, prognostic value of targets suggested AP-2α/γ as candidates for novel cancer treatment. It was also revealed that AP-2 targets are related to tumor progression and that some mutual target genes could be inversely regulated.

Comprehensive Analysis of Enhancer RNAs Identifies LINC00689 and ELFN1-AS1 as Novel Prognostic Biomarkers in Uveal Melanoma

Enhancer RNAs (eRNAs) have emerged as key players in the pathology of several tumors, including uveal melanoma. Here, we aimed to explore the prognostic values of eRNAs in uveal melanoma (UVM) patients. The expressing data and survival data of UVM patients were downloaded from TCGA and GSE22138 datasets. The Kaplan-Meier methods with the log-rank test were applied to screen survival-related eRNAs in UVM. GEPIA was applied to analyze the associations between expressions of eRNA and disease-free survival. KEGG assays were applied to explore the potential signaling pathways of the key eRNA. The prognostic values of eRNAs were further explored by multivariate assays by the R package survival. The eRNAs were validated in pan-cancer. In this study, we identified 89 survival-related eRNAs in UVM based on TCGA datasets. Based on GSE22138 datasets, we found 27 survival-related eRNAs in UVM. Only two eRNAs (LINC00689 and ELFN1-AS1) were overlapped in both two datasets. The results of multivariate analysis revealed that both LINC00689 and ELFN1-AS1 were independent prognostic factors in UVM patients. The pan-cancer validation results further confirmed the prognostic values of LINC00689 and ELFN1-AS1 in eight tumors. Overall, we identified two novel UVM-related eRNAs, LINC00689 and ELFN1-AS1 which may serve as prognostic and diagnostic biomarkers of UVM patients for clinical decision-making.

Function and transcriptional regulation of TCTN1 in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most common types of head and neck squamous cell carcinoma (HNSCC) with a poor survival rate. In the present study, the involvement of tectonic 1 (TCTN1) in OSCC was explored. The relevance between TCTN1 and HNSCC clinicopathological features was first analyzed and it was revealed that TCTN1 was associated with the tumor clinical stage and grade. In in vitro experiments, it was demonstrated that the proliferative, migratory and invasive capacity of OSCC CAL27 cells and SCC15 cells was significantly suppressed due to TCTN1 knockdown. Additionally, the core promoter of TCTN1 was confirmed and transcription factor AP-2 alpha (TFAP2A) was suggested as a regulator of TCTN1 mRNA expression. On the whole, the present study elucidated the direct association between TCTN1 and OSCC for the first time, to the best of our knowledge, and the TFAP2A/TCTN1 axis was suggested as a potential novel therapeutic target for OSCC.

Deep analysis of neuroblastoma core regulatory circuitries using online databases and integrated bioinformatics shows their pan-cancer roles as prognostic predictors

AIM

Neuroblastoma is a heterogeneous childhood cancer derived from the neural crest. The dual cell identities of neuroblastoma include Mesenchymal (MES) and Adrenergic (ADRN). These identities are conferred by a small set of tightly-regulated transcription factors (TFs) binding super enhancers, collectively forming core regulatory circuitries (CRCs). The purpose of this study was to gain a deep understanding of the role of MES and ADRN TFs in neuroblastoma and other cancers as potential indicators of disease prognosis, progression, and relapse.

METHODS

To that end, we first investigated the expression and mutational profile of MES and ADRN TFs in neuroblastoma. Moreover, we established their correlation with neuroblastoma risk groups and overall survival while establishing their extended networks with long non-coding RNAs (lncRNAs). Furthermore, we analysed the pan-cancer expression and mutational profile of these TFs and their correlation with patient survival and finally their network connectivity, using a panel of bioinformatic tools including GEPIA2, human pathology atlas, TIMER2, Omicsnet, and Cytoscape.

RESULTS

We show the association of multiple MES and ADRN TFs with neuroblastoma risk groups and overall survival and find significantly higher expression of various MES and ADRN TFs compared to normal tissues and their association with overall survival and disease-free survival in multiple cancers. Moreover, we report the strong correlation of the expression of these TFs with the infiltration of stromal and immune cells in the tumour microenvironment and with stemness and metastasis-related genes. Furthermore, we reveal extended pan-cancer networks comprising these TFs that influence the tumour microenvironment and metastasis and may be useful indicators of cancer prognosis and patient survival.

CONCLUSION

Our meta-analysis shows the significance of MES and ADRN TFs as indicators of patient prognosis and the putative utility of these TFs as potential novel biomarkers.

SPRY4-AS1, A Novel Enhancer RNA, Is a Potential Novel Prognostic Biomarker and Therapeutic Target for Hepatocellular Carcinoma

A growing number of evidence have demonstrated the involvement of enhancer RNAs (eRNAs) in tumor progression. However, the possible functions of eRNAs in hepatocellular carcinoma (HCC) remain largely unclear. Our present research aimed to screen critical eRNAs and to further delve into the clinical significance of eRNAs in HCC patients. In this study, we identified 124 prognosis-related eRNAs by analyzing The Cancer Genome Atlas (TCGA) datasets. Among them, SPRY4 antisense RNA 1 (SPRY4-AS1) may be a key eRNA involved in HCC progression. SPRY4 was a regulatory target of SPRY4-AS1. High SPRY4-AS1 expression was associated with poor prognosis of HCC patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) assays revealed that the mainly enriched biological process included Human papillomavirus infection, Hippo signaling pathway, and Proteoglycans in cancer. Besides, RT-PCR and immunohistochemical staining confirmed SPRY4-AS1 as an overexpressed eRNA in HCC specimens. The pan-cancer assays revealed that SPRY4-AS1 was associated with glioblastoma multiforme (GBM), adrenocortical carcinoma (ACC), brain lower grade glioma (LGG) and mesothelioma(MESO). Positive associations were observed between SPRY4-AS1 and SPRY4 (its target gene) in 16 tumor types. Collectively, our findings reveal a novel eRNA SPRY4-AS1 for HCC progression and suggest that SPRY4-AS1 may be a potential biomarker and therapeutic target for HCC.

DCP1A is an unfavorable prognostic-related enhancer RNA in hepatocellular carcinoma

Long non-coding RNAs (lncRNAs) are associated with occurrence and development of tumors. Enhancer RNA (eRNA) is a special type of lncRNAs produced from transcription of enhancer elements. The function of eRNAs in tumors have elicited significant attention recently. However, the clinical significance and role of eRNAs in hepatocellular carcinoma (HCC) has not been fully explored. The current study sought to explore the expression level and prognostic value of key eRNAs in HCC. Bioinformatics analyses were used to explore expression levels of key prognostic eRNAs in HCC and their correlation with target genes. A total of 1580 enhancer RNAs (eRNAs) and 1791 target genes were initially retrieved from TCGA-LIHC gene expression database. Further analysis through survival and correlation analysis led to identification of 12 eRNAs and 13 target genes. The findings showed that DCP1A was the most prognosis-related eRNA. This eRNA showed the highest correlation with the target gene, PRKCD. Analysis showed that poor overall survival (OS) in HCC patients was correlated with high expression level of DCP1A (eRNA) and PRKCD (target gene). The up-regulation of DCP1A was associated with advanced tumor stage, larger tumor size and higher histological grade. The results of pan-cancer analysis showed that the expression of DCP1A was differentially expressed in 13 other types of tumor tissues and their corresponding normal tissues. This eRNA was highly expressed in digestive system tumors. Functional analysis showed that high expression level of DCP1A was implicated in multiple tumor-related signaling pathways. The findings of the current study indicated DCP1A is a novel biomarker that can be used as a potential therapeutic target for HCC patients.

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.

Immune-related long non-coding RNAs can serve as prognostic biomarkers for clear cell renal cell carcinoma

Background

The immune microenvironment is a critical regulator of clear cell renal cell carcinoma (ccRCC) progression. However, the underlying mechanisms the regulatory role of immune-related long non-coding RNAs (irlncRNAs) in the ccRCC tumor microenvironment (TME) are still obscure. Herein, we investigated prognostics role of irlncRNAs for ccRCC.

Methods

The raw data of patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the ImmPort database. First, we investigated the correlation between the immune-related genes and irlncRNAs. Then, we identified the differentially expressed irlncRNA pairs (ILRPs) between normal and cancer tissue samples, and prognostic model was constructed with the differentially expressed ILRPs. We further explored whether the signature risk scores of ILRPs had a considerable impact on immune cell infiltration. Finally, we performed a drug sensitivity analysis based on risk score.

Results

There were 13 upregulated and 40 downregulated irlncRNAs between the ccRCC and normal tissue samples. We further selected the irlncRNAs that significantly affect the prognosis of patients with ccRCC via univariate Cox, lasso regression, and multivariate regression analyses. Twelve ILRPs were used to construct a prognostic signature. The model showed the ILRPs model could be used to assess the prognosis of ccRCC patients. Study of the influence of risk score and clinical characteristics on the prognosis of patients with ccRCC showed risk score to be an independent factor affecting the outcome of ccRCC. We further performed the difference analysis of immune cell abundance between ccRCC and normal tissue samples. The results showed that patients with higher abundance of M0 macrophages, plasma cells, follicular helper T cells, and regulatory T cells (Tregs) had a poor outcome. Finally, we performed a drug sensitivity analysis based on risk score. The results showed that high-risk score patients are sensitive to orafenib, sunitinib, temsirolimus, cisplatin, and gemcitabine.

Conclusions

Our study has developed a novel and reasonable ILPRs model for prognostic prediction, which does not require transcriptional levels to be detected.