Long Non-coding RNA Expression Profiling in Biopsy to Identify Renal Allograft at Risk of Chronic Damage and Future Graft Loss

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

A novel lipid metabolism-related lncRNA signature predictive of clinical prognosis in cervical cancer

Background: Cervical cancer (CC) is a serious threat to women populations worldwide. Lipid metabolism is believed to have modulating functions in cancer. Long non-coding RNAs (lncRNAs) are potential biomarkers for the different tumor prognosis. Our work aims at investigating the prognostic value of lipid metabolism-related lncRNAs in CC.

Methods: LncRNA expression profiling was conducted in 291 patients from The Cancer Genome Atlas (TCGA). Patient samples were randomly assigned to the training or testing set in a 3:2 ratio. A novel lipid metabolism-related five-lncRNA signature with prognostic value for CC was built through the univariate Cox regression, least absolute contraction and selection operator (LASSO) regression and multivariate Cox regression analyses, and was further evaluated by the Kaplan-Meier methods. Relevant analyses were also applied to identify the independent clinicopathological factors. GO and KEGG analyses were conducted to investigate the biological functions and molecular pathways. Immune infiltration analysis was included to probe the relationship between lncRNA signature and cancer cell microenvironment.

Results: The novel lipid metabolism-related five-lncRNA signature was confirmed to be predictive of overall survival (OS) in CC patients. Risk score, cancer stage, pregnancy, and BMI were validated as independent factors with prognostic value. GO and KEGG indicated that lipid metabolism participated in several tumor associated functions and pathways. Moreover, our results suggested that the five-lncRNA expression has potential link with tumor immune microenvironment.

Conclusion: In conclusion, we built an innovative prognostic risk signature based upon lipid metabolism-related lncRNAs. The five-lncRNA signature may be beneficial to provide novel potential therapeutic targets and improve personalized treatment strategies for CC patients in future clinical treatments.

Epigenetic Regulation in Kidney Transplantation

Kidney transplantation is a standard care for end stage renal disease, but it is also associated with a complex pathogenesis including ischemia-reperfusion injury, inflammation, and development of fibrosis. Over the past decade, accumulating evidence has suggested a role of epigenetic regulation in kidney transplantation, involving DNA methylation, histone modification, and various kinds of non-coding RNAs. Here, we analyze these recent studies supporting the role of epigenetic regulation in different pathological processes of kidney transplantation, i.e., ischemia-reperfusion injury, acute rejection, and chronic graft pathologies including renal interstitial fibrosis. Further investigation of epigenetic alterations, their pathological roles and underlying mechanisms in kidney transplantation may lead to new strategies for the discovery of novel diagnostic biomarkers and therapeutic interventions.

Potential Roles of Long Noncoding RNAs as Therapeutic Targets in Organ Transplantation

Organ transplantation is the most preferred treatment option for end-stage organ diseases; however, allograft rejection is the major hurdle in successful long-term transplant survival. In spite of developing better HLA matching and more effective immunosuppressive regimen, one-year graft survival has been increased by nearly 90% and the incidence of acute rejection by one-year post-transplantation has been decreased by 12.2% in the last decades, chronic allograft rejection has remained as one of the major obstacles to the long-lasting survival of the transplanted allograft. Therefore, seemingly preventing the allograft rejection and inducing immunological tolerance against transplanted allografts is one of the primary goals in transplantation research to enable long-lasting graft survival. Various mechanisms such as long noncoding RNAs (lncRNAs) have been proposed that induce immune tolerance by modulating the gene expression and regulating innate and adaptive immune responses during transplantation. Besides, because of involvement in regulating epigenetic, transcriptional, and post-translational mechanisms, lncRNAs could affect allograft status. Therefore, these molecules could be considered as the potential targets for prediction, prognosis, diagnosis, and treatment of graft rejection. It is suggested that the noninvasive predictive biomarkers hold promise to overcome the current limitations of conventional tissue biopsy in the diagnosis of rejection. Hence, this review aims to provide a comprehensive overview of lncRNAs and their function to facilitate diagnosis, prognosis, and prediction of the risk of graft rejection, and the suggestive therapeutic choices after transplantation.

High Expression of the Component 3a Receptor 1 (C3AR1) Gene in Stomach Adenocarcinomas Infers a Poor Prognosis and High Immune-Infiltration Levels

Background

This study was designed to explore the incompletely investigated role of the complement component 3a receptor 1 (C3AR1) in the prognosis of stomach adenocarcinomas (STAD).

Material/Methods

Using bioinformatic methods, we systematically determined the expression and prognosis value of C3AR1 in various cancers by using the TIMER (Tumor Immune Estimation Resource) database, UALCAN platform, GEPIA (Gene Expression Profiling Interactive Analysis) server, and the OncoLnc tool. The biological processes influenced by C3AR1 were determined using the GSEA (Gene Set Enrichment Analysis) software (Copyright 2004–2020 Broad Institute, Inc., Massachusetts Institute of Technology, and Regents of the University of California). The correlation between C3AR1 expression and the immune-infiltrating cells as well as the correlation analysis between C3AR1 expression and the corresponding immune-marker sets were conducted using the TIMER and GEPIA databases.

Results

The expression of C3AR1 was significantly (P<0.001) differentially expressed on several tumor types, while its prognosis value could only be determined on STAD, with a high expression of C3AR1 closely correlated with a poor prognosis. The GSEA analysis revealed that the differential expression of C3AR1 profoundly affected the immune-related biological processes. The expression of C3AR1 was strongly and positively correlated with the infiltration of monocytes, tumor-associated macrophages, M2 macrophages, dendritic cells, and exhausted T cells.

Conclusions

Our results have revealed that a high expression of C3AR1 is positively correlated with a poor prognosis and increased tumor-immune infiltration. C3AR1 can promote the polarization of M2 macrophages and T cell exhaustion, leading to the immune escape of STAD. These findings suggest that C3AR1 could be used as a prognostic and immune-infiltration marker in the pathogenesis of STAD.

Circulating Long Noncoding RNA LNC-EPHA6 Associates with Acute Rejection after Kidney Transplantation

Acute rejection (AR) of a kidney graft in renal transplant recipients is associated with microvascular injury in graft dysfunction and, ultimately, graft failure. Circulating long noncoding RNAs (lncRNAs) may be suitable markers for vascular injury in the context of AR. Here, we first investigated the effect of AR after kidney transplantation on local vascular integrity and demonstrated that the capillary density markedly decreased in AR kidney biopsies compared to pre-transplant biopsies. Subsequently, we assessed the circulating levels of four lncRNAs (LNC-RPS24, LNC-EPHA6, MALAT1, and LIPCAR), that were previously demonstrated to associate with vascular injury in a cohort of kidney recipients with a stable kidney transplant function (n = 32) and recipients with AR (n = 15). The latter were followed longitudinally six and 12 months after rejection. We found higher levels of circulating LNC-EPHA6 during rejection, compared with renal recipients with a stable kidney function (p = 0.017), that normalized one year after AR. In addition, LNC-RPS24, LNC-EPHA6, and LIPCAR levels correlated significantly with the vascular injury marker soluble thrombomodulin. We conclude that AR and microvascular injury are associated with higher levels of circulating LNC-EPHA6, which emphasizes the potential role of lncRNAs as biomarker in the context of AR.

IL-27Rα: A Novel Molecular Imaging Marker for Allograft Rejection

Non-invasively monitoring allogeneic graft rejection with a specific marker is of great importance for prognosis of patients. Recently, data revealed that IL-27Rα was up-regulated in alloreactive CD4⁺ T cells and participated in inflammatory diseases. Here, we evaluated whether IL-27Rα could be used in monitoring allogeneic graft rejection both in vitro and in vivo. Allogeneic (C57BL/6 donor to BALB/c recipient) and syngeneic (BALB/c both as donor and recipient) skin grafted mouse models were established. The expression of IL-27Rα in grafts was detected. The radio-probe, ¹²⁵I-anti-IL-27Rα mAb, was prepared. Dynamic whole-body phosphor-autoradiography, ex vivo biodistribution and immunofluorescence staining were performed. The results showed that the highest expression of IL-27Rα was detected in allogeneic grafts on day 10 post transplantation (top period of allorejection). ¹²⁵I-anti-IL-27Rα mAb was successfully prepared with higher specificity and affinity. Whole-body phosphor-autoradiography showed higher radioactivity accumulation in allogeneic grafts than syngeneic grafts on day 10. The uptake of ¹²⁵I-anti-IL-27Rα mAb in allogeneic grafts could be almost totally blocked by pre-injection with excess unlabeled anti-IL-27Rα mAb. Interestingly, we found that ¹²⁵I-anti-IL-27Rα mAb accumulated in allogeneic grafts, along with weaker inflammation earlier on day 6. The high uptake of ¹²⁵I-anti-IL-27Rα mAb was correlated with the higher infiltrated IL-27Rα positive cells (CD3⁺/CD68⁺) in allogeneic grafts. In conclusion, IL-27Rα may be a novel molecular imaging marker to predict allorejection.

Diagnostic, Prognostic, and Therapeutic Value of Non-Coding RNA Expression Profiles in Renal Transplantation

End-stage renal disease is a public health problem responsible for millions of deaths worldwide each year. Although transplantation is the preferred treatment for patients in need of renal replacement therapy, long-term allograft survival remains challenging. Advances in high-throughput methods for large-scale molecular data generation and computational analysis are promising to overcome the current limitations posed by conventional diagnostic and disease classifications post-transplantation. Non-coding RNAs (ncRNAs) are RNA molecules that, despite lacking protein-coding potential, are essential in the regulation of epigenetic, transcriptional, and post-translational mechanisms involved in both health and disease. A large body of evidence suggests that ncRNAs can act as biomarkers of renal injury and graft loss after transplantation. Hence, the focus of this review is to discuss the existing molecular signatures of non-coding transcripts and their value to improve diagnosis, predict the risk of rejection, and guide therapeutic choices post-transplantation.

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.

LncRNA RP11-422N16.3 Inhibits Cell Proliferation and EMT, and Induces Apoptosis in Hepatocellular Carcinoma Cells by Sponging miR-23b-3p

Objective

This study investigated the mechanism of RP11-422N16.3 sponging miR-23b-3p in cell proliferation, apoptosis and epithelial-mesenchymal transition (EMT) in liver cancer.

Methods

Expressions of RP11-422N16.3, miR-23b-3p and dimethylglycine dehydrogenase (DMGDH) were determined in liver cancer tissues, adjacent normal tissues, hepatocellular carcinoma cell lines and normal liver epithelial cell line. Up-regulation of RP11-422N16.3 and down-regulation of miR-23b-3p were conducted in hepatocellular carcinoma cells. Bioinformatics analysis, luciferase reporter assay and RNA-pull down assay were performed to verify the relationship among miR-23b-3p, DMGDH, as well as RP11-422N16.3. Cell proliferation and cell apoptosis were determined by CCK-8 and Flow Cytometry analysis, respectively.

Results

Expressions of RP11-422N16.3 and DMGDH were down-regulated while that of miR-23b-3p were up-regulated in hepatocellular carcinoma cancer tissues and cells. RP11-422N16.3 localized in cytoplasm and competitively bound to miR-23b-3p. Up-regulation of RP11-422N16.3 and down-regulation of miR-23b-3p contributed to increased expressions of DMGDH and E-cadherin, and decreased expressions of miR-23b-3p, ZEB1, Snail and Vimentin, resulting in inhibiting cell proliferation and promoting cell apoptosis. Inhibition of RP11-422N16.3 or overexpression of miR-23b-3p accelerated cell proliferation and slowed down cell apoptosis. miR-23b-3p inhibited the expression of DMGDH.

Conclusion

Our data suggested that LncRNA RP11-422N16.3, by competitively binding to miR-23b-3p, promoted DMGDH expression, contributing to inhibit cell proliferation and EMT, and induce cell apoptosis in hepatocellular carcinoma cells.