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.

Zhang Z ，Tang Y ，Zhuang H ，Lin E ，Xie L ，Feng X ，Zeng J ，Liu Y ，Liu J ，Yu Y ... -  《-》

Differential Expression of Long Noncoding RNAs During Cardiac Allograft Rejection.

Gu G ，Huang Y ，Wu C ，Guo Z ，Ma Y ，Xia Q ，Awasthi A ，He X ... -  《-》

Analysis of long noncoding RNAs for acute rejection and graft outcome in kidney transplant biopsies.

Zou Y ，Zhang W ，Zhou HH ，Liu R ... -  《-》

Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.

Fan CN ，Ma L ，Liu N 《Journal of Translational Medicine》

Identification of long noncoding RNAs biomarkers for diagnosis and prognosis in patients with colon adenocarcinoma.

In the study, we aimed to find key long noncoding RNAs (lncRNAs) significantly associated with the diagnosis of colon adenocarcinoma (COAD) and lncRNA signatures to provide survival risk prognosis for patients with COAD. The lncRNA and messenger RNA (mRNA) expression profiles and clinical information of patients with COAD were obtained from the Cancer Genome Atlas database. The differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between COAD and normal tissues were identified. The optimal diagnostic and prognostic lncRNA biomarkers for COAD were identified by using feature selection procedure and classification model. Functional enrichment analysis revealed the possible roles of mRNAs coexpressed with lncRNAs in some cancer-related biological processes and pathways. Receiver operating characteristic curve of these lncRNA biomarkers were obtained by using 10-fold cross-validation. Univariate and multivariate Cox regression analysis for these DElncRNAs were performed to obtain the lncRNAs related to overall survival time. The expression levels of selected DElncRNAs were validated by quantitative real time polymerase chain reaction (qRT-PCR). A total of 169 DElncRNAs (60 downregulated and 109 upregulated) and 1236 DEmRNAs (708 downregulated and 528 upregulated) between COAD and normal tissues were identified. Eight lncRNAs of XXbac-B476C20.9, PP7080, CDKN2B-AS1, LINC00092, CA3-AS1, HAND2-AS1, CTD-2269F5.1, and LINC01082 were selected as optimal diagnostic lncRNA biomarkers for COAD. The expression of eight optimal diagnostic lncRNA biomarkers in qRT-PCR validation was consistent with our integrated analysis. Among them, XXbac-B476C20.9 was not only one of the eight optimal diagnostic lncRNA biomarkers, but also related to the prognosis of COAD. Our study demonstrated the promising potential of XXbac-B476C20.9 as an independent biomarker for diagnosis and prognosis of patients with COAD.

Huang W ，Liu Z ，Li Y ，Liu L ，Mai G ... -  《-》