Identification and Validation of Six Autophagy-related Long Non-coding RNAs as Prognostic Signature in Colorectal Cancer.

Colorectal cancer (CRC) is a commonly occurring tumour with poor prognosis. Autophagy-related long non-coding RNAs (lncRNAs) have received much attention as biomarkers for cancer prognosis and diagnosis. However, few studies have focused on their prognostic predictive value specifically in CRC. This research aimed to construct a robust autophagy-related lncRNA prognostic signature for CRC. Autophagy-related lncRNAs from The Cancer Genome Atlas database were screened using univariate Cox, LASSO, and multivariate Cox regression analyses, and the resulting key lncRNAs were used to establish a prognostic risk score model. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) analysis was performed to detect the expression of several lncRNAs in cancer tissues from CRC patients and in normal tissues adjacent to the cancer tissues. A prognostic signature comprising lncRNAs AC125603.2, LINC00909, AC016876.1, MIR210HG, AC009237.14, and LINC01063 was identified in patients with CRC. A graphical nomogram based on the autophagy-related lncRNA signature was developed to predict CRC patients' 1-, 3-, and 5-year survival. Overall survival in patients with low risk scores was significantly better than in those with high risk scores (P < 0.0001); a similar result was obtained in an internal validation sample. The nomogram was shown to be suitable for clinical use and gave correct predictions. The 1- and 3-year values of the area under the receiver operating characteristic curve were 0.797 and 0.771 in the model sample, and 0.656 and 0.642 in the internal validation sample, respectively. The C-index values for the verification samples and training samples were 0.756 (95% CI = 0.668-0.762) and 0.715 (95% CI = 0.683-0.829), respectively. Gene set enrichment analysis showed that the six autophagy-related lncRNAs were greatly enriched in CRC-related signalling pathways, including p53 and VEGF signalling. The qRT-PCR results showed that the expression of lncRNAs in CRC was higher than that in adjacent tissues, consistent with the expression trends of lncRNAs in the CRC data set. In summary, we established a signature of six autophagy-related lncRNAs that could effectively guide clinical prediction of prognosis in patients with CRC. This lncRNA signature has significant clinical implications for improving the prediction of outcomes and, with further prospective validation, could be used to guide tailored therapy for CRC patients.

Cheng L ，Han T ，Zhang Z ，Yi P ，Zhang C ，Zhang S ，Peng W ... -  《International Journal of Medical Sciences》

N6-Methyladenosine-Related lncRNA Signature Predicts the Overall Survival of Colorectal Cancer Patients.

Song W ，Ren J ，Yuan W ，Xiang R ，Ge Y ，Fu T ... -  《Genes》

Discovery of a novel six-long non-coding RNA signature predicting survival of colorectal cancer patients.

Colorectal cancer (CRC) is one of the most leading causes of cancer deaths worldwide. In the study, we aimed to identify key long non-coding RNAs (lncRNAs) significantly associated with prognosis of CRC and develop an expression-based lncRNA signature to provide survival risk prediction for CRC patients. LncRNA expression profiles and clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) database. Six hundred and eighteen differentially expressed lncRNAs were identified between CRC and normal tissues. After univariate and multivariate Cox regression analysis for these differentially expressed lncRNAs and overall survival of CRC patients, six predictive lncRNAs (RP1-170O19.17, RP11-785D18.3, RP11-798K3.2, XXbac-B476C20.9, RP11-481J13.1, and RP11-167H9.4) were finally screened out to construct a six-lncRNA signature, based on which patients in the training dataset were divided into the high-risk and low-risk group with significantly different overall survival. ROC curve analysis demonstrated competitive performance of the six-lncRNA signature. The prognostic power of the six-lncRNA signature was successfully validated in the testing and entire dataset. Multivariate Cox regression analysis and stratification analysis further suggested that the six-lncRNA signature was independent of other conventional clinical variables for survival prediction in CRC patients. Functional enrichment analysis revealed the possible roles of these predictive lncRNAs in some cancer-related biological processes and pathways. Our study demonstrated the promising potential of the novel six-lncRNA signature as an independent biomarker for survival prediction of CRC patients.

Fan Q ，Liu B 《-》

Long non-coding RNA profile study identifies a metabolism-related signature for colorectal cancer.

Heterogeneity in colorectal cancer (CRC) patients provides novel strategies in clinical decision-making. Identifying distinctive subgroups in patients can improve the screening of CRC and reduce the cost of tests. Metabolism-related long non-coding RNA (lncRNA) can help detection of tumorigenesis and development for CRC patients. RNA sequencing and clinical data of CRC patients which extracted and integrated from public databases including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were set as training cohort and validation cohort. Metabolism-related genes were acquired from Kyoto Encyclopedia of Genes and Genomes (KEGG) and the metabolism-related lncRNAs were filtered using correlation analysis. The risk score was calculated based on lncRNAs with prognostic value and verified through survival curve, receiver operating characteristic (ROC) curve and risk curve. Prognostic factors of CRC patients were also analyzed. Nomogram was constructed based on the results of cox regression analyses. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA). The training cohort and the validation cohort enrolled 432 and 547 CRC patients respectively. A total of 23 metabolism-related lncRNAs with prognostic value were screened out and 10 of which were significantly differentially expressed between tumour and normal tissues. Finally, 8 lncRNAs were used to establish a risk score (DICER1-AS1, PCAT6, GAS5, PRR7-AS1, MCM3AP-AS1, GAS6-AS1, LINC01082 and ADIRF-AS1). Patients were divided into high-risk and low-risk groups according to the median of risk scores in training cohort and the survival curves indicated that the survival prognosis was significantly different. The area under curve (AUC) of the ROC curve in two cohorts were both greater than 0.6. The age, tumour stage and risk score were selected as independent factors and used to construct a nomogram to predict CRC patients' survival rate with the c-index of 0.806. The ssGSEA indicated that the risk score was associated with immune cells and functions. Our systematic study established a metabolism-related lncRNA signature to predict outcomes of CRC patients which may contribute to individual prevention and treatment.

Lu Y ，Wang W ，Liu Z ，Ma J ，Zhou X ，Fu W ... -  《-》

A robust signature of immune-related long non-coding RNA to predict the prognosis of bladder cancer.

Bladder cancer is the second most common malignant tumor in the urogenital system. The research investigated the prognostic role of immune-related long non-coding RNA (lncRNA) in bladder cancer. We extracted 411 bladder cancer samples from The Cancer Genome Atlas database. Single-sample gene set enrichment analysis was employed to assess the immune cell infiltration of these samples. We recognized differentially expressed lncRNAs between tumors and paracancerous tissues, and differentially expressed lncRNAs between the high and low immune cell infiltration groups. Venn diagram analysis detected differentially expressed lncRNAs that intersected the above groups. LncRNAs with prognostic significance were identified by regression analysis. Multivariate Cox analysis was used to establish the risk score model. Then we established and evaluated the nomogram. Additionally, we performed gene set enrichment analysis to explore the potential functions of the screened lncRNAs in tumor pathogenesis. Three hundred and twenty differentially expressed lncRNAs were recognized. We randomly divided patients into the training data set and the testing data set at a 2: 1 ratio. In the training data set, 9 immune-related lncRNAs with prognostic significance were identified. The risk score model was constructed to classify patients as high- and low-risk cohorts. Patients in the low-risk cohort had better survival outcomes than those in the high-risk cohort. The nomogram was established based on the indicators including age, gender, tumor-node-metastases stage, and risk score. The model's predictive performance was confirmed by the receiver operating characteristic curve analysis, concordance index method, calibration curve, and decision curve analysis. The testing data set also achieved similar results. Bioinformatics analysis suggested that the 9-lncRNA signature was involved in the modulation of various immune responses, antigen processing and presentation, and T cell receptor signaling pathway. Our study uncovered the prognostic value of immune-related lncRNAs for bladder cancer and showed that they may regulate tumor pathogenesis in various ways.

Lai C ，Wu Z ，Li Z ，Yu H ，Li K ，Tang Z ，Liu C ，Xu K ... -  《Cancer Medicine》