RNA-Sequencing Data Reveal a Prognostic Four-lncRNA-Based Risk Score for Bladder Urothelial Carcinoma: An in Silico Update

Abstract

Background/Aims: Current practical advances in high-throughput data technologies including RNA-sequencing have led to the identification of long non-coding RNAs (lncRNAs) for potential clinical application against bladder urothelial cancer (BLCA). However, most previous studies focused on the clinical value of individual lncRNAs, which has limited the potential for future clinical application. Methods: In this study, RNA-sequencing data of lncRNAs was downloaded from The Cancer Genome Atlas database. Risk score was constructed based on survival-associated lncRNAs identified using differential expression analysis as well as univariate and multivariate Cox proportional hazards regression analysis. Receiver operating characteristic and Kaplan-Meier curve analyses were employed to evaluate the clinical and prognostic value of risk scores. Bioinformatics analyses were used to investigate the potential mechanisms of newly identified lncRNAs. Results: Among 2,127 differentially expressed lncRNAs (DELs), four new lncRNAs (AC145124.1, AC010168.2, MIR200CHG, and AC098613.1) showed valuable prognostic effects in BLCA patients. More importantly, the four-DEL-based risk score had the potential to become an independent marker for the survival status prediction of BLCA patients. Distinct co-expressed genes and signaling pathways were identified when BLCA was categorized into low- and high-risk groups. Furthermore, a protein-coding gene, HIST4H4 was found only 68 bp from the AC010168.2 DEL. HIST4H4 expression level was evidently up-regulated and positively correlated with AC010168.2 in BLCA patients. Conclusion: This in silico investigation pioneers the future investigation of the utility of prognostic lncRNAs for BLCA.

Prognostic value of long non-coding RNA signatures in bladder cancer

“…In the time-dependent ROC curve analysis, the AUCs for OS (Figure 5A) in the first, third, and fifth year were 0.734, 0.78, and 0.78 respectively, while the prediction capability of the 14-lncRNA classifier was superior to the previously published lncRNA classifier [17]. As for RFS (Figure 5B), the AUCs in the first, third, and fifth year were 0.755, 0.715, and 0.740 respectively, whilst the 12-lncRNA-based classifier was mainly built to be a powerful prognostic predictor of BLCA recurrence.…”

“…Several lncRNA-based signatures have been applied to predict the risk of cancer progression in patients with different cancer types, such as renal cell carcinoma [14] and colon cancer [15]. As for BLCA, although the prognostic value of lncRNAs has also been explored by some authors [17, 23], there are still many things to be improved. The reasons for this are the following: (1) the internal validation dataset is needed to validate the stability of the constructed model; (2) the comparison between the constructed model and the existing TNM staging system is indispensable; (3) the prognostic value of BLCA recurrence should be further explored.…”

<p>Extracellular Matrix–Related Six-lncRNA Signature as a Novel Prognostic Biomarker for Bladder Cancer</p>

“…19 However, due to the complexity of the lncRNA-transcription landscape, a single lncRNA may not accurately predict the prognosis of cancer patients. Although attempts to use lncRNAs in prognosesfor BC patients have been described, 55,56 further exploration and improvement is required in this field. By comprehensive mining of lncRNA-expression profiles in the TCGA cohort, we established a novel six-lncRNA signature, the SMALLL signature, that was significantly related to the prognosis of BC patients.…”

BigMPI4py: Python module for parallelization of Big Data objects

“…7, up. There are no clear associations to gastrointestinal activity in any of those genes, although some of them have been associated to different cancers: CDH1 is associated to gastric, breast, colorrectal, and thyroid cancer [26], [27], [28], [29], KLF5 is associated to colorrectal cancer [30], MIR200B has been shown to promote mesenchymal-to-epithelial transition (MET) in last steps of metastasis [31], MIR200CHG is associated to bladder urothelial carcinoma [32], and PRR15L is associated to sigmoid colon cancer [33].…”