LncRNA BANCR promotes tumorigenesis and enhances adriamycin resistance in colorectal cancer

Comprehensive analysis of differentially expressed lncRNAs as diagnostic and prognostic markers for colorectal cancer

Colorectal cancer (CRC) is the third most common type of cancer worldwide. Recent studies had revealed the important roles of long non-coding RNAs (lncRNAs) in a variety of human cancers, including CRC. However, the molecular mechanisms associated with CRC remain largely undetermined. In the current study, the GSE21510 dataset was analyzed to identify differentially expressed mRNAs and lncRNAs in CRC samples. The Database for Annotation, Visualization and Integrated Discovery was used to perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway bioinformatics analysis. Furthermore, protein-protein interaction networks were constructed to reveal interactions among differentially expressed proteins. Kaplan-Meier analysis was subsequently performed to determine the association between key lncRNA expression and the overall survival of patients with CRC. A total of 107 upregulated lncRNAs and 43 downregulated lncRNAs were identified in CRC. A lncRNA mediated co-expression network was also constructed in CRC. Bioinformatics analysis indicated that lncRNAs were associated with a series of biological processes, including 'xenobiotic glucuronidation', 'rRNA processing', 'sister chromatid cohesion', 'cell proliferation', 'mitotic nuclear division' and 'cell cycle regulation'. Furthermore, a higher expression of small nucleolar RNA host gene 17, tetratricopeptide repeat domain 2B-antisense RNA (AS) 1, erythrocyte membrane protein band 4.1 like 4A-AS2, deleted in lymphocytic leukemia 2, and a lower expression of muscle blind like splicing regulator 1-AS1 and LOC389332 were associated with shorter overall survival time in CRC samples. The present study provides useful information that can be used in the identification of novel biomarkers for CRC.

Identification of a six-gene signature predicting overall survival for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) remains a major challenge for public health worldwide. Considering the great heterogeneity of HCC, more accurate prognostic models are urgently needed. To identify a robust prognostic gene signature, we conduct this study.

Materials and methods

Level 3 mRNA expression profiles and clinicopathological data were obtained in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC). GSE14520 dataset from the gene expression omnibus (GEO) database was downloaded to further validate the results in TCGA. Differentially expressed mRNAs between HCC and normal tissue were investigated. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic (ROC), Kaplan–Meier curve, multivariate Cox regression analysis, nomogram, and decision curve analysis (DCA) were used to assess the prognostic capacity of the six-gene signature. The prognostic value of the gene signature was further validated in independent GSE14520 cohort. Gene Set Enrichment Analyses (GSEA) was performed to further understand the underlying molecular mechanisms. The performance of the prognostic signature in differentiating between normal liver tissues and HCC were also investigated.

Results

A novel six-gene signature (including CSE1L, CSTB, MTHFR, DAGLA, MMP10, and GYS2) was established for HCC prognosis prediction. The ROC curve showed good performance in survival prediction in both the TCGA HCC cohort and the GSE14520 validation cohort. The six-gene signature could stratify patients into a high- and low-risk group which had significantly different survival. Cox regression analysis showed that the six-gene signature could independently predict OS. Nomogram including the six-gene signature was established and shown some clinical net benefit. Furthermore, GSEA revealed several significantly enriched oncological signatures and various metabolic process, which might help explain the underlying molecular mechanisms. Besides, the prognostic signature showed a strong ability for differentiating HCC from normal tissues.

Conclusions

Our study established a novel six-gene signature and nomogram to predict overall survival of HCC, which may help in clinical decision making for individual treatment.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0858-2) contains supplementary material, which is available to authorized users.

Long noncoding RNA HCP5 contributes to epithelial-mesenchymal transition in colorectal cancer through ZEB1 activation and interacting with miR-139-5p

Long noncoding RNAs (lncRNAs) play key roles in various malignancy pathogenesis. However, the mechanisms remain poorly understood in the development and progression of colorectal cancer (CRC). Here, we focused on the specific role of human leukocyte antigen (HLA) Complex P5 (HCP5) in CRC. Quantitative real-time PCR (qRT-PCR) analysis and western blot were used to assess the expression of HCP5 in CRC tissues. The association between the expressions of HCP5 and miR-139-5p was assessed by Pearson's correlation analysis. The prognosis of CRC patients was analyzed by Kaplan-Meier survival analysis. Specific siRNAs were stably transfected into CRC cells with lentivirus approaches. The proliferative, migrative and invasive capacities of CRC cells were detected by Transwell, MTT and scratch assay, respectively. Dual-luciferase assay was performed to measure miR-139-5p-targeted relationship with lncRNA HCP5. HCP5 overexpression and of miR-139-5p downregulation were dramatically correlated with low TNM stage, poor differentiation, low tumor depth invasion in CRC patients (P < 0.05). Besides, HCP5 overexpression or ZEB1 knockdown repressed Snail family transcriptional repressor (SNAI) and vimentin expressions, upregulated E-cadherin expression, and inhibited cell proliferation and metastasis (P < 0.05). Moreover, luciferase reporter assay demonstrated that miR-139-5p was a directly target of HCP5 (P < 0.05). Overall, the present study indicated that HCP5 played a key regulator in CRC development and progression by targeting HCP5/miR-139-5p/ZEB1 axis, which may serve as a novel therapeutic target for CRC therapy.