Long Non-coding RNAs and their Role in Metastasis

A genome-wide comprehensively analyses of long noncoding RNA profiling and metastasis associated lncRNAs in renal cell carcinoma

Recently, a growing number of studies have indicated that long noncoding RNAs (lncRNAs) are emerging as new critical regulators of tumorigenesis and prognostic markers in multiple cancers. However, the expression pattern of lncRNAs and their contributions in renal cell carcinoma (RCC) remains poorly understood. In this study, we performed a genome-wide comprehensively analysis of lncRNAs profiling and clinical relevance to provide valuable lncRNA candidates for the further study in RCC. RCC and non-tumor tissues RNA sequencing data, and microarray data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), then, these data were annotated and analyzed to find dysregulated lncRNAs in RCC. We identified that hundreds of lncRNAs were differentially expressed in RCC tissues compared with normal tissues, and genomic variation analyses revealed that copy number amplification or deletion happened in some of these lncRNAs genome loci. Moreover, lots of lncRNAs expression levels are significantly associated RCC patients overall survival time, such as PVT1 and DUXAP8. Finally, we identified some novel metastasis associated lncRNAs in RCC (such as DUXAP8) by analyzing lncRNAs profiling in the RCC tissues from patients with metastasis compared with the primary RCC tissues without metastasis; knockdown of DUXAP8 could impair RCC cells invasive ability in vitro. Overall, our findings illuminate a lot of lncRNAs are aberrantly expressed in RCC that may offer useful resource for identification novel prognostic markers in this disease.

LncRNA PVT1 as an effective biomarker for cancer diagnosis and detection based on transcriptome data and meta-analysis

PURPOSE

Long noncoding RNA (lncRNA) PVT1 was detected all types of cancer from Cancer Genome Atlas (TCGA) project; however, the role of PVT1 in cancer is not clear. This study aimed to reanalyze and determine the effect of PVT1 on cancer diagnosis, especially detection in serum.

MATERIALS AND METHODS

Differential expression of PVT1 between cancers and corresponding normal tissues and receiver operating characteristic (ROC) curve were analyzed for all types of cancers in TCGA database. RevMan5.3, Meta-DiSc1.4 and STATA14.0 were used to estimate pooled diagnostic effects of PVT1 in tissue as well as serum.

RESULTS

Compared to corresponding normal tissues, PVT1 expression was significantly upregulated in 18 types of cancer and further being an effective diagnosis biomarker in 16 of them. For the 23 diagnosis tests performed in tissue, the pooled AUC and diagnostic odd ratio (DOR) were estimated to be 0.81 (95% CI: 0.76-0.86) and 17.25 (95% CI: 8.43-35.27), when the pooled AUC and DOR were 0.83 (95%CI: 0.75-0.91) and 13.86 (95% CI: 4.70-40.66) for serum tests. Furthermore, the pooled sensitivity and specificity were 0.83 (95% CI: 0.76-0.89) and 0.74 (95% CI:0.70-0.84) for tissue as well as 0.81 (95% CI: 0.76-0.86) and 0.76 (95% CI:0.70-0.81) for serum.

CONCLUSIONS

PVT1, especially in serum, might be a usable biomarker for cancer diagnosis / detection.