Jukun Song1, Juxiang Peng2, Chen Zhu2, Guohui Bai3, Yongda Liu4, Jianguo Zhu5, Jianguo Liu3. 1. Department of Oral and Maxillofacial Surgery, Guizhou Provincial People's Hospital, Guiyang, China. 2. Guiyang Hospital of Stomatology, Guiyang, China. 3. Special Key Laboratory of Oral Diseases Research, Stomatological Hospital Affiliated to Zunyi Medical College, Guiyang, China. 4. Department of Urology, Minimally Invasive Surgery Center, the First Affiliated Hospital of Guangzhou Medical Universtiy, Guangzhou, China. 5. Department of Urology, Guizhou Provincial People's Hospital, Zunyi, China.
Abstract
BACKGROUND/AIMS: Kidney renal clear cell carcinoma (KIRC) is one of the most fatal malignancies due to late diagnosis and poor treatment. To improve its prognosis, a screening for molecular biomarkers of KIRC is urgently needed. Long non-coding RNAs (lncRNAs) play important roles in tumorigenesis and prognosis of cancers. However, it is not clear whether lncRNAs can be used as molecular biomarkers in predicting the survival of KIRC patients. METHODS: In this study, our aim was to identify lncRNAs/mRNAs signatures and their prognostic values in KIRC. The aberrant expression profile of mRNAs and lncRNAs in 529 KIRC tissues and 72 adjacent non-tumor pancreatic tissues were obtained from the Cancer Genome Atlas (TCGA). A weighted gene co-expression network analysis (WGCNA) of two key lncRNAs was constructed. We constructed an aberrant lncRNA-mRNA-miRNA ceRNA network in CESC. In addition, Gene Ontology (GO) and KEGG pathway analysis were performed. RESULTS: Using lncRNA/mRNA expression profiling data, the overall analysis revealed that two novel lncRNA signatures (DNM1P35 and MIR155HG) and several mRNAs were found to be significantly correlated with KIRC patient's overall analysis. Based on the target gene of the two lncRNA in co-expression network, the GO and KEGG analysis were also performed. A dysregulated lncRNA-related ceRNA network was also observed. CONCLUSION: These results suggested that the two novel lncRNAs signatures may act as independent prognostic biomarkers for predicting the survival of KIRC patient.
BACKGROUND/AIMS: Kidney renal clear cell carcinoma (KIRC) is one of the most fatal malignancies due to late diagnosis and poor treatment. To improve its prognosis, a screening for molecular biomarkers of KIRC is urgently needed. Long non-coding RNAs (lncRNAs) play important roles in tumorigenesis and prognosis of cancers. However, it is not clear whether lncRNAs can be used as molecular biomarkers in predicting the survival of KIRC patients. METHODS: In this study, our aim was to identify lncRNAs/mRNAs signatures and their prognostic values in KIRC. The aberrant expression profile of mRNAs and lncRNAs in 529 KIRC tissues and 72 adjacent non-tumor pancreatic tissues were obtained from the Cancer Genome Atlas (TCGA). A weighted gene co-expression network analysis (WGCNA) of two key lncRNAs was constructed. We constructed an aberrant lncRNA-mRNA-miRNA ceRNA network in CESC. In addition, Gene Ontology (GO) and KEGG pathway analysis were performed. RESULTS: Using lncRNA/mRNA expression profiling data, the overall analysis revealed that two novel lncRNA signatures (DNM1P35 and MIR155HG) and several mRNAs were found to be significantly correlated with KIRC patient's overall analysis. Based on the target gene of the two lncRNA in co-expression network, the GO and KEGG analysis were also performed. A dysregulated lncRNA-related ceRNA network was also observed. CONCLUSION: These results suggested that the two novel lncRNAs signatures may act as independent prognostic biomarkers for predicting the survival of KIRC patient.