scholarly journals Long non-coding RNA HOTTIP promotes hepatocellular carcinoma tumorigenesis and development: A comprehensive investigation based on bioinformatics, qRT-PCR and meta-analysis of 393 cases

2017 ◽  
Vol 51 (6) ◽  
pp. 1705-1721 ◽  
Author(s):  
Yu Zhang ◽  
Jia-Cheng Huang ◽  
Kai-Teng Cai ◽  
Xi-Bing Yu ◽  
You-Rong Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Meta Analysis ◽  
Comprehensive Investigation ◽  
Qrt Pcr ◽  
Non Coding Rna ◽  
Long Non Coding Rna

scholarly journals The value of lncRNAs as prognostic biomarkers on clinical outcomes in osteosarcoma: a meta-analysis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenchao Zhang ◽  
Xiaolei Ren ◽  
Lin Qi ◽  
Chenghao Zhang ◽  
Chao Tu ◽  
...  
Keyword(s):  
Web Of Science ◽  
Meta Analysis ◽  
Positive Outcome ◽  
Clinical Applications ◽  
Clinicopathological Features ◽  
Cochrane Library ◽  
Human Osteosarcoma ◽  
Non Coding Rna ◽  
The Cochrane Library ◽  
Long Non Coding Rna

Abstract Background In recent years, emerging studies have demonstrated critical functions and potential clinical applications of long non-coding RNA (lncRNA) in osteosarcoma. To further validate the prognostic value of multiple lncRNAs, we have conducted this updated meta-analysis. Methods Literature retrieval was conducted by searching PubMed, Web of Science and the Cochrane Library (last update by October 2, 2019). A meta-analysis was performed to explore association between lncRNAs expression and overall survival (OS) of osteosarcoma patients. Relationships between lncRNAs expression and other clinicopathological features were also analyzed respectively. Results Overall, 4351 patients from 62 studies were included in this meta-analysis and 25 lncRNAs were identified. Pooled analyses showed that high expression of 14 lncRNAs connoted worse OS, while two lncRNAs were associated with positive outcome. Further, analysis toward osteosarcoma clinicopathologic features demonstrated that overexpression of TUG1 and XIST indicated poor clinical parameters of patients. Conclusions This meta-analysis has elucidated the prognostic potential of 16 lncRNAs in human osteosarcoma. Evidently, desperate expression and functional targets of these lncRNAs offer new approaches for prognosis and therapy of osteosarcoma.

scholarly journals Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma

Bioengineered ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 673-681
Author(s):  
Jie Cao ◽  
Lili Wu ◽  
Xin Lei ◽  
Keqing Shi ◽  
Liang Shi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Long non-coding RNA UCA1 regulates the expression of Snail2 by miR-203 to promote hepatocellular carcinoma progression

2017 ◽  
Vol 143 (6) ◽  
pp. 981-990 ◽  
Author(s):  
Ji-Nan Xiao ◽  
Ting-Hua Yan ◽  
Rui-Ming Yu ◽  
Yi Gao ◽  
Wen-Long Zeng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Non Coding Rna ◽  
Long Non Coding Rna

A long non-coding RNA-based signature predicts early recurrence in hepatocellular carcinoma

2021 ◽  
pp. 1-10
Author(s):  
Shuai He ◽  
Jin-Feng Li ◽  
Hao Tian ◽  
Ye Sang ◽  
Xiao-Jing Yang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Curative Resection ◽  
Risk Model ◽  
Cox Regression ◽  
Early Recurrence ◽  
Support Vector ◽  
Term Survival ◽  
Cox Regression Analysis ◽  
Non Coding Rna ◽  
Long Non Coding Rna

BACKGROUND: Early recurrence is the main obstacle for long-term survival of hepatocellular carcinoma (HCC) patients after curative resection. OBJECTIVE: We aimed to develop a long non-coding RNA (lncRNA) based signature to predict early recurrence. METHODS: Using bioinformatics analysis and quantitative reverse transcription PCR (RT-qPCR), we screened for lncRNA candidates that were abnormally expressed in HCC. The expression levels of candidate lncRNAs were analyzed in HCC tissues from 160 patients who underwent curative resection, and a risk model for the prediction of recurrence within 1 year (early recurrence) of HCCs was constructed with linear support vector machine (SVM). RESULTS: A lncRNA-based classifier (Clnc), which contained nine differentially expressed lncRNAs including AF339810, AK026286, BC020899, HEIH, HULC, MALAT1, PVT1, uc003fpg, and ZFAS1 was constructed. In the test set, this classifier reliably predicted early recurrence (AUC, 0.675; sensitivity, 72.0%; specificity, 63.1%) with an odds ratio of 4.390 (95% CI, 2.120–9.090). Clnc showed higher accuracy than traditional clinical features, including tumor size, portal vein tumor thrombus (PVTT) in predicting early recurrence (AUC, 0.675 vs 0.523 vs 0.541), and had much higher sensitivity than Barcelona Clinical Liver Cancer (BCLC; 72.0% vs 50.0%), albeit their AUCs were comparable (0.675 vs 0.678). Moreover, combining Clnc with BCLC significantly increased the AUC, compared with Clnc or BCLC alone in predicting early recurrence (all P< 0.05). Finally, logistic and Cox regression analysis suggested that Clnc was an independent prognostic factor and associated with the early recurrence and recurrence-free survival of HCC patients after resection, respectively (all P= 0.001). CONCLUSIONS: Our lncRNA-based classifier Clnc can predict early recurrence of patients undergoing surgical resection of HCC.

scholarly journals Long non-coding RNA PVT1 is associated with tumor progression and predicts recurrence in hepatocellular carcinoma patients

2014 ◽  
Vol 9 (2) ◽  
pp. 955-963 ◽  
Author(s):  
CHAOFENG DING ◽  
ZHE YANG ◽  
ZHEN LV ◽  
CHENGLI DU ◽  
HENG XIAO ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Progression ◽  
Non Coding Rna ◽  
Long Non Coding Rna

scholarly journals Association Between Long Non-Coding RNA POLR2E rs3787016 Polymorphism and Cancer Susceptibility: A Meta-analysis of 8725 Cancer Cases and 10710 Controls

2020 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Saeid Ghavami ◽  
Mohsen Taheri ◽  
Mohammad Hashemi
Keyword(s):  
Breast Cancer ◽  
Web Of Science ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Positive Association ◽  
Cancer Development ◽  
Non Coding Rna ◽  
Stratified Analysis ◽  
The Relationship ◽  
Long Non Coding Rna

Objectives: Several studies have reported a correlation between the POLR2E rs3787016 polymorphism and cancer development, but findings are inconsistent. Therefore, we designed the current study to understand how rs3787016 polymorphism impacts cancer susceptibility. Methods: We searched the Scopus, Web of Science, and PubMed databases for studies related to the topic of interest published up to March 2019. A total of 11 relevant studies, encompassing 8,761 cancer cases and 10,534 controls, were retrieved and subject to quantitative analysis. The strength of the relationship was evaluated using the pooled odds ratios (ORs) with 95% confidence intervals (CIs). Results: Overall, the findings proposed a positive association between rs189037 polymorphism and susceptibility to cancer in homozygous (OR = 1.32, 95% CI = 1.11 - 1.57, P = 0.002, TT vs. CC), recessive (OR = 1.21, 95% CI = 1.06-1.39, P = 0.005, TT vs. CT + CC), and allele (OR = 1.12, 95% CI = 1.02-1.22, P = 0.021, T vs. C) genetic models. Stratified analysis showed that rs3787016 increased the risk of prostate and breast cancer. In addition, we found a significant association between the variant and increased cancer risk in Asian and Caucasian populations. Conclusions: In summary, the findings of the current meta-analysis suggest that the POLR2E rs3787016 polymorphism is an indicator of cancer susceptibility.

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