The role of UCA1 and WRAP53 in diagnosis 
of hepatocellular carcinoma: A single-center 
case-control study

Abdelmoety, Amr Aly; Elhassafy, Mohamed Youssef; Omar Said, Rasha Said; Elsheaita, Ahmed; Mahmoud, Manal Mohamed

doi:10.5114/ceh.2023.127569

Cited by 3 publications

(2 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many ncRNAs are in clinical trials for potential biomarkers and therapeutic targets for cancers and other diseases. LncRNA MFI2-AS1 is in clinical trials for use as a diagnostic biomarker for kidney cancer [105], and lncRNAs UCA1 and WRAP53 are in clinical trials for use as diagnostic biomarkers for hepatocellular carcinoma [106]. Results from safety trials of RNA-targeted therapies using ASO against lncRNAs are also promising [107].…”

Section: Discussionmentioning

confidence: 99%

Role of Non-Coding RNAs in TGF-β Signalling in Glioma

Shree,

Sharma

2023

Brain Sciences

View full text Add to dashboard Cite

Brain tumours and Gliomas, in particular, are among the primary causes of cancer mortality worldwide. Glioma diagnosis and therapy have not significantly improved despite decades of efforts. Autocrine TGF-β signalling promotes glioma proliferation, invasion, epithelial-to-mesenchymal transition (EMT), and drug resistance. Non-coding RNAs such as miRNA, lncRNA, and circRNAs have emerged as critical transcriptional and post-transcriptional regulators of TGF-β pathway components in glioma. Here, we summarize the complex regulatory network among regulatory ncRNAs and TGF-β pathway during Glioma pathogenesis and discuss their role as potential therapeutic targets for Gliomas.

show abstract

Section: Discussionmentioning

confidence: 99%

Role of Non-Coding RNAs in TGF-β Signalling in Glioma

Shree,

Sharma

2023

Brain Sciences

View full text Add to dashboard Cite

show abstract

“…Furthermore, several studies identified lncRNAs, such as UCA1 and WRAP53, as promising biomarkers in HCC diagnosis when used in conjunction with AFP [ 146 , 147 ]. Another group also identified LINC00152, RP11-160H22.5, and XLOC014172 as new biomarkers for HCC.…”

Section: Lncrnas As Serum Biomarkers In Liver Cancermentioning

confidence: 99%

A New Understanding of Long Non-Coding RNA in Hepatocellular Carcinoma—From m6A Modification to Blood Biomarkers

Eun,

Cheong,

Jeong

et al. 2023

Cells

View full text Add to dashboard Cite

With recent advancements in biological research, long non-coding RNAs (lncRNAs) with lengths exceeding 200 nucleotides have emerged as pivotal regulators of gene expression and cellular phenotypic modulation. Despite initial skepticism due to their low sequence conservation and expression levels, their significance in various biological processes has become increasingly apparent. We provided an overview of lncRNAs and discussed their defining features and modes of operation. We then explored their crucial function in the hepatocarcinogenesis process, elucidating their complex involvement in hepatocellular carcinoma (HCC). The influential role of lncRNAs within the HCC tumor microenvironment is emphasized, illustrating their potential as key modulators of disease dynamics. We also investigated the significant influence of N6-methyladenosine (m6A) modification on lncRNA function in HCC, enhancing our understanding of both their roles and their upstream regulators. Additionally, the potential of lncRNAs as promising biomarkers was discussed in liver cancer diagnosis, suggesting a novel avenue for future research and clinical application. Finally, our work underscored the dual potential of lncRNAs as both contributors to HCC pathogenesis and innovative tools for its diagnosis. Existing challenges and prospective trajectories in lncRNA research are also discussed, emphasizing their potential in advancing liver cancer research.

show abstract

Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques

Samir,

Abdeldaim,

Mohammed

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Hepatocellular carcinoma (HCC) represents a significant health burden in Egypt, largely attributable to the endemic prevalence of hepatitis B and C viruses. Early identification of HCC remains a challenge due to the lack of widespread screening among at-risk populations. The objective of this study was to assess the utility of machine learning in predicting HCC by analyzing the combined expression of lncRNAs and conventional laboratory biomarkers. Plasma levels of four lncRNAs (LINC00152, LINC00853, UCA1, and GAS5) were quantified in a cohort of 52 HCC patients and 30 age-matched controls. The individual diagnostic performance of each lncRNA was assessed using ROC curve analysis. Subsequently, a machine learning model was constructed using Python’s Scikit-learn platform to integrate these lncRNAs with additional clinical laboratory parameters for HCC diagnosis. Individual lncRNAs exhibited moderate diagnostic accuracy, with sensitivity and specificity ranging from 60 to 83% and 53–67%, respectively. In contrast, the machine learning model demonstrated superior performance, achieving 100% sensitivity and 97% specificity. Notably, a higher LINC00152 to GAS5 expression ratio significantly correlated with increased mortality risk. The integration of lncRNA biomarkers with conventional laboratory data within a machine learning framework demonstrates significant potential for developing a precise and cost-effective diagnostic tool for HCC. To enhance the model’s robustness and prognostic capabilities, future studies should incorporate larger cohorts and explore a wider array of lncRNAs.

show abstract

The role of UCA1 and WRAP53 in diagnosis of hepatocellular carcinoma: A single-center case-control study

Cited by 3 publications

References 28 publications

Role of Non-Coding RNAs in TGF-β Signalling in Glioma

Role of Non-Coding RNAs in TGF-β Signalling in Glioma

A New Understanding of Long Non-Coding RNA in Hepatocellular Carcinoma—From m6A Modification to Blood Biomarkers

Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques

Contact Info

Product

Resources

About