Preliminary investigation of five novel long non-coding RNAs in hepatocellular carcinoma cell lines

Xia, Jufeng; Inagaki, Yoshiaki; Sawakami, Tatsuo; Song, Peipei; Cai, Yulong; Hasegawa, Kiyoshi; Sakamoto, Yoshihiro; Akimitsu, Nobuyoshi; Tang, Wei

doi:10.5582/bst.2016.01140

Cited by 5 publications

(4 citation statements)

References 17 publications

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“… 11 , 58 Regulation of PRC1-AS1 is known to differ with respect to different types of breast cancers, 72 and increased expression of PRC1-AS1 lncRNA is associated with hepatocellular carcinoma (MIM: 114550 ). 73 …”

Section: Resultsmentioning

confidence: 99%

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

Parrish

Gibson

Epstein

et al. 2022

Human Genetics and Genomics Advances

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Summary Standard transcriptome-wide association study (TWAS) methods first train gene expression prediction models using reference transcriptomic data and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we developed Transcriptome-Integrated Genetic Association Resource V2 (TIGAR-V2), which directly reads Variant Call Format (VCF) files, enables parallel computation, and reduces up to 90% of computation cost (mainly due to loading genotype data) compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet process regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWASs using either individual-level or summary-level genome-wide association study (GWAS) data, and implement both burden and variance-component statistics for gene-based association tests. We trained gene expression prediction models by DPR for 49 tissues using Genotype-Tissue Expression (GTEx) V8 by TIGAR-V2 and illustrated the usefulness of these Bayesian cis -expression quantitative trait locus (eQTL) weights through TWASs of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes, respectively, for breast and ovarian cancer, most of which are either known or near previously identified GWAS (∼95%) or TWAS (∼40%) risk genes and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWASs can provide biological insight into the transcriptional regulation of complex diseases. The TIGAR-V2 tool, trained Bayesian cis -eQTL weights, and linkage disequilibrium (LD) information from GTEx V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.

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Section: Resultsmentioning

confidence: 99%

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

Parrish

Gibson

Epstein

et al. 2022

Human Genetics and Genomics Advances

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“…For example, the expression of XLOC_007433 and AC144449.1 was found to be increased and decreased, respectively, in male patients with HBV-related HCC (88). In HBV-related HCC tissues and cell lines, n346077 (89) and uc.306 (90) are downregulated, while BAIAP2-AS1, PRC1-AS1, LINC00665 and AC092171.4 are upregulated (91,92). n346077 is associated with invasion and migration of HCC cells (89), and uc.306 is negatively correlated with the OS of HBV-related HCC patients (90).…”

Section: Dbh-as1 Dbh-as1mentioning

confidence: 97%

Long non‑coding RNAs in HBV‑related hepatocellular carcinoma (Review)

et al. 2019

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“…LncRNAs PRC1-AS1, LINC00665 and AC092171.4 are highly upregulated in HBV-infected HCC cell lines (106). AF085935 and uc003wbd are significantly expressed in the serum of HBVinfected HCC patients suggesting utility as potential biomarkers for detection of the disease (107).…”

Section: Lncrnas With Unknown Mechanisms In Hbv-related Hccmentioning

confidence: 99%

Diversity of Dysregulated Long Non-Coding RNAs in HBV-Related Hepatocellular Carcinoma

et al. 2022

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Infection with the hepatitis B virus (HBV) continues to pose a major threat to public health as approximately 292 million people worldwide are currently living with the chronic form of the disease, for which treatment is non-curative. Chronic HBV infections often progress to hepatocellular carcinoma (HCC) which is one of the world’s leading causes of cancer-related deaths. Although the process of hepatocarcinogenesis is multifaceted and has yet to be fully elucidated, several studies have implicated numerous long non-coding RNAs (lncRNAs) as contributors to the development of HCC. These host-derived lncRNAs, which are often dysregulated as a consequence of viral infection, have been shown to function as signals, decoys, guides, or scaffolds, to modulate gene expression at epigenetic, transcriptional, post-transcriptional and even post-translational levels. These lncRNAs mainly function to promote HBV replication and oncogene expression or downregulate tumor suppressors. Very few lncRNAs are known to suppress tumorigenesis and these are often downregulated in HCC. In this review, we describe the mechanisms by which lncRNA dysregulation in HBV-related HCC promotes tumorigenesis and cancer progression.

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Preliminary investigation of five novel long non-coding RNAs in hepatocellular carcinoma cell lines

Cited by 5 publications

References 17 publications

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

Long non‑coding RNAs in HBV‑related hepatocellular carcinoma (Review)

Diversity of Dysregulated Long Non-Coding RNAs in HBV-Related Hepatocellular Carcinoma

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