LncRNA ASTILCS as an important regulator of liver carcinoma cell survival
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA639962 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12032778.fastq.gz | Fastqsanger.gz | |||
| SRR12032779.fastq.gz | Fastqsanger.gz | |||
| SRR12032780.fastq.gz | Fastqsanger.gz | |||
| SRR12032781.fastq.gz | Fastqsanger.gz | |||
| SRR12032782.fastq.gz | Fastqsanger.gz |
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Project description:LncRNA ASTILCS as an important regulator of liver carcinoma cell survival [shRNA cassette seq]
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Project description:LncRNA ASTILCS as an important regulator of liver carcinoma cell survival [non-coding RNA-Seq]
| PRJNA639970 | ENA
Project description:Extensive genomic studies have significantly improved our understanding of hepatocellular carcinoma (HCC) biology and have led to the discovery of multiple protein-coding genes driving hepatocarcinogenesis. In addition, these studies have identified thousands of new non-coding transcripts deregulated in HCC, suggesting these transcripts are important for disease progression. Long non-coding RNA is a large class of non-coding transcripts which participate in the regulation of virtually all cellular functions. However, a majority of lncRNAs remain dramatically understudied. Here, we applied a pooled shRNA-based screen to identify lncRNAs essential for HCC cell survival. We validated our screening results using RNAi, CRISPRi, and antisense oligonucleotides. We found a lncRNA, termed ASTILCS, is critical for HCC cell growth and is overexpressed in tumors from HCC patients. We demonstrated that HCC cell death upon ASTILCS knockdown is associated with apoptosis induction and downregulation of a neighboring gene, Protein Tyrosine Kinase 2 (PTK2), a crucial protein for HCC cell survival. Taken together, our study describes a novel regulator of HCC progression providing valuable insight in HCC biology.
2021-02-02 | GSE152649 | GEO
Project description:Extensive genomic studies have significantly improved our understanding of hepatocellular carcinoma (HCC) biology and have led to the discovery of multiple protein-coding genes driving hepatocarcinogenesis. In addition, these studies have identified thousands of new non-coding transcripts deregulated in HCC, suggesting these transcripts are important for disease progression. Long non-coding RNA is a large class of non-coding transcripts which participate in the regulation of virtually all cellular functions. However, a majority of lncRNAs remain dramatically understudied. Here, we applied a pooled shRNA-based screen to identify lncRNAs essential for HCC cell survival. We validated our screening results using RNAi, CRISPRi, and antisense oligonucleotides. We found a lncRNA, termed ASTILCS, is critical for HCC cell growth and is overexpressed in tumors from HCC patients. We demonstrated that HCC cell death upon ASTILCS knockdown is associated with apoptosis induction and downregulation of a neighboring gene, Protein Tyrosine Kinase 2 (PTK2), a crucial protein for HCC cell survival. Taken together, our study describes a novel regulator of HCC progression providing valuable insight in HCC biology.
2021-02-02 | GSE152650 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2021-02-02 | GSE152651 | GEO
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction. The lncRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were studied by microarray and an lncRNA signature that can perdict the survival of ESCC patients was identified.
2014-03-07 | E-GEOD-53624 | biostudies-arrayexpress
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction. The lncRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were studied by microarray and an lncRNA signature that can perdict the survival of ESCC patients was identified.
2014-03-07 | E-GEOD-53622 | biostudies-arrayexpress
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction.
2014-03-07 | GSE53624 | GEO
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction.
2014-03-07 | GSE53622 | GEO
Project description:There is increasing evidence that the architecture of long non-coding RNAs – just like that of proteins – is hierarchically organized into independently folding sub-modules with distinct functions. Studies characterizing the cellular activities of such modules, however, are rare. The lncRNA growth arrest specific 5 (Gas5) is a key regulator of cell survival in response to stress and nutrient availability. We used SHAPE-MaP to probe the structure of Gas5 in vitro and in cellulo. The results show that Gas5 contains three separate structural modules including the previously predicted steroid receptor binding hairpin motif. Functional assays show that the newly identified modules act independently in leukemic T cells. The 5’ terminal module with low secondary structure content affects basal survival and slows the cell cycle, whereas the highly structured core module mediates the effects of mTOR inhibition on cell growth. Disruption of specific secondary structures within the modules abolish their function in cells. These results highlight the central role of Gas5 in regulating cell survival and reveals how a single lncRNA transcript utilizes a modular structure-function relationship to respond to a variety of cellular stresses under various cellular conditions.
2021-04-07 | PXD018584 | Pride