Integrate multi-omics analysis of LINC01767 in HCC
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ABSTRACT:
PROVIDER: PRJNA1017899 | ENA |
REPOSITORIES: ENA
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Project description:Hepatocellular carcinoma (HCC) is a significant contributor to cancer-related mortality rates worldwide. In previous studies, LINC01767, a type of ncRNAs, has been identified as playing a crucial role in the metastasis of colorectal cancer to the liver and was included in the diagnostic signature of HCC. No study of LINC01767 in HCC was published. We conducted a multi-omics analysis to examine the roles of LINC01767 in HCC at the first time. We employed bioinformatic analysis to evaluate its diagnostic and prognostic performance, as well as its correlation with clinical characteristics. We further used RNA sequencing and bioinformatic analysis to reveal the underlying mechanism, including its sensitivity to drugs. Our findings suggest that LINC01767 is a potential diagnostic marker and a stable independent OS predictor for HCC. It may associate with cancer stem cells in HCC, the RNA-seq and bioinformatic analysis identified its regulatory gene net and the potential sensitive drug including the PD1. The in vitro experiment verified it would influence the growth and clone formation of Huh7 cell.
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Project description:Rare cells exert substantial impact on tissue physiology and pathology across a spectrum of biological realms. The elucidation of their physiological functions through multi-omics analysis is pivotal. Nonetheless, advancements in trace-level cell multi-omics technology are impeded by cellular loss during experimental procedures. Mitochondrial DNA (mtDNA) editing facilitates disease modeling of mitochondrial genetic disorders in cell lines and animals, with potential for future therapeutic applications. However, the absence of technology capable of simultaneously assessing the efficiency of mitochondrial gene editors and molecular phenotypes limits the development of mitochondrial gene editors and their in vivo therapeutic applications. Here, to address these challenges, we devised a novel omics carrier microparticle, abbreviated as OmicsCam for driving low-input cells multi-omics. OmicsCam consists of three key components: miniaturized open microparticles for multi-step biochemistry, an enlarged cell chamber boundary for streamline manipulation and minimize cell loss, and tunable permeability to ensure compatibility with key steps of magnetic separation in automated systems. By refining OmicsCam's manufacturing process, optimizing cell permeation conditions, and fine-tuning multi-omics library biochemistry, we demonstrated simultaneous assessment of mtDNA editing efficiency (mtDNA sequencing), post-editing cellular transcriptome, and chromatin accessibility in minute cell samples containing as few as 25,000 cells. Moreover, we can concurrently analyze off-target effects of gene editing. The OmicsCam platform offers a powerful way for microscale cell multi-omics analysis, enabling interrogation mitochondrial gene editing efficiency and molecular phenotypes in a unified framework. This offers a holistic perspective on the consequences of genetic manipulation within the mitochondrial genome, thereby advancing our understanding of mitochondrial biology and facilitating the development of precision therapeutics for mitochondrial disorders.
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Project description:38 paires of tumor tissues and adjacent non-tumor tissues from HCC patients The number of known lncRNAs increased sharply upon the tiling microarrays and RNA-sequencing were applied to identify lncRNAs. However, only about a dozen of lncRNAs have been well characterized and demonstrated to be tightly associated with development and progression of HCC. A major challenge remains to identify functional lncRNAs associated with HCC. Previous reports mainly selected differentially expressed lncRNAs in cancer tissue or cell lines as candidates for further validation and characterizing. Here, based on mRNA and lncRNA gene expression profiles data collected from tumor and adjacent normal tissues of thirty-eight HCC patients, we adapted integrative omics strategy to identify HCC-associated lncRNAs.
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Project description:38 paires of tumor tissues and adjacent non-tumor tissues from HCC patients The number of known lncRNAs increased sharply upon the tiling microarrays and RNA-sequencing were applied to identify lncRNAs. However, only about a dozen of lncRNAs have been well characterized and demonstrated to be tightly associated with development and progression of HCC. A major challenge remains to identify functional lncRNAs associated with HCC. Previous reports mainly selected differentially expressed lncRNAs in cancer tissue or cell lines as candidates for further validation and characterizing. Here, based on mRNA and lncRNA gene expression profiles data collected from tumor and adjacent normal tissues of thirty-eight HCC patients, we adapted integrative omics strategy to identify HCC-associated lncRNAs.
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