Project description:The pathogenesis of Colorectal cancer (CRC) metastasis remains unclear.We collect clinical data from our center and use Integrative omics to analyze and predict candidate biomarkers of colorectal cancer and distant metastasis.
Project description:we conducted integrative multiple levels of omics data including transcriptome, phosphoproteome, proteome and metabolome in different time-course of sepsis-associated liver dysfunction (SALD). This is the first trial to suggest the statistical pathway of integrative multi-omics data in sepsis. Given the increasing number of studies collecting multi-omics data but limited overview of the methodological framework for integrative analyses (Liu, Ding et al. 2013, Petersen, Zeilinger et al. 2014, Shah, Bonder et al. 2015), integrative approach in sepsis with liver dysfunction in this study will provide novel insights into the development of sepsis and ultimately offer new tools for overcoming the present diagnostic limitation. Therefore, a combined multi-omics dataset will give better accessibility of adoption in disease, and insight to identify the promising candidates for therapeutic strategies.
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.
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.
Project description:DNA methylation array data generated from epidermal samples (suction blister roofs) of healthy female subjects between 21 and 76 years. Aim of the project was the investigation of non-linearities in the human aging progression using an integrative multi-omics analysis. DNA was extracted from suction blisters taken from the volar forearms of each subject, bisulfite converted, and profiled using Illumina Infinium HumanMethylation450 BeadChip arrrays.
Project description:DNA methylation array data generated from epidermal samples (suction blister roofs) of healthy female subjects between 21 and 76 years. Aim of the project was the investigation of non-linearities in the human aging progression using an integrative multi-omics analysis. DNA was extracted from suction blisters taken from the volar forearms of each subject, bisulfite converted, and profiled using Illumina Infinium MethylationEPIC BeadChip arrrays.