A novel medication decision gene signature predicts response to individualized therapy and prognosis outcomes in hepatocellular carcinoma patients
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ABSTRACT:
PROVIDER: PRJNA881935 | ENA |
REPOSITORIES: ENA
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Project description:Molecular targeted therapy has shown potential in hepatocellular carcinoma (HCC) patients, and immunotherapy applications are developing rapidly. However, clinical guidance for making individualized therapy decisions for HCC patients remains lacking. To facilitate individualized and reasonable clinical guidance for each HCC patient, we constructed the MDH score.
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2014-06-10 | GSE45684 | GEO
Project description:The source of most errors in RNA sequencing (RNA-seq) read alignment is in the repetitive structure of the genome and not with the alignment algorithm. Genetic variation away from the reference sequence exacerbates this problem causing reads to be assigned to the wrong location. We developed a method, implemented as the software package Seqnature, to construct the imputed genomes of individuals (individualized genomes) of experimental model organisms including inbred mouse strains and genetically unique outbred animals. Alignment to individualized genomes increases read mapping accuracy and improves transcript abundance estimates. In an application to expression QTL mapping, this approach corrected erroneous linkages and unmasked thousands of hidden associations. Individualized genomes accounting for genetic variation will be useful for human short-read sequencing and other sequencing applications including ChIP-seq. Illumina 100bp single-end liver RNA-seq from 277 male and female Diversity Outbred 26-week old mice raised on standard chow or high fat diet. In addition, Illumina 100bp single-end liver RNA-seq from 128 male 26-week old male mice (20 weeks for NZO strain) from each of the DO founder strains raised on standard chow or high fat diet (8 males per strain by diet group). Each sample was sequenced in 2-4x technical replicates across multiple flowcells. Samples were randomly assigned lanes and multiplexed at 12-24x.
2014-06-10 | E-GEOD-45684 | biostudies-arrayexpress
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2023-09-29 | GSE244095 | GEO
Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets. Two conditions were compared and each sample has a biological replicate. Samples are hybridized in dye-swap, resulting in 4 hybridizations.
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