Project description:Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.SignificanceThere is a great need for accessible and sensitive screening approaches for HCC worldwide. We have developed an approach for examining genome-wide cfDNA fragmentation features to provide a high-performing and cost-effective approach for liver cancer detection. See related commentary Rolfo and Russo, p. 532. This article is highlighted in the In This Issue feature, p. 517.
Project description:The Genetic Association Information Network (GAIN) Data Access Committee was established in June 2007 to provide prompt and fair access to data from six genome-wide association studies through the database of Genotypes and Phenotypes (dbGaP). Of 945 project requests received through 2011, 749 (79%) have been approved; median receipt-to-approval time decreased from 14 days in 2007 to 8 days in 2011. Over half (54%) of the proposed research uses were for GAIN-specific phenotypes; other uses were for method development (26%) and adding controls to other studies (17%). Eight data-management incidents, defined as compromises of any of the data-use conditions, occurred among nine approved users; most were procedural violations, and none violated participant confidentiality. Over 5 years of experience with GAIN data access has demonstrated substantial use of GAIN data by investigators from academic, nonprofit, and for-profit institutions with relatively few and contained policy violations. The availability of GAIN data has allowed for advances in both the understanding of the genetic underpinnings of mental-health disorders, diabetes, and psoriasis and the development and refinement of statistical methods for identifying genetic and environmental factors related to complex common diseases.
Project description:Azacitidine (AZA) and decitabine (DAC) are cytidine azanucleoside analogs with clinical activity in myelodysplastic syndromes (MDS) and potential activity in solid tumors. To better understand the mechanism of action of these drugs, we examined the effects of AZA and DAC in a panel of non-small cell lung cancer (NSCLC) cell lines. Of 5 NSCLC lines tested in a cell viability assay, all were sensitive to AZA (EC50 of 1.8M-bM-^@M-^S10.5 M-BM-5M), while only H1299 cells were equally sensitive to DAC (EC50 of 5.1 M-BM-5M). In the relatively DAC-insensitive cell line A549, both AZA and DAC caused DNA methyltransferase I depletion and DNA hypomethylation; however, only AZA significantly induced markers of DNA damage and apoptosis, suggesting that mechanisms in addition to, or other than, DNA hypomethylation are important for AZA-induced cell death. Cell cycle analysis indicated that AZA induced an accumulation of cells in sub-G1 phase, whereas DAC mainly caused an increase of cells in G2/M. Gene expression analysis of AZA- and DAC-treated cells revealed strikingly different profiles, with many genes distinctly regulated by each drug. In summary, while both AZA and DAC caused DNA hypomethylation, distinct effects were demonstrated on regulation of gene expression, cell cycle, DNA damage, and apoptosis. A549 and H1299 cells were treated with a dose range (0.3M-bM-^@M-^S3.0 M-NM-<M) of AZA or DAC for 48 hours, and effects on gene expression were assessed by microarray analysis.
Project description:Azacitidine (AZA) and decitabine (DAC) are cytidine azanucleoside analogs with clinical activity in myelodysplastic syndromes (MDS) and potential activity in solid tumors. To better understand the mechanism of action of these drugs, we examined the effects of AZA and DAC in a panel of non-small cell lung cancer (NSCLC) cell lines. Of 5 NSCLC lines tested in a cell viability assay, all were sensitive to AZA (EC50 of 1.8–10.5 µM), while only H1299 cells were equally sensitive to DAC (EC50 of 5.1 µM). In the relatively DAC-insensitive cell line A549, both AZA and DAC caused DNA methyltransferase I depletion and DNA hypomethylation; however, only AZA significantly induced markers of DNA damage and apoptosis, suggesting that mechanisms in addition to, or other than, DNA hypomethylation are important for AZA-induced cell death. Cell cycle analysis indicated that AZA induced an accumulation of cells in sub-G1 phase, whereas DAC mainly caused an increase of cells in G2/M. Gene expression analysis of AZA- and DAC-treated cells revealed strikingly different profiles, with many genes distinctly regulated by each drug. In summary, while both AZA and DAC caused DNA hypomethylation, distinct effects were demonstrated on regulation of gene expression, cell cycle, DNA damage, and apoptosis.
Project description:Liver damage is typically inferred from serum measurements of cytoplasmic liver enzymes. DNA molecules released from dying hepatocytes are an alternative biomarker, unexplored so far, potentially allowing for quantitative assessment of liver cell death. Here we describe a method for detecting acute hepatocyte death, based on quantification of circulating, cell-free DNA (cfDNA) fragments carrying hepatocyte-specific methylation patterns. We identified 3 genomic loci that are unmethylated specifically in hepatocytes, and used bisulfite conversion, PCR, and massively parallel sequencing to quantify the concentration of hepatocyte-derived DNA in mixed samples. Healthy donors had, on average, 30 hepatocyte genomes/ml plasma, reflective of basal cell turnover in the liver. We identified elevations of hepatocyte cfDNA in patients shortly after liver transplantation, during acute rejection of an established liver transplant, and also in healthy individuals after partial hepatectomy. Furthermore, patients with sepsis had high levels of hepatocyte cfDNA, which correlated with levels of liver enzymes aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Duchenne muscular dystrophy patients, in which elevated AST and ALT derive from damaged muscle rather than liver, did not have elevated hepatocyte cfDNA. We conclude that measurements of hepatocyte-derived cfDNA can provide specific and sensitive information on hepatocyte death, for monitoring human liver dynamics, disease, and toxicity.
Project description:JIMT-1 and T-47D cell lines, were transfected with a DCK expression vector and exposed to low-dose decitabine (DAC). DAC, a DNA methyltransferase (DNMT) inhibitor, is tested in combination with conventional anticancer drugs as a treatment option for various solid tumors.
Project description:BACKGROUND:The present study sought to identify a panel of DNA markers for noninvasive diagnosis using cell-free DNA (cfDNA) from urine supernatant or cellular DNA from urine sediments of hematuria patients. A panel of 48 bladder cancer-specific genes was selected. A next-generation sequencing-based assay with a cfDNA barcode-enabled single-molecule test was employed. Mutation profiles of blood, urine, and tumor sample from 16 bladder cancer patients were compared. Next, urinary cellular DNA and cfDNA were prospectively collected from 125 patients (92 bladder cancer cases and 33 controls) and analyzed using the 48-gene panel. The individual gene markers and combinations of markers were validated according to the pathology results. The mean areas under the receiver operating characteristic (ROC) curves (AUCs) obtained with the various modeling approaches were calculated and compared. RESULTS:This pilot study of 16 bladder cancer patients demonstrated that gene mutations in urine supernatant and sediments had better concordance with cancer tissue as compared with plasma. Logistic analyses suggested two powerful combinations of genes for genetic diagnostic modeling: five genes for urine supernatant (TERT, FGFR3, TP53, PIK3CA, and KRAS) and seven genes for urine sediments (TERT, FGFR3, TP53, HRAS, PIK3CA, KRAS, and ERBB2). The accuracy of the five-gene panel and the seven-gene panel in the validation cohort yielded AUCs of 0.94 [95% confidence interval (CI) 0.91-0.97] and 0.91 (95% CI 0.86-0.96), respectively. With the addition of age and gender, the diagnostic power of the urine supernatant five-gene model and the urine sediment seven-gene model improved as the revised AUCs were 0.9656 (95% CI 0.9368-0.9944) and 0.9587 (95% CI 0.9291-0.9883). CONCLUSIONS:cfDNA from urine bears great diagnostic potential. A five-gene panel for urine supernatant and a seven-gene panel for urine sediments are promising options for identifying bladder cancer in hematuria patients.