AIM： To study a more accurate quantification of hepatic fibrosis which would provide dinically useful information for monitoring the progression of chronic liver disease. METHODS： Using a cDNA microarray containing ...AIM： To study a more accurate quantification of hepatic fibrosis which would provide dinically useful information for monitoring the progression of chronic liver disease. METHODS： Using a cDNA microarray containing over 22000 clones, we analyzed the gene-expression profiles of non-cancerous liver in 74 patients who underwent hepatic resection. We calculated the ratio of azanstained： total area, and determined the morphologic fibrosis index （MFI）, as a mean of 9 section-images. We used the MFI as a reference standard to evaluate our method for assessing liver fibrosis. RESULTS： We identified 39 genes that collectively showed a good correlation （r 〉 0.50） between geneexpression and the severity of liver fibrosis. Many of the identified genes were involved in immune responses and cell signaling. To quantify the extent of liver fibrosis, we developed a new genetic fibrosis index （GFI） based on gene-expression profiling of 4 clones using a linear support vector regression analysis. This technique, based on a supervised learning analysis, correctly quantified the various degrees of fibrosis in both 74 training samples （r = 0.76, 2.2% vs 2.8%, P 〈 0.0001） and 12 independent additional test samples （r = 0.75, 9.8% vs 8.6%, P 〈 0.005）. It was far better in assessing liver fibrosis than blood markers such as prothrombin time （r = -0.53）, type IV collagen 7s （r = 0.48）, hyaluronic acid （r = 0.41）, and aspartate aminotransferase to platelets ratio index （APRI） （r = 0.38）. CONCLUSION： Our cDNA microarray-based strategy may help clinicians to precisely and objectively monitor the severity of liver fibrosis.展开更多
Following the publication of the US National Research Council （N RC） report ＂ Toward PrecMon Medicine.＂ Building a Knowledge Network for Biomedical Research and a New Taxonomy of Diseases＂ in 2011 [1], several n...Following the publication of the US National Research Council （N RC） report ＂ Toward PrecMon Medicine.＂ Building a Knowledge Network for Biomedical Research and a New Taxonomy of Diseases＂ in 2011 [1], several nations have announced that their national research programs would definitely head toward this direction. Now,展开更多
基金Supported partly by Grants-in-Aid for Scientific Research (S) (17109013) and for Scientific Research (C) (17591411 and 15591411)a Health and Labor Sciences Research Grant on Hepatitis and BSE (14230801)the Uehara Memorial Foundation, Yasuda Medical Research Foundation, Japanese Foundation for Multidisciplinary Treatment of Cancer, and Princes Takamatsu Cancer research Fund
文摘AIM： To study a more accurate quantification of hepatic fibrosis which would provide dinically useful information for monitoring the progression of chronic liver disease. METHODS： Using a cDNA microarray containing over 22000 clones, we analyzed the gene-expression profiles of non-cancerous liver in 74 patients who underwent hepatic resection. We calculated the ratio of azanstained： total area, and determined the morphologic fibrosis index （MFI）, as a mean of 9 section-images. We used the MFI as a reference standard to evaluate our method for assessing liver fibrosis. RESULTS： We identified 39 genes that collectively showed a good correlation （r 〉 0.50） between geneexpression and the severity of liver fibrosis. Many of the identified genes were involved in immune responses and cell signaling. To quantify the extent of liver fibrosis, we developed a new genetic fibrosis index （GFI） based on gene-expression profiling of 4 clones using a linear support vector regression analysis. This technique, based on a supervised learning analysis, correctly quantified the various degrees of fibrosis in both 74 training samples （r = 0.76, 2.2% vs 2.8%, P 〈 0.0001） and 12 independent additional test samples （r = 0.75, 9.8% vs 8.6%, P 〈 0.005）. It was far better in assessing liver fibrosis than blood markers such as prothrombin time （r = -0.53）, type IV collagen 7s （r = 0.48）, hyaluronic acid （r = 0.41）, and aspartate aminotransferase to platelets ratio index （APRI） （r = 0.38）. CONCLUSION： Our cDNA microarray-based strategy may help clinicians to precisely and objectively monitor the severity of liver fibrosis.
文摘Following the publication of the US National Research Council （N RC） report ＂ Toward PrecMon Medicine.＂ Building a Knowledge Network for Biomedical Research and a New Taxonomy of Diseases＂ in 2011 [1], several nations have announced that their national research programs would definitely head toward this direction. Now,
