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Kim, Ji Hoon,Sohn, Bo Hwa,Lee, Hyun-Sung,Kim, Sang-Bae,Yoo, Jeong Eun,Park, Yun-Yong,Jeong, Woojin,Lee, Sung Sook,Park, Eun Sung,Kaseb, Ahmed,Kim, Baek Hui,Kim, Wan Bae,Yeon, Jong Eun,Byun, Kwan Soo,C Public Library of Science 2014 PLoS medicine Vol.11 No.12
<▼1><P>In this study, Lee and colleagues develop a genomic predictor that can identify patients at high risk for late recurrence of hepatocellular carcinoma (HCC) and provided new biomarkers for risk stratification.</P></▼1><▼2><P><B>Background</B></P><P>Typically observed at 2 y after surgical resection, late recurrence is a major challenge in the management of hepatocellular carcinoma (HCC). We aimed to develop a genomic predictor that can identify patients at high risk for late recurrence and assess its clinical implications.</P><P><B>Methods and Findings</B></P><P>Systematic analysis of gene expression data from human liver undergoing hepatic injury and regeneration revealed a 233-gene signature that was significantly associated with late recurrence of HCC. Using this signature, we developed a prognostic predictor that can identify patients at high risk of late recurrence, and tested and validated the robustness of the predictor in patients (<I>n = </I>396) who underwent surgery between 1990 and 2011 at four centers (210 recurrences during a median of 3.7 y of follow-up). In multivariate analysis, this signature was the strongest risk factor for late recurrence (hazard ratio, 2.2; 95% confidence interval, 1.3–3.7; <I>p</I> = 0.002). In contrast, our previously developed tumor-derived 65-gene risk score was significantly associated with early recurrence (<I>p</I> = 0.005) but not with late recurrence (<I>p</I> = 0.7). In multivariate analysis, the 65-gene risk score was the strongest risk factor for very early recurrence (<1 y after surgical resection) (hazard ratio, 1.7; 95% confidence interval, 1.1–2.6; <I>p</I> = 0.01). The potential significance of <I>STAT3</I> activation in late recurrence was predicted by gene network analysis and validated later. We also developed and validated 4- and 20-gene predictors from the full 233-gene predictor. The main limitation of the study is that most of the patients in our study were hepatitis B virus–positive. Further investigations are needed to test our prediction models in patients with different etiologies of HCC, such as hepatitis C virus.</P><P><B>Conclusions</B></P><P>Two independently developed predictors reflected well the differences between early and late recurrence of HCC at the molecular level and provided new biomarkers for risk stratification.</P><P><I>Please see later in the article for the Editors' Summary</I></P></▼2><▼3><P><B>Editors' Summary</B></P><P><B>Background</B></P><P>Primary liver cancer—a tumor that starts when a liver cell acquires genetic changes that allow it to grow uncontrollably—is the second-leading cause of cancer-related deaths worldwide, killing more than 600,000 people annually. If hepatocellular cancer (HCC; the most common type of liver cancer) is diagnosed in its early stages, it can be treated by surgically removing part of the liver (resection), by liver transplantation, or by local ablation, which uses an electric current to destroy the cancer cells. Unfortunately, the symptoms of HCC, which include weight loss, tiredness, and jaundice (yellowing of the skin and eyes), are vague and rarely appear until the cancer has spread throughout the liver. Consequently, HCC is rarely diagnosed before the cancer is advanced and untreatable, and has a poor prognosis (likely outcome)—fewer than 5% of patients survive for five or more years after diagnosis. The exact cause of HCC is unclear, but chronic liver (hepatic) injury and inflammation (caused, for example, by infection with hepatitis B virus [HBV] or by alcohol abuse) promote tumor development.</P><P><B>Why Was This Study Done?</B></P><P>Even when it is diagnosed early, HCC has a poor prognosis because it often recurs. Patients treated for HCC can experience two distinct types of tumor recurrence. Early recurrence, which usually happens within the first two years after surg
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Sixty‐five gene‐based risk score classifier predicts overall survival in hepatocellular carcinoma
Kim, Soo Mi,Leem, Sun‐,Hee,Chu, In‐,Sun,Park, Yun‐,Yong,Kim, Sang Cheol,Kim, Sang‐,Bae,Park, Eun Sung,Lim, Jae Yun,Heo, Jeonghoon,Kim, Yoon Jun,Kim, Dae‐,Ghon,Kaseb, Ahme Wiley Subscription Services, Inc., A Wiley Company 2012 Hepatology Vol.55 No.5
<P><B>Abstract</B></P><P>Clinical application of the prognostic gene expression signature has been delayed due to the large number of genes and complexity of prediction algorithms. In the current study we aimed to develop an easy‐to‐use risk score with a limited number of genes that can robustly predict prognosis of patients with hepatocellular carcinoma (HCC). The risk score was developed using Cox coefficient values of 65 genes in the training set (n = 139) and its robustness was validated in test sets (n = 292). The risk score was a highly significant predictor of overall survival (OS) in the first test cohort (<I>P</I> = 5.6 × 10<SUP>−5</SUP>, n = 100) and the second test cohort (<I>P</I> = 5.0 × 10<SUP>−5</SUP>, n = 192). In multivariate analysis, the risk score was a significant risk factor among clinical variables examined together (hazard ratio [HR], 1.36; 95% confidence interval [CI], 1.13‐1.64; <I>P</I> = 0.001 for OS). <I>Conclusion:</I> The risk score classifier we have developed can identify two clinically distinct HCC subtypes at early and late stages of the disease in a simple and highly reproducible manner across multiple datasets. (H<SMALL>EPATOLOGY</SMALL> 2011)</P>
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