Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression profiles of 186-gene signature in Italian hepatitis C virus (HCV)-related liver cirrhosis

ABSTRACT: OBJECTIVE: The number of patients with HCV-related cirrhosis is increasing, leading to a rising risk of complications and death. Prognostic stratification in patients with early-stage cirrhosis is still challenging. We aimed to develop and validate a clinically useful prognostic index based on genomic and clinical variables to identify patients at high risk of disease progression. DESIGN: We developed a prognostic index, comprised of a 186-gene signature validated in our previous genome-wide profiling study, bilirubin (>1 mg/dL) and platelet count (<100 000/mm3), in an Italian HCV cirrhosis cohort (training cohort, n=216, median follow-up 10 years). The gene signature test was implemented using a digital transcript counting (nCounter) assay specifically developed for clinical use and the prognostic index was evaluated using archived specimens from an independent cohort of HCV-related cirrhosis in the USA (validation cohort, n=145, median follow-up 8 years). RESULTS: In the training cohort, the prognostic index was associated with hepatic decompensation (HR=2.71, p=0.003), overall death (HR=6.00, p<0.001), hepatocellular carcinoma (HR=3.31, p=0.001) and progression of Child-Turcotte-Pugh class (HR=6.70, p<0.001). The patients in the validation cohort were stratified into high-risk (16%), intermediate-risk (42%) or low-risk (42%) groups by the prognostic index. The high-risk group had a significantly increased risk of hepatic decompensation (HR=7.36, p<0.001), overall death (HR=3.57, p=0.002), liver-related death (HR=6.49, p<0.001) and all liver-related adverse events (HR=4.98, p<0.001). CONCLUSIONS: A genomic and clinical prognostic index readily available for clinical use was successfully validated, warranting further clinical evaluation for prognostic prediction and clinical trial stratification and enrichment for preventive interventions. 90 liver tissue needle biopsy specimens from patients with histologically proven cirrhosis lacking evidence and a history of hepatic decompensation or HCC.

ORGANISM(S): Homo sapiens

SUBMITTER: Yujin Hoshida

PROVIDER: E-GEOD-54099 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration.

King Lindsay Y LY Canasto-Chibuque Claudia C Johnson Kara B KB Yip Shun S Chen Xintong X Kojima Kensuke K Deshmukh Manjeet M Venkatesh Anu A Tan Poh Seng PS Sun Xiaochen X Villanueva Augusto A Sangiovanni Angelo A Nair Venugopalan V Nair Venugopalan V Mahajan Milind M Kobayashi Masahiro M Kumada Hiromitsu H Iavarone Massimo M Colombo Massimo M Fiel Maria Isabel MI Friedman Scott L SL Llovet Josep M JM Chung Raymond T RT Hoshida Yujin Y

Gut 20140820 8

<h4>Objective</h4>The number of patients with HCV-related cirrhosis is increasing, leading to a rising risk of complications and death. Prognostic stratification in patients with early-stage cirrhosis is still challenging. We aimed to develop and validate a clinically useful prognostic index based on genomic and clinical variables to identify patients at high risk of disease progression.<h4>Design</h4>We developed a prognostic index, comprised of a 186-gene signature validated in our previous ge ...[more]

PMID: 25143343

Similar Datasets

Project description:OBJECTIVE: The number of patients with HCV-related cirrhosis is increasing, leading to a rising risk of complications and death. Prognostic stratification in patients with early-stage cirrhosis is still challenging. We aimed to develop and validate a clinically useful prognostic index based on genomic and clinical variables to identify patients at high risk of disease progression. DESIGN: We developed a prognostic index, comprised of a 186-gene signature validated in our previous genome-wide profiling study, bilirubin (>1?mg/dL) and platelet count (<100?000/mm3), in an Italian HCV cirrhosis cohort (training cohort, n=216, median follow-up 10?years). The gene signature test was implemented using a digital transcript counting (nCounter) assay specifically developed for clinical use and the prognostic index was evaluated using archived specimens from an independent cohort of HCV-related cirrhosis in the USA (validation cohort, n=145, median follow-up 8?years). RESULTS: In the training cohort, the prognostic index was associated with hepatic decompensation (HR=2.71, p=0.003), overall death (HR=6.00, p<0.001), hepatocellular carcinoma (HR=3.31, p=0.001) and progression of Child-Turcotte-Pugh class (HR=6.70, p<0.001). The patients in the validation cohort were stratified into high-risk (16%), intermediate-risk (42%) or low-risk (42%) groups by the prognostic index. The high-risk group had a significantly increased risk of hepatic decompensation (HR=7.36, p<0.001), overall death (HR=3.57, p=0.002), liver-related death (HR=6.49, p<0.001) and all liver-related adverse events (HR=4.98, p<0.001). CONCLUSIONS: A genomic and clinical prognostic index readily available for clinical use was successfully validated, warranting further clinical evaluation for prognostic prediction and clinical trial stratification and enrichment for preventive interventions. 145 liver tissue needle biopsy specimens from U.S. HCV cirrhosis cohort patients with histologically proven cirrhosis lacking evidence and a history of hepatic decompensation or HCC.

Project description:OBJECTIVE: The number of patients with HCV-related cirrhosis is increasing, leading to a rising risk of complications and death. Prognostic stratification in patients with early-stage cirrhosis is still challenging. We aimed to develop and validate a clinically useful prognostic index based on genomic and clinical variables to identify patients at high risk of disease progression. DESIGN: We developed a prognostic index, comprised of a 186-gene signature validated in our previous genome-wide profiling study, bilirubin (>1 mg/dL) and platelet count (<100 000/mm3), in an Italian HCV cirrhosis cohort (training cohort, n=216, median follow-up 10 years). The gene signature test was implemented using a digital transcript counting (nCounter) assay specifically developed for clinical use and the prognostic index was evaluated using archived specimens from an independent cohort of HCV-related cirrhosis in the USA (validation cohort, n=145, median follow-up 8 years). RESULTS: In the training cohort, the prognostic index was associated with hepatic decompensation (HR=2.71, p=0.003), overall death (HR=6.00, p<0.001), hepatocellular carcinoma (HR=3.31, p=0.001) and progression of Child-Turcotte-Pugh class (HR=6.70, p<0.001). The patients in the validation cohort were stratified into high-risk (16%), intermediate-risk (42%) or low-risk (42%) groups by the prognostic index. The high-risk group had a significantly increased risk of hepatic decompensation (HR=7.36, p<0.001), overall death (HR=3.57, p=0.002), liver-related death (HR=6.49, p<0.001) and all liver-related adverse events (HR=4.98, p<0.001). CONCLUSIONS: A genomic and clinical prognostic index readily available for clinical use was successfully validated, warranting further clinical evaluation for prognostic prediction and clinical trial stratification and enrichment for preventive interventions. Paired core needle liver biopsy specimens obtained with time interval ranging from 1 month to 7.5 years from three individuals, and liver tissues from right and left lobes of explanted liver with chronic HCV infection from one individual.

Project description:Background: Accurate survival stratification in early-stage NSCLC could inform the use of adjuvant therapy. We developed a clinically-implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables. Methods: Gene expression profiles from 1106 non-squamous NSCLCs were used for generation and internal validation of a 9-gene molecular prognostic index (MPI). Expression of the MPI genes was determined within sorted tumor cell subpopulations. A quantitative PCR (qPCR) assay was developed and validated on an independent cohort of FFPE tissues. A prognostic score using clinical variables was generated using Surveillance Epidemiology and End Results (SEER) data and combined with the MPI. Results: The MPI stratified stage I patients into prognostic categories in four independent validation datasets, including three microarray and one FFPE qPCR cohorts (HR=2.4, 95% CI, 1.8-3.3, P=7x10-9 in the largest microarray cohort; and HR=2.5, 95% CI 1.1-6.0, P=.03 in stage I patients of the qPCR validation cohort). Prognostic genes were expressed in distinct tumor cell subpopulations and expression of genes implicated in cellular proliferation and stem cells portended poor outcomes, while expression of genes involved in normal lung differentiation and immune infiltration was associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR=3.3, 95% CI 2.4-4.6; P=2x10-15 in the largest microarray cohort; and HR=3.6, 95% CI 1.5-8.8, P=.003 in stage I patients of the qPCR validation cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK. Conclusion: The MPI incorporates genes expressed in the tumor and its microenvironment, and designates risk of death for patients with early-stage non-squamous NSCLC. The MPI can be implemented clinically using qPCR assays on FFPE tissues and a composite model integrating the MPI with clinical variables provides the most accurate risk stratification.

Project description:To identify and evaluate the prognostic ability of progression-free survival-related profile for advanced-stage ovarian cancer, advanced-stage serous ovarian cancer tissues from 110 patients who received primary surgery and a platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays of more than 40,000 transcripts. We first selected 88 genes by a univariate Cox proportional hazard analysis (p<0.01) and next optimized regression coefficients by ridge regression model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p,0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). In multivariable analysis, our prognostic index was independently associated with progression-free survival times compared to other clinical factors (p<0.001). Furthermore, the prognostic ability of our prognostic index was validated in external, publicly available dataset (n = 87), and was proved in multivariate analysis (p = 0.0032). These results suggest that disease progression or recurrence of advanced-stage serous ovarian cancer can be predicted by gene expression profile. The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.

Dataset Information

Expression profiles of 186-gene signature in Italian hepatitis C virus (HCV)-related liver cirrhosis

Publications

A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure