Dataset Information

Prognostic classifier to identify intermediate and high-risk clear-cell renal cell carcinoma patients at higher risk for tumor progression

ABSTRACT: Background. Current clinicopathological factors are not accurate enough to predict tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC). Objective: To develop a prognostic classifier for intermediate/high-risk ccRCC based on gene expression and histopathological prognostic factors. Design, setting and participants: Retrospective, multicenter study including 84 intermediate/high-risk ccRCC patients who underwent surgery. Global gene expression patterns were analyzed in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 2000 kit. Expression levels of 22 selected genes were assessed by nCounter Analysis in an independent series of 71 ccRCC. A combined genetic-clinicopathological classifier for predicting tumor progression was developed. Outcomes measurements and statistical analysis: Logistic regression analysis was used to identify independent prognostic factors. Results and Limitations: A total of 1202 genes were found differentially expressed between progressive and non-progressive intermediate/high-risk ccRCC. In the independent cohort, 7 genes remained significant differentially expressed between the groups. Expression of HS6ST2, pT stage, tumor size and ISUP grade were found independent prognostic factors for tumor progression (p<0.05). A risk score generated using these variables was able to distinguish a subset of patients at higher-risk of progression (HR 7,27; p<0,001), improving the individual discriminative performance of each of these variables on their own. Conclusions: A novel prognostic algorithm based on genetic and clinicopathological factors was successfully developed. This model may aid physicians to select high-risk patients for further adjuvant target therapy or immune therapy.

ORGANISM(S): Homo sapiens

PROVIDER: GSE175648 | GEO | 2021/12/29

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

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. 90 liver tissue needle biopsy specimens from 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. 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:Purpose: In this study, we have undertaken the whole proteomic analysis and got a better understanding of biological processes involved in the development and progression of ccRCC. We hope promising biomarkers can be uncovered to facilitate early diagnosis, predict the prognosis and progression, more importantly, to be applied as potential therapeutic targets. Experimental design: Fresh frozen tissue samples were surgically resected from patients with local or locally advanced ccRCC. Trypsin digested proteins were analyzed using TMT-based LC-MS/MS proteomic approach, followed by bioinformatic analysis. A potential prognostic marker FMNL1, annotated with actin cytoskeleton assembly and cell migration, was chosen to be validated in TCGA_KIRC datasets(n=597), further validation sets(n=20) and expanded validation sets(n=97). Results: A total of 657 differentially expressed proteins were identified and quantified between ccRCC and adjacent normal tissues (p-value<0.05, FC>2 or<1/2), of which 186 proteins were up-regulated and 471 proteins were down-regulated. Bioinformatic analysis showed enriched metabolic biological processes and pathways including oxidative phosphorylation, valine, leucine and isoleucine degeneration, propanoate metabolism, fatty-acid degeneration, TCA cycle, glycolysis/gluconeogenesis, etc. Univariate and multivariate analysis defined FMNL1 as an independent negative prognostic marker in the TCGA datasets. High expression of FMNL1 correlated significantly with tumor stage, T stage, lymph node metastasis(P<0.05), and distant metastasis(P<0.05) both in the TCGA-KIRC datasets and expanded validation sets. And KM survival curve illustrated that patients with high FMNL1 protein level had shorter OS time in the expanded validation sets (p=0.0273) Conclusion and clinical relevance: The proteomic results uncovered sophisticated metabolic reprogramming of ccRCC and indicated that the upregulation of rate-limiting enzymes in glycolysis and mitochondrial impairment may be the cause of metabolic reprogramming in ccRCC. Moreover, FMNL1 has been identified as a diagnostic and prognostic marker, and may be implicated in the progression of ccRCC.

Dataset Information

Prognostic classifier to identify intermediate and high-risk clear-cell renal cell carcinoma patients at higher risk for tumor progression

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets