Ignite Creation Date:
2024-05-06 @ 12:11 PM
Last Modification Date:
2024-10-26 @ 12:55 PM
Study NCT ID:
NCT03694912
Status:
UNKNOWN
Last Update Posted:
2019-09-17
First Post:
2018-09-28
Brief Title:
Development and Evaluation of High Risk Group Prediction Model in T1 Stage Renal Cell Cancer Using Molecular Biomarkers
Sponsor:
Yonsei University
Organization:
Yonsei University
Study Overview
Official Title:
Development and Evaluation of High Risk Group Prediction Model in T1 Stage Renal Cell Cancer Using Molecular Biomarkers
Status:
UNKNOWN
Status Verified Date:
2019-09
Last Known Status:
RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
For the appropriate individualized treatment of T1-stage renal cell carcinoma with heterogeneous biological features the expression of PBRM1 SETD2 BAP1 KDM5C and the newly proposed FOXC2 and CLIP4 are compared with clinical features The investigators evaluated the efficacy of FOXC2 and CLIP4 as prognostic biomarkers and developed a high risk prediction model based on these results In a previous study the investigators evaluated the efficacy of FOXC2 and CLIP4 as prognostic biomarkers and reported their association with synchronous metastasis in renal cell carcinomas less than 7 cm in size The investigators analyzed the expression level of renal cell carcinoma according to the size and malignancy Fuhrman grade of renal cell carcinoma in T1-stage clear cell type renal cell carcinoma of tumor size less than 7cm The aim of this study was to analyze the association of tumor recurrence or metastasis cancer specific survival rate overall survival rate tumor size malignancy and T stage in postoperative biopsy For expression analysis PCR amplification and bidirectional Sanger sequencing and mRNA expression analysis qRT-PCR were used For statistical analysis Fisher exact test Wilcoxon exact 2-tailed test Cox proportional hazard regression analysis and competing risk method were used In this study the investigators compared the expression of PBRM1 SETD2 BAP1 and KDM5 with newly proposed biomarkers FOXC2 and CLIP4 and demonstrate the prognostic value of FOXC2 and CLIP4 as new prognostic biomarkers and compared the clinical outcomes with the clinical outcome Based on these results the investigators propose a high risk prediction model for individualized treatment of T1-stage renal cell carcinoma This study is expected to establish a new prediction model and molecular biologic stage for risk stratification of T1-stage renal cell carcinoma patients and apply genetic test for selection of optimal tailored treatment for T1-stage renal cell carcinoma In addition it will be an important basic data of the molecular biologic mechanism of metastasis in early renal cell carcinoma and may be used as a basic data for the development and selection of customized therapeutic agents in patients with distant metastasis
Detailed Description:
collection of FFPE samples collection of primary or metastatic site
micro-dissection only when the tumor contents are more than 90 are analyzed
B Data analysis and model development
Development goals - Analysis of prospective biomarker expression in FFPE and frozen tissue specimens
- Development of a high-risk prediction model for post-surgical morbidity in T1-stage RCC
Contents and scope
1 Expression analysis of prospective biomarkers in FFPE and frozen tissue samples of T1-stage clear cell type RCC PBRM1 SETD2 BAP1 and KDM5C expressed as prognostic biomarkers of renal cell carcinoma in other studies
The newly proposed FOXC2 CLIP4
1 Mutational analysis Transcriptome sequencing with variant calling
2 mRNA expression analysis qRT-PCR - only when the tumor contents are more than 90 are analyzed
- Analysis of tumor size and malignancy as a prognostic predictor of RCC
- The expression of primary and metastatic lesions was analyzed by considering intratumor heterogeneity in RCC Fisher exact test Wilcoxon exact 2-tailed test
Analysis of association with postoperative local recurrence or distant metastasis cancer-specific survival and overall survival Cox proportional hazard regression analysis Time to recurrence and distant metastasis overall survival competing risk method cancer specific survival
2 Development of predictive model for high-risk molecular disease in T1-Stage RCC survival rate - elastic net Cox model in glmnet version 173
- prediction accuracy was evaluated using Harrel concordance probability C-index internal validation was performed using bootstrap
3 Development of predictive model for preoperative molecular high risk in T1- Stage RCC for Poor Pathologic Findings
multivariate logisticlinear regression model
prediction accuracy was evaluated using Harrel concordance probability C-index internal validation was performed using bootstrap
micro-dissection only when the tumor contents are more than 90 are analyzed
B Data analysis and model development
Development goals - Analysis of prospective biomarker expression in FFPE and frozen tissue specimens
- Development of a high-risk prediction model for post-surgical morbidity in T1-stage RCC
Contents and scope
1 Expression analysis of prospective biomarkers in FFPE and frozen tissue samples of T1-stage clear cell type RCC PBRM1 SETD2 BAP1 and KDM5C expressed as prognostic biomarkers of renal cell carcinoma in other studies
The newly proposed FOXC2 CLIP4
1 Mutational analysis Transcriptome sequencing with variant calling
2 mRNA expression analysis qRT-PCR - only when the tumor contents are more than 90 are analyzed
- Analysis of tumor size and malignancy as a prognostic predictor of RCC
- The expression of primary and metastatic lesions was analyzed by considering intratumor heterogeneity in RCC Fisher exact test Wilcoxon exact 2-tailed test
Analysis of association with postoperative local recurrence or distant metastasis cancer-specific survival and overall survival Cox proportional hazard regression analysis Time to recurrence and distant metastasis overall survival competing risk method cancer specific survival
2 Development of predictive model for high-risk molecular disease in T1-Stage RCC survival rate - elastic net Cox model in glmnet version 173
- prediction accuracy was evaluated using Harrel concordance probability C-index internal validation was performed using bootstrap
3 Development of predictive model for preoperative molecular high risk in T1- Stage RCC for Poor Pathologic Findings
multivariate logisticlinear regression model
prediction accuracy was evaluated using Harrel concordance probability C-index internal validation was performed using bootstrap
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None