Creation of a tissue expression biomarker-augmented prognostic model for patients with metastatic renal cell carcinoma.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 703-703
Author(s):  
Bimal Bhindi ◽  
Christine M. Lohse ◽  
John C. Cheville ◽  
Ross Mason ◽  
Matthew K. Tollefson ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Model ◽  
External Validation ◽  
Survivin Expression ◽  
Tissue Expression ◽  
Multivariable Model ◽  
Cell Renal Cell Carcinoma ◽  
Clinical Metastases

703 Background: Clinical and pathologic factors alone have limited prognostic ability in patients with metastatic clear cell renal cell carcinoma (ccRCC). We sought to determine if tissue biomarkers, along with our previously reported clinical metastases score, can be used to predict cancer specific survival (CSS) in patients with metastatic ccRCC. Methods: Patients with metastatic ccRCC who underwent nephrectomy between 1990-2004 were identified using the Mayo Clinic Nephrectomy Registry. Sections from paraffin-embedded primary tumor tissue blocks were used for immunohistochemistry staining for PD-1, B7-H1 (PD-L1), B7-H3, Bim (downstream pro-apoptotic signaling molecule in PD-1 pathway), CA-IX, IMP3, Ki67, and survivin. CSS was the primary outcome. Biomarkers that were significantly associated with CSS after adjusting for the metastases score were used to develop a biomarker-specific multivariable model using a bootstrap resampling approach and forward selection. Predictive ability was summarized using a bootstrap-corrected c-index. Results: The cohort included 602 patients, 192 (32%) with metastases at diagnosis and 410 (68%) who developed metastases after nephrectomy. Median follow-up among survivors was 9.6 years (IQR 4.2,12.8) and 504 patients died of RCC. Bim, IMP3, Ki67, and survivin expression were significantly associated with CSS after adjusting for the metastases score and were used to develop a biomarker-specific model. High Bim (HR 1.44; 95%CI 1.16-1.78; p < 0.001), high survivin (HR 1.35; 95%CI 1.08-1.68; p = 0.008), and the metastases score (HR 1.13 per one point; 95%CI 1.10-1.16; p < 0.001) were retained as independent predictors in the final multivariable model (c-index 0.69). Conclusions: We created a prognostic model combining the clinical metastases score and two primary tissue expression biomarkers, Bim and survivin, for patients with metastatic RCC who underwent nephrectomy. External validation will be required prior to clinical use.

Proteomic stratification of clear cell renal cell carcinoma utilizing The Cancer Genome Atlas (TCGA) with external validation.

2015 ◽  
Vol 33 (7_suppl) ◽  
pp. 406-406
Author(s):  
Samuel D. Kaffenberger ◽  
Giovanni Ciriello ◽  
Andrew G. Winer ◽  
Martin Henner Voss ◽  
Jodi Kathleen Maranchie ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
External Validation ◽  
Mtor Pathway ◽  
The Cancer Genome Atlas ◽  
Genomic Alterations ◽  
Cell Renal Cell Carcinoma ◽  
Cluster 2

406 Background: Proteomics represents the ultimate convergence of DNA and expression alterations. We therefore sought to leverage TCGA reverse phase protein array (RPPA) data with an independent proteomic platform to identify druggable targets and pathways associated with prognosis in clear cell renal cell carcinoma (ccRCC). Methods: Unsupervised hierarchical consensus clustering was performed and differentially expressed proteins were identified for pathway analysis. Associations with clinicogenomic factors were assessed and Cox proportional hazards models were performed for disease-specific survival (DSS). Results: RPPA clustering of 324 patients from the ccRCC TCGA revealed 5 robust clusters characterized by alterations in specific pathways and divergent prognoses. Cluster 1 was characterized by poor DSS, decreased expression of receptor tyrosine kinases (RTK) and upregulation of the mTOR pathway. It was also associated with mTOR pathway genomic alterations, sarcomatoid histology and the ccb prognostic mRNA signature (all p<0.001). Cluster 2 was characterized by increased expression of RTKs and interestingly, had upregulation of the mTOR pathway with excellent DSS. After accounting for stage and grade, cluster designation remained independently associated with DSS (HR 0.23 for cluster 2, 95% CI 0.08-0.68; p=0.008). External validation was performed on a separate cohort of 189 patients with a different quantitative proteomics platform. A panel of phosphoproteins (pHER1, pHER2, pHER3, pSHC, pMEK, pAKT), highly discriminant between the most divergent RPPA clusters (1 and 2) was evaluated. Those at the highest quartile of activation in > 3 proteins were associated with improved DSS (HR 0.19, 95% CI 0.05-0.082; p=0.03). Patients with mTOR pathway activation segregated to those with coincident RTK activation (n=83) and those without (n=13). Conclusions: We have identified and validated proteomic signatures which cluster ccRCC patients into 5 prognostic groups. Furthermore, two distinct mTOR-activated clusters—one with high RTK activity and one with increased mTOR pathway genomic alterations were revealed, which may have prognostic and therapeutic implications.

scholarly journals A New Survival Model Based on ADAMTSs for Prognostic Prediction in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guangzhen Wu ◽  
Jianyi Li ◽  
Yingkun Xu ◽  
Xiangyu Che ◽  
Feng Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Model ◽  
Clear Cell ◽  
Survival Model ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Types

The main purpose of this study was to explore the genetic variation, gene expression, and clinical significance of ADAMTSs (a disintegrin and metalloprotease domains with thrombospondin motifs) across cancer types. Analysis of data from the TCGA (The Cancer Genome Atlas) database showed that the ADAMTSs have extensive CNV (copy number variation) and SNV (single nucleotide variation) across cancer types. Compared with normal tissues, the methylation of ADAMTSs in cancer tissues is also significantly different, which affects the expression of ADAMTS gene and the prognosis of cancer patients. Through gene expression analysis, we found that ADAMTS family has significant changes in gene expression across cancer types and is closely related to the prognosis of carcinoma, especially in ccRCC (clear cell renal cell carcinoma). LASSO regression analysis was used to establish a prognostic model based on the ADAMTSs to judge the prognosis of patients with ccRCC. Multiple Cox regression analysis suggested that age, grade, stage, and risk score of the prognostic model of ccRCC were independent prognostic factors in patients with renal clear cell carcinoma. These findings indicate that the ADAMTSs-based survival model can accurately predict the prognosis of patients with ccRCC and suggest that ADAMTSs are a potential prognostic biomarker and therapeutic target in ccRCC.

MicroRNA-15a tissue expression is a prognostic marker for survival in patients with clear cell renal cell carcinoma

2019 ◽  
Vol 19 (4) ◽  
pp. 515-524 ◽  
Author(s):  
Yulian Mytsyk ◽  
Yuriy Borys ◽  
Lesia Tumanovska ◽  
Dmytro Stroy ◽  
Askold Kucher ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Prognostic Marker ◽  
Renal Cell ◽  
Clear Cell ◽  
Tissue Expression ◽  
Cell Renal Cell Carcinoma

scholarly journals Development and external validation of a pathological nodal staging score for patients with clear cell renal cell carcinoma

2018 ◽  
Vol 37 (8) ◽  
pp. 1631-1637
Author(s):  
Malte Rieken ◽  
Stephen A. Boorjian ◽  
Luis A. Kluth ◽  
Umberto Capitanio ◽  
Alberto Briganti ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
External Validation ◽  
Nodal Staging ◽  
Cell Renal Cell Carcinoma

387 PLASMATIC METASTIN, KISSPEPTIN AND KISS1R TISSUE EXPRESSION AS BIOMARKERS IN CLEAR CELL RENAL CELL CARCINOMA (CCRCC)

2011 ◽  
Vol 185 (4S) ◽  
Author(s):  
Stefano Squillacciotti ◽  
Kai Krämer ◽  
Susanne Füssel ◽  
Mathias Meinhardt ◽  
Stefan Zastrow ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Tissue Expression ◽  
Cell Renal Cell Carcinoma
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