No abstract

In patients with clear cell RCC a prognostic model for survival that includes molecular and clinical predictors is significantly more accurate than a standard clinical model using the combination of stage, histological grade and performance status.

Purpose: An accurate system for predicting survival for patients with solid tumors will allow for better patient selection for both established and novel therapies. We propose a staging system for clear cell variants of renal cell carcinoma (RCC) that includes molecular predictors and standard clinical predictors such as tumor-node-metastasis (TNM) stage, histological grade, and performance status (PS).Experimental Design: A custom tissue array was constructed using clear cell RCC from 318 patients, representing all stages of localized and metastatic RCC, and immunohistochemically stained for molecular markers Ki67, p53, gelsolin, CA9, CA12, PTEN, EpCAM, and vimentin. We present a strategy for evaluating individual candidate markers for prognostic information and integrating informative markers into a multivariate prognostic system.Results: The overall median follow-up and the median follow-up for surviving patients were 28 and 55 months, respectively. A prognostic model based primarily on molecular markers included metastasis status, p53, CA9, gelsolin, and vimentin as predictors and had high discriminatory power: its statistically validated concordance index (Cindex) was found to be 0.75. A prognostic model based on a combination of clinical and molecular predictors included metastasis status, T stage, Eastern Cooperative Oncology Group PS, p53, CA9, and vimentin as predictors and had a C-index of 0.79, which was significantly higher (P < 0.05) than that of prognostic models based on grade alone (C ‫؍‬ 0.65), TNM stage alone (C ‫؍‬ 0.73), or the University of California Los Angeles integrated staging system (C ‫؍‬ 0.76).Conclusions: Protein expressions obtained using widely available technology can complement standard clinical predictors such as TNM stage, histological grade, and PS.

Purpose To investigate the utility of whole-exome sequencing (WES) to define a molecular diagnosis in patients clinically diagnosed with congenital anomalies of kidney and urinary tract (CAKUT). Methods WES was performed in 62 families with CAKUT. WES data were analyzed for Single Nucleotide Variants (SNVs) in 35 known CAKUT genes, putatively deleterious sequence changes in new candidate genes, and potentially disease-associated copy-number variants (CNVs). Results In approximately 5% of families, pathogenic SNVs were identified in PAX2, HNF1B, and EYA1. Observed phenotypes in these families expand the current understanding about the role of these genes in CAKUT. Four pathogenic CNVs were also identified using two CNV detection tools. In addition, we found one deleterious de novo SNV in FOXP1 among the 62 families with CAKUT. Database of clinical BMGL laboratory was queried and seven additional unrelated individuals with novel de novo SNVs in FOXP1 were identified. Six of these 8 individuals with FOXP1 SNVs, have syndromic urinary tract defects, implicating this gene in urinary tract development. Conclusion We conclude that WES can be used to identify the molecular etiology (SNVs, CNVs) in a subset of individuals with CAKUT. WES can also help identify novel CAKUT genes.