Purpose: The purpose of this study was to determine the incidence and clinical significance of occult metastases in the lymph nodes of patients with prostate cancer originally considered node negative by routine histologic evaluation. Methods: Two hundred seventy four patients with pT3 prostate carcinoma treated by radical prostatectomy and bilateral lymph node dissection were included in this study. One hundred eighty patients were staged node negative (N0), while 94 patients were lymph node positive (N+), based on routine histologic evaluation. All lymph nodes from the 180 N0 patients were evaluated for occult metastases by immunohistochemistry using antibodies to cytokeratins and, if positive, prostate-specific antigen. Recurrence and overall survival were compared among patients with occult tumor cells (OLN+), with patients whose lymph nodes remained negative (OLN−), and with the 94 N+ patients. Results: A total of 3,914 lymph nodes were evaluated from 180 N0 patients (average, 21.7 lymph nodes per patient). Occult tumor cells were found in 24 of 180 patients (13.3%). The presence of OLN+ was significantly associated with increased recurrence and decreased survival compared with OLN− patients (P < .001 and P = .019, respectively; relative risk of recurrence, 2.27; relative risk of death 2.07, respectively). The presence of occult lymph node metastases was an independent predictor of recurrence and death in a multivariable analysis. The outcome for patients with OLN+ disease was similar to that for patients with N+ disease. Conclusion: The detection of occult lymph node metastases in patients with pT3N0 prostate cancer identifies those with significantly increased risk of prostate cancer recurrence and death.

Purpose: This study sought to determine if alterations in molecular pathways could supplement TNM staging to more accurately predict clinical outcome in patients with urothelial carcinoma (UC). Patients and Methods: Expressions of 69 genes involved in known cancer pathways were quantified on bladder specimens from 58 patients with UC (stages Ta-T4) and five normal urothelium controls. All tumor transcript values beyond two standard deviations from the normal mean expression were designated as over- or underexpressed. Univariate and multivariable analyses were conducted to obtain a predictive expression signature. A published external data set was used to confirm the potential of the prognostic gene panels. Results: In univariate analysis, six genes were significantly associated with time to recurrence, and 10 with overall survival. Recursive partitioning identified three genes as significant determinants for recurrence, and three for overall survival. Of all genes identified by either univariate or partitioning analysis, four were found to significantly predict both recurrence and survival (JUN, MAP2K6, STAT3, and ICAM1); overexpression was associated with worse outcome. Comparing the favorable (low or normal) expression of ≥ three of four versus ≤ two of four of these oncogenes showed 5-year recurrence probability of 41% versus 88%, respectively (P < .001), and 5-year overall survival probability of 61% versus 5%, respectively (P < .001). The prognostic potential of this four-gene panel was confirmed in a large independent external cohort (disease-specific survival, P = .039). Conclusion: We have documented the generation of a concise, biologically relevant four-gene panel that significantly predicts recurrence and survival and may also identify potential therapeutic targets for UC.

Background: Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. Methods: The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. Results: The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. Conclusion: Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR, CDK8 and ANXA5 in unique mathematical combinations in the progression towards nodal positivity. Further studies are needed to identify more class-specific signatures and confirm the role of these genes in the evolution of nodal metastasis in bladder cancer.