Anirban P. Mitra

Discovery and Validation of a Prostate Cancer Genomic Classifier that Predicts Early Metastasis Following Radical Prostatectomy

Purpose Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67–0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.

Molecular Pathways in Invasive Bladder Cancer: New Insights Into Mechanisms, Progression, and Target Identification

Papillary and invasive cancers of the urinary bladder appear to evolve and progress through distinct molecular pathways. Invasion in bladder cancer forebodes a graver prognosis, and these tumors are generally characterized by alterations in the p53 and retinoblastoma (RB) pathways that normally regulate the cell cycle by interacting with the Ras-mitogen activated protein kinase signal transduction pathway. Tumor angiogenesis further contributes to the neoplastic growth by providing a constant supply of oxygen and nutrients. Distinct epigenetic and genetic events characterize the interplay between the molecules involved in these pathways, thus affording their use as indicators of prognosis. Efforts are now underway to construct molecular panels comprising multiple markers that can serve as more robust predictors of outcome. While clinical trials for targeted chemotherapy for bladder cancer have commenced, novel genetic and pharmacologic agents that can target pathway-specific molecules are currently under development. The next generation of clinical management for urothelial carcinoma will witness the use of multimarker panels for prognostic prediction and combination therapy directed at novel molecular targets for treatment.

Validation of a Genomic Classifier that Predicts Metastasis Following Radical Prostatectomy in an At Risk Patient Population

PURPOSE Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population. MATERIALS AND METHODS A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20% random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 219 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance. RESULTS The genomic classifier AUC was 0.79 for predicting 5-year metastasis after radical prostatectomy. Decision curves showed that the genomic classifier net benefit exceeded that of clinical only models. The genomic classifier was the predominant predictor of metastasis on multivariable analysis. The cumulative incidence of metastasis 5 years after radical prostatectomy was 2.4%, 6.0% and 22.5% in patients with low (60%), intermediate (21%) and high (19%) genomic classifier scores, respectively (p<0.001). CONCLUSIONS Results indicate that genomic information from the primary tumor can identify patients with adverse pathological features who are most at risk for metastasis and potentially lethal prostate cancer.

Molecular Pathogenesis and Diagnostics of Bladder Cancer

Despite elaborate characterization of the risk factors, bladder cancer is still a major epidemiological problem whose incidence continues to rise each year. Urothelial carcinoma is now recognized as a disease of alterations in several cellular processes. The more prevalent, less aggressive, recurrent, noninvasive tumors are characterized by constitutive activation of the Ras-MAPK pathway. The less common but more aggressive invasive tumors, which have a higher mortality rate, are characterized by alterations in the p53 and retinoblastoma pathways. Several diagnostic tests have attempted to identify these molecular alterations in tumor cells exfoliated in the urine, whereas prognostic tests have tried to identify aberrations so as to predict tumor behavior and identify therapeutic targets. The future of bladder cancer patient management will rely on the use of molecular tests to reliably diagnose the presence of disease, predict individual tumor behavior, and suggest potential targeted therapeutics.

Enhanced Recovery Protocol after Radical Cystectomy for Bladder Cancer

PURPOSE Enhanced recovery after surgery protocols aim to improve patient care and decrease complications and hospital stay. We evaluated our enhanced recovery after surgery protocol, focusing on length of stay, early complication and readmission rates after radical cystectomy for bladder cancer. MATERIALS AND METHODS From May 2012 to July 2013 a perioperative protocol was applied in 126 consecutive patients who underwent open radical cystectomy and urinary diversion. Nonconsenting patients (2), those with previous diversion (2) and prolonged postoperative intubation (3), and those who underwent additional surgery (9) were excluded from study. The protocol focuses on avoiding bowel preparation and nasogastric tube, early feeding, nonnarcotic pain management and the use of cholinergic and μ-opioid antagonists. Outcomes were compared to those in matched controls from our bladder cancer database. RESULTS A total of 110 patients with a median age of 69 years were included in analysis, of whom 68% underwent continent urinary diversion. Of the patients 82% had a bowel movement by postoperative day 2. Median length of stay was 4 days. The 30-day minor and major complication rates were 64% and 14%, respectively. The most common minor complication was anemia requiring transfusion in 19% of patients, urinary tract infection in 13% and dehydration in 10%. The latter 2 complications were the most common etiologies for readmission. The 30-day readmission rate was 21% (23 patients). Patients 75 years old or older had a longer length of stay (5 vs 4 days, p = 0.03) and a higher minor complication rate (72% vs 51%, p = 0.04) than younger patients. CONCLUSIONS Our enhanced recovery after surgery protocol expedites bowel function recovery and shortens hospital stay after RC and urinary diversion without an increase in the hospital readmission rates.

A Central Role for Long Non-Coding RNA in Cancer

Long non-coding RNAs (ncRNAs) have been shown to regulate important biological processes that support normal cellular functions. Aberrant regulation of these essential functions can promote tumor development. In this review, we underscore the importance of the regulatory role played by this distinct class of ncRNAs in cancer-associated pathways that govern mechanisms such as cell growth, invasion, and metastasis. We also highlight the possibility of using these unique RNAs as diagnostic and prognostic biomarkers in malignancies.

Generation of a Concise Gene Panel for Outcome Prediction in Urinary Bladder Cancer

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 > or = three of four versus < or = 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.

A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy

Background:Due to their varied outcomes, men with biochemical recurrence (BCR) following radical prostatectomy (RP) present a management dilemma. Here, we evaluate Decipher, a genomic classifier (GC), for its ability to predict metastasis following BCR.Methods:The study population included 85 clinically high-risk patients who developed BCR after RP. Time-dependent receiver operating characteristic (ROC) curves, weighted Cox proportional hazard models and decision curves were used to compare GC scores to Gleason score (GS), PSA doubling time (PSAdT), time to BCR (ttBCR), the Stephenson nomogram and CAPRA-S for predicting metastatic disease progression. All tests were two-sided with a type I error probability of 5%.Results:GC scores stratified men with BCR into those who would or would not develop metastasis (8% of patients with low versus 40% with high scores developed metastasis, P<0.001). The area under the curve for predicting metastasis after BCR was 0.82 (95% CI, 0.76–0.86) for GC, compared to GS 0.64 (0.58–0.70), PSAdT 0.69 (0.61–0.77) and ttBCR 0.52 (0.46–0.59). Decision curve analysis showed that GC scores had a higher overall net benefit compared to models based solely on clinicopathologic features. In multivariable modeling with clinicopathologic variables, GC score was the only significant predictor of metastasis (P=0.003).Conclusions:When compared to clinicopathologic variables, GC better predicted metastatic progression among this cohort of men with BCR following RP. While confirmatory studies are needed, these results suggest that use of GC may allow for better selection of men requiring earlier initiation of treatment at the time of BCR.

Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

BACKGROUND Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based on specific tumor biology, are yet to be identified. OBJECTIVE To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. DESIGN, SETTING, AND PARTICIPANTS Retrospective study of patients with Ta G2/3 bladder tumors at initial presentation with three distinct clinical outcomes: absence of recurrence (n=16), recurrence without progression (n=16), and progression to carcinoma in situ or invasive disease (n=16). MEASUREMENTS Expressions of 24 genes that feature in relevant pathways that are deregulated in bladder cancer were quantified by real-time polymerase chain reaction on tumor biopsies from the patients at initial presentation. RESULTS AND LIMITATIONS CCND3 (p=0.003) and HRAS (p=0.01) were predictive for recurrence by univariate analysis. In a multivariable model based on CCND3 expression, sensitivity and specificity for recurrence were 97% and 63%, respectively. HRAS (p<0.001), E2F1 (p=0.017), BIRC5/Survivin (p=0.038), and VEGFR2 (p=0.047) were predictive for progression by univariate analysis. Multivariable analysis based on HRAS, VEGFR2, and VEGF identified progression with 81% sensitivity and 94% specificity. Since this is a small retrospective study using medium-throughput profiling, larger confirmatory studies are needed. CONCLUSIONS Gene expression profiling across relevant cancer pathways appears to be a promising approach for Ta bladder tumor outcome prediction at initial diagnosis. These results could help differentiate between patients who need aggressive versus expectant management.

Factors influencing post‐recurrence survival in bladder cancer following radical cystectomy

Study Type – Prognosis (individual cohort)