Alex Tsodikov

A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

Although prostate-specific antigen (PSA) serum level is currently the standard of care for prostate cancer screening in the United States, it lacks ideal specificity and additional biomarkers are needed to supplement or potentially replace serum PSA testing. Emerging evidence suggests that monitoring the noncoding RNA transcript PCA3 in urine may be useful in detecting prostate cancer in patients with elevated PSA levels. Here, we show that a multiplex panel of urine transcripts outperforms PCA3 transcript alone for the detection of prostate cancer. We measured the expression of seven putative prostate cancer biomarkers, including PCA3, in sedimented urine using quantitative PCR on a cohort of 234 patients presenting for biopsy or radical prostatectomy. By univariate analysis, we found that increased GOLPH2, SPINK1, and PCA3 transcript expression and TMPRSS2:ERG fusion status were significant predictors of prostate cancer. Multivariate regression analysis showed that a multiplexed model, including these biomarkers, outperformed serum PSA or PCA3 alone in detecting prostate cancer. The area under the receiver-operating characteristic curve was 0.758 for the multiplexed model versus 0.662 for PCA3 alone (P = 0.003). The sensitivity and specificity for the multiplexed model were 65.9% and 76.0%, respectively, and the positive and negative predictive values were 79.8% and 60.8%, respectively. Taken together, these results provide the framework for the development of highly optimized, multiplex urine biomarker tests for more accurate detection of prostate cancer.

Quantifying the role of PSA screening in the US prostate cancer mortality decline

ObjectiveTo quantify the plausible contribution of prostate-specific antigen (PSA) screening to the nearly 30% decline in the US prostate cancer mortality rate observed during the 1990s.MethodsTwo mathematical modeling teams of the US National Cancer Institute’s Cancer Intervention and Surveillance Modeling Network independently projected disease mortality in the absence and presence of PSA screening. Both teams relied on Surveillance, Epidemiology, and End Results (SEER) registry data for disease incidence, used common estimates of PSA screening rates, and assumed that screening, by shifting disease from distant to local-regional clinical stage, confers a corresponding improvement in disease-specific survival.ResultsThe teams projected similar mortality increases in the absence of screening and decreases in the presence of screening after 1985. By 2000, the models projected that 45% (Fred Hutchinson Cancer Research Center) to 70% (University of Michigan) of the observed decline in prostate cancer mortality could be plausibly attributed to the stage shift induced by screening.ConclusionsPSA screening may account for much, but not all, of the observed drop in prostate cancer mortality. Other factors, such as changing treatment practices, may also have played a role in improving prostate cancer outcomes.

The role of SPINK1 in ETS rearrangement-negative prostate cancers

ETS gene fusions have been characterized in a majority of prostate cancers; however, the key molecular alterations in ETS-negative cancers are unclear. Here we used an outlier meta-analysis (meta-COPA) to identify SPINK1 outlier expression exclusively in a subset of ETS rearrangement-negative cancers ( approximately 10% of total cases). We validated the mutual exclusivity of SPINK1 expression and ETS fusion status, demonstrated that SPINK1 outlier expression can be detected noninvasively in urine, and observed that SPINK1 outlier expression is an independent predictor of biochemical recurrence after resection. We identified the aggressive 22RV1 cell line as a SPINK1 outlier expression model and demonstrate that SPINK1 knockdown in 22RV1 attenuates invasion, suggesting a functional role in ETS rearrangement-negative prostate cancers.

Estimating Cure Rates From Survival Data: An Alternative to Two-Component Mixture Models.

This article considers the utility of the bounded cumulative hazard model in cure rate estimation, which is an appealing alternative to the widely used two-component mixture model. This approach has the following distinct advantages: (1) It allows for a natural way to extend the proportional hazards regression model, leading to a wide class of extended hazard regression models. (2) In some settings the model can be interpreted in terms of biologically meaningful parameters. (3) The model structure is particularly suitable for semiparametric and Bayesian methods of statistical inference. Notwithstanding the fact that the model has been around for less than a decade, a large body of theoretical results and applications has been reported to date. This review article is intended to give a big picture of these modeling techniques and associated statistical problems. These issues are discussed in the context of survival data in cancer.

Stochastic Models of Tumor Latency and Their Biostatistical Applications

Statistical inference from censored data mathematical description of tumour latency regression analysis of tumour recurrence data threshold models of tumor growth statistical analysis of discrete cancer surveillance optimal strategies of cancer surveillance - minimum delay time approach, minimum cost approach.

Lymphoma After Solid Organ Transplantation: Risk, Response to Therapy, and Survival at a Transplantation Center

PURPOSE We studied the incidence, risk factors, treatment, and outcomes of post-transplantation lymphoproliferative disorder (PTLD) that occurred at the University of Michigan since 1964. PATIENTS AND METHODS We identified 7,040 patients who received solid organ transplantation (SOT) and post-transplantation immunosuppressive therapy. Seventy-eight patients developed PTLD. RESULTS Diffuse large B-cell lymphoma (n = 43), polymorphic PTLD (n = 10), Hodgkins lymphoma (n = 7), Burkitts lymphoma (n = 6), plasmacytoma (n = 5), and mucosa-associated lymphoid tissue lymphoma (n = 3) were all over-represented in the SOT population compared with a population sample from the Surveillance, Epidemiology, and End Results (SEER) database; follicular lymphoma (n = 0) was underrepresented. Negative pretransplantation Epstein-Barr virus (EBV) serology was a risk factor for PTLD. Available histologic analysis of tumor tissue showed that 75% were CD20 positive and that 62% were EBV positive; EBV-positive tumors occurred sooner after SOT than EBV-negative tumors (mean, 29 v 66 months). Extralymphatic disease (79%), poor performance status (68%), elevated lactate dehydrogenase (LDH; 71%), and advanced stage (68%) disease were all common at the time of lymphoma diagnosis. Two thirds of patients had a complete response when treated with cyclophosphamide, doxorubicin, vincristine, and prednisone-like chemotherapy (either with or without rituximab). Median overall survival in all patients with PTLD was 8.23 years (95% CI, 2.28 to 30.0 years). CONCLUSION EBV-naïve patients who receive a donor organ from an EBV-infected donor are in the highest-risk situation for PTLD development. Most of these lymphomas are CD20 positive. Follicular lymphoma is unusual. With treatment, survival of patients with PTLD was indistinguishable from that of the SEER population sample.

Epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF) negatively affect overall survival in carcinoma of the cervix treated with radiotherapy.

PURPOSE The purpose of this study was to examine a variety of biomarkers in carcinoma of the cervix to better characterize (1). the natural history of the disease, (2). response to radiotherapy (RT), and (3). potential for new therapeutic strategies. MATERIALS AND METHODS Fifty-five patients with Stage IB-IVA carcinoma of the cervix, treated with definitive intent RT, and on whom tumor tissue blocks were available were included in this study. Charts were reviewed for clinical parameters and disease status. Immunohistochemistry was performed for epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), CD34, topoisomerase II alpha (topo-II), and cyclooxygenase-2 (COX-2). Univariate and multivariate Cox proportional hazards modeling was performed with disease-free survival (DFS) and overall survival (OS) as the end points. Biomarkers were evaluated for correlation between various prognostic factors. RESULTS In this series of 55 patients with carcinoma of the cervix treated with definitive RT, only stage was significant on univariate analysis for DFS (p < 0.0001). On univariate analysis, increasing FIGO stage (p < 0.0001) and membranous staining of EGFR (p < 0.037) indicated diminished OS. On multivariate analysis for DFS, COX-2, VEGF, and stage were significant (p = 0.012, p = 0.014, and p = 0.03, respectively), with increased expression indicating a worse prognosis. For OS, multivariate analysis revealed that VEGF, EGFR, and FIGO stage were significant (p = 0.005, p = 0.011, and p < 0.0001, respectively). Significant direct correlations were identified between VEGF and CD34 (p = 0.04), COX-2 and topo-II (p = 0.04), COX-2 and grade (p = 0.04), and tumor size and clinical stage (p = 0.04). CONCLUSION Multivariate analysis revealed that increased staining for VEGF and COX-2 indicated diminished DFS, and VEGF and EGFR identified patients at increased risk of death. A significant direct correlation between VEGF and CD34 implicates the process of angiogenesis. Topo-II is a proliferative marker and it correlated directly with COX-2, indicating that expression of COX-2 may be greater in more proliferative tumors. Increased expression of EGFR, VEGF, and COX-2 has identified patients with a worse prognosis in cancer of the cervix. These data support the investigation of therapeutics that target these proteins in carcinoma of the cervix.

De novo nonalcoholic fatty liver disease after liver transplantation

Hepatic steatosis is a recognized problem in patients after orthotopic liver transplant (OLT). However, de novo development of nonalcoholic fatty liver disease (NAFLD) has not been well described. The aim of this study was to determine the prevalence and predictors of de novo NAFLD after OLT. A retrospective analysis was performed on 68 OLT patients with donor liver biopsies and posttransplantation liver biopsies. Individual medical charts were reviewed for demographics, indication for OLT, serial histology reports, genotypes for hepatitis C, comorbid conditions, and medications. Liver biopsies were reviewed blindly and graded according to the Brunt Scoring System. Multivariate logistic regression analysis was used to study the risk factors for developing NAFLD. The interval time from OLT to subsequent follow‐up liver biopsy was 28 ± 18 months. A total of 12 patients (18%) developed de novo NAFLD, and 6 (9%) developed de novo NASH. The regression model indicated that the use of angiotensin‐converting enzyme inhibitors (ACE‐I) was associated with a reduced risk of developing NAFLD after OLT (odds ratio, 0.09; 95% confidence interval, 0.010‐0.92; P = 0.042). Increase in body mass index (BMI) of greater than 10% after OLT was associated with a higher risk of developing NAFLD (odds ratio, 19.38; 95% confidence interval, 3.50‐107.40; P = 0.001). In conclusion, de novo NAFLD is common in the post‐OLT setting, with a significant association with weight gain after transplant. The use of an ACE‐I may reduce the risk of developing post‐OLT NAFLD. Liver Transpl, 2006.

A PROPORTIONAL HAZARDS MODEL TAKING ACCOUNT OF LONG-TERM SURVIVORS

A proportional hazards (PH) model is modified to take account of long-term survivors by assuming the cumulative hazard to be bounded but otherwise unspecified to yield an improper survival function. A marginal likelihood is derived under the restriction for type I censoring patterns. For a PH model with cure, the marginal and the partial likelihood are not the same. In the absence of covariate information, the estimate of the cure rate based on the marginal likelihood reduces to the value of the Kaplan-Meier estimate at the end of the study. An example of low asymptotic efficiency of the partial likelihood as compared to the marginal, profile, and parametric likelihoods is given. An algorithm is suggested to fit the full PH model with cure.

Deficiency of platelet-activating factor acetylhydrolase is a severity factor for asthma

Asthma, a family of airway disorders characterized by airway inflammation, has an increasing incidence worldwide. Platelet-activating factor (PAF) may play a role in the pathophysiology of asthma. Its proinflammatory actions are antagonized by PAF acetylhydrolase. A missense mutation (V279F) in the PAF acetylhydrolase gene results in the complete loss of activity, which occurs in 4% of the Japanese population. We asked if PAF acetylhydrolase deficiency correlates with the incidence and severity of asthma in Japan. We found that the prevalence of PAF acetylhydrolase deficiency is higher in Japanese asthmatics than healthy subjects and that the severity of this syndrome is highest in homozygous-deficient subjects. We conclude that the PAF acetylhydrolase gene is a modulating locus for the severity of asthma.