Pre-treatment biomarker levels improve the accuracy of post-prostatectomy nomogram for prediction of biochemical recurrence

Prioritization of drug targets for thyroid cancer: a multi-omics Mendelian randomization study

OBJECTIVES

Recurrence or tumor metastasis and drug resistance remain the major challenge in the treatment of thyroid cancer. It is needed to identify novel drug targets for thyroid cancer.

METHODS

Summary data-based Mendelian randomization (SMR) and colocalization analysis were performed to evaluate the associations between gene methylation, expression, protein levels with thyroid cancer. We additionally performed protein-protein interaction (PPI) network, gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses to further explore the potential roles of identified genes in thyroid cancer.

RESULTS

SDCCAG8 and VCAM1 genes were associated with risk of thyroid cancer with tier 1 evidence, while TCN2 gene was with tier 3 evidence. SDCCAG8 gene was associated with risk of papillary thyroid cancer with tier 1 evidence. At the level of circulating proteins, genetically predicted higher levels of SDCCAG8 (OR = 0.46, 95% CI 0.34-0.64) and VCAM1 (OR = 0.21, 95% CI 0.10-0.45) were inversely associated with thyroid cancer risk; higher level of TCN2 was associated with an increased risk of thyroid cancer (OR = 1.30, 95% CI 1.15-1.47); and the higher level of SDCCAG8 (OR = 0.40, 95% CI 0.28-0.58) was associated with a decreased risk of papillary thyroid cancer. The bioinformatics analysis showed that SDCCAG8, VCAM1 and TCN2 might play roles in immune-related pathways.

CONCLUSION

SDCCAG8, VCAM1 and TCN2 genes were associated with thyroid cancer risk with evidence at multi-omics levels. There were potential roles of SDCCAG8, VCAM1 and TCN2 in immune-related pathways. Our findings might improve the understanding of the pathogenesis of thyroid cancer and discovery of novel potential drug targets for this disease.

Integrating Serum Biomarkers into Prediction Models for Biochemical Recurrence Following Radical Prostatectomy

This study undertook to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy using serum biomarkers and clinical features. Three radical prostatectomy cohorts were used to build and validate a model of clinical variables and serum biomarkers to predict BCR. The Cox proportional hazard model with stepwise selection technique was used to develop the model. Model evaluation was quantified by the AUC, calibration, and decision curve analysis. Cross-validation techniques were used to prevent overfitting in the Irish training cohort, and the Austrian and Norwegian independent cohorts were used as validation cohorts. The integration of serum biomarkers with the clinical variables (AUC = 0.695) improved significantly the predictive ability of BCR compared to the clinical variables (AUC = 0.604) or biomarkers alone (AUC = 0.573). This model was well calibrated and demonstrated a significant improvement in the predictive ability in the Austrian and Norwegian validation cohorts (AUC of 0.724 and 0.606), compared to the clinical model (AUC of 0.665 and 0.511). This study shows that the pre-operative biomarker PEDF can improve the accuracy of the clinical factors to predict BCR. This model can be employed prior to treatment and could improve clinical decision making, impacting on patients' outcomes and quality of life.

Can serum endoglin be used to improve the diagnostic performance in prostate cancer?

PURPOSE

New biomarkers may contribute to avoid unnecessary biopsies resulting from the suboptimal performance of prostate-specific antigen (PSA) testing. This study aimed to assess serum endoglin as a prostate cancer (PCa) diagnostic tool among biopsy candidates.

METHODS

A total of 262 consecutive patients referred for prostate biopsy based on abnormal digital rectal examination and/or elevated total PSA (tPSA) who had serum endoglin assessed by solid-phase enzyme-linked immunosorbent assay were selected. Receiver operating characteristic curves were used to compare the predictive accuracy of different combinations of biomarkers to distinguish between PCa and benign prostatic conditions, and to identify cut-offs that maximize the ability of endoglin to rule out patients for biopsy (highest sensitivities).

RESULTS

Serum endoglin levels were higher in patients with PCa (median: 7.86 vs. 5.88 pg/mL, P < 0.001). Among patients with baseline tPSA ≤ 10 ng/mL the area under the curve was 0.69 for endoglin. Approximately one-quarter of the patients had serum endoglin < 4.92 ng/mL (sensitivity: 90.3%; specificity: 32.8%), and the probability of PCa varied from 37.7% before testing to 15.2% among those with low endoglin levels [negative predictive value (NPV) = 84.8%]. When restricting the analyses to patients with free/total PSA ratio > 0.25, the probability of cancer was less than 5% among those with serum endoglin < 6.04 ng/mL (sensitivity: 93.8%; specificity: 56.1%), corresponding to a NPV of 95.8%; this could allow sparing approximately 40% of patients from biopsy.

CONCLUSIONS

Serum endoglin may be useful in clinical practice to distinguish between PCa and non-cancer patients among prostatic biopsy candidates.

Tissue-based molecular markers in upper tract urothelial carcinoma and their prognostic implications

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive disease that is associated with high rates of recurrence and death. Radical nephroureterectomy (RNU) with excision of the bladder cuff is considered the standard of care for high-risk UTUC, whereas kidney-sparing techniques can be indicated for select patients with low-risk disease. There is a significant lack of clinical and pathological prognostic factors for stratifying patients with regard to making treatment decisions. Incorporation of tissue-based molecular markers into prognostic tools could help accurately stratify patients for clinical decision-making in this heterogeneous disease. Although the number of studies on tissue-based markers in UTUC has risen dramatically in the past several years-many of which are based on single centers and small cohorts, with a low level of evidence-many discrepancies remain between their results. Nevertheless, certain biomarkers are promising tools, necessitating prospective multi-institution studies to validate their function.

Prediction of prostate cancer recurrence using quantitative phase imaging: Validation on a general population

Prediction of biochemical recurrence risk of prostate cancer following radical prostatectomy is critical for determining whether the patient would benefit from adjuvant treatments. Various nomograms exist today for identifying individuals at higher risk for recurrence; however, an optimistic under-estimation of recurrence risk is a common problem associated with these methods. We previously showed that anisotropy of light scattering measured using quantitative phase imaging, in the stromal layer adjacent to cancerous glands, is predictive of recurrence. That nested-case controlled study consisted of specimens specifically chosen such that the current prognostic methods fail. Here we report on validating the utility of optical anisotropy for prediction of prostate cancer recurrence in a general population of 192 patients, with 17% probability of recurrence. Our results show that our method can identify recurrent cases with 73% sensitivity and 72% specificity, which is comparable to that of CAPRA-S, a current state of the art method, in the same population. However, our results show that optical anisotropy outperforms CAPRA-S for patients with Gleason grades 7-10. In essence, we demonstrate that anisotropy is a better biomarker for identifying high-risk cases, while Gleason grade is better suited for selecting non-recurrence. Therefore, we propose that anisotropy and current techniques be used together to maximize prediction accuracy.

Significance of TNF-α and the Adhesion Molecules: L-Selectin and VCAM-1 in Papillary Thyroid Carcinoma

Circulating levels of TNF-α and the adhesion molecules L-Selectin and VCAM-1 as well as their expression in the primary tumors of patients with benign thyroid diseases and papillary thyroid carcinoma (PTC) have been determined in this study. The serum levels of TNF-α, L-Selectin, and VCAM-1 were significantly higher in patients with both benign thyroid diseases and PTC as compared to the healthy individuals. However, the levels of only TNF-α and L-Selectin, and not VCAM-1, were significantly higher in patients with PTC in comparison to those observed in patients with benign thyroid diseases. Further the expression of TNF-α and L-Selectin was also significantly higher in the primary tumors of PTC patients, relative to the benign thyroid diseases. The expression of L-Selectin and VCAM-1 significantly correlated with aggressive tumor behavior. In PTC patients, the circulating TNF-α levels significantly positively correlated with the levels of L-Selectin, while TNF-α immunoreactivity was significantly associated with VCAM-1 expression. Serum TNF-α was found to be a significant prognosticator for OS in PTC patients. Overall the results signify that the interaction between TNF-α and the adhesion molecules may have a role in thyroid carcinogenesis and understanding this complexity may offer potential therapeutic targets for better management of thyroid cancer.

Genome-wide detection of allelic genetic variation to predict biochemical recurrence after radical prostatectomy among prostate cancer patients using an exome SNP chip

PURPOSES

Genetic variations among prostate cancer patients who underwent radical prostatectomies were evaluated to predict biochemical recurrence, and used to develop a clinical-genetic model that combines data on clinicopathological factors of prostate cancer and individual genetic variations.

MATERIALS AND METHODS

We genotyped 242,186 SNPs on a custom HumanExome BeadChip v1.0 (Illuminam Inc.) from the blood DNA of 776 PCa patients who underwent radical prostatectomy. Genetic data were analyzed to calculate an odds ratio as an estimate of the relative risk of biochemical recurrence. And we compared accuracies from the multivariate model incorporating clinicopathological factors between included and excluded selected lead single nucleotide polymorphisms. Biochemical recurrence-free survival outcomes also analyzed using these genetic variations.

RESULTS

Genetic array analysis indicated that eight single nucleotide polymorphisms (rs77080351, rs200944490, rs2071292, rs117237810, rs191118242, rs4965121, rs61742396, and rs6573513) were significant to predict biochemical recurrence after radical prostatectomy. When a multivariate model incorporating clinicopathological factors was devised to predict biochemical recurrence, the predictive accuracy of model was 85.1 %. By adding in two individual variations of single nucleotide polymorphisms in the multivariate model, the predictive accuracy increased to 87.7 % (P = 0.045). With three variations of single nucleotide polymorphisms, the predictive accuracy further improved to 89.0 % (P = 0.025). These genetic variations had a significantly decreased biochemical recurrence-free survival rate.

CONCLUSIONS

Based on exome array, the selected single nucleotide polymorphisms were predictors for biochemical recurrence. The addition of individualized genetic information effectively enhanced the predictive accuracy of biochemical recurrence among prostate cancer patients who underwent radical prostatectomy.

A clinicogenetic model to predict lymph node invasion by use of genome-based biomarkers from exome arrays in prostate cancer patients

Purpose

Genetic variations among prostate cancer (PCa) patients who underwent radical prostatectomy (RP) and pelvic lymph node dissection were evaluated to predict lymph node invasion (LNI). Exome arrays were used to develop a clinicogenetic model that combined clinical data related to PCa and individual genetic variations.

Materials and Methods

We genotyped 242,186 single-nucleotide polymorphisms (SNPs) by using a custom HumanExome BeadChip v1.0 (Illumina Inc.) from the blood DNA of 341 patients with PCa. The genetic data were analyzed to calculate an odds ratio as an estimate of the relative risk of LNI. We compared the accuracies of the multivariate logistic model incorporating clinical factors between the included and excluded selected SNPs. The Cox proportional hazard models with or without genetic factors for predicting biochemical recurrence (BCR) were analyzed.

Results

The genetic analysis indicated that five SNPs (rs75444444, rs8055236, rs2301277, rs9300039, and rs6908581) were significant for predicting LNI in patients with PCa. When a multivariate model incorporating clinical factors was devised to predict LNI, the predictive accuracy of the multivariate model was 80.7%. By adding genetic factors in the aforementioned multivariate model, the predictive accuracy increased to 93.2% (p=0.006). These genetic variations were significant factors for predicting BCR after adjustment for other variables and after adding the predictive gain to BCR.

Conclusions

Based on the results of the exome array, the selected SNPs were predictors for LNI. The addition of individualized genetic information effectively enhanced the predictive accuracy of LNI and BCR among patients with PCa who underwent RP.

A Quest to Identify Prostate Cancer Circulating Biomarkers with a Bench-to-Bedside Potential

Prostate cancer (PCA) is a major health concern in current times. Ever since prostate specific antigen (PSA) was introduced in clinical practice almost three decades ago, the diagnosis and management of PCA have been revolutionized. With time, concerns arose as to the inherent shortcomings of this biomarker and alternatives were actively sought. Over the past decade new PCA biomarkers have been identified in tissue, blood, urine, and other body fluids that offer improved specificity and supplement our knowledge of disease progression. This review focuses on superiority of circulating biomarkers over tissue biomarkers due to the advantages of being more readily accessible, minimally invasive (blood) or noninvasive (urine), accessible for sampling on regular intervals, and easily utilized for follow-up after surgery or other treatment modalities. Some of the circulating biomarkers like PCA3, IL-6, and TMPRSS2-ERG are now detectable by commercially available kits while others like microRNAs (miR-21, -221, -141) and exosomes hold potential to become available as multiplexed assays. In this paper, we will review some of these potential candidate circulating biomarkers that either individually or in combination, once validated with large-scale trials, may eventually get utilized clinically for improved diagnosis, risk stratification, and treatment.

The role of single nucleotide polymorphisms in predicting prostate cancer risk and therapeutic decision making

Prostate cancer (PCa) is a major health care problem because of its high prevalence, health-related costs, and mortality. Epidemiological studies have suggested an important role of genetics in PCa development. Because of this, an increasing number of single nucleotide polymorphisms (SNPs) had been suggested to be implicated in the development and progression of PCa. While individual SNPs are only moderately associated with PCa risk, in combination, they have a stronger, dose-dependent association, currently explaining 30% of PCa familial risk. This review aims to give a brief overview of studies in which the possible role of genetic variants was investigated in clinical settings. We will highlight the major research questions in the translation of SNP identification into clinical practice.

Involvement of urokinase-type plasminogen activator system in cancer: an overview

Currently, there are several studies supporting the role of urokinase-type plasminogen activator (uPA) system in cancer. The association of uPA to its receptor triggers the conversion of plasminogen into plasmin. This process is regulated by the uPA inhibitors (PAI-1 and PAI-2). Plasmin promotes degradation of basement membrane and extracellular matrix (ECM) components as well as activation of ECM latent matrix metalloproteases. Degradation and remodeling of the surrounding tissues is crucial in the early steps of tumor progression by facilitating expansion of the tumor mass, release of tumor growth factors, activation of cytokines as well as induction of tumor cell proliferation, migration, and invasion. Hence, many tumors showed a correlation between uPA system component levels and tumor aggressiveness and survival. Therefore, this review summarizes the structure of the uPA system, its contribution to cancer progression, and the clinical relevance of uPA family members in cancer diagnosis. In addition, the review evaluates the significance of uPA system in the development of cancer-targeted therapies.

Plasma vascular endothelial growth factors A and C in patients undergoing prostatic biopsy and TURP for suspected prostatic neoplasia

BACKGROUND

Formation of new blood vessels is necessary for the development and spread of neoplasms more than 1 mm3 in volume, angiogenesis being responsible for formation of new from pre-existing blood vessels. Vascular endothelial growth factor (VEGF) is pivotal and the best studied angiogenic factor in all human cancers. Therefore we designed this study to investigate the role of VEGF-A and VEGF-C in prostate cancer in comparison with BPH controls in a north Indian population.

METHODS

In this case-control study a total of 100 subjects were included on the basis of confirmed histopathological reports, out of which 50 were prostate cancer patients and the other 50 were BPH patients with PSA levels >2 ng/ml and abnormal digital rectal examination (DRE) findings during September 2009 to August 2011 from the Department of Urology, KGMU, Lucknow, India. Plasma levels of VEGF were determined using quantitative immunoassay (ELISA- enzyme linked immunosorbent assay). Statistical analysis was carried out using SPSS 15.0 version.

RESULTS

The mean age of prostate cancer (67.6±5.72) patients was significantly higher (p=0.005) than BPH (63.6±7.92) patients. Expression of VEGF-A was not significantly higher in disease stage C1 than D1 or D2 and A or B (p=0.13) while the level of VEGF-A was significantly higher (p=0.04) in prostate cancer as compared to BPH subjects (PCa=13.0 pg/ml, BPH=6.8 pg/ml). Levels of VEGF-C were similar in both groups (PCa=832.6 pg/ml, BPH=823.7 pg/ml). In ROC curve, the area under curve (AUC) was 0.70 (95%CI: 0.60-0.80) and the cut-off value for which a higher proportion of patients was correctly classified (20%) was 26.0 pg/mL.

CONCLUSION

Although VEGF-A is increased in cancer prostate patients a statistically significant correlation could not be established in this study. VEGF-C was not found to be a useful biomarker.

Prognostic value of vascular endothelial growth factor expression in patients with prostate cancer: a systematic review with meta-analysis

BACKGROUND

The vascular endothelial growth factor (VEGF) mediates vasculogenesis and angiogenesis through promoting endothelial cell growth, migration and mitosis, and has involvement in cancer pathogenesis, progression and metastasis. However, the prognostic value of VEGF in patients with prostate cancer remains controversial.

OBJECTIVES

The aim of our study was to evaluate the prognostic value of VEGF in prostate cancer, and summarise the results of related research on VEGF.

METHODS

In accordance with an established search strategy, 11 studies with 1,529 patients were included in our meta-analysis. The correlation of VEGF-expression with overall survival and progression-free survival was evaluated by hazard ratio, either given or calculated.

RESULTS

The studies were categorized by introduction of the author, demographic data in each study, prostate cancer-relatived information, VEGF cut-off value, VEGF subtype, methods of hazard ratio (HR) estimation and its 95% confidence interval (CI). High VEGF-expression in prostate cancer is a poor prognostic factor with statistical significance for OS (HR=2.32, 95%CI: 1.40-3.24). However, high VEGF-expression showed no effect on poor PFS (HR=1.30, 95%CI: 0.88-1.72). Using Begg's, Egger's test and funnel plots, we confirmed lack of publication bias in our analysis.

CONCLUSION

VEGF might be regarded as a prognostic maker for prostate cancer, as supported by our meta-analysis. To achieve a more definitive conclusion enabling the clinical use of VEGF in prostate cancer, we need more high-quality interventional original studies following agreed research approaches or standards.

IL-6/IL-6R as a potential key signaling pathway in prostate cancer development

Interleukin-6 (IL-6) is a pleiotropic cytokine involved in prostate regulation and in prostate cancer (PC) development/progression. IL-6 acts as a paracrine and autocrine growth stimulator in benign and tumor prostate cells. The levels of IL-6 and respective receptors are increased during prostate carcinogenesis and tumor progression. Several studies reported that increased serum and plasma IL-6 and soluble interleukin-6 receptor levels are associated with aggressiveness of the disease and are associated with a poor prognosis in PC patients. In PC treatment, patients diagnosed with advanced stages are frequently submitted to hormonal castration, although most patients will eventually fail this therapy and die from recurrent castration-resistant prostate cancer (CRPC). Therefore, it is important to understand the mechanisms involved in CRPC. Several pathways have been proposed to be involved in CRPC development, and their understanding will improve the way to more effective therapies. In fact, the prostate is known to be dependent, not exclusively, on androgens, but also on growth factors and cytokines. The signaling pathway mediated by IL-6 may be an alternative pathway in the CRPC phenotype acquisition and cancer progression, under androgen deprivation conditions. The principal goal of this review is to evaluate the role of IL-6 pathway signaling in human PC development and progression and discuss the interaction of this pathway with the androgen recepto pathway. Furthermore, we intend to evaluate the inclusion of IL-6 and its receptor levels as a putative new class of tumor biomarkers.The IL-6/IL-6R signaling pathway may be included as a putative molecular marker for aggressiveness in PC and it may be able to maintain tumor growth through the AR pathway under androgen-deprivation conditions. The importance of the IL-6/IL-6R pathway in regulation of PC cells makes it a good candidate for targeted therapy.

The additional value of TGFβ1 and IL-7 to predict the course of prostate cancer progression

Background

Given the fact that prostate cancer incidence will increase in the coming years, new prognostic biomarkers are needed with regard to the biological aggressiveness of the prostate cancer diagnosed. Since cytokines have been associated with the biology of cancer and its prognosis, we determined whether transforming growth factor beta 1 (TGFβ1), interleukin-7 (IL-7) receptor and IL-7 levels add additional prognostic information with regard to prostate cancer-specific survival.

Materials and methods

Retrospective survival analysis of forty-four prostate cancer patients, that underwent radical prostatectomy, was performed (1989–2001). Age, Gleason score and pre-treatment PSA levels were collected. IL-7, IL-7 receptor and TGFβ1 levels in prostate cancer tissue were determined by quantitative real-time RT-PCR and their additional prognostic value analyzed with regard to prostate cancer survival. Hazard ratios and their confidence intervals were estimated, and Akaike’s information criterion was calculated for model comparison.

Results

The predictive ability of a model for prostate cancer survival more than doubled when TGFβ1 and IL-7 were added to a model containing only the Gleason score and pre-treatment PSA (AIC: 18.1 and AIC: 6.5, respectively).

Conclusion

IL-7 and TGFβ1 are promising markers to indicate those at risk for poor prostate cancer survival. This additional information may be of interest with regard to the biological aggressiveness of the diagnosed prostate cancer, especially for those patients screened for prostate cancer and their considered therapy.

Identification of inflammatory biomarkers for pediatric malarial anemia severity using novel statistical methods

Areas where Plasmodium falciparum transmission is holoendemic are characterized by high rates of pediatric severe malarial anemia (SMA) and associated mortality. Although the etiology of SMA is complex and multifactorial, perturbations in inflammatory mediator production play an important role in the pathogenic process. As such, the current study focused on identification of inflammatory biomarkers in children with malarial anemia. Febrile children (3 to 30 months of age) presenting at Siaya District Hospital in western Kenya underwent a complete clinical and hematological evaluation. Children with falciparum malaria and no additional identifiable anemia-promoting coinfections were stratified into three groups: uncomplicated malaria (hemoglobin [Hb] levels of ≥11.0 g/dl; n = 31), non-SMA (Hb levels of 6.0 to 10.9 g/dl; n = 37), and SMA (Hb levels of <6.0 g/dl; n = 80). A Luminex hu25-plex array was used to determine potential biomarkers (i.e., interleukin 1β [IL-1β], IL-1 receptor antagonist [IL-1Ra], IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-15, IL-17, tumor necrosis factor alpha [TNF-α], alpha interferon [IFN-α], IFN-γ, granulocyte-macrophage colony-stimulating factor [GM-CSF], macrophage inflammatory protein 1 alpha [MIP-1α], MIP-1β, IFN-inducible protein of 10 kDa [IP-10], monokine induced by IFN-γ [MIG], eotaxin, RANTES, and monocyte chemoattractant protein 1 [MCP-1]) in samples obtained prior to any treatment interventions. To determine the strongest biomarkers of anemia, a parsimonious set of predictor variables for Hb was generated by least-angle regression (LAR) analysis, controlling for the confounding effects of age, gender, glucose-6-phosphate dehydrogenase (G6PD) deficiency, and sickle cell trait, followed by multiple linear regression analyses. IL-12p70 and IFN-γ emerged as positive predictors of Hb, while IL-2R, IL-13, and eotaxin were negatively associated with Hb. The results presented here demonstrate that the IL-12p70/IFN-γ pathway represents a set of biomarkers that predicts elevated Hb levels in children with falciparum malaria, while activation of the IL-13/eotaxin pathway favors more profound anemia.

Tumor markers in prostate cancer I: blood-based markers

The introduction of total prostate specific antigen (total PSA) testing in blood has revolutionized the detection and management of men with prostate cancer (PCa). The objective of this review was to discuss the challenges of PCa biomarker research, definition of the type of PCa biomarkers, the statistical considerations for biomarker discovery and validation, and to review the literature regarding total PSA velocity and novel blood-based biomarkers.

METHODS

An English-language literature review of the Medline database (1990 to August 2010) of published data on blood-based biomarkers and PCa was undertaken.

RESULTS

The inherent biological variability of total PSA levels affects the interpretation of any single result. Men who will eventually develop PCa have increased total PSA levels years or decades before the cancer is diagnosed. Total PSA velocity improves predictiveness of total PSA only marginally, limiting its value for PCa screening and prognostication. The combination of PSA molecular forms and other biomarkers improve PCa detection substantially. Several novel blood-based biomarkers such as human glandular kallikrein 2 (hK2), urokinase plasminogen activator (uPA) and its receptor (uPAR), transforming growth factor-beta 1 (TGF-β1); interleukin-6 (IL-6) and its receptor (IL-6R) may help PCa diagnosis, staging, prognostication, and monitoring. Panels of biomarkers that capture the biologic potential of PCa are in the process of being validated for PCa prognostication.

CONCLUSIONS

PSA is a strong prognostic marker for long-term risk of clinically relevant cancer. However, there is a need for novel biomarkers that aid clinical decision making about biopsy and initial treatment. There is no doubt that progress will continue based on the integrated collaboration of researchers, clinicians and biomedical firms.

Statistical consideration for clinical biomarker research in bladder cancer

OBJECTIVE

To critically review and illustrate current methodological and statistical considerations for bladder cancer biomarker discovery and evaluation.

METHODS

Original, review, and methodological articles, and editorials were reviewed and summarized.

RESULTS

Biomarkers may be useful at multiple stages of bladder cancer management: early detection, diagnosis, staging, prognosis, and treatment; however, few novel biomarkers are currently used in clinical practice. The reasons for this disjunction are many and reflect the long and difficult pathway from candidate biomarker discovery to clinical assay, and the lack of coherent and comprehensive processes (pipelines) for biomarker development. Conceptually, the development of new biomarkers should be a process that is similar to therapeutic drug evaluation-a highly regulated process with carefully regulated phases from discovery to human applications. In a further effort to address the pervasive problem of inadequacies in the design, analysis, and reporting of biomarker prognostic studies, a set of reporting recommendations are discussed. For example, biomarkers should provide unique information that adds to known clinical and pathologic information. Conventional multivariable analyses are not sufficient to demonstrate improved prediction of outcomes. Predictive models, including or excluding any new putative biomarker, need to show clinically significant improvement of performance in order to claim any real benefit. Towards this end, proper model building, avoidance of overfitting, and external validation are crucial. In addition, it is important to choose appropriate performance measures dependent on outcome and prediction type and to avoid the use of cutpoints. Biomarkers providing a continuous score provide potentially more useful information than cutpoints since risk fits a continuum model. Combination of complementary and independent biomarkers is likely to better capture the biological potential of a tumor than any single biomarker. Finally, methods that incorporate clinical consequences such as decision curve analysis are crucial to the evaluation of biomarkers.

CONCLUSIONS

Attention to sound design and statistical practice should be delivered as early as possible and will help maximize the promise of biomarkers for patient care. Studies should include a measure of predictive accuracy and clinical decision-analysis. External validation using data from an independent cohort provides the strongest evidence that a model is valid. There is a need for adequately assessed clinical biomarkers in bladder cancer.

A multiplexed, particle-based flow cytometric assay identified plasma matrix metalloproteinase-7 to be associated with cancer-related death among patients with bladder cancer

BACKGROUND

The current study was conducted to demonstrate the utility of a multiplexed, particle-based flow cytometric assay for the simultaneous analysis of a panel of matrix metalloproteinases (MMPs) using small volumes of plasma samples from patients with bladder cancer. In addition, the authors attempted to test the hypothesis that plasma levels of MMPs are associated with time to cancer-related death.

METHODS

Plasma MMP concentrations (MMP-1, -2, -3, -7, -8, -9, and -12) in 135 patients presenting with high-grade≥T1 bladder cancer were measured. Data regarding clinical and pathologic features was ascertained in a retrospective fashion.

RESULTS

The median duration of follow-up was 30.4 months. At the time of analysis, 61 patients had died, including 45 (33.3%) who died of bladder cancer. Plasma MMP-12 was not measurable. For all other MMPs, the intra-assay coefficient of variation varied from 6.12% to 9.82%. MMP-1, -2, -3, -8, and -9 were not found to be significantly associated with time to cancer-related death. Plasma MMP-7 levels were significantly associated with time to cancer-related death after adjustment for competing clinical and pathologic features (hazard ratio [HR], 2.2; 95% confidence interval [95% CI], 1.1-4.5 [P=.022]). The 5-year median cancer-specific survival rates for those patients with MMP-7 levels above and below the median value (300 pg/mL) were 73.6% (95% CI, 60.0-83.2%) and 48.0% (95% CI, 32.5-61.9%), respectively (P=.01).

CONCLUSIONS

Multiplexed, particle-based flow cytometric assay allows for the high-throughput measurement of multiple plasma or serum proteins simultaneously. By using this new technology in a cohort of patients with bladder cancer, plasma levels of MMP-7 were identified as being significantly associated with time to cancer-related death.

Postoperative prostate-specific antigen nadir improves accuracy for predicting biochemical recurrence after radical prostatectomy: Results from the Shared Equal Access Regional Cancer Hospital (SEARCH) and Duke Prostate Center databases

OBJECTIVES

We previously showed that prostate-specific antigen (PSA) nadir after radical prostatectomy (RP) significantly predicts biochemical recurrence (BCR). Herein, we sought to explore the effect of including PSA nadir into commonly used models on their accuracy to predict BCR after RP.

METHODS

This was a retrospective analysis of 943 and 1792 subjects from the Shared Equal Access Regional Cancer Hospital (SEARCH) and Duke Prostate Cancer (DPC) databases, respectively. The discrimination accuracy for BCR of seven previously published models was assessed using concordance index and compared with and without adding PSA nadir level in SEARCH. Using data from SEARCH, we developed a new nomogram incorporating PSA nadir to other known predictors (preoperative PSA, pathological Gleason score, PSA nadir level, surgical findings, prostate weight, body mass index and race) of BCR and externally validated it in the DPC.

RESULTS

In SEARCH, the mean concordance index across all seven nomograms was 0.687. After the inclusion of PSA nadir, the concordance index increased by nearly 7% (mean=0.753). The concordance index of the new nomogram in SEARCH was 0.779 (bias-corrected=0.767), which was 5% better than the next best model. In DPC, the new nomogram yielded a concordance index of 0.778.

CONCLUSION

The addition of postoperative PSA nadir to commonly used nomograms increased their accuracies by nearly 7%. Based upon this, we developed and externally validated a new nomogram, which was well calibrated and highly accurate, and is a potentially valuable tool for patients and physicians to predict BCR after RP.

[Emerging biomarkers for the diagnosis, staging and prognosis of prostate cancer]

The introduction and widespread adoption of prostate-specific antigen (PSA) has revolutionized the way prostate cancer is diagnosed and treated. However, the use of PSA has also led to overdiagnosis and overtreatment of prostate cancer resulting in controversy about its use for screening. PSA also has limited predictive accuracy for predicting outcomes after treatment and for making clinical decisions about adjuvant and salvage therapies. Hence, there is an urgent need for novel biomarkers to supplement PSA for detection and management of prostate cancer. A plethora of promising blood- and urine-based biomarkers have shown promise in early studies and are at various stages of development (Human kallikrein 2, Early Prostate Cancer Antigen, Transforming Growth Factor-Beta 1 and Interleukin-6, Endoglin, PCA3, AMACR and ETS Gene Fusions). In this article, we review those biomarkers and then discuss the challenges a biomarker has to undergo before it is approved in a clinical use.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms

PURPOSE

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy.

MATERIALS AND METHODS

We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index.

RESULTS

The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities.

CONCLUSIONS

Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information.

Markers for detection of prostate cancer

Early detection of prostate cancer is problematic, not just because of uncertainly whether a diagnosis will benefit an individual patient, but also as a result of the imprecise and invasive nature of establishing a diagnosis by biopsy. Despite its low sensitivity and specificity for identifying patients harbouring prostate cancer, serum prostate specific antigen (PSA) has become established as the most reliable and widely-used diagnostic marker for this condition. In its wake, many other markers have been described and evaluated. This review focuses on the supporting evidence for the most prominent of these for detection and also for predicting outcome in prostate cancer.

Susceptibility loci associated with prostate cancer progression and mortality

PURPOSE

Prostate cancer is a heterogeneous disease with a variable natural history that is not accurately predicted by currently used prognostic tools.

EXPERIMENTAL DESIGN

We genotyped 798 prostate cancer cases of Ashkenazi Jewish ancestry treated for localized prostate cancer between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to clinical data. The survival analysis was adjusted for Gleason score and prostate-specific antigen. We investigated associations between 29 single nucleotide polymorphisms (SNP) and biochemical recurrence, castration-resistant metastasis, and prostate cancer-specific survival. Subsequently, we did an independent analysis using a high-resolution panel of 13 SNPs.

RESULTS

On univariate analysis, two SNPs were associated (P<0.05) with biochemical recurrence, three SNPs were associated with clinical metastases, and one SNP was associated with prostate cancer-specific mortality. Applying a Bonferroni correction (P<0.0017), one association with biochemical recurrence (P=0.0007) was significant. Three SNPs showed associations on multivariable analysis, although not after correcting for multiple testing. The secondary analysis identified an additional association with prostate cancer-specific mortality in KLK3 (P<0.0005 by both univariate and multivariable analysis).

CONCLUSIONS

We identified associations between prostate cancer susceptibility SNPs and clinical end points. The rs61752561 in KLK3 and rs2735839 in the KLK2-KLK3 intergenic region were strongly associated with prostate cancer-specific survival, and rs10486567 in the 7JAZF1 gene were associated with biochemical recurrence. A larger study will be required to independently validate these findings and determine the role of these SNPs in prognostic models.

Critical review of prostate cancer predictive tools

Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities and potential treatment-related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, look-up and propensity scoring tables, risk-class stratification prediction tools, classification and regression tree analysis, nomograms and artificial neural networks. Criteria to evaluate tools include discrimination, calibration, generalizability, level of complexity, decision analysis and ability to account for competing risks and conditional probabilities. The available predictive tools and their features, with a focus on nomograms, are described. While some tools are well-calibrated, few have been externally validated or directly compared with other tools. In addition, the clinical consequences of applying predictive tools need thorough assessment. Nevertheless, predictive tools can facilitate medical decision-making by showing patients tailored predictions of their outcomes with various alternatives. Additionally, accurate tools may improve clinical trial design.