Phase II prospective randomized trial of weight loss prior to radical prostatectomy.

BACKGROUND:Obesity is associated with poorly differentiated and advanced prostate cancer and increased mortality. In preclinical models, caloric restriction delays prostate cancer progression and prolongs survival. We sought to determine if weight loss (WL) in men with prostate cancer prior to radical prostatectomy affects tumor apoptosis and proliferation, and if WL effects other metabolic biomarkers. METHODS:In this Phase II prospective trial, overweight and obese men scheduled for radical prostatectomy were randomized to a 5-8 week WL program consisting of standard structured energy-restricted meal plans (1200-1500 Kcal/day) and physical activity or to a control group. The primary endpoint was apoptotic index in the radical prostatectomy malignant epithelium. Secondary endpoints were proliferation (Ki67) in the radical prostatectomy tissue, body weight, body mass index (BMI), waist to hip ratio, body composition, and serum PSA, insulin, triglyceride, cholesterol, testosterone, estradiol, leptin, adiponectin, interleukin 6, interleukin 8, insulin-like growth factor 1, and IGF binding protein 1. RESULTS:In total 23 patients were randomized to the WL intervention and 21 patients to the control group. Subjects in the intervention group had significantly more weight loss (WL:-3.7 ± 0.5 kg; Control:-1.6 ± 0.5 kg; p = 0.007) than the control group and total fat mass was significantly reduced (WL:-2.1 ± 0.4; Control: 0.1 ± 0.3; p = 0.015). There was no significant difference in apoptotic or proliferation index between the groups. Among the other biomarkers, triglyceride, and insulin levels were significantly decreased in the WL compared with the control group. CONCLUSIONS:In summary, this short-term WL program prior to radical prostatectomy resulted in significantly more WL in the intervention vs. the control group and was accompanied by significant reductions in body fat mass, circulating triglycerides, and insulin. However, no significant changes were observed in malignant epithelium apoptosis or proliferation. Future studies should consider a longer term or more intensive weight loss intervention

A population-based study of glutathione-S-transferase M1, T1 and P1 genotypes

A retrospective study on healthy, unrelated subjects was conducted in order to estimate population glutathione-S-transferases (GST) genotype frequencies in Slovak population of men and compare our results with already published data (GSEC project)^1^. A further aim of the study was to evaluate frequencies of the _GST_ polymorphisms also in patients with prostate cancer in order to compare the evaluated proportions with those found in the control subjects. Analysis for the _GST_ gene polymorphisms was performed by PCR and PCR-RFLP. We found that the proportions are not significantly different from those estimated in a European multicentre study or from the results published by another group in Slovakia. We found significantly increased age-standardized prostate cancer prevalence rates in the carriers of _GSTM1_ null genotype (P = 0.037) and trend for such an increase in the carriers of _GSTP1_ polymorphism when compared with the respective groups of non-carriers. Because understanding of the contribution of _GST_ gene polymorphisms and their interactions with other relevant factors may improve screening diagnostic assays for prostate cancer, we discuss issues of study feasibility, study design, and statistical power, which should be taken into account in planning further trials

Diagnostic accuracy of urinary prostate protein glycosylation profiling in prostatitis diagnosis

Introduction: Although prostatitis is a common male urinary tract infection, clinical diagnosis of prostatitis is difficult. The developmental mechanism of prostatitis is not yet unraveled which led to the elaboration of various biomarkers. As changes in asparagine-linked-(N-)-glycosylation were observed between healthy volunteers (HV), patients with benign prostate hyperplasia and prostate cancer patients, a difference could exist in biochemical parameters and urinary N-glycosylation between HV and prostatitis patients. We therefore investigated if prostatic protein glycosylation could improve the diagnosis of prostatitis. Materials and methods: Differences in serum and urine biochemical markers and in total urine N-glycosylation profile of prostatic proteins were determined between HV (N = 66) and prostatitis patients (N = 36). Additionally, diagnostic accuracy of significant biochemical markers and changes in N-glycosylation was assessed. Results: Urinary white blood cell (WBC) count enabled discrimination of HV from prostatitis patients (P < 0.001). Urinary bacteria count allowed for discriminating prostatitis patients from HV (P < 0.001). Total amount of biantennary structures (urinary 2A/MA marker) was significantly lower in prostatitis patients compared to HV (P < 0.001). Combining the urinary 2A/MA marker and urinary WBC count resulted in an AUC of 0.79, 95% confidence interval (CI) = (0.70-0.89) which was significantly better than urinary WBC count (AUC = 0.70, 95% CI = [0.59-0.82], P = 0.042) as isolated test. Conclusions: We have demonstrated the diagnostic value of urinary N-glycosylation profiling, which shows great potential as biomarker for prostatitis. Further research is required to unravel the developmental course of prostatic inflammation

Sex-associated differences in baseline urinary metabolites of healthy adults.

The biological basis for gender variability among disease states is not well established. There have been many prior efforts attempting to identify the unique urine metabolomic profiles associated with specific diseases. However, there has been little advancement in investigating the metabolomic differences associated with gender, which underlies the misconception that risk factors and treatment regimens should be the same for both male and female patients. This present study aimed to identify biologically-meaningful baseline sex-related differences using urine samples provided by healthy female and male participants. To elucidate whether urinary metabolic signatures are globally distinct between healthy males and females, we applied metabolomics profiling of primary metabolism with comprehensive bioinformatics analyses on urine samples from 60 healthy males and females. We found that levels of α-ketoglutarate and 4-hydroxybutyric acid increased 2.3-fold and 4.41-fold in males compared to females, respectively. Furthermore, chemical similarity enrichment analysis revealed that differentially expressed metabolites, such as saturated fatty acids, TCA, and butyrates, were significantly related to the gender effect. These findings indicate that there are baseline sex-related differences in urinary metabolism, which should be considered in biomarker discovery, diagnosis, and treatment of bladder diseases, such as interstitial cystitis

Rank discriminants for predicting phenotypes from RNA expression

Statistical methods for analyzing large-scale biomolecular data are commonplace in computational biology. A notable example is phenotype prediction from gene expression data, for instance, detecting human cancers, differentiating subtypes and predicting clinical outcomes. Still, clinical applications remain scarce. One reason is that the complexity of the decision rules that emerge from standard statistical learning impedes biological understanding, in particular, any mechanistic interpretation. Here we explore decision rules for binary classification utilizing only the ordering of expression among several genes; the basic building blocks are then two-gene expression comparisons. The simplest example, just one comparison, is the TSP classifier, which has appeared in a variety of cancer-related discovery studies. Decision rules based on multiple comparisons can better accommodate class heterogeneity, and thereby increase accuracy, and might provide a link with biological mechanism. We consider a general framework ("rank-in-context") for designing discriminant functions, including a data-driven selection of the number and identity of the genes in the support ("context"). We then specialize to two examples: voting among several pairs and comparing the median expression in two groups of genes. Comprehensive experiments assess accuracy relative to other, more complex, methods, and reinforce earlier observations that simple classifiers are competitive.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS738 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The modified Glasgow prognostic score in prostate cancer: results from a retrospective clinical series of 744 patients

&lt;p&gt;Background: As the incidence of prostate cancer continues to rise steeply, there is an increasing need to identify more accurate prognostic markers for the disease. There is some evidence that a higher modified Glasgow Prognostic Score (mGPS) may be associated with poorer survival in patients with prostate cancer but it is not known whether this is independent of other established prognostic factors. Therefore the aim of this study was to describe the relationship between mGPS and survival in patients with prostate cancer after adjustment for other prognostic factors.&lt;/p&gt; &lt;p&gt;Methods: Retrospective clinical series on patients in Glasgow, Scotland, for whom data from the Scottish Cancer Registry, including Gleason score, Prostate Specific Antigen (PSA), C-reactive protein (CRP) and albumin, six months prior to or following the diagnosis, were included in this study.&lt;/p&gt; &lt;p&gt;The mGPS was constructed by combining CRP and albumin. Five-year and ten-year relative survival and relative excess risk of death were estimated by mGPS categories after adjusting for age, socioeconomic circumstances, Gleason score, PSA and previous in-patient bed days.&lt;/p&gt; &lt;p&gt;Results: Seven hundred and forty four prostate cancer patients were identified; of these, 497 (66.8%) died during a maximum follow up of 11.9 years. Patients with mGPS of 2 had poorest 5-year and 10-year relative survival, of 32.6% and 18.8%, respectively. Raised mGPS also had a significant association with excess risk of death at five years (mGPS 2: Relative Excess Risk = 3.57, 95% CI 2.31-5.52) and ten years (mGPS 2: Relative Excess Risk = 3.42, 95% CI 2.25-5.21) after adjusting for age, socioeconomic circumstances, Gleason score, PSA and previous in-patient bed days.&lt;/p&gt; &lt;p&gt;Conclusions: The mGPS is an independent and objective prognostic indicator for survival of patients with prostate cancer. It may be useful in determining the clinical management of patients with prostate cancer in addition to established prognostic markers.&lt;/p&gt

TCR Convergence in Individuals Treated With Immune Checkpoint Inhibition for Cancer.

Tumor antigen-driven selection may expand T cells having T cell receptors (TCRs) of shared antigen specificity but different amino acid or nucleotide sequence in a process known as TCR convergence. Substitution sequencing errors introduced by TCRβ (TCRB) repertoire sequencing may create artifacts resembling TCR convergence. Given the anticipated differences in substitution error rates across different next-generation sequencing platforms, the choice of platform could be consequential. To test this, we performed TCRB sequencing on the same peripheral blood mononuclear cells (PBMC) from individuals with cancer receiving anti-CTLA-4 or anti-PD-1 using an Illumina-based approach (Sequenta) and an Ion Torrent-based approach (Oncomine TCRB-LR). While both approaches found similar TCR diversity, clonality, and clonal overlap, we found that Illumina-based sequencing resulted in higher TCR convergence than with the Ion Torrent approach. To build upon this initial observation we conducted a systematic comparison of Illumina-based TCRB sequencing assays, including those employing molecular barcodes, with the Oncomine assay, revealing differences in the frequency of convergent events, purportedly artifactual rearrangements, and sensitivity of detection. Finally, we applied the Ion Torrent-based approach to evaluate clonality and convergence in a cohort of individuals receiving anti-CTLA-4 blockade for cancer. We found that clonality and convergence independently predicted response and could be combined to improve the accuracy of a logistic regression classifier. These results demonstrate the importance of the sequencing platform in assessing TCRB convergence

Conditional Concordance-Assisted Learning Under Matched Case-Control Design For Combining Biomarkers For Population Screening

Incorporating promising biomarkers into cancer screening practices for early-detection is increasingly appealing because of the unsatisfactory performance of current cancer screening strategies. The matched case-control design is commonly adopted in biomarker development studies to evaluate the discriminative power of biomarker candidates, with an intention to eliminate confounding effects. Data from matched case-control studies have been routinely analyzed by the conditional logistic regression, although the assumed logit link between biomarker combinations and disease risk may not always hold. We propose a conditional concordance-assisted learning method, which is distribution-free, for identifying an optimal combination of biomarkers to discriminate cases and controls. We are particularly interested in combinations with a clinically and practically meaningful specificity to prevent disease-free subjects from unnecessary and possibly intrusive diagnostic procedures, which is a top priority for cancer population screening. We establish asymptotic properties for the derived combination and confirm its favorable finite sample performance in simulations. We apply the proposed method to the prostate cancer data from the carotene and retinol efficacy trial (CARET)