Precision Medicine Approach in Prostate Cancer

Prostate cancer is the most prevalent type of cancer and the second cause of death in men worldwide. Various diagnostic and treatment procedures are available for this type of malignancy, but High-grade or locally advanced prostate cancers showed the potential to develop to lethal phase that can be causing dead. Therefore, new approaches are needed to prolong patients' survival and to improve their quality of life. Precision medicine is a novel emerging field that plays an essential role in identifying new sub-classifications of diseases and in providing guidance in treatment that is based on individual multi-omics data. Multi-omics approaches include the use of genomics, transcriptomics, proteomics, metabolomics, epigenomics and phenomics data to unravel the complexity of a disease-associated biological network, to predict prognostic biomarkers, and to identify new targeted drugs for individual cancer patients. We review the impact of multi-omics data in the framework of systems biology in the era of precision medicine, emphasising the combination of molecular imaging modalities with highthroughput techniques and the new treatments that target metabolic pathways involved in prostate cancer.

NMR-based metabolomics studies of human prostate cancer tissue

INTRODUCTION

Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. Serum prostate-specific antigen (PSA) remains the most used biomarker in the detection and management of patients with PCa, in spite of the problems related with its low specificity, false positive rate and overdiagnosis. Furthermore, PSA is unable to discriminate indolent from aggressive PCa, which can lead to overtreatment. Early diagnosed and treated PCa can have a good prognosis and is potentially curable. Therefore, the discovery of new biomarkers able to detect clinically significant aggressive PCa is urgently needed.

METHODS

This revision was based on an electronic literature search, using Pubmed, with Nuclear Magnetic Resonance (NMR), tissue and prostate cancer as keywords. All metabolomic studies performed in PCa tissues by NMR spectroscopy, from 2007 until March 2018, were included in this review.

RESULTS

In the context of cancer, metabolomics allows the analysis of the entire metabolic profile of cancer cells. Several metabolic alterations occur in cancer cells to sustain their abnormal rates of proliferation. NMR proved to be a suitable methodology for the evaluation of these metabolic alterations in PCa tissues, allowing to unveil alterations in citrate, spermine, choline, choline-related compounds, lactate, alanine and glutamate.

CONCLUSION

The study of the metabolic alterations associated with PCa progression, accomplished by the analysis of PCa tissue by NMR, offers a promising approach for elucidating biochemical pathways affected by PCa and also for discovering new clinical biomarkers. The main metabolomic alterations associated with PCa development and promising biomarker metabolites for diagnosis of PCa were outlined.

Heterobivalent agents targeting PSMA and integrin-αvβ3

Differential expression of surface proteins on normal vs malignant cells provides the rationale for the development of receptor-, antigen-, and transporter-based, cancer-selective imaging and therapeutic agents. However, tumors are heterogeneous, and do not always express what can be considered reliable, tumor-selective markers. That suggests development of more flexible targeting platforms that incorporate multiple moieties enabling concurrent targeting to a variety of putative markers. We report the synthesis, biochemical, in vitro, and preliminary in vivo evaluation of a new heterobivalent (HtBv) imaging agent targeting both the prostate-specific membrane antigen (PSMA) and integrin-αvβ3 surface markers, each of which can be overexpressed in certain tumor epithelium and/or neovasculature. The HtBv agent was functionalized with either 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) or the commercially available IRDye800CW. DOTA-conjugated HtBv probe 9 bound to PSMA or αvβ3 with affinities similar to those of monovalent (Mnv) compounds designed to bind to their targets independently. In situ energy minimization experiments support a model describing the conformations adapted by 9 that enable it to bind both targets. IRDye800-conjugated HtBv probe 10 demonstrated target-specific binding to either PSMA or integrin-αvβ3 overexpressing xenografts. HtBv agents 9 and 10 may enable dual-targeted imaging of malignant cells and tissues in an effort to address heterogeneity that confounds many cancer-targeted imaging agents.

Genotyping analysis and ¹⁸FDG uptake in breast cancer patients: a preliminary research

Background

Diagnostic imaging plays a relevant role in the care of patients with breast cancer (BC). Positron Emission Tomography (PET) with 18F-fluoro-2-deoxy-D-glucose (FDG) has been widely proven to be a clinical tool suitable for BC detection and staging in which the glucose analog supplies metabolic information about the tumor. A limited number of studies, sometimes controversial, describe possible associations between FDG uptake and single nucleotide polymorphisms (SNPs). For this reason this field has to be explored and clarified. We investigated the association of SNPs in GLUT1, HIF-1a, EPAS1, APEX1, VEGFA and MTHFR genes with the FDG uptake in BC.

Methods

In 26 caucasian individuals with primary BC, whole-body PET-CT scans were obtained and quantitative analysis was performed by calculating the maximum Standardized Uptake Value normalized to body-weight (SUVmax) and the mean SUV normalized to body-weight corrected for partial volume effect (SUVpvc). Human Gene Mutation Database and dbSNP Short Genetic Variations database were used to analyze gene regions containing the selected SNPs. Patient genotypes were obtained using Sanger DNA sequencing analysis performed by Capillary Electrophoresis.

Results

BC patients were genotyped for the following nine SNPs: GLUT1: rs841853 and rs710218; HIF-1a: rs11549465 and rs11549467; EPAS1: rs137853037 and rs137853036; APEX1: rs1130409; VEGFA: rs3025039 and MTHFR: rs1801133. In this work correlations between the nine potentially useful polymorphisms selected and previously suggested with tracer uptake (using both SUVmax and SUVpvc) were not found.

Conclusions

The possible functional influence of specific SNPs on FDG uptake needs further studies in human cancer. In summary, this is the first pilot study, to our knowledge, which investigates the association between a large panel of SNPs and FDG uptake specifically in BC patients. This work represents a multidisciplinary and translational medicine approach to study BC where, the possible correlation between SNPs and tracer uptake, may be considered to improve personalized cancer treatment and care.

Serum proteomics in biomedical research: a systematic review

Proteins that are important indicators of physiological or pathological states may contribute to the early diagnosis of disease, which may provide a basis for identifying the underlying mechanism of disease development. Serum, contains an abundance of proteins, offers an easy and inexpensive approach for disease detection and possesses a high potential to revolutionize the diagnostics. These differentially expressed proteins in serum have become an important role to monitoring the state for disease. Availability of emerging proteomic techniques gives optimism that serum can eventually be placed as a biomedium for clinical diagnostics. Advancements have benefited biomarker research to the point where serum is now recognized as an excellent diagnostic medium for the detection of disease. Comprehensive proteome of human serum fluid with high accuracy and availability has the potential to open new doors for disease biomarker discovery and for disease diagnostics, providing insights useful for future study. Thus, this review presents an overview of the value of serum as a credible diagnostic tool, and we aim to summarize the proteomic technologies currently used for global analysis of serum proteins and to elaborate on the application of serum proteomics to the discovery of disease biomarkers, and discuss some of the critical challenges and perspectives for this emerging field.

Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks

Metabolic profiling is the unbiased detection and quantification of low molecular-weight metabolites in a living system. It is rapidly developing in biological and translational research, contributing to disease mechanism elucidation, environmental chemical surveillance, biomarker detection, and health outcome prediction. Recent developments in experimental and computational technology allow more and more known metabolites to be detected and quantified from complex samples. As the coverage of the metabolic network improves, it has become feasible to examine metabolic profiling data from a systems perspective, i.e. interpreting the data and performing statistical inference in the context of pathways and genome-scale metabolic networks. Recently a number of methods have been developed in this area, and much improvement in algorithms and databases are still needed. In this review, we survey some methods for the analysis of metabolic profiling data based on metabolic networks.

Challenges and opportunities of metabolomics

The metabolome is a data-rich source of information concerning all the low-molecular-weight metabolites in a biofluid, which can indicate early biological changes to the host due to perturbations in metabolic pathways. Major changes can be seen after minor stimuli, which make it a valuable target for analysis. Due to the diverse and sensitive nature of the metabolome, studies must be designed in a manner to maintain consistency, reduce variation between subjects, and optimize information recovery. Technological advancements in experimental design, mouse models and instrumentation have aided in this effort. Metabolomics has the ultimate potential to be valuable in a clinical setting where it could be used for early diagnosis of a disease and as a predictor of treatment response and survival. During drug treatment, the metabolic status of an individual could be monitored and used to indicate possible toxic effects. Metabolomics therefore has great potential for improving diagnosis, treatment and aftercare of disease.

Fluorescence guidance in urologic surgery

PURPOSE OF REVIEW

Fluorescent tracers can provide anatomical and functional information without altering the visual surgical field. Despite the advances that are being made in tracer development, only a few fluorescent tracers are available for urological interventions.

RECENT FINDINGS

Protoporphyrin IX, hypericin, fluorescein, and indocyanine green were shown to facilitate surgical resection in various ways. Hybrid imaging agents, combining radio and fluorescent labels, have shown improved integration between preoperative and intraoperative imaging. With the rise of surgical fluorescence guidance, various camera systems have been developed that are tailored for optimal detection of the fluorochromes of interest.

SUMMARY

In this review, the basics of fluorescence-guided surgery, including tracer and hardware requirements are discussed.

The discovery of putative urine markers for the specific detection of prostate tumor by integrative mining of public genomic profiles

Urine has emerged as an attractive biofluid for the noninvasive detection of prostate cancer (PCa). There is a strong imperative to discover candidate urinary markers for the clinical diagnosis and prognosis of PCa. The rising flood of various omics profiles presents immense opportunities for the identification of prospective biomarkers. Here we present a simple and efficient strategy to derive candidate urine markers for prostate tumor by mining cancer genomic profiles from public databases. Prostate, bladder and kidney are three major tissues from which cellular matters could be released into urine. To identify urinary markers specific for PCa, upregulated entities that might be shed in exosomes of bladder cancer and kidney cancer are first excluded. Through the ontology-based filtering and further assessment, a reduced list of 19 entities encoding urinary proteins was derived as putative PCa markers. Among them, we have found 10 entities closely associated with the process of tumor cell growth and development by pathway enrichment analysis. Further, using the 10 entities as seeds, we have constructed a protein-protein interaction (PPI) subnetwork and suggested a few urine markers as preferred prognostic markers to monitor the invasion and progression of PCa. Our approach is amenable to discover and prioritize potential markers present in a variety of body fluids for a spectrum of human diseases.

Circulating tumor cells as biomarkers in prostate cancer

Unmet needs in prostate cancer drug development and patient management are the ability to monitor treatment effects and to identify therapeutic targets in a tumor at the time treatment is being considered. This review focuses on establishing analytically valid biomarkers for specific contexts of use in patients with castration-resistant prostate cancer (CRPC), emphasizing a biomarker currently in clinical use, circulating tumor cells (CTC). The FDA Critical Path provides a road map for these investigations, which, if followed, will facilitate the incorporation of these types of assays into clinical decision-making. CTC enumeration at baseline and post-treatment is prognostic of survival, with no threshold effect, and the shedding of cells into the circulation represents an intrinsic property of the tumor, distinct from extent of disease. The clinical utility of monitoring CTC changes with treatment, as an efficacy-response surrogate biomarker of survival, is currently being tested in large phase III trials, with the novel antiandrogen therapies abiraterone acetate and MDV3100. Molecular determinants can be identified and characterized in CTCs as potential predictive biomarkers of tumor sensitivity to a therapeutic modality. Additionally, we discuss novel technologies to enrich and characterize CTCs from more patients, the potential clinical uses of CTCs in determining prognosis and monitoring treatment effects, and CTCs as a source of tissue to identify predictive markers of drug sensitivity to guide treatment selection. Prospective studies, designed around the biomarker itself and the specific clinical context for which it is applied, are needed to further assess the role of these and novel markers in clinical practice.

Metabolomics: a novel approach to early and noninvasive prostate cancer detection

Prostate cancer (PCa) is the most commonly diagnosed visceral cancer in men and is responsible for the second highest cancer-related male mortality rate in Western countries, with increasing rates being reported in Korea, Japan, and China. Considering the low sensitivity of prostate-specific antigen (PSA) testing, it is widely agreed that reliable, age-independent markers of the presence, nature, and progression of PCa are required to facilitate diagnosis and timely treatment. Metabolomics or metabonomics has recently emerged as a novel method of PCa detection owing to its ability to monitor changes in the metabolic signature, within biofluids or tissue, that reflect changes in phenotype and function. This review outlines the physiology of prostate tissue and prostatic fluid in health and in malignancy in relation to metabolomics as well as the principles underlying the methods of metabolomic quantification. Promising metabolites, metabolic profiles, and their correlation with the presence and stage of PCa are summarized. Application of metabolomics to biofluids and in vivo quantification as well as the direction of current research in supplementing and improving current methods of detection are discussed. The current debate in the urology literature on sarcosine as a potential biomarker for PCa is reviewed and discussed. Metabolomics promises to be a valuable tool in the early detection of PCa that may enable earlier treatment and improved clinical outcomes.