The association of prostatic lipids with progression,racial disparity and discovery of biomarkers in prostate cancer

BackgroundIt remains under-investigated whether prostatic lipid profiles are associated with pathogenesis, progression, racial disparity, and discovery of biomarkers in prostate cancer (PCa).MethodsThe electrospray ionization-tandem mass spectrometry was applied to quantitate prostatic lipids in human and mouse PCa and non-cancer prostatic tissues. Biostatistics and bioinformatics were used to compare the concentrations of prostatic lipids at levels of total lipid, group, class and individual species between PCa and benign prostatic tissues, between races, and among pathological conditions of PCa.ResultsProstatic concentrations of total lipids as well as neutral lipids were significantly higher in PCa than in benign prostatic tissues in all population and Caucasian American population, but not in African American population. The prostatic phospholipid were not statistically different between PCa and benign prostatic tissues in all study populations. Cholesteryl ester is the only lipid class significantly higher in PCa than in benign prostatic tissues in all study populations. A panel of prostatic lipid parameters in each study population was identified as diagnostic and prognostic biomarkers with >60% of sensitivity, specificity and accuracy simultaneously. Lipid profiling on mouse prostatic tissues further confirmed correlation of prostatic lipid profiles to the pathogenesis and progression of PCa. In addition, a few prostatic lipids in mouse can serve as prognostic biomarkers in differentiation of indolent from aggressive PCa.ConclusionThe prostatic lipids are widely associated with the pathogenesis, progression and racial disparity of PCa. A panel of prostatic lipids can serve as diagnostic, prognostic and race-specific biomarkers for PCa.     

iTRAQ identification of candidate serum biomarkers associated with metastatic progression of human prostate cancer

A major challenge in the management of patients with prostate cancer is identifying those individuals at risk of developing metastatic disease, as in most cases the disease will remain indolent. We analyzed pooled serum samples from 4 groups of patients (n?=?5 samples/group), collected prospectively and actively monitored for a minimum of 5 yrs. Patients groups were (i) histological diagnosis of benign prostatic hyperplasia with no evidence of cancer 'BPH', (ii) localised cancer with no evidence of progression, 'non-progressing' (iii) localised cancer with evidence of biochemical progression, 'progressing', and (iv) bone metastasis at presentation 'metastatic'. Pooled samples were immuno-depleted of the 14 most highly abundant proteins and analysed using a 4-plex iTRAQ approach. Overall 122 proteins were identified and relatively quantified. Comparisons of progressing versus non-progressing groups identified the significant differential expression of 25 proteins (p<0.001). Comparisons of metastatic versus progressing groups identified the significant differential expression of 23 proteins. Mapping the differentially expressed proteins onto the prostate cancer progression pathway revealed the dysregulated expression of individual proteins, pairs of proteins and 'panels' of proteins to be associated with particular stages of disease development and progression. The median immunostaining intensity of eukaryotic translation elongation factor 1 alpha 1 (eEF1A1), one of the candidates identified, was significantly higher in osteoblasts in close proximity to metastatic tumour cells compared with osteoblasts in control bone (p?=?0.0353, Mann Whitney U). Our proteomic approach has identified leads for potentially useful serum biomarkers associated with the metastatic progression of prostate cancer. The panels identified, including eEF1A1 warrant further investigation and validation.     

Multiple mediation analysis of racial disparity in breast cancer survival

BackgroundRacial (Black vs. White) disparities in breast cancer survival have proven difficult to mitigate. Targeted strategies aimed at the primary factors driving the disparity offer the greatest potential for success. The purpose of this study was to use multiple mediation analysis to identify the most important mediators of the racial disparity in breast cancer survival.MethodsThis was a retrospective cohort study of non-Hispanic Black and non-Hispanic White women diagnosed with invasive breast cancer in Florida between 2004 and 2015. Cox regression was used to obtain unadjusted and adjusted hazard ratios (HR) with 95% confidence intervals (CI) for the association of race with 5- and 10-year breast cancer death. Multiple mediation analysis of tumor (advanced disease stage, tumor grade, hormone receptor status) and treatment-related factors (receipt of surgery, chemotherapy, radiotherapy, and hormone therapy) was used to determine the most important mediators of the survival disparity.ResultsThe study population consisted of 101,872 women of whom 87.0% (n = 88,617) were White and 13.0% were Black (n = 13,255). Black women experienced 2.3 times (HR, 2.27; 95% CI, 2.16–2.38) the rate of 5-year breast cancer death over the follow-up period, which decreased to a 38% increased rate (HR, 1.38; 95% CI, 1.31–1.45) after adjustment for age and the mediators of interest. Combined, all examined mediators explained 73% of the racial disparity in 5-year breast cancer survival. The most important mediators were: (1) advanced disease stage (44.8%), (2) nonreceipt of surgery (34.2%), and (3) tumor grade (18.2%) and hormone receptor status (17.6%). Similar results were obtained for 10-year breast cancer death.ConclusionThese results suggest that additional efforts to increase uptake of screening mammography in hard-to-reach women, and, following diagnosis, access to and receipt of surgery may offer the greatest potential to reduce racial disparities in breast cancer survival for women in Florida.     

The role of lipids in cancer progression and metastasis

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Serum early prostate cancer antigen (EPCA) level and its association with disease progression in prostate cancer in a Chinese population

Background

Early prostate cancer antigen (EPCA) has been shown a prostate cancer (PCa)-associated nuclear matrix protein, however, its serum status and prognostic power in PCa are unknown. The goals of this study are to measure serum EPCA levels in a cohort of patients with PCa prior to the treatment, and to evaluate the clinical value of serum EPCA.

Methods

Pretreatment serum EPCA levels were determined with an ELISA in 77 patients with clinically localized PCa who underwent radical prostatectomy and 51 patients with locally advanced or metastatic disease who received primary androgen deprivation therapy, and were correlated with clinicopathological variables and disease progression. Serum EPCA levels were also examined in 40 healthy controls.

Results

Pretreatment mean serum EPCA levels were significantly higher in PCa patients than in controls (16.84±7.60 ng/ml vs. 4.12±2.05 ng/ml, P<0.001). Patients with locally advanced and metastatic PCa had significantly higher serum EPCA level than those with clinically localized PCa (22.93±5.28 ng/ml and 29.41±8.47 ng/ml vs. 15.17±6.03 ng/ml, P = 0.014 and P<0.001, respectively). Significantly elevated EPCA level was also found in metastatic PCa compared with locally advanced disease (P<0.001). Increased serum EPCA levels were significantly and positively correlated with Gleason score and clinical stage, but not with PSA levels and age. On multivariate analysis, pretreatment serum EPCA level held the most significantly predictive value for the biochemical recurrence and androgen-independent progression among pretreatment variables (HR = 4.860, P<0.001 and HR = 5.418, P<0.001, respectively).

Conclusions

Serum EPCA level is markedly elevated in PCa. Pretreatment serum EPCA level correlates significantly with the poor prognosis, showing prediction potential for PCa progression.     

Application of mass spectrometry to the discovery of biomarkers for detection of prostate cancer

There has been an impressive emergence of mass spectrometry based technologies applied toward the study of proteins. Equally notable is the rapid adaptation of these technologies to biomedical approaches in the realm of clinical proteomics. Concerted efforts toward the elucidation of the proteomes of organ sites or specific disease state are proliferating and from these efforts come the promise of better diagnostics/prognostics and therapeutic intervention. Prostate cancer has been a focus of many such studies with the promise of improved care to patients via biomarkers derived from these proteomic approaches. The newer technologies provide higher analytical capabilities, employ automated liquid handling systems, fractionation techniques and bioinformatics tools for greater sensitivity and resolving power, more robust and higher throughput sample processing, and greater confidence in analytical results. In this prospects, we summarize the proteomic technologies applied to date in prostate cancer, along with their respective advantages and disadvantages. The development of newer proteomic strategies for use in future applications is also discussed.     

Newer potential biomarkers in prostate cancer

Prostate-specific antigen (PSA) screening has led to a significant rise in the number of men diagnosed with prostate cancer and an associated increase in biopsies performed. Despite its limitations, including a positive predictive value of only 25%-40%, PSA remains the only generally accepted biomarker for prostate cancer. There is a need for better tools to not only identify men with prostate cancer, but also to recognize those with potentially lethal disease who will benefit from intervention. A great deal of work has been done worldwide to improve our knowledge of the genetics behind prostate cancer and the specificity of PSA by developing assays for different PSA isoforms. Common genetic alterations in prostate cancer patients have been identified, including CpG hypermethylation of GSPT1 and TMPRSS2:ERG gene fusion. Serum and urine detection of RNA biomarkers (eg, PCA3) and prostate cancer tissue protein antibodies (eg, EPCA) are being evaluated for detection and prognostic tools. This article reviews some of the promising developments in biomarkers.     

Proteomic analysis of conditioned media from the PC3, LNCaP, and 22Rv1 prostate cancer cell lines: discovery and validation of candidate prostate cancer biomarkers

Early detection of prostate cancer is problematic due to the lack of a marker that has high diagnostic sensitivity and specificity. The prostate specific antigen (PSA) test, in combination with digital rectal examination, is the gold standard for prostate cancer diagnosis. However, this modality suffers from low specificity. Therefore, specific markers for clinically relevant prostate cancer are needed. Our objective was to proteomically characterize the conditioned media from three human prostate cancer cell lines of differing origin [PC3 (bone metastasis), LNCaP (lymph node metastasis), and 22Rv1 (localized to prostate)] to identify secreted proteins that could serve as novel prostate cancer biomarkers. Each cell line was cultured in triplicate, followed by a bottom-up analysis of the peptides by two-dimensional chromatography and tandem mass spectrometry. Approximately, 12% (329) of the proteins identified were classified as extracellular and 18% (504) as membrane-bound among which were known prostate cancer biomarkers such as PSA and KLK2. To select the most promising candidates for further investigation, tissue specificity, biological function, disease association based on literature searches, and comparison of protein overlap with the proteome of seminal plasma and serum were examined. On the basis of this, four novel candidates, follistatin, chemokine (C-X-C motif) ligand 16, pentraxin 3 and spondin 2, were validated in the serum of patients with and without prostate cancer. The proteins presented in this study represent a comprehensive sampling of the secreted and shed proteins expressed by prostate cancer cells, which may be useful as diagnostic, prognostic or predictive serological markers for prostate cancer.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Secretome proteomics for discovery of cancer biomarkers

“Secretome” is referred to as the rich, complex set of molecules secreted from living cells. In a less strict definition frequently followed in “secretome” studies, the term also includes molecules shed from the surface of living cells. Proteins of secretome (will be referred to as secreted) play a key role in cell signaling, communication and migration. The need for developing more effective cancer biomarkers and therapeutic modalities has led to the study of cancer cell secretome as a means to identify and characterize diagnostic and prognostic markers and potential drug and therapeutic targets. Significant technological advances in the field of proteomics during the last two decades have greatly facilitated research towards this direction. Nevertheless, secretome analysis still faces some difficulties mainly related to sample collection and preparation. The goal of this article is to provide an overview of the main findings from the analysis of cancer cell secretome. Specifically, we focus on the presentation of main methodological approaches that have been developed for the study of secreted proteins and the results thereof from the analysis of secretome in different types of malignancies; special emphasis is given on correlation of findings with protein expression in body fluids.     

The racial disparity in breast cancer mortality in the 25 largest cities in the United States

Introduction: Although the racial disparity in breast cancer mortality is widely discussed there are no studies that analyze this phenomenon at the city level. Methods: We used national death files, abstracting those cases for which the cause was malignant neoplasm of the breast (ICD-10 = C50) for the numerators and American Community Survey data for the denominators. The 25 largest cities in the US were the units of analysis. Non-Hispanic Black:non-Hispanic White rate ratios (RRs) were calculated, along with their confidence intervals, as measures of the racial disparity. Seven ecological (city-level) variables were examined as possible correlates. Results: Almost all the NHB rates were greater than almost all the NHW rates. All but 3 of the RRs (range 0.78–2.09; median = 1.44) were >1, 13 of them significantly so. None of the RRs < 1 were significant. From among the 7 potential correlates, only median household income (r = ?0.43, p = 0.037) and a measure of segregation (r = 0.42, r = 0.039) were significantly related to the RR. Conclusion: This is the first study that we have been able to locate which examines city-level racial disparities in breast cancer mortality. The results are of concern for several cities and for the field in general. A strategy for reducing this disparity in Chicago is in place and may serve as a model for other cities wanting to initiate a similar process. Clearly it is time to take action.     

Interleukin-6 and prostate cancer progression

Prostate cancer, while initially dependent on androgens for proliferation, progresses to an androgen-independent state. Evidence has been accumulating that interleukin-6 (IL-6) may contribute to prostate cancer progression. Serum levels of IL-6 correlate with prostate tumor burden and patient morbidity. The prostate tissue itself appears to be a source of IL-6 and its receptor. Furthermore, experimental data suggest that IL-6 is an autocrine and paracrine growth factor for androgen-independent prostate cancer cell lines. For example, inhibition of IL-6, with anti-IL-6 antibody, sensitizes androgen-independent prostate cancer cells to chemotherapeutic agents in vitro. Finally, IL-6 activates a variety of signal transduction cascades, some which stimulate androgen receptor activity, in prostate cancer cells. These data suggest that targeting IL-6 may have multiple benefits in prostate cancer patients.     

Integrative biology in the discovery of relevant biomarkers monitoring cognitive disorders pathogenesis and progression

Cognitive disorders are highly heterogeneous in terms of symptoms, clinical aetiologies, disease progression and therapeutic responses. Furthermore, their potential biological causes remain largely unknown. Progress at these different levels is currently mired in a vicious circle. The identification of coherent biomarkers, essential for clinical and therapeutic progress, requires an understanding of either the relevant pathogenic processes or, at the very least, of the parameters that need to be monitored. But, syndrome-dominated conceptual thinking has become a barrier to understanding the biological processes linked to diseases characterized by clinical and therapeutic heterogeneity. As a result, current biomarkers of cognitive disorders are much too numerous, too heterogeneous and too variable to serve useful purposes. This leads to an untenable situation that precludes coherent therapeutic developments since it effectively prevents defining what could constitute valid biological, clinical and therapeutic approaches. How to escape from this situation? The problem could be partly resolved by adopting the much wider views allowed by “system-wide” approaches: indeed, by constructing predictive theoretical models of what could constitute pathological cognitive processes. This, naturally, shall require the integration of massive amounts of highly heterogeneous and often conflicting information. The following article aims to provide a necessarily brief overview of the concepts, the breadth of data and the variety of network dynamics that will have to be considered while proposing a functional modelbuilding approach, experimentally validated in vitro and in vivo, that could be fruitfully utilised.     

Genomic signatures associated with the development, progression, and outcome of prostate cancer

Prostate cancer remains a common cause of cancer death in men. Applications of new genomic technologies to the recent development of high-quality prostate cancer models in multiple contexts have added great molecular insight into the development of and progression to metastasis. Genomic analysis of DNA, RNA, and protein alterations allows for the global assessment of this disease and provides the molecular framework to improve risk classification, outcome prediction, and development of targeted therapies. The creation of expression profiles and signatures will allow the evaluation of cancer phenotypes and give insight into determining those with increased risk of cancer, identification of critical pathways involved in the development of cancer, prediction of disease outcome, and assessment of the response of cancer to established and novel therapies.This review focuses on highlighting recent work in genomics and on its role in evaluating potential genetic modifiers of prostate cancer and novel biomarkers that may help with prostate cancer diagnosis, its potential to provide a better understanding of prostate cancer behavior and transition to metastatic disease, and its role in current and new therapies in prostate cancer. This framework has the exciting potential to be predictive and provide personalized and individual treatment to the large number of men diagnosed with prostate cancer each year.