A glance at the emerging diagnostic biomarkers in the most prevalent genitourinary cancers

Genitourinary cancers comprise of a heterogenous group of cancers of which renal cell carcinoma, urothelial bladder carcinoma, and prostate adenocarcinoma are the most commonly encountered subtypes. A lot of research is ongoing using various strategies for exploration of novel biomarkers for genitourinary cancers. These biomarkers would not reduce the need for invasive diagnostic techniques but also could be used for early and accurate diagnosis to improve the clinical management required for the disease. Moreover, selecting the appropriate treatment regimen for the responsive patients based on these biomarkers would reduce the treatment toxicity as well as cost. Biomarkers identified using various advanced techniques like next generation sequencing and proteomics, which have been classified as immunological biomarkers, tissue-specific biomarkers and liquid biomarkers. Immunological biomarkers include markers of immunological pathways such as CTLA4, PD-1/PDl-1, tissue biomarkers include tissue specific molecules such as PSA antigen and liquid biomarkers include biomarkers detectable in urine, circulating cells etc.The purpose of this review is to provide a brief introduction to the most prevalent genitourinary malignancies, including bladder, kidney, and prostate cancers along with a major focus on the novel diagnostic biomarkers and the importance of targeting them prior to genitourinary cancers treatment. Understanding these biomarkers and their potential in diagnosis of genitourinary cancer would not help in early and accurate diagnosis as mentioned above but may also lead towards a personalized approach for better diagnosis, prognosis and specified treatment approach for an individual.     

Biomarkers intersect with the exposome

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.     

Biomarkers intersect with the exposome

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.     

Introduction to proteomics: tools for the new biology

Towards revolutionary biomarkers, a considerable amount of research funds and time have been dedicated to proteomics. Although the discovery of novel biomarkers at the dawn of proteomics was a promising development, only a few identified biomarkers seemed to be beneficial for cancer patients. We may need to approach this issue differently, instead of only extending the conventional approaches that have been used historically. The study of biomarkers is essentially a study of diseases and the biochemistry relating to peptide, protein and post-translational modifications is only a tool. A problem-oriented approach should be needed in biomarker development. Clinician participation in the study of biomarkers will lead to realistic, practical and interesting biomarker candidates, which justify the time and expense involved in validation studies. Although discussion in this article is focused on cancer biomarkers, it can generally be applied to biomarker studies for other diseases.     

The impact of cerebrospinal fluid biomarkers on the diagnosis of Alzheimer's disease

The cerebrospinal fluid (CSF) biomarkers β-amyloid(1-42) (Aβ(1-42)), total tau protein (T-tau), and tau phosphorylated at threonine 181 (P-tau(181P)) are gradually finding their way into routine clinical practice as an affirmative diagnostic tool for Alzheimer's disease (AD). These biomarkers have also been implemented in the revised diagnostic criteria for AD. The combination of the CSF biomarkers Aβ(1-42), T-tau, and P-tau(181P) leads to high (around 80%) levels of sensitivity, specificity, and diagnostic accuracy for discrimination between AD and controls (including psychiatric disorders like depression) and can be applied for diagnosing AD in the predementia phases of the disease (mild cognitive impairment). The added value of CSF biomarkers could lie within those cases in which the clinical diagnostic work-up is not able to discriminate between AD and non-AD dementias. However, their discriminatory power for the differential diagnosis of dementia is suboptimal. Other CSF biomarkers, especially those that are reflective of the pathology of non-AD dementia etiologies, could improve the accuracy of differential dementia diagnosis. CSF biomarkers will be of help to establish a correct and early AD diagnosis, even in the preclinical stages of the disease, which will be of importance once disease-modifying drugs for AD become available. Variation in biomarker measurements still jeopardize the introduction of CSF biomarkers into routine clinical practice and clinical trials, but several national and international standardization initiatives are ongoing.     

Cardiac biomarkers for the prediction and diagnosis of atherosclerotic disease and its complications

Inflammation has been implicated in all stages of cardiovascular disease. This has driven a very fruitful search for new biomarkers, which potentially can be used as tools in the diagnosis and prognosis of atherothrombotic disease. While these new markers might prove useful in predicting the onset of atherosclerosis in healthy individuals, the utility of biomarkers in risk assessment for events in those patients with established disease and/or those with acute coronary syndrome requires further work. Effective biomarkers must be standardized, logistically simple to analyze, and clinically useful. Understanding what impact sex, age, ethnicity, and comorbid conditions may have on biomarkers is also of importance. Unfortunately, many of the candidate markers have yet to satisfy these requirements.     

On the analysis of glycomics mass spectrometry data via the regularized area under the ROC curve

Background  

Novel molecular and statistical methods are in rising demand for disease diagnosis and prognosis with the help of recent advanced biotechnology. High-resolution mass spectrometry (MS) is one of those biotechnologies that are highly promising to improve health outcome. Previous literatures have identified some proteomics biomarkers that can distinguish healthy patients from cancer patients using MS data. In this paper, an MS study is demonstrated which uses glycomics to identify ovarian cancer. Glycomics is the study of glycans and glycoproteins. The glycans on the proteins may deviate between a cancer cell and a normal cell and may be visible in the blood. High-resolution MS has been applied to measure relative abundances of potential glycan biomarkers in human serum. Multiple potential glycan biomarkers are measured in MS spectra. With the objection of maximizing the empirical area under the ROC curve (AUC), an analysis method was considered which combines potential glycan biomarkers for the diagnosis of cancer.     

Biomarkers for the development of cancer vaccines: current status

Significant improvements in our knowledge of tumor immunology have resulted in more sophisticated vaccine approaches for the treatment of cancer. However, research into biomarkers that correlate with the clinical outcome of immunotherapy has lagged behind vaccine development. To this extent, very few immunological or other markers exist that can be used in clinical trials for immunotherapy. In this review, we discuss the current status of biomarker development specifically for the monitoring and development of cancer vaccines. This includes immunological biomarkers (measurement of T-cell and cytokine responses), autoimmunity as a correlate for treatment outcome, and the possible development of multiple biomarkers using high-throughput proteomics technologies. The generation of such biomarkers will allow us to make clinical decisions about patient treatment at an earlier stage and should aid in shortening the development time for vaccines.     

Biomarkers for severity of spinal cord injury in the cerebrospinal fluid of rats

One of the major challenges in management of spinal cord injury (SCI) is that the assessment of injury severity is often imprecise. Identification of reliable, easily quantifiable biomarkers that delineate the severity of the initial injury and that have prognostic value for the degree of functional recovery would significantly aid the clinician in the choice of potential treatments. To find such biomarkers we performed quantitative liquid chromatography-mass spectrometry (LC-MS/MS) analyses of cerebrospinal fluid (CSF) collected from rats 24 h after either a moderate or severe SCI. We identified a panel of 42 putative biomarkers of SCI, 10 of which represent potential biomarkers of SCI severity. Three of the candidate biomarkers, Ywhaz, Itih4, and Gpx3 were also validated by Western blot in a biological replicate of the injury. The putative biomarkers identified in this study may potentially be a valuable tool in the assessment of the extent of spinal cord damage.     

Tumour biomarkers—Tracing the molecular function and clinical implication

In recent years, with the increase in cancer mortality caused by metastasis, and with the development of individualized and precise medical treatment, early diagnosis with precision becomes the key to decrease the death rate. Since detecting tumour biomarkers in body fluids is the most non‐invasive way to identify the status of tumour development, it has been widely investigated for the usage in clinic. These biomarkers include different expression or mutation in microRNAs (miRNAs), circulating tumour DNAs (ctDNAs), proteins, exosomes and circulating tumour cells (CTCs). In the present article, we summarized and discussed some updated research on these biomarkers. We overviewed their biological functions and evaluated their multiple roles in human and small animal clinical treatment, including diagnosis of cancers, classification of cancers, prognostic and predictive values for therapy response, monitors for therapy efficacy, and anti‐cancer therapeutics. Biomarkers including different expression or mutation in miRNAs, ctDNAs, proteins, exosomes and CTCs provide more choice for early diagnosis of tumour detection at early stage before metastasis. Combination detection of these tumour biomarkers may provide higher accuracy at the lowest molecule combination number for tumour early detection. Moreover, tumour biomarkers can provide valuable suggestions for clinical anti‐cancer treatment and execute monitoring of treatment efficiency.     

Biomarkers for the lung cancer diagnosis and their advances in proteomics

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.     

Use of ProteinChip technology for identifying biomarkers of parasitic diseases: the example of porcine cysticercosis (Taenia solium)

Taenia solium cysticercosis is a significant public health problem in endemic countries. The current serodiagnostic techniques are not able to differentiate between infections with viable cysts and infections with degenerated cysts. The objectives of this study were to identify specific novel biomarkers of these different disease stages in the serum of experimentally infected pigs using ProteinChip technology (Bio-Rad) and to validate these biomarkers by analyzing serum samples from naturally infected pigs. In the experimental sample set 30 discriminating biomarkers (p < 0.05) were found, 13 specific for the viable phenotype, 9 specific for the degenerated phenotype and 8 specific for the infected phenotype (either viable or degenerated cysts). Only 3 of these biomarkers were also significant in the field samples; however, the peak profiles were not consistent among the two sample sets. Five biomarkers discovered in the sera from experimentally infected pigs were identified as clusterin, lecithin-cholesterol acyltransferase, vitronectin, haptoglobin and apolipoprotein A-I.     

Pilot study using SELDI-TOF-MS based proteomic profile for the identification of diagnostic biomarkers of thyroid proliferative diseases

Biomarkers for thyroid cancer (TCa) lack specificity. To develop TCa specific biomarkers, SELDI-TOF-MS was used to examine the proteomic profile of biopsies obtained from papillary TCa along with adjacent normal tissue. Sixty-three potential biomarkers were categorized by univariate analysis into single biomarker candidates and segregated by multivariate analysis into normal and cancerous groups. Our studies demonstrate the sensitivity and reproducibility of this approach to detect biomarkers for TCa.     

A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.     

Sex Differences in Biological Markers of Health in the Study of Stress,Aging and Health in Russia

Background

The apparent contradiction that women live longer but have worse health than men, the so called male-female health-survival paradox, is very pronounced in Russia. The present study investigates whether men in Moscow are healthier than women at the level of biomarkers, and whether the associations between biomarkers and subjective health have sex-specific patterns.

Materials

Previously collected data in the study of Stress, Aging, and Health in Russia (SAHR, n = 1800) were used to examine sex differences in biomarkers and their associations with physical functioning and self-rated health.

Results

The present study found mixed directions and magnitudes for sex differences in biomarkers. Women were significantly disadvantaged with regard to obesity and waist circumference, whereas men had a tendency toward higher prevalence of electrocardiographic abnormalities. No sex differences were indicated in the prevalence of immunological biomarkers, and mixed patterns were found for lipid profiles. Many biomarkers were associated with physical functioning and general health. Obesity and waist circumference were related to lower physical functioning among females only, while major Q-wave abnormalities with high probabilities of myocardial infarction and atrial fibrillation or atrial flutter were associated with physical functioning and self-rated health among males only.

Conclusion

No clear patterns of sex differences in prevalence of high-risk levels of biomarkers suggest that the male-female health-survival paradox is weaker at the level of health biomarkers. We found some evidence that certain biomarkers reflecting pathophysiological changes in the organism that do not possess acute health risks, but over many years may lead to physical disability, are associated with physical functioning and self-rated health in women, whereas others reflecting more serious life-threatening pathophysiological changes are associated with physical functioning and self-rated health in men.     

Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers

Introduction: Mass spectrometry (MS) is the premier tool for discovering novel disease-associated protein biomarkers. Unfortunately, when applied to complex body fluid samples, MS has poor sensitivity for the detection of low abundance biomarkers (?10 ng/mL), derived directly from the diseased tissue cells or pathogens.

Areas covered: Herein we discuss the strengths and drawbacks of technologies used to concentrate low abundance analytes in body fluids, with the aim to improve the effective sensitivity for MS discovery. Solvent removal by dry-down or dialysis, and immune-depletion of high abundance serum or plasma proteins, is shown to have disadvantages compared to positive selection of the candidate biomarkers by affinity enrichment. A theoretical analysis of affinity enrichment reveals that the yield for low abundance biomarkers is a direct function of the binding affinity (Association/Dissociation rates) used for biomarker capture. In addition, a high affinity capture pre processing step can effectively dissociate the candidate biomarker from partitioning with high abundance proteins such as albumin.

Expert commentary: Properly designed high affinity capture materials can enrich the yield of low abundance (0.1–10 picograms/mL) candidate biomarkers for MS detection. Affinity capture and concentration, as an upfront step in sample preparation for MS, combined with MS advances in software and hardware that improve the resolution of the chromatographic separation can yield a transformative new class of low abundance biomarkers predicting disease risk or disease latency.     

在医疗保健领域开发和使用生物标记物的政策性问题

描述了发展中的生物标记物所处的科学、产业、监管和医疗保健管理系统背景,指出了可能阻碍生物标记物研究、发现、发展、商业化及最终临床应用的一些障碍,聚焦了医疗保健中基于生物标记物的诊断方法和医学检验的应用,探索了生物标记物在改良药物开发中的应用。