Use of biomarkers for breast cancer risk assessment and prevention

Epidemiologic models used for cancer risk prediction, such as the Gail model, are validated for populations undergoing regular screening but often have suboptimal individual predictive accuracy. Risk biomarkers may be employed to improve predictive accuracy based on the Gail or other epidemiologic models and, to the extent that they are reversible, may be used to assess response in phase I–II prevention trials. Risk biomarkers used as intermediate response endpoints include high mammographic breast density, intra-epithelial neoplasia, and cytomorphology with associated molecular markers such as Ki-67. At the present time these biomarkers may not be used to predict or monitor individual response to standard prevention interventions but are used in early phase clinical trials as preliminary indicators of efficacy.     

Systematic Review of Screening and Surveillance Programs to Protect Workers from Nanomaterials

BackgroundScreening and surveillance approaches for workers exposed to nanomaterials could aid in early detection of health effects, provide data for epidemiological studies and inform action to decrease exposure. The aim of this review is to identify such screening and surveillance approaches, in order to extract available data regarding (i) the studies that have successfully been implemented in present day, (ii) identification of the most common and/or toxic nano-related health hazards for workers and (iii) possible exposure surveillance markers. This review contributes to the current understanding of the risk associated with nanomaterials by determining the knowledge gap and making recommendations based on current findings.MethodsA systematic review was conducted. PubMed and Embase were searched to identify articles reporting on any surveillance-related study that described both exposure to nanomaterials and the health indicators that were measured. Four reviewers worked in pairs to independently assess the eligibility of studies and risk of bias before extraction of data. Studies were categorised according to the type of study and the medical surveillance performed, which included the type of nanomaterial, any exposure details provided, as well as health indicators and biomarkers tested.ResultsInitially 92 studies were identified, from which 84 full texts were assessed for eligibility. Seven studies met all the inclusion criteria, i.e. those performed in Taiwan, Korea, Czech Republic and the US. Of these, six compared health indicators between exposed and unexposed workers and one study described a surveillance program. All studies were at a high risk of bias. Workers were exposed to a mix of nanomaterials in three studies, carbon-based nanomaterials in two studies, nano-silver in one study and nano-titanium oxide in the other study. Two studies did not find a difference in biomarkers between exposed and unexposed workers. In addition, differences in early effects on pulmonary function or neurobehavioral tests were not observed. One study found an increased prevalence of allergic dermatitis and “sneezing” in the exposed group.ConclusionsThis review of recently published data on surveillance studies proves that there is a gap in the current knowledge, where most of the surveillance-related studies reported do not follow a set format that provides the required information on ENM characterisation, the type of exposure and the measured indicators/biomarkers. Hence, there is very low quality evidence that screening and surveillance might detect adverse health effects associated with workplace exposure. This systematic review is relevant because it proves that, although surveillance programs have been initiated and preliminary results are being published, the current studies are actually not answering the important questions or solving the overall problem regarding what the potential health hazards are among workers either handling or potentially exposed to ENMs. The recommendations, thus proposed, are based on an obvious need for (i) exposure registries, where longitudinal follow-up studies should inform surveillance, (ii) known exposure measurements or summary indices for ENMs as a reference (iii) validation of candidate biomarkers and (iv) studies that compare the effects of these surveillance approaches to usual care, e.g. those commonly followed for bulk-size hazardous materials.     

Biomarkers in molecular epidemiology studies for health risk prediction

The field of molecular epidemiology is very promising, as sophisticated techniques are being developed to address etiology, genetic susceptibility and mechanisms for induction of disease. The use of biomarkers plays a key role in these investigations because the information can be used to predict the development of disease and to implement disease prevention programs. However, as emphasized by Frederica P. Perera, the field is strewn with studies either that failed to use validated biomarkers or whose designs did not adequately consider the biology of the endpoints, and the availability of validated biomarkers of health risk is still limited. In this review, we have briefly described the usefulness of certain biomarkers for the documentation of exposure and early biological effects, with special concern for the prediction of cancer. An emphasis is placed on understanding the biological and health significance of biomarkers. By building reliable biomarker databases, a promising future is the integration of information from the genome programs to expand the scientific frontiers on etiology, health risk prediction and prevention of environmental disease.     

Current and proposed biomarkers of anthracycline cardiotoxicity in cancer: emerging opportunities in oxidative damage and autophagy

A biomarker is defined as "a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or biological responses to a therapeutic intervention". Biomarkers can be utilized to detect disease, evaluate treatment risks, or determine treatment effectiveness. In the case of cancer, anthracyclines such as doxorubicin are front-line therapy to treat a number of different malignancies including breast cancer. However, a significant fraction of patients experience drug-induced cardiotoxicity. This toxicity is dose-limiting and can cause long-term morbidity or mortality. There is an unmet medical need to identify patients who are at risk for doxorubicin-induced cardiotoxicity, to detect cardiac damage early so that patient risk can be minimized, and to monitor the success of cardioprotective strategies. Therefore, doxorubicin treatment of cancer is an excellent example of the need for biomarkers to indicate drug safety in addition to drug efficacy. In this review we will discuss the mechanism of doxorubicinassociated cardiotoxicity, as well as other cancer therapies that induce cardiac toxicity by causing oxidative damage. We will also evaluate established and proposed biomarkers for cardiotoxicity based on our evolving knowledge of oxidative damage and subsequent autophagy. Finally, we will discuss advantages of combining oxidative damage- and autophagy-based protein biomarkers with current biomarkers such as troponins to facilitate early detection and mitigation of cardiotoxicity induced by cancer therapeutic agents.     

Genomic and proteomic biomarkers for cancer: A multitude of opportunities

Biomarkers are molecular indicators of a biological status, and as biochemical species can be assayed to evaluate the presence of cancer and therapeutic interventions. Through a variety of mechanisms cancer cells provide the biomarker material for their own detection. Biomarkers may be detectable in the blood, other body fluids, or tissues. The expectation is that the level of an informative biomarker is related to the specific type of disease present in the body. Biomarkers have potential both as diagnostic indicators and monitors of the effectiveness of clinical interventions. Biomarkers are also able to stratify cancer patients to the most appropriate treatment. Effective biomarkers for the early detection of cancer should provide a patient with a better outcome which in turn will translate into more efficient delivery of healthcare. Technologies for the early detection of cancer have resulted in reductions in disease-associated mortalities from cancers that are otherwise deadly if allowed to progress. Such screening technologies have proven that early detection will decrease the morbidity and mortality from cancer. An emerging theme in biomarker research is the expectation that panels of biomarker analytes rather than single markers will be needed to have sufficient sensitivity and specificity for the presymptomatic detection of cancer. Biomarkers may provide prognostic information of disease enabling interventions using targeted therapeutic agents as well as course-corrections in cancer treatment. Novel genomic, proteomic and metabolomic technologies are being used to discover and validate tumor biomarkers individually and in panels.     

Tissue biomarkers for prostate cancer radiation therapy

Prostate cancer is the most common cancer and second leading cause of cancer deaths among men in the United States. Most men have localized disease diagnosed following an elevated serum prostate specific antigen test for cancer screening purposes. Standard treatment options consist of surgery or definitive radiation therapy directed by clinical factors that are organized into risk stratification groups. Current clinical risk stratification systems are still insufficient to differentiate lethal from indolent disease. Similarly, a subset of men in poor risk groups need to be identified for more aggressive treatment and enrollment into clinical trials. Furthermore, these clinical tools are very limited in revealing information about the biologic pathways driving these different disease phenotypes and do not offer insights for novel treatments which are needed in men with poor-risk disease. We believe molecular biomarkers may serve to bridge these inadequacies of traditional clinical factors opening the door for personalized treatment approaches that would allow tailoring of treatment options to maximize therapeutic outcome. We review the current state of prognostic and predictive tissue-based molecular biomarkers which can be used to direct localized prostate cancer treatment decisions, specifically those implicated with definitive and salvage radiation therapy.     

Combining several screening tests: optimality of the risk score

The development of biomarkers for cancer screening is an active area of research. While several biomarkers exist, none is sufficiently sensitive and specific on its own for population screening. It is likely that successful screening programs will require combinations of multiple markers. We consider how to combine multiple disease markers for optimal performance of a screening program. We show that the risk score, defined as the probability of disease given data on multiple markers, is the optimal function in the sense that the receiver operating characteristic (ROC) curve is maximized at every point. Arguments draw on the Neyman-Pearson lemma. This contrasts with the corresponding optimality result of classic decision theory, which is set in a Bayesian framework and is based on minimizing an expected loss function associated with decision errors. Ours is an optimality result defined from a strictly frequentist point of view and does not rely on the notion of associating costs with misclassifications. The implication for data analysis is that binary regression methods can be used to yield appropriate relative weightings of different biomarkers, at least in large samples. We propose some modifications to standard binary regression methods for application to the disease screening problem. A flexible biologically motivated simulation model for cancer biomarkers is presented and we evaluate our methods by application to it. An application to real data concerning two ovarian cancer biomarkers is also presented. Our results are equally relevant to the more general medical diagnostic testing problem, where results of multiple tests or predictors are combined to yield a composite diagnostic test. Moreover, our methods justify the development of clinical prediction scores based on binary regression.     

Biomarkers in cancer screening, research and detection: present and future: a review

Biomarkers provide a powerful and dynamic approach to understanding the spectrum of malignancies with applications in observational and analytic epidemiology, randomized clinical trials, screening, diagnosis and prognosis. Defined as alterations in the constituents of tissues or body fluids, these markers offer a means for homogeneous classification of a disease and risk factor, and they can extend one's basic information about the underlying pathogenesis of disease. The goals in cancer research include finding biomarkers that can be used for the early detection of cancers, design individual therapies, and to identify underlying processes involved in the disease. Because so many myriad processes are involved in the diseased states, the goal is similar to 'finding a needle in a haystack'. However, the development of many -omic technologies, such as genomics and proteomics, has allowed us to monitor a large number of key cellular pathways simultaneously. This has enabled the identification of biomarkers and signalling molecules associated with cell growth, cell death and cellular metabolism. These are also facilitating in monitoring the functional disturbance, molecular and cellular damage, and damage response. This brief review describes the development of biomarkers in cancer research and detection with emphasis on different proteomic tools for the identification and discovery of new biomarkers, different clinical assays to detect various biomarkers in different specimens, role of biomarkers in cancer screening and last but not the least, the challenges in this direction of cancer research.     

Predictive markers in early research and companion diagnostic developments in oncology

Predictive biomarkers are discovered and used in oncology research to formulate hypotheses aimed at the identification of patients benefiting from specific therapeutic intervention(s). They pave the way to the development of companion diagnostic tests which are tools readily implemented in the clinic and serve to qualify a patient for treatment with a particular targeted drug or the continued use of a particular drug, thus maximizing the benefit to risk ratio of the medical intervention to the patient. Predictive biomarkers are defined by biological characteristics of the patient's or tumor status that can be measured objectively and correlated with clinical outcome: these can be molecular, cellular or biochemical features. Predictive markers need extensive analytical validation - specific for the tool utilized for their assessment - as well as rigorous clinical qualification in the context of the drug treatment for which they define clinical utility. The process of companion diagnostic development is a highly interdisciplinary and complex one, driven by key crucial milestones and accompanying the same and typical process of a whole drug discovery and development continuum, from marker discovery and validation, assay development, clinical qualification until test approval and commercialization.     

Medical Surveillance for Biological Terrorism Agents

The first recognition of a bioterrorist attack may be sick patients. Recognition and subsequent notification of an attack at the earliest possible moment will assist in rapidly instituting protective measures. New methods of medical surveillance can assist with rapid detection. Syndromic surveillance is the use of newly created or pre-existing databases to track the health of communities. The data can include medical and non-medical information, but typically contains non-specific indicators of health status. These systems are currently being tested and fielded in multiple locations, and nationwide systems are being developed in the United States. Retrospective and prospective analyses have demonstrated the ability of the data to detect disease outbreaks, but the systems have yet to be proven to lead to more effective interventions.     

Biomarkers in cancer screening,research and detection: present and future: a review

Biomarkers provide a powerful and dynamic approach to understanding the spectrum of malignancies with applications in observational and analytic epidemiology, randomized clinical trials, screening, diagnosis and prognosis. Defined as alterations in the constituents of tissues or body fluids, these markers offer a means for homogeneous classification of a disease and risk factor, and they can extend one's basic information about the underlying pathogenesis of disease. The goals in cancer research include finding biomarkers that can be used for the early detection of cancers, design individual therapies, and to identify underlying processes involved in the disease. Because so many myriad processes are involved in the diseased states, the goal is similar to ‘finding a needle in a haystack’. However, the development of many -omic technologies, such as genomics and proteomics, has allowed us to monitor a large number of key cellular pathways simultaneously. This has enabled the identification of biomarkers and signalling molecules associated with cell growth, cell death and cellular metabolism. These are also facilitating in monitoring the functional disturbance, molecular and cellular damage, and damage response. This brief review describes the development of biomarkers in cancer research and detection with emphasis on different proteomic tools for the identification and discovery of new biomarkers, different clinical assays to detect various biomarkers in different specimens, role of biomarkers in cancer screening and last but not the least, the challenges in this direction of cancer research.     

Monitoring oxidative stress biomarkers in the lipidome: is there a roadmap for "human inspection"?

Oxidative stress is more and more recognized as the underlying motif for a broad variety of diseases including cancer. Medicine faces the paramount task to develop better diagnostic tools and drug treatment prediction models in the future to significantly enhance the quality of life. Special interest will focus on earlystage disease biomarkers and biomarkers that could predict healing success at the earliest time point after the treatment started. The accelerated formation of so-called reactive oxygen species (ROS) is becoming widely regarded as the underlying process associated with many diseases like myocardial infarction, Alzheimer's, Parkinson's and kidney disease, etc. Once generated within cells and tissues, ROS can react with a variety of cellular metabolites like fatty acids, proteins or DNA. This review investigates the possibilities for various oxidized metabolites as well as proteomics, genomics and bioimaging biomarkers to serve as early-stage disease biomarkers or biomarkers for drug treatment success. We also assess the value of a step-by-step or cascade biomarker approach as a new paradigm in medical diagnostics. Examples are given for possible analytical methodology and tools as well as statistical methods that could be applied. Such an approach may straighten the road toward new medical diagnostics and treatment regimes, which ultimately could lead to a significantly enhanced medical service for patients suffering from chronic and debilitating or deadly diseases including cancer. Examples from recent research are given to show the progress and possibilities for the proposed model.     

Understanding HPV tests and their appropriate applications

Greater understanding of the role played by human papillomavirus (HPV) in the causation of disease has led to the development of an increasing number of HPV tests with different characteristics. The bewildering choice facing healthcare professionals and providers is daunting. Clearly, HPV testing is no longer simply of research interest, but can provide information that can be used for individual patient management and at the population level for cervical screening and vaccine surveillance. This review aims to provide the background to the development of HPV tests, to explain the different technologies and to discuss the challenges of the application of these optimally in the varied contexts of disease management. Few HPV tests are approved for clinical use and it is important that clinicians understand which test can be utilized, in what circumstances, with what specimens and the meaning of the report issued. HPV testing is no longer applicable only to cervical disease, and we have suggested additional areas, such as the oropharynx, in which HPV testing services might be implemented in the near future. New tests will continue to emerge and we have identified some of the indirect measures of HPV activity, or biomarkers, that could help in the risk stratification of HPV infection and associated disease. The challenges relating to the optimal application of the various HPV technologies are compounded by the lack of evidence regarding their performance in vaccinated populations. Currently published work, including modelling studies, has been undertaken in non‐immunized populations. We therefore end by addressing the issues regarding appropriate strategies and tests for immunized populations.     

Advances in ovarian cancer proteomics: the quest for biomarkers and improved therapeutic interventions

Epithelial ovarian cancer is the leading cause of cancer-related death among gynecological cancers due to the asymptomatic nature of the disease, a lack of early detection markers and the development of resistance to current chemotherapeutic agents. Currently available tests (CA-125, transvaginal ultrasound or combination of both) lack the sensitivity and specificity to be useful as an efficient screening tool for surveillance of the general population. Thus, there is an urgent need for the development and validation of new molecular markers that would be both specific and sensitive indicators of disease onset, as well as progression. Proteomic profiling has emerged as a powerful tool to study ovarian cancer in an unbiased way at the molecular level, to monitor the effects of given treatment options and for the discovery of biomarkers. In this review we discuss the challenges associated with proteomics-based biomarker discovery and some recent concepts to potentially overcome these hurdles. Recent proteomics work on ovarian cancer cells and tissues will be discussed in light of obtaining new insights into fundamental biological processes, as well as their potential integration with ongoing biomarker discovery pipelines.     

Advances in ovarian cancer proteomics: the quest for biomarkers and improved therapeutic interventions

Epithelial ovarian cancer is the leading cause of cancer-related death among gynecological cancers due to the asymptomatic nature of the disease, a lack of early detection markers and the development of resistance to current chemotherapeutic agents. Currently available tests (CA-125, transvaginal ultrasound or combination of both) lack the sensitivity and specificity to be useful as an efficient screening tool for surveillance of the general population. Thus, there is an urgent need for the development and validation of new molecular markers that would be both specific and sensitive indicators of disease onset, as well as progression. Proteomic profiling has emerged as a powerful tool to study ovarian cancer in an unbiased way at the molecular level, to monitor the effects of given treatment options and for the discovery of biomarkers. In this review we discuss the challenges associated with proteomics-based biomarker discovery and some recent concepts to potentially overcome these hurdles. Recent proteomics work on ovarian cancer cells and tissues will be discussed in light of obtaining new insights into fundamental biological processes, as well as their potential integration with ongoing biomarker discovery pipelines.     

Biomarkers in nutritional epidemiology: applications, needs and new horizons

Modern epidemiology suggests a potential interactive association between diet, lifestyle, genetics and the risk of many chronic diseases. As such, many epidemiologic studies attempt to consider assessment of dietary intake alongside genetic measures and other variables of interest. However, given the multi-factorial complexities of dietary exposures, all dietary intake assessment methods are associated with measurement errors which affect dietary estimates and may obscure disease risk associations. For this reason, dietary biomarkers measured in biological specimens are being increasingly used as additional or substitute estimates of dietary intake and nutrient status. Genetic variation may influence dietary intake and nutrient metabolism and may affect the utility of a dietary biomarker to properly reflect dietary exposures. Although there are many functional dietary biomarkers that, if utilized appropriately, can be very informative, a better understanding of the interactions between diet and genes as potentially determining factors in the validity, application and interpretation of dietary biomarkers is necessary. It is the aim of this review to highlight how some important biomarkers are being applied in nutrition epidemiology and to address some associated questions and limitations. This review also emphasizes the need to identify new dietary biomarkers and highlights the emerging field of nutritional metabonomics as an analytical method to assess metabolic profiles as measures of dietary exposures and indicators of dietary patterns, dietary changes or effectiveness of dietary interventions. The review will also touch upon new statistical methodologies for the combination of dietary questionnaire and biomarker data for disease risk assessment. It is clear that dietary biomarkers require much further research in order to be better applied and interpreted. Future priorities should be to integrate high quality dietary intake information, measurements of dietary biomarkers, metabolic profiles of specific dietary patterns, genetics and novel statistical methodology in order to provide important new insights into gene-diet-lifestyle-disease risk associations.     

Banking of biological fluids for studies of disease-associated protein biomarkers

With the increasing demand of providing personalized medicine the need for biobanking of biological material from individual patients has increased. Such samples are essential for molecular research aimed at characterizing diseases at several levels ranging from epidemiology and diagnostic and prognostic classification to prediction of response to therapy. Clinically validated biomarkers may provide information to be used for diagnosis, screening, evaluation of risk/predisposition, assessment of prognosis, monitoring (recurrence of disease), and prediction of response to treatment and as a surrogate response marker. Many types of biological fluids or tissues can be collected and stored in biorepositories. Samples of blood can be further processed into plasma and serum, and tissue pieces can be either frozen or fixed in formalin and then embedded into paraffin. The present review focuses on biological fluids, especially serum and plasma, intended for study of protein biomarkers. In biomarker studies the process from the decision to take a sample from an individual to the moment the sample is safely placed in the biobank consists of several phases including collection of samples, transport of the samples, and handling and storage of samples. Critical points in each step important for high quality biomarker studies are described in this review. Failure to develop and adhere to robust standardized protocols may have significant consequences as the quality of the material stored in the biobank as well as conclusions and clinical recommendations based on analysis of such material may be severely affected.     

Biomarkers for atherosclerosis: pathophysiological role and pharmacological modulation

PURPOSE OF REVIEW: The aim of this article is to discuss the potential value of biomarkers for atherosclerosis in the assessment of risk for cardiovascular disease, in the pathogenesis of atherosclerosis, and in the monitoring of pharmacological treatment. RECENT FINDINGS: In an attempt to improve global cardiovascular risk prediction, considerable effort has been made in the discovery and characterization of soluble biomarkers which can go beyond the measure of total and LDL cholesterol levels. In particular, circulating molecules related to chronic inflammation have emerged as potential biomarkers for atherosclerosis. Evidence, obtained from in-vitro and in-vivo experimental models, has also documented that the majority of biomarkers play a pathological role in atherogenesis. Multiple screening of different biomarkers may therefore improve the assessment of risk, diagnosis, and prognosis for cardiovascular disease. In addition, soluble biomarkers have been shown to be modulated by hypolipidemic drugs and to be potentially useful in determining the clinical benefits of pharmacological therapies that do not alter serum lipid levels. SUMMARY: Altered levels of soluble biomarkers are associated with cardiovascular disease, and profiling of multiple biomarkers for atherosclerosis will be a useful indicator for better risk assessment, diagnosis, and prognosis, as well as monitoring pharmacological treatments for atherosclerosis.     

Beyond sepsis pathophysiology with cytokines: what is their value as biomarkers for disease severity?

Sepsis is a major challenge in medicine. It is a common and frequently fatal infectious condition. The incidence continues to increase, with unacceptably high mortality rates, despite the use of specific antibiotics, aggressive operative intervention, nutritional support, and anti-inflammatory therapies. Typically, septic patients exhibit a high degree of heterogeneity due to variables such as age, weight, gender, the presence of secondary disease, the state of the immune system, and the severity of the infection. We are at urgent need for biomarkers and reliable measurements that can be applied to risk stratification of septic patients and that would easily identify those patients at the highest risk of a poor outcome. Such markers would be of fundamental importance to decision making for early intervention therapy or for the design of septic clinical trials. In the present work, we will review current biomarkers for sepsis severity and especially the use of cytokines as biomarkers with important pathophysiological role.