Biomarkers for Early Detection and as Surrogate Endpoints in Cancer Prevention Trials: Issues and Opportunities
In order to improve the early detection and diagnosis of cancer, give more accurate prognoses, stratify individuals by risk, predict response to treatment, and help the transition of basic research into clinical application, biomarkers are needed that accurately represent or predict clinical outcomes. To be useful in trials for chemopreventive agent development, biomarkers must be subject to modulation, easy to obtain and quantify, and have biological meaning, ideally representing steps in well-understood carcinogenic pathways. Though difficult to validate fully, wisely chosen biomarkers in early-phase trials can inform the prioritization of large-scale, long-term trials that measure clinical outcomes. When well-designed, smaller trials using biomarkers as surrogate endpoints should promote faster decisions regarding which targeted preventive agents to pursue, promising greater progress in the personalization of medicine. Biomarkers could become useful in distinguishing indolent from aggressive forms of ductal carcinoma in situ as well as localized invasive breast and prostate cancer, lesions that are often overtreated. Chemopreventive strategies that reduce the progression of early forms of premalignancy can benefit patients not only by reducing their risk of cancer and death from cancer but also by reducing their need for invasive interventions. Genomic and proteomic methods offer the possibility of revealing new potential markers, especially for diseases whose biology is complex or not well understood. Panels of markers may be used to accommodate the molecular heterogeneity of cancers. Biomarkers in phase 2 prevention trials of combinations of chemopreventive drugs have been used to demonstrate synergistic action of multiple agents, allowing use of lower doses, with less toxicity, a critical feature of interventions intended for cancer prevention.
Available from: Claudio Sorio
- "Therefore , analytical platforms are generally integrated within computational biology and bioinformatics facilities that are necessary to analyze , associate and correlate large amounts of data obtained from different sources  . Technologies and biomarkers must be tested and validated in pre-clinical cell and animal models before undergoing final evaluation and validation in clinical trials and definitively used in clinics  . These steps are necessary to define the performances of each test (e.g. "
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ABSTRACT: Since the middle of 20(th) century infrared (IR) spectroscopy coupled to microscopy (IR microspectroscopy) has been recognized as a non destructive, label free, highly sensitive and specific analytical method with many potential useful applications in different fields of biomedical research and in particular cancer research and diagnosis. Although many technological improvements have been made to facilitate biomedical applications of this powerful analytical technique, it has not yet properly come into the scientific background of many potential end users. Therefore, to achieve those fundamental objectives an interdisciplinary approach is needed with basic scientists, spectroscopists, biologists and clinicians who must effectively communicate and understand each other's requirements and challenges. In this review we aim at illustrating some principles of Fourier transform (FT) Infrared (IR) vibrational spectroscopy and microscopy (microFT-IR) as a useful method to interrogate molecules in specimen by mid-IR radiation. Penetrating into basics of molecular vibrations might help us to understand whether, when and how complementary information obtained by microFT-IR could become useful in our research and/or diagnostic activities. MicroFT-IR techniques allowing to acquire information about the molecular composition and structure of a sample within a micrometric scale in a matter of seconds will be illustrated as well as some limitations will be discussed. How biochemical, structural, and dynamical information about the systems can be obtained by bench top microFT-IR instrumentation will be also presented together with some methods to treat and interpret IR spectral data and applicative examples. The mid-IR absorbance spectrum is one of the most information-rich and concise way to represent the whole "… omics" of a cell and, as such, fits all the characteristics for the development of a clinically useful biomarker.
Available from: Heath D Schmidt
- "However, group identity may be optimized by using equation modeling in which each individual variable has a designated weight, depending on its positive predictive value (PPV) (Altman and Bland, 1994). While the use of multiple biomarkers for diagnosis and treatment prediction is not generally done in psychiatry, it is a common strategy in other fields such as oncology (Dunn et al, 2011; Malinowski, 2007a, b; Marrero et al, 2010; Vauthey et al, 2010; Yurkovetsky et al, 2010; Zhu et al, 2011). A simple clinical example would be methods for staging of various cancers that may use multiple predictive characteristics (Vauthey et al, 2010). "
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ABSTRACT: Major depressive disorder (MDD) is a heterogeneous illness for which there are currently no effective methods to objectively assess severity, endophenotypes, or response to treatment. Increasing evidence suggests that circulating levels of peripheral/serum growth factors and cytokines are altered in patients with MDD, and that antidepressant treatments reverse or normalize these effects. Furthermore, there is a large body of literature demonstrating that MDD is associated with changes in endocrine and metabolic factors. Here we provide a brief overview of the evidence that peripheral growth factors, pro-inflammatory cytokines, endocrine factors, and metabolic markers contribute to the pathophysiology of MDD and antidepressant response. Recent preclinical studies demonstrating that peripheral growth factors and cytokines influence brain function and behavior are also discussed along with their implications for diagnosing and treating patients with MDD. Together, these studies highlight the need to develop a biomarker panel for depression that aims to profile diverse peripheral factors that together provide a biological signature of MDD subtypes as well as treatment response.
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ABSTRACT: Breast cancer is the most common cancer among women in the United States, with 192,870 new cases and 40,170 deaths due to this disease estimated to have occurred 2009. An emphasis on prevention has been increasing in view of a persisting high incidence of disease. Seventy percent of breast cancers are estrogen receptor (ER)-positive, and are therefore presumed to be hormone-responsive and potentially treatable or preventable by anti-estrogenic agents. To date, the large, phase III randomized controlled breast cancer prevention trials have tested and are testing only hormonal drugs designed to antagonize the carcinogenic effect of endogenous estrogen; these agents are either selective estrogen receptor modulators (SERMs) or aromatase inhibitors (AIs). The SERMs, tamoxifen and raloxifene, have been shown in these large trials to reduce the risk of ER-positive breast cancers; prevention trials of AIs are ongoing. Interest is now focusing on developing agents with a broader spectrum of preventive activity, particularly with regard to ER-negative subtypes of breast cancer. A number of phase I and II trials using tissue-derived surrogate endpoint biomarkers (SEBs) as outcomes have been implemented. These smaller trials address prevention not only of ER-negative but also ER-positive breast cancers, since approximately 50% of the latter have been shown to be resistant to the estrogen-targeting drugs used in the large trials. Issues of importance in these smaller trials include choice of agent, selection of appropriate trial participants, trial design, method of access to breast tissue in women without cancer, selection and monitoring of SEBs, and monitoring of drug toxicity.
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