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Eleftherios P Diamandis - One of the best experts on this subject based on the ideXlab platform.
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utility of circulating tumor dna in Cancer Diagnostics with emphasis on early detection
BMC Medicine, 2018Co-Authors: Clare Fiala, Eleftherios P DiamandisAbstract:Various recent studies have focused on analyzing tumor genetic material released into the blood stream, known as circulating tumor DNA (ctDNA). Herein, we describe current research on the application of ctDNA to Cancer management, including prognosis determination, monitoring for treatment efficacy/relapse, treatment selection, and quantification of tumor size and disease burden. Specifically, we examine the utility of ctDNA for early Cancer Diagnostics focusing on the development of a blood test to detect Cancer in asymptomatic individuals by sequencing and analyzing mutations in ctDNA. Next, we discuss the prospect of using ctDNA to test for Cancer, and present our calculations based on previously published empirical findings in Cancer and prenatal Diagnostics. We show that very early stage (asymptomatic) tumors are not likely to release enough ctDNA to be detectable in a typical blood draw of 10 mL. Data are also presented showing that mutations in circulating free DNA can be found in healthy individuals and will likely be very difficult to distinguish from those associated with Cancer. We conclude that the ctDNA test, in addition to its high cost and complexity, will likely suffer from the same issues of low sensitivity and specificity as traditional biomarkers when applied to population screening and early (asymptomatic) Cancer diagnosis.
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peptidomics of urine and other biofluids for Cancer Diagnostics
Clinical Chemistry, 2014Co-Authors: Josep Miquel Bauca, Eleftherios P Diamandis, Eduardo MartinezmorilloAbstract:BACKGROUND: Cancer is a leading cause of death worldwide. The low diagnostic sensitivity and specificity of most current Cancer biomarkers make early Cancer diagnosis a challenging task. The comprehensive study of peptides and small proteins in a living system, known as “peptidomics,” represents an alternative technological approach to the discovery of potential biomarkers for the assessment of a wide variety of pathologies. This review examines the current status of peptidomics for several body fluids, with a focus on urine, for Cancer Diagnostics applications. CONTENT: Several studies have used high-throughput technologies to characterize the peptide content of different body fluids. Because of its noninvasive collection and high stability, urine is a valuable source of candidate Cancer biomarkers. A wide variety of preanalytical issues concerning patient selection and sample handling need to be considered, because not doing so can affect the quality of the results by introducing bias and artifacts. Optimization of both the analytical strategies and the processing of bioinformatics data is also essential to minimize the false-discovery rate. SUMMARY: Peptidomics-based studies of urine and other body fluids have yielded a number of biomolecules and peptide panels with potential for diagnosing different types of Cancer, especially of the ovary, prostate, and bladder. Large-scale studies are needed to validate these molecules as Cancer biomarkers.
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Mass spectrometry as a diagnostic and a Cancer biomarker discovery tool: opportunities and potential limitations.
Molecular & cellular proteomics : MCP, 2004Co-Authors: Eleftherios P DiamandisAbstract:Serum proteomic profiling, by using surfaced-enhanced laser desorption/ionization-time-of-flight mass spectrometry, is one of the most promising new approaches for Cancer Diagnostics. Exceptional sensitivities and specificities have been reported for some Cancer types such as prostate, ovarian, breast, and bladder Cancers. These sensitivities/specificities are far superior to those obtained by using classical Cancer biomarkers. In this review, I concentrate more on questions that cast doubt on the results reported and propose experiments to investigate these questions in detail, before the technique is used at the clinic. It is clear that the method needs to be externally and thoroughly validated before clinical implementation is warranted.
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proteomic patterns in biological fluids do they represent the future of Cancer Diagnostics
Clinical Chemistry, 2003Co-Authors: Eleftherios P DiamandisAbstract:Writing on the future of Cancer Diagnostics, this author has predicted that multiparametric biomarker analysis, in combination with artificial neural networks and pattern recognition, will likely represent one of the most promising methodologies for diagnosing and monitoring Cancer (1)(2). Over the last few years, we have witnessed publication of many reports dealing with proteomic patterns in biological fluids, and especially serum, by using the so-called “SELDI-TOF” technique (surface-enhanced laser desorption/ionization time-of-flight mass spectrometry), in combination with artificial intelligence (3)(4)(5)(6)(7). The reported sensitivities and specificities of this method for ovarian, prostate, and breast Cancer diagnosis are clearly impressive, and they are superior to the sensitivities and specificities obtained with current serologic Cancer biomarkers (8)(9)(10)(11)(12). In particular, these techniques appear to detect early as well as advanced disease with similar efficiency, making them candidate tools for Cancer screening, an application that is not currently recommended, by utilizing the classical Cancer biomarkers, e.g., CA125, carcinoembryonic antigen (CEA), and α-fetoprotein (AFP) (1). In addition to scientific journals, these reports have also been presented in international news media and have attracted public attention. Despite of some important shortcomings of these methodologies, criticism has been minimal (13)(14). It seems that the impressive bottom line (very high diagnostic sensitivity and specificity) overshadows potential problems. The recent publication of three reports, from two different research groups, on the use of this technology in the diagnosis of prostate Cancer allows for comparison of the data and the methodology and for the presentation of some important questions that have not been adequately addressed. In the following paragraphs, I will focus on some critical questions and provide discussion that could form the basis for further investigations. I will concentrate only …
Thomas Wurdinger - One of the best experts on this subject based on the ideXlab platform.
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platelet rna in Cancer Diagnostics
Seminars in Thrombosis and Hemostasis, 2017Co-Authors: Leeann Tjonkonfat, Nik Sol, Thomas Wurdinger, Jonas R A NilssonAbstract:Platelets are involved in several steps of Cancer metastasis. During this process, platelets are exposed to the tumor and its environment, thereby exchanging biomolecules with the tumor cells and resulting in tumor-mediated "education" of the platelets and a change in their RNA profile. Analysis of platelet RNA profiles or direct measurement of tumor-derived biomarkers within platelets can provide information on ongoing Cancer-related processes in the individual (e.g., whether the patient has Cancer, the tumor type, and possibly identify oncogenic alterations driving the disease for treatment selection). The close interaction with the disease process and the ability to respond to systemic alterations make platelets an interesting biosource for implementation in precision medicine.
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platelet rna as a circulating biomarker trove for Cancer Diagnostics
Journal of Thrombosis and Haemostasis, 2017Co-Authors: Myron G Best, Thomas Wurdinger, Adrienne VancuraAbstract:Summary Platelets are multifunctional cell fragments, circulating in blood in high abundance. Platelets assist in thrombus formation, sensing of pathogens entering the blood stream, signaling to immune cells, releasing vascular remodeling factors, and, negatively, enhancing Cancer metastasis. Platelets are ‘educated’ by their environment, including in patients with Cancer. Cancer cells appear to initiate intraplatelet signaling, resulting in splicing of platelet pre-mRNAs, and enhance secretion of cytokines. Platelets can induce leukocyte and endothelial cell modeling factors, for example, through adenine nucleotides (ATP), thereby facilitating extravasation of Cancer cells. Besides releasing factors, platelets can also sequester RNAs and proteins released by Cancer cells. Thus, platelets actively respond to queues from local and systemic conditions, thereby altering their transcriptome and molecular content. Platelets contain a rich repertoire of RNA species, including mRNAs, small non-coding RNAs and circular RNAs; although studies regarding the functionality of the various platelet RNA species require more attention. Recent advances in high-throughput characterization of platelet mRNAs revealed 10 to > 1000 altered mRNAs in platelets in the presence of disease. Hence, platelet RNA appears to be dynamically affected by pathological conditions, thus possibly providing opportunities to use platelet RNA as diagnostic, prognostic, predictive, or monitoring biomarkers. In this review, we cover the literature regarding the platelet RNA families, processing of platelet RNAs, and the potential application of platelet RNA as disease biomarkers.
James Zou - One of the best experts on this subject based on the ideXlab platform.
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how to evaluate deep learning for Cancer Diagnostics factors and recommendations
Biochimica et Biophysica Acta, 2021Co-Authors: Roxana Daneshjou, David Ouyang, James ZouAbstract:The large volume of data used in Cancer diagnosis presents a unique opportunity for deep learning algorithms, which improve in predictive performance with increasing data. When applying deep learning to Cancer diagnosis, the goal is often to learn how to classify an input sample (such as images or biomarkers) into predefined categories (such as benign or Cancerous). In this article, we examine examples of how deep learning algorithms have been implemented to make predictions related to Cancer diagnosis using clinical, radiological, and pathological image data. We present a systematic approach for evaluating the development and application of clinical deep learning algorithms. Based on these examples and the current state of deep learning in medicine, we discuss the future possibilities in this space and outline a roadmap for implementations of deep learning in Cancer diagnosis.
Yong Zeng - One of the best experts on this subject based on the ideXlab platform.
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advances in microfluidic extracellular vesicle analysis for Cancer Diagnostics
Lab on a Chip, 2021Co-Authors: Shibo Cheng, He Yan, Yunjie Wen, Xin Zhou, Lee R Friedman, Yong ZengAbstract:Extracellular vesicles (EVs) secreted by cells into the bloodstream and other bodily fluids, including exosomes, have been demonstrated to be a class of significant messengers that mediate intercellular communications. Tumor-derived extracellular vesicles are enriched in a selective set of biomolecules from original cells, including proteins, nucleic acids, and lipids, and thus offer a new perspective of liquid biopsy for Cancer diagnosis and therapeutic monitoring. Owing to the heterogeneity of their biogenesis, physical properties, and molecular constituents, isolation and molecular characterization of EVs remain highly challenging. Microfluidics provides a disruptive platform for EV isolation and analysis owing to its inherent advantages to promote the development of new molecular and cellular sensing systems with improved sensitivity, specificity, spatial and temporal resolution, and throughput. This review summarizes the state-of-the-art advances in the development of microfluidic principles and devices for EV isolation and biophysical or biochemical characterization, in comparison to the conventional counterparts. We will also survey the progress in adapting the new microfluidic techniques to assess the emerging EV-associated biomarkers, mostly focused on proteins and nucleic acids, for clinical diagnosis and prognosis of Cancer. Lastly, we will discuss the current challenges in the field of EV research and our outlook on future development of enabling microfluidic platforms for EV-based liquid biopsy.
Nicholas Stone - One of the best experts on this subject based on the ideXlab platform.
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vibrational spectroscopy for Cancer Diagnostics
Analytical Methods, 2014Co-Authors: Oliver Old, Leanne M Fullwood, Robert A H Scott, Gavin R Lloyd, L M Almond, Neil A Shepherd, Nicholas Stone, H Barr, Catherine KendallAbstract:The vibrational spectroscopy techniques of Raman spectroscopy and Fourier-transform infrared spectroscopy offer a number of potential advantages as tools for clinical diagnosis. The ability of these methods to detect subtle biochemical changes relating to pathology opens the possibility of their use in tissue diagnosis. Potential applications include use as an ‘optical biopsy’ technique for in vivo tissue diagnosis or to guide therapy, as a ‘digital staining’ method to assist a histopathologist in analysing a sample, or as an entirely automated process for histopathology classification. To date, much work has been undertaken in applying these spectroscopic methods to discriminate between disease states across a wide range of pathologies and organ systems, but as yet none have entered routine clinical practice. There is a pressing clinical need for real-time, accurate tissue diagnosis, especially in malignant conditions for which rapid diagnosis and comprehensive identification and treatment of diseased tissue are of paramount importance. Cancer Diagnostics remains reliant on analysis of tissue samples by histopathologists to confirm malignancy, based on morphological tissue changes and immunohistochemical staining techniques. There is increasing evidence that vibrational spectroscopy, in combination with chemometric data analysis, is a powerful and accurate technique for detecting Cancerous and pre-Cancerous biochemical changes both in vitro and in vivo, for a range of malignant conditions. This review examines the progress of vibrational spectroscopy towards selected clinical applications, with a particular focus on Cancer Diagnostics.
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advances in the clinical application of raman spectroscopy for Cancer Diagnostics
Photodiagnosis and Photodynamic Therapy, 2013Co-Authors: Charlotte Kallaway, H Barr, Catherine Kendall, Joanne Hutchings, Max L Almond, J J Wood, Nicholas StoneAbstract:Light interacts with tissue in a number of ways including, elastic and inelastic scattering, reflection and absorption, leading to fluorescence and phosphorescence. These interactions can be used to measure abnormal changes in tissue. Initial optical biopsy systems have potential to be used as an adjunct to current investigative techniques to improve the targeting of blind biopsy. Future prospects with molecular-specific techniques may enable objective optical detection providing a real-time, highly sensitive and specific measurement of the histological state of the tissue. Raman spectroscopy has the potential to identify markers associated with malignant change and could be used as diagnostic tool for the early detection of preCancerous and Cancerous lesions in vivo. The clinical requirements for an objective, non-invasive, real-time probe for the accurate and repeatable measurement of pathological state of the tissue are overwhelming. This paper discusses some of the recent advances in the field.
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vibrational spectroscopy a clinical tool for Cancer Diagnostics
Analyst, 2009Co-Authors: Catherine Kendall, M Isabelle, Florian Bazanthegemark, Joanne Hutchings, Linda Orr, Jaspreet Babrah, Rebecca Baker, Nicholas StoneAbstract:Vibrational spectroscopy techniques have demonstrated potential to provide non-destructive, rapid, clinically relevant diagnostic information. Early detection is the most important factor in the prevention of Cancer. Raman and infrared spectroscopy enable the biochemical signatures from biological tissues to be extracted and analysed. In conjunction with advanced chemometrics such measurements can contribute to the diagnostic assessment of biological material. This paper also illustrates the complementary advantage of using Raman and FTIR spectroscopy technologies together. Clinical requirements are increasingly met by technological developments which show promise to become a clinical reality. This review summarises recent advances in vibrational spectroscopy and their impact on the diagnosis of Cancer.
