Advances in Clinical Chemistry (eBook)

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2014 | 1. Auflage
314 Seiten
Elsevier Science (Verlag)
978-0-12-801612-1 (ISBN)

Infos

Volume 66 in the internationally acclaimed Advances in Clinical Chemistry contains chapters authored by world renowned clinical laboratory scientists, physicians and research scientists. The serial provides the latest and most up-to-date technologies related to the field of Clinical Chemistry and is the benchmark for novel analytical approaches in the clinical laboratory. - Expertise of international contributors - Latest cutting-edge technologies - Comprehensive in scope

Inhalt

Front Cover 1
Advances in Clinical Chemistry 4
Copyright 5
Contents 6
Contributors 10
Preface 12
Chapter One: PSA in Screening for Prostate Cancer: More Good than Harm or More Harm than Good? 14
1. Introduction 15
2. PSA: A Protease with Multiple Isoforms 15
3. PSA as a Screening Test for Prostate Cancer 16
4. Evaluation of PSA as a Screening Test for Prostate Cancer 19
4.1. Randomized prospective trials 19
4.2. Systematic reviews and meta-analysis of screening trials 22
5. Potential Harms of Prostate Cancer Screening 23
6. Attempts to Increase Benefits and Decrease Harms of PSA Screening 24
7. Attempts to Improve the Accuracy of PSA in Detecting Prostate Cancer 25
7.1. Percent-free PSA (free/total ratio) 25
7.2. PCA3 27
7.3. ProPSA 28
7.4. TMPRSS2-ETS fusion mRNA 30
7.5. Other emerging markers 30
8. Conclusion 30
References 31
Chapter Two: Ovarian Cancer Biomarkers: Current State and Future Implications from High-Throughput Technologies 38
1. Introduction 40
2. Ovarian Cancer 42
2.1. Etiology 42
2.2. Pathophysiology 43
2.3. Clinical management 46
2.3.1. Staging and diagnosis of ovarian cancer 46
2.3.2. Pelvic mass dilemma 47
3. Tumor Markers 48
3.1. Types of tumor markers 49
3.2. Tumor marker guidelines 50
3.3. Biomarker development 51
4. FDA-Approved Biomarkers 52
4.1. CA125 54
4.2. HE4 55
4.3. ROMA 56
4.4. OVA1 58
5. Other Prominent Biomarkers 60
5.1. PLCO markers 60
5.1.1. Mesothelin 60
5.1.2. Interleukin-6 and interleukin-8 61
5.1.3. B7-H4 62
5.1.4. Osteopontin 62
5.1.5. Kallikreins 63
5.2. Other markers 64
5.2.1. Vascular endothelial growth factor 64
5.2.2. Prostasin 65
6. Emerging Biomarker Research 65
6.1. MicroRNAs 65
6.1.1. Diagnosis 66
6.1.2. Prognosis 66
6.1.3. Therapeutic resistance 67
6.2. Targeted proteomics 68
6.2.1. Glycomics 68
6.2.2. Metabolomics 70
6.2.3. Peptidomics 71
6.2.4. Autoantibody signatures 72
6.3. Circulating tumor DNA 73
6.3.1. Pre-NGS Era 73
6.3.2. NGS platforms and beyond 75
7. Conclusion 77
References 77
Chapter Three: Procollagen Assays in Cancer 92
1. Introduction 93
2. Procollagen Assays: Principles and Methods 93
2.1. Type I procollagen 95
2.2. Type III procollagen 96
3. Fibroproliferation in Healthy Tissues and Cancer 96
4. Bone Turnover in Health and Malignant Disease 99
5. Effects of Malignant Bone Lesions on Procollagen Propeptides 102
5.1. Prostate cancer 103
5.2. Breast cancer 104
5.3. Other malignancies 106
6. Clinical Use of Procollagen Propeptides 107
7. Conclusion 108
References 108
Chapter Four: Metabolomics in Dyslipidemia 114
1. Introduction 115
2. Metabolomics 115
3. Data Collection 116
4. Data Analysis 117
5. Hyperlipidemia 117
6. Metabolomics in Hyperlipidemia 118
6.1. Metabolomics in animal research 118
6.1.1. Animal pathologic model research 118
6.1.2. Antilipemic agent research 123
6.2. Metabolomics in clinical research 126
7. Conclusion 127
Acknowledgments 128
References 128
Chapter Five: Metabolism in Chronic Fatigue Syndrome 134
1. Introduction 135
2. Chronic Fatigue Syndrome 137
2.1. Definition 137
2.2. Diagnosis and symptoms 139
2.3. Epidemiology 141
2.3.1. History 141
2.3.2. Pathogens and immune system 142
2.3.3. Gastrointestinal microbiota 144
2.3.4. Psychiatric and psychological research 145
2.3.5. Nervous system and endocrine system 146
2.3.6. Circulatory system and oxidative stress 147
2.3.7. Genetics 147
3. Metabolism in Chronic Fatigue Syndrome 148
3.1. Energy metabolism 148
3.2. Amino acid metabolism 153
3.3. Nitrogen metabolism 158
3.4. Nucleotide metabolism 161
3.5. Oxidative stress metabolism 164
3.6. Hormone metabolism 164
3.7. Nutrition and microbiota 166
4. Metabolomics 167
4.1. Metabolic profiling and metabolic fingerprinting 168
4.2. Overview of experimental design 169
4.2.1. Sampling 170
4.2.2. Sample preparation 170
4.2.3. Detection 170
4.2.4. Analysis 171
5. Conclusions 172
Acknowledgments 173
References 174
Chapter Six: Cellular Regulation of Glucose Uptake by Glucose Transporter GLUT4 186
1. Type 2 Diabetes, Insulin Resistance, and GLUT4 187
2. GLUT4: Structure, Function, and Expression 190
3. Intracellular Localization of GLUT4 194
3.1. Presence of GLUT4 in (non-endosomal) GSVs 195
3.1.1. Definition of GSVs 197
3.1.2. GSV biogenesis 198
3.1.3. Regulation of GSV function 201
3.2. Role of TGN/Golgi in GLUT4 traffic 203
3.3. Retention and insulin sensitivity of GLUT4 in endosomes 205
4. Intracellular Signaling Implicated in GLUT4 Translocation 208
4.1. Main insulin receptor signaling pathways 208
4.2. PKB substrate AS160 210
4.3. Other PKB substrates 213
4.4. Small GTPase Rab proteins 214
4.5. SNARE proteins 216
4.6. SNARE regulation in GLUT4 exocytosis 218
4.7. Signaling in muscle 219
5. Intracellular GLUT4 Traffic 221
5.1. GLUT4 traffic in basal adipocytes 221
5.2. Major insulin actions on GSVs 222
5.3. Effect of insulin on GLUT4 in endosomes 223
5.4. Insulin action on cell surface GLUT4 226
5.5. GLUT4 traffic in muscle 226
6. Additional Organizers of Intracellular GLUT4 Traffic 227
7. Conclusions 230
Acknowledgment 231
References 231
Chapter Seven: Identifying and Reducing Potentially Wrong Immunoassay Results Even When Plausible and ``Not-Unreasonable´´ 254
1. Conventional and Bayesian Statistics in Laboratory Medicine: Basic and Pertaining Rationale 255
1.1. Conventional statistics: An über-used paradigm in laboratory medicine 256
1.2. Bayesian statistics: An under-used paradigm in laboratory medicine 257
1.2.1. Prior probability distribution 258
1.2.2. The likelihood function 259
1.3. Simple exposition of Bayes theorem 260
1.4. Utility of conventional and Bayesian statistics in meta-analysis and evidence-based medicine 262
2. The Problem of Interference in Immunoassays from Endogenous Immunoglobulin Antibodies: A Short Perspective 264
2.1. Antibodies as reagents in immunoassays 266
2.2. The antigen-antibody binding reactions in immunoassays 268
2.3. The unknown variables in the binding reaction in immunoassays 269
2.4. Variability and sporadicity of interference from endogenous antibodies 271
3. Stratagems to Reduce Erroneous and Potentially Misleading Immunoassay Results 275
3.1. Clinical validation using probabilistic Bayesian reasoning to identify potentially false immunoassays results even w... 278
3.1.1. Examples to highlight the utility of probabilistic Bayesian reasoning in the clinical validation of immunoassay re... 279
3.1.1.1. Thyrotrophin in subclinical hypothyroidism 279
3.1.1.2. Prostate-specific antigen as a tumor marker in middle-age men 280
3.1.1.3. Human chorionic gonadotrophin (hCG) as tumor marker 281
3.1.1.4. Rheumatoid Factor (RF) in Rheumatoid Arthritis (RA) 282
3.1.1.5. Cardiac Troponin (cTn) in patients with myocardial infarction/coronary syndrome 282
3.1.1.6. Serum insulin, proinsulin, and C-peptide in hypoglycemia 284
4. Affirmative Follow-Up Tests for Detecting Interference in Immunoassays 285
4.1. Repeat analysis using a different immunoassay platform 286
4.2. Serial doubling dilutions test 287
4.2.1. Immunoassays format: Characteristics of endogenous-interfering antibodies and their impact on the outcome of doubl... 289
4.2.2. Extending the utility of serial doubling dilutions test 292
4.3. Addition of native non-immune serum or blocking antibodies reagent to neutralize interference from endogenous immuno... 293
5. Overview and Conclusion 294
5.1. Take-home message 298
References 299
Index 308

Textauszug

Chapter One

PSA in Screening for Prostate Cancer

More Good than Harm or More Harm than Good?

Michael J. Duffy*,†,1    * Clinical Research Centre, St Vincent's University Hospital, Elm Park, Dublin, Ireland
† UCD School of Medicine and Medical Science, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
1 Corresponding author: email address: [e-mail]

Abstract

The aim of screening for prostate cancer is to detect malignancy at an early and potentially treatable stage, thereby increasing the chance of cure. Although serum PSA has been used as a screening test for prostate cancer for over 20 years, the practice is controversial. As a screening test for prostate cancer, PSA lacks sensitivity and specificity for early disease. Furthermore, screening may lead to unnecessary biopsies, overdetection, and overtreatment. It is thus unclear whether the benefits of screening outweigh the harms. Although published guidelines differ in their recommendation for PSA screening, almost all state that prior to PSA testing, men should be informed of the risks and benefits of the process. Most guidelines also state that men with a life expectancy of less than 10 years should not be screened. New markers currently undergoing evaluation such as -2proPSA, Prostate Health Index, and PCA3 may complement PSA in the detection of early prostate cancer.

Keywords

PSA

Prostate cancer

Screening

PCA3

-2proPSA

Tumor marker

Biomarkers

Abbreviations

Alpha-2M alpha-2-macroglobulin

DD3 differential display-3

ERSPC European Randomized Study for Screening of Prostate Cancer

ETS E twenty six

PCA3 prostate cancer antigen 3

PSA prostate-specific antigen

TMPRSS transmembrane protease serine

1 Introduction

Since the introduction of prostate-specific antigen (PSA) screening in the late 1980s and early 1990s, the number of men diagnosed with prostate cancer has greatly increased in several Western countries. Indeed, in many countries, prostate cancer has become the most common non-skin cancer diagnosed in men, surpassing lung cancer [1]. It is widely believed that this increase in prostate cancer diagnosis directly relates to the increased use of PSA screening. As a result of this screening, most men that are diagnosed with prostate cancer, now present with localized and asymptomatic disease. While the incidence of prostate cancer has increased since the introduction of PSA screening, mortality from the disease has decreased. Indeed, by 2008, mortality rates in the United States had decreased by almost 40%, relative to the levels in the early 1990s. At least part of this decrease has been speculated to be due to early detection due to PSA screening [2].

Despite this apparent benefit of PSA screening for prostate cancer, the practice is highly controversial, with mixed views from expert panels as to whether or not it should be performed [3–9]. The aim of this chapter is to critically review the role of PSA in screening for prostate cancer. Firstly, however, a brief discussion of the biochemistry of PSA is provided.

2 PSA: A Protease with Multiple Isoforms

PSA is a member of the kallikrein family of molecules (for review, see Refs. [10,11]). The kallikreins are a family of 15 homologous trypsin or chymotrypsin-like serine proteases, with PSA being denoted kallikrein-3 or KLK3. Similar to most kallikreins and indeed other mammalian proteases, PSA is initially synthesized as a biologically inactive precursor protein. Following activation, most of the protein forms covalent bonds with endogenous protease inhibitors. Thus, in blood, 70–90% of the immunoreactive PSA protein exists as a complex with alpha-1-antichymotrypsin (ACT or SERPINA3). Low concentrations are bound to other protease inhibitors such as alpha-1-proteinase inhibitor (SERPINA1) and protein C inhibitor (SERPINA5). PSA is also attached to alpha-2-macroglobulin (alpha-2M). However, this fraction cannot be accurately determined by standard immunoassays as alpha-2M being a large protein completely surrounds and engulfs the PSA molecule, restricting reactivity with an antibody. Less information is available regarding the forms of PSA in normal or malignant prostate tissue.

Although most of the PSA in blood is complexed with inhibitors, approximately 10–30% of the immunoreactive protein exists in a free or unbound form, known as free PSA. This free fraction, however, is thought to be biologically inactive. Free PSA is present in three main molecular forms, i.e., intact inactive PSA (iPSA), BPSA, and proPSA. iPSA is similar to native active PSA except that it is enzymatically inactive. BPSA is so-named as it was first found in patients with benign prostate hypertrophy (BPH), being mostly expressed in the transitional zone of the prostate. BPSA is a degraded form of PSA, similar to the native mature form except that it is clipped at amino acid residues 145–146 and 182–183. The protein, however, remains intact as its conformation is held together by multiple disulfide bonds [10,11]. ProPSA exists in at least four different forms, depending on the number of amino acids at its leader sequence [12]. These are known as (-7)proPSA, (-5)proPSA, (-4)proPSA, and (-2)proPSA. These proforms are produced mostly in the peripheral zone of the prostate, the location in which prostate cancer tends to occur. Some of these precursor forms of PSA, especially the (-2)proform, have been proposed as new markers for prostate cancer, see below. Additional properties of the PSA protein are summarized in Table 1.1.

Table 1.1

Some of the main properties of PSA protein

A member of the kallikrein protein family, i.e., HK3
Type of protease: serine with chymotrypsin/trypsin-like specificity
Precursor form: 262 amino acids
Processed form: 237 amino acids
Molecular mass (including carbohydrate component): 28.4 kDa
Main substrate: semenogelin I and II
Main form in blood: 1:1 molar complex with ACT
Expression regulated by androgens

ACT, alpha-1-antichymotrypsin.

3 PSA as a Screening Test for Prostate Cancer

The aim of screening for prostate cancer is to detect localized disease that is potentially curable following radical prostatectomy or radiotherapy. Although hundreds of potential markers have undergone evaluation for prostate cancer screening, PSA (i.e., total PSA) is the most detailed investigated and only one in widespread clinical use [13,14]. A major advantage of PSA, as a marker for prostate cancer, is that it is almost exclusively produced by prostate tissue. Indeed, PSA is one of the few organ-specific or almost organ-specific cancer markers that can be detected in serum. However, its production is not specific for malignancy as it can also be synthesized in both normal and benign prostate tissue.

Another advantage of PSA as a marker for prostate is that its levels are elevated in some men with early prostate cancer and indeed may be increased 5–10 years prior to a clinical diagnosis of prostate cancer. Serial levels of the marker may thus provide a long lead time for its diagnosis [15]. However, as discussed below, high PSA levels in asymptomatic men do not necessary denote the presence of prostate cancer or more importantly life-threatening disease.

Although PSA is organ specific and can be elevated preclinically, it is less than an ideal marker in screening for prostate cancer [13,16]. Thus, at the commonly used cut-off point of 4 μg/L, sensitivity is only approximately 20% and specificity only 60–70% [6,16]. Sensitivity and specificity can be altered by decreasing or increasing the cut-off point, i.e., lowering the cut-off point increases sensitivity and increasing it enhances specificity. On the other hand, lowering the cut-off point decrease specificity and increasing it reduces sensitivity.

Altering the PSA cut-off point to increase sensitivity or specificity, however, may have consequences. For example, decreasing the cut-off point to increase sensitivity would result in a decrease in both specificity and positive predictive value. This in turn would lead to an increase number of biopsies due to false-positive results as well as an increase in the number of indolent cancers detected and thus the possibility of overtreatment. On the other hand, increasing the cut-off point could results in missing the detection of some clinically important cancers.

In an attempt to establish an optimum cut-off value, Holmström et al. [17] investigated multiple PSA thresholds for predicting the formation of prostate cancer. In this study, blood was taken an average of 7 years prior to the diagnosis of prostate cancer in 540 men. One thousand and thirty-four men, matched for age and date of blood draw, were used as controls. Although multiple PSA cut-off points between 0.5 and 20 μg/L were evaluated, none provided the necessary likelihood ratio, formally required for a screening test.

A further...

Produkt-Details

• Erscheint lt. Verlag: 12.8.2014
• Mitarbeit: Herausgeber (Serie): Gregory S. Makowski
• Sprache: englisch
• Themenwelt: Medizin / Pharmazie ► Medizinische Fachgebiete ► Laboratoriumsmedizin
• Themenwelt: Studium ► 2. Studienabschnitt (Klinik) ► Anamnese / Körperliche Untersuchung
• Themenwelt: Naturwissenschaften ► Biologie ► Biochemie
• Themenwelt: Naturwissenschaften ► Chemie
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Angewandte Physik
• Themenwelt: Technik
• ISBN-10: 0-12-801612-4 / 0128016124
• ISBN-13: 978-0-12-801612-1 / 9780128016121