Overview
Cancer refers to any one of a large number of diseases characterized by the development of abnormal cells that divide uncontrollably and have the ability to infiltrate and destroy normal body tissue. Cancer often has the ability to spread throughout your body.
Cancer is the second-leading cause of death in the world. But survival rates are improving for many types of cancer, thanks to improvements in cancer screening and cancer treatment.
Cancer research has progressed from empiric to mechanistic: this has allowed great progress in translational and clinical research which has improved medical practice and changed patient outcomes for the better.
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The mechanisms by which genetic, genomic, epigenetic, and immunobiologic alterations are key to cancer have contributed to more precise definition of cancer types and cancer vulnerabilities for targeted therapies.
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Translational cancer research promotes a view of the science as a continuum from preclinical research to biomarker and treatment testing in patients with cancer of many types.
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A comprehensive understanding of recurrent genomic and nongenomic alterations across a variety of human cancer types and its connection with critical pathways can be linked with clinical data to gain important insights and stimulate rational translational research.
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International cooperative consortia and collaborations are essential for a cancer research model based on both genomewide, large-scale studies, but also on smaller-scale hypothesis-driven discovery science, which eventually should converge to bring real advances in cancer patients.
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Introduction to Exosomes and Cancer
Phillip B. Munson, Arti Shukla, in Diagnostic and Therapeutic Applications of Exosomes in Cancer, 2018
Abstract
Cancer research has found a novel foothold in studying exosomes, the 40–140 nm membrane-bound vesicles secreted by cells as molecular messengers. These secreted vesicles of endocytic origin act as signaling conveyors between cells by shuttling molecular cargo in the form of proteins, mRNA, miRNA, and lipids. The many roles of exosomes in normal physiology and disease are becoming clearer as they are increasingly studied. Their role in cancer is being found to range from sending protumorigenic messages between cancer cells and to noncancer cells to aid in the growth and spread of tumor. Tumor exosomes are implicated in angiogenesis, metastasis, drug resistance, immune evasion, and even more processes involved in the pathophysiology of cancer. As we begin to uncover these roles, researchers are discovering the importance of understanding exosomes, as they pertain to cancer, as a means of discovering much-needed biomarkers, elucidating the mechanisms of cancer biology, identifying therapeutic targets, and using exosomes themselves as a mode of therapy against cancer.
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Phytoestrogens
Alice L. Murkies, Mark Frydenberg, in Encyclopedia of Hormones, 2003
VII Summary
Cancer research is still in its infancy. The epidemiological and animal data suggest that phytoestrogens may play a beneficial role in breast and prostate cancer. It may be that prepubertal exposure is of importance and ingestion needs to be lifelong. Extrapolations from cell line and animal studies need to be viewed with caution. It is probably naive to attribute many health outcomes to one food, and other lifestyle factors, such as exercise, substance abuse, and the diet as a whole, may be relevant.
In contrast to animal studies in which deleterious effects were observed with consumption of a phytoestrogen diet, in humans few adverse effects are observed. In humans, a genetic tolerance may have evolved in nations with a high-soy-intake diet or the varied human diet may be protective of one food group alone dominating and causing adverse effects. The limited studies to date have confirmed that diet can have significant hormonal effects and these may be of benefit in preventing some of the common diseases. Global nutrition is an increasing problem and further knowledge from scientific studies of plant-based foods is warranted.
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Cancer*
D. Spiegel, in Encyclopedia of Stress (Second Edition), 2007
Mind–Body Interactions and Cancer
Cancer research has productively focused on the pathophysiology of the disease, emphasizing aspects of tumor biology as predictors of disease outcome at the expense of studying the role of the body's psychophysiological reactions to tumor invasion. These reactions are mediated by brain–body mechanisms, including the endocrine, neuroimmune, and autonomic nervous systems. Although a large portion of the variance in any disease outcome is accounted for by the specific local pathophysiology of that disease, some variability must also be explained by host-resistance factors, which include the manner of response to the stress of the illness.
That the stress of cancer is felt psychologically is indicated by the fact that as many as 80% of breast cancer patients report significant distress during initial treatment. Estimates of the prevalence of psychiatric disorders among newly diagnosed cancer patients has ranged from 30 to 44%, and 20–45% of patients exhibit emotional morbidity 1–2 years later. Even though the majority of women diagnosed with breast cancer do not meet the criteria for a psychiatric diagnosis, the vast majority experience the diagnosis of cancer as a major stressor, and 10% have severe maladjustment problems as long as 6 years later. Thus, breast cancer is a disease that causes considerable psychological stress.
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Cancer Clinical Research
Warren Kibbe PhD, in Oncology Informatics, 2016
3.14 Precision Medicine Drivers
Cancer research, cancer prevention, cancer treatment, cancer control, and patient outcomes will all benefit from the focus on precision medicine. Dr Douglas R. Lowy, in 2015 as the Acting Director of NCI, gave this definition, based on the 2011 National Academy report Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease: "Interventions to prevent, diagnose, or treat cancer, based on a molecular and/or mechanistic understanding of the causes, pathogenesis, and/or pathology of the disease. Where the individual characteristics of the patient are sufficiently distinct, interventions can be concentrated on those who will benefit, sparing expense and side effects for those who will not."
Our ability to gather and integrate evidence from preclinical models, from patients in the clinic, and from clinical trials is critical to the success of precision medicine for cancer. We need to build multiscale, predictive models of cancer that are based on fundamental understanding of biology, and can integrate clinical findings, including imaging, pathology, family history, lab data, and of course molecular analyses including sequencing and mass spectrometry. Each of these domains has an important role to play in building meaningful predictive models for cancer. Existing NCI investments in imaging, common data elements (and the necessary semantics and vocabularies), tools for patient data entry (CTCAE-PRO, Family Health History, the PROMIS/Neuro-QoL/NIH Toolbox instruments), and understanding genomic and microenvironment contributions to cancer are critical assets. The Cancer Genome Atlas (TCGA) [114], the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) [115], the Cancer Genome Characterization Initiative (CGCI) [116], and the Cancer Target Discovery and Development project (CTD2) [117], among others, all contribute to fundamental components necessary for precision oncology.
The world of cancer science and cancer care is changing and will continue to change. Clinical genomics and deep sequencing are now commonplace in many cancer care organizations for cancer types shown to be amenable to and informed by these approaches. These data will enable us to understand the prevalence of germline and somatic variants, their association with risk (germline variants), and their contribution to outcomes in a given disease and therapy. We also have an opportunity to carefully examine treatment response to look for early indications of response (or lack of response) to therapy using patient-reported data. These can include fairly subtle responses (eg, fatigue, nociception, sleep patterns, neuropathy, hair loss, nail discoloration, cognition, equilibrioception, proprioception, kinesthesia, edema, depression, and lymphedema). Also, more carefully capturing and delineating these responses will be very helpful for research and for patients. The lack of information on symptom prevalence, severity, and disease staging and progression creates anxiety for patients and is an area of blindness in our understanding of subtle differences between therapies. We need to be able to incorporate these data into predictive models. For us to realize the value of these approaches we need to create mechanisms for engaging patients to capture these data broadly and uniformly, and in turn enable sharing these data, models, and simulations to allow both the creation of analyses and validation of the models.
There are multiple projects currently under consideration or in active development that will inform and start to create this capacity. The American Society of Clinical Oncologists (ASCO) [118] is creating the Cancer Learning Intelligence Network for Quality (CancerLinQ) [119] for sharing some of these data for quality purposes across any and all oncology clinics, from individual oncologist practices to large continuum of care providers. The Clinical Sequencing Exploratory Research program, funded by the National Human Genome Research Institute, was started in 2010 to fund the ethical, legal, and psychosocial research required to integrate sequencing into the clinic [120]. ClinVar is a repository run by the National Center for Biotechnology Information (NCBI) that seeks to aggregate data on mutations and phenotypes including supporting evidence, providing evidence behind the actionability of specific mutations in a disease context [121]. The Clinical Genome Resource (ClinGen) [122] is an NIH-funded (as of mid 2015, cofunded by the National Human Genome Research Institute, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and NCI) to build an annotation and curation framework for capturing evidence for both germline and somatic mutations. It uses ClinVar as the repository of that evidence, but includes more guidelines and restrictions on what constitutes evidence by disease and datatype. The Global Alliance for Genomics and Health (GA4GH) [18] is defining data structures, policies, and best practices to enable sharing of the molecular, clinical, and other attributes that are critical for understanding the genomic context of disease and health, and defining the conditions under which these data can be shared at a global scale. Cancer is a global disease and will require global participation to effectively address it.
In summary, we need to use data to inform and enhance our understanding of fundamental cancer biology as well as build predictive models for cancer risk, cancer prevention, and cancer therapy. Our ability to effectively address prevention, treatment, control, and survivorship will require fundamental shifts in data liquidity (making cancer data findable, accessible, interoperable, and reusable) and effectively engage the public and cancer patients in cancer research as citizen scientists and data donors (data altruists).
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The Role of the Immune System in Hematologic Malignancies that Affect Bone
Jessica A. Fowler, ... Gregory R. Mundy, in Osteoimmunology, 2011
Tumor-associated macrophages
Cancer research has begun to investigate the role of macrophages in tumor progression. Macrophages are divided into two categories: M1 and M2 macrophages. M1 macrophages are antigen-presenting cells that promote differentiation of naïve CD4+ T cells into Th1 cells [7]. M1 macrophages are induced by "classical activators", such as lipopolysaccharide (LPS) and interferon γ (IFNγ) [7]. Tumor-associated macrophages (TAMs) are a dominant inflammatory cell population in a majority of tumor sites and often display characteristics of M2 macrophages. M2 macrophages are activated by interleukins (IL)-4, -10, and/or -13 and then subsequently stimulate differentiation of CD4+ Th2 and regulatory T (Treg) cells [8, 9]. Zheng et al. demonstrated that co-culture with TAMs protected myeloma cells against chemotherapy drug-induced apoptosis, in contrast to co-culture with normal macrophages [10]. These studies determined that this protection against apoptosis was cell-contact-dependent by inhibiting the activation and cleavage of caspase-3 and poly(ADP-ribose) polymerization (Figure 14-1). Additionally, myeloma patients had significant numbers of CD68+ macrophages present in bone marrow biopsies in comparison to control samples [10].

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Figure 14-1. Tumor-associated macrophages (TAMs) promote myeloma pathogenesis.
(A) TAMs within the myeloma bone marrow microenvironment are important in protecting myeloma cells from chemotherapy-induced apoptosis. (B) TAMs from myeloma patients begin expressing endothelial-cell-specific markers when stimulated with angiogenic growth factors. (C) TAMs from myeloma patients have the unique ability to undergo "vasculogenic mimicry" to form capillary-like structures.
Another mechanism by which TAMs contribute to cancer progression is by stimulating angiogenesis. Various studies in solid tumors have demonstrated that TAMs are a rich source of proangiogenic factors and cytokines, such as vascular endothelial growth factor (VEGF). In addition to the production of angiogenic factors, TAMs also produce matrix-degrading enzymes, including various members of the matrix-metalloproteinase family of enzymes. In the field of multiple myeloma, numerous groups have demonstrated the angiogenic potential of macrophages isolated from myeloma patients. Neovascularization within the bone marrow cavity is one of the hallmark features in patients with myeloma. Scavelli and colleagues have shown that macrophages from multiple myeloma patients can display "vasculogenic mimicry" (Figure 14-1) [11]. In these studies the authors demonstrated that VEGF- and basic fibroblast growth factor (bFGF)- stimulated macrophages from myeloma patients resulted in the expression of endothelial cell markers, at both the mRNA and protein level. Additionally, the authors found myeloma-associated macrophages formed capillary-like structures in Matrigel following 24 hours of exposure to VEGF and bFGF. Macrophages isolated from control patients and patients with the pre-malignant stage of monoclonal gammopathy of undetermined significance (MGUS) were less capable of forming these capillary-like structures; therefore demonstrating the unique features of TAMs in multiple myeloma.
More recently, Chen et al. demonstrated that the angiogenic factor pleiotrophin (PTN) combined with macrophage colony-stimulating factor (M-CSF) induces the expression of vascular endothelial cell genes Tie-2, Flk-1, von Willebrand factor (VWF), and VE-cadherin in CD14+ monocyte cell populations [12]. PTN was expressed in the bone marrow of myeloma patients. Culturing of monocytes with myeloma bone marrow not only induced protein expression of Flk-1, Tie-2 and VWF but also stimulated the formation Flk-1+ tube-like structures in vitro. Further in vitro investigation revealed that addition of PTN and M-CSF to monocytes promoted Flk-1+ tube formation. Treatment with both these cytokines induced expression of the endothelial precursor cell marker, CD133, on the surface of CD14+ monocytes. Co-inoculation of human monocyte and myeloma cell lines in vivo resulted in the monocytes incorporating into the tumor vasculature while also expressing vascular endothelial cell genes. These results further support the concept of "vascular mimicry" in the context of myeloma.
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Prostate Cancer Economics
Lars Ellison, ... Carl Olsson, in Prostate Cancer, 2003
NCI RESEARCH FUNDING HISTORY
Prostate cancer research receives funding from a large number of private and public sources. The National Institutes of Health (NIH) is the federal government's umbrella organization through which the majority of appropriations are funneled. The NCI serves as central agency within the NIH for the oversight of intramural and extramural government-funded research. Certainly there are other organizations (the Department of Defense, the Centers for Disease Control, for example) within the federal government that play an important role in this regard. Our focus is the NCI and a review of the timeline of change in prostate cancer funding as well as a broad outline of the current research portfolio.
Federal funding of cancer research has been in place for over 50 years. The National Cancer Institute act of 1937 (public law 244)15 outlined a multilevel approach for federal involvement in cancer research, diagnosis, epidemiology and treatment: first, establishment of the National Cancer Institute within the Public Health Service; second, direction of the Surgeon General to 'promote the coordination of researches conducted by the Institute and similar researches conducted by other agencies, organizations, and individuals'; third, to establish the National Cancer Advisory Council; and fourth, 'to purchase radium; to make such radium available … for the study of the cause, prevention, or methods of diagnosis or treatment of cancer, or for the treatment of cancer'. Between 1938 and 1968, the NCI received a cumulative total of $1.69 billion in federal funds;16 however, by the FY2002, the annual budget of the NCI was $5.03 billion.17
Cancer research became a major federal initiative under the Nixon administration. The National Cancer Act of 1971 (PL 92-218)18 greatly expanded the role and independence of the NCI. Among the provisions were efforts to extend to the Director the 'coordination of all the activities of the NIH relating to cancer'. The Director was to present a budget directly to the President and Congress after review and comment (without change) by the Secretary of Health, the Director of the NIH and the National Cancer Advisory Board. In addition to the annual budgets of 1972–74, $70 million was allocated for development of 15 new cancer training and research centers.
As a check to the unprecedented latitude of the director of the NCI, PL 92-218 created the 'Presidents Cancer Panel'. This panel consisted of three individuals appointed by the president who served as a liaison to and watchdog for the president. As stipulated, the Panel was to meet with the Director not less than 12 times per year, and was to report progress and problems directly to the President. The members of this panel were clearly afforded a significant amount of influence over the priorities of the NCI at any given time. The current members are: Harold Freeman, a surgeon and Chief Executive Officer of North General Hospital in New York City; Maureen Wilson, a Ph.D. basic science researcher involved with tumor virology; and Frances Visco, a lawyer and president of the National Breast Cancer Coalition.
The Community Mental Health Center Extension Act and Biomedical Research and Research Training Amendments of 1978 [PL 95-622]19 modified the 1971 National Cancer Act. At the core of the changes was a consolidation of the duties of the director and the scope of the NCI mandate for control of research. In addition, the intense scrutiny of the Presidents Cancer Council was reduced. Most importantly, language was added which expanded the research agenda to include programs on prevention as well as the impact of environmental and occupational exposure in carcinogenesis.
The Health Research Extension Act of 1985 [PL 99-158]20 and the Health Omnibus Programs Extension of 1988 [PL 100-607]21 further expanded the scope of the NCI to include research on continuing care of cancer patients and their families and rehabilitation research.
Significant changes for urology came with the NIH Revitalization Amendments of 1993 [PL 103-43].22 Within these amendments were mandates for intensified and expanded research programs in breast/women's cancers and prostate cancer. However, also included was an unprecedented and egregious example of special interest lobbying. The specific language within the amendments was '(Sec. 1911) Requires studies: (1) on environmental and other potential risk factors contributing to the incidence of breast cancer in specified counties in New York State and two other northeastern U.S. counties listed in a specified report'.22 In other words, a case-control study of elevated breast cancer rates on Long Island was mandated as a result of pressure from women in that area who believed they suffered excess cancer incidence due to environmental exposures. This marked the opening of the door to aggressive lobbying from disease-specific special interest groups. To its credit, the American Urological Association responded in kind, and has been a powerful voice for increased appropriations for prostate cancer research.
Since the 105th Congress, a number of bipartisan pieces of legislation have come to committee and floor vote. Of these are included the Prostate Cancer Research Commitment Resolution of 1999 (S Res-92),23 which expressed the need for increases in funding for research within the NIH and the Department of Defense. The House Resolution Raising Public Awareness of Prostate Cancer (H Res-211)24 encouraged the dissemination of the importance of prostate cancer screening. The Prostate Cancer Research and Prevention Act introduced by Senator Bill Frist (R-TN) suggested revision and extension of the prostate cancer preventive health program.25 Finally, a bill that generated a great deal of debate, the Stamp Out Prostate Cancer Act was passed in 1999, and was based on the prior and analogous The Stamp Out Breast Cancer Act (Public Law 105-41) of 1997.26–28
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Epidemiology of tumors
Leon P. Bignold, in Principles of Tumors (Second Edition), 2020
(b) Death certificate data
As mentioned above, acceptable terms of causes of death have changed in Western countries over the last century. At present in different countries, different diagnoses may be included in lists of acceptable causes of death.
These enumeration errors cause the data to be difficult to interpret [27,32].
The Cancer Research UK (2012) affirms this in the statement:
Caution should be taken when interpreting trends over time for cancers worldwide because changes probably also reflect changes in data recording. [28].
Using 2012 figures in 2018, Cancer Research UK made this following summary:
The World AS (age standardized) incidence rates in males vary more than fourfold across the different world regions, ranging from 79 per 100,000 in Western Africa to 365 per 100,000 in Australia/New Zealand (2012). In females, rates vary around threefold, ranging from 103 per 100,000 in South-Central Asia to 295 per 100,000 in Northern America (2012).
France has the highest cancer incidence in males (385 per 100,000), while Denmark has the highest rates in females (328 per 100,000) (2012). Of 193 countries worldwide, the United Kingdom has the 37th highest cancer incidence rate for males and the 14th highest for females (2012).
Incidence rates also vary by Human Development Index (HDI) values. In males, incidence rates vary around threefold between very high HDI countries (316 cases per 100,000) and low HDI countries (103 cases per 100,000) (2012). In females, rates vary around twofold between very high HDI countries (253 cases per 100,000) compared with low HDI countries (123 cases per 100,000) (2012).
Despite the lower rates, their large population size means that the less developed regions (LDRs) carry a substantial burden of cancer, accounting for over half (57%) of the world's cancer cases.
Caution should be taken when interpreting cancer incidence by HDI values because differences may reflect differences in data quality [33].
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Integrative Molecular Tumor Classification: A Pathologist's View
Fred T. Bosman, in Encyclopedia of Cancer (Third Edition), 2019
Conclusions
The cancer research and care providing community is gradually introducing molecular characteristics into cancer classification. This will have significant implications for but will not completely upset present approaches.
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The current WHO approach to cancer classification will remain a solid basis for the years to come. The definition of main tumor classes will remain histomorphologic. As David Huntsman and Mark Ladanyi put it in the concluding phrase of their introduction to the 2018 Annual Review Issue of the Journal of Pathology: "Thus, oncological pathology's oldest technology remains meaningfully connected with and continues to inform genomic pathology."
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New cancer subtypes will continue to emerge, of which the definition will be largely or entirely "omics" oriented.
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Digital microscopy will rapidly complement and gradually replace conventional microscopy. This will provide a higher level of objectivity to cancer diagnostics, notably when it comes to quantitative parameters. Artificial intelligence through machine deep learning might provide decisional support in the future.
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Pathologists will need to adapt postgraduate training programs to this shift in emphasis in cancer classification. In the 20th century the endpoint of cancer classification was the information a histological section offered. In the 21st century the histological section represents its first phase, providing a solid basis upon which "genomic pathology" will be grafted, and this should be reflected in the curricula. This holds true also for postgraduate education in other oncology oriented clinical disciplines.
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Bioinformaticians contribute essential competencies to molecular based classification. A new class of "in silico" oncobiologists with profound understanding of cancer biology and its clinical implications needs to be educated to face increasing demand for this type of support.
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The likelihood that many new "omics" defined subtypes will emerge goes along with decreasing case numbers per subtype. To nonetheless arrive at case collections allowing solid conclusions as to the relationship between molecular characteristics and clinical behaviour including treatment response, data sharing will become imperative. This needs to be supervised by a legal and ethics framework to guarantee patient safety and privacy protection.
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Cytogenomics of Solid Tumors by Next-Generation Sequencing
D. Sie, ... B. Ylstra, in Molecular Diagnostics (Third Edition), 2017
15.4.1 Chromosomal Aberrations
In cancer research, we use copy number profiling to assess prognostic and predictive biomarkers in various tumor types including colon, low-grade glioma, and head and neck tumors (Van Thuijl et al., 2014; Haan et al., 2014; Smeets et al., 2009). A routine diagnostic application in our clinic is the assessment of the clonal relationship among multiple tumors from a single patient. The assay determines whether multiple tumors can be regarded as independent tumors or a single primary tumor with metastasis. The clonal relationship can be interpreted in an automated fashion by calculating a likelihood ratio to distinguish tumor pairs (Ostrovnaya et al., 2010). In our daily practice, we complement this procedure by calculating a correlation of aberrant segment values (Fig. 15.1), which has brought valuable insights to the clinic for effective cancer treatment (Kuiper et al., 2015). Copy number aberrations are classically investigated by FISH, karyotyping of condensed chromosomal structures, CGH, and later, array CGH (Ylstra et al., 2006). It is a time-consuming and expensive undertaking to design probes for the FISH and CGH techniques and requires prior knowledge about the genomic sequences of interest. Whole-genome sequencing (WGS) offers an unbiased approach because the complete DNA content of the acquired nuclei is simply read out by NGS. An equivalent resolution to microarrays (180,000 features) can be achieved with a limited amount of data in which only a tenth of the (human) genome (0.1× coverage) is actually sequenced. This low-pass or shallow-WGS (sWGS) allows for cheap and efficient copy number profiling, even when using DNA isolated from FFPE tissue material (Scheinin et al., 2014). The general approach involves dividing the human reference genome into nonoverlapping fixed-size bins. After mapping the reads to the reference genome, the raw read count is determined by the number of mappings contained in each bin. After guanine-cytosine content and "mappability" correction, filtering, segmentation, and calling, this read count reflects an accurate copy number state of the analyzed sample.

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Figure 15.1. Workflow of clonality test. The primary resected tumor from the lung (2010) is compared with a secondary resected tumor from the lung (2015). Tissue is formalin-fixed and embedded in paraffin (A, B). Sections are cut (10 μm) and stained with hematoxylin–eosin (C) followed by demarcation of tumor tissue (D). DNA is isolated from cells scraped from the marked region (D). The isolated DNA is randomly fragmented (E) and sequencing adapters are ligated for compatibility with sequencing technology (F). The resulting sequencing data are processed by quantitative DNA sequencing to produce a genome-wide copy number profile. Log likelihoods and correlation of segments is calculated to determine the clonality score of the two samples. The clonality score is located in the lower left quadrant, which indicates the samples have no clonal relationship (H)