Some tumor suppressor genes and the types of cancer they cause [75].
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"5241",leadTitle:null,fullTitle:"Applications of Spatial Statistics",title:"Applications of Spatial Statistics",subtitle:null,reviewType:"peer-reviewed",abstract:"Spatial statistics has been widely used in many environmental studies. This book is a collection of recent studies on applying spatial statistics in subjects such as demography, transportation, precision agriculture and ecology. Different subjects require different aspects of spatial statistics. In addition to quantitative statements from statistics and tests, visualization in forms of maps, drawings, and images are provided to illustrate the relationship between data and locations. This book will be valuable to researchers who are interested in applying statistics to spatial data, as well as graduate students who know statistics and want to explore how it can be applied to spatial data. With the processing part being simplified to several mouse clicks by commercial software, one should pay more attention to justification of using spatial statistics, as well as interpretation and assessment of the results. GIScience proves to be a useful tool in visualization of spatial data, and such useful technology should be utilized, as part, for the interpretation and assessment of the results.",isbn:"978-953-51-2757-4",printIsbn:"978-953-51-2756-7",pdfIsbn:"978-953-51-5085-5",doi:"10.5772/61666",price:119,priceEur:129,priceUsd:155,slug:"applications-of-spatial-statistics",numberOfPages:156,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"acc5941907640ecc7a3e350c5fe3df19",bookSignature:"Ming-Chih Hung",publishedDate:"November 2nd 2016",coverURL:"https://cdn.intechopen.com/books/images_new/5241.jpg",numberOfDownloads:13363,numberOfWosCitations:14,numberOfCrossrefCitations:17,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:31,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:62,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 28th 2015",dateEndSecondStepPublish:"November 18th 2015",dateEndThirdStepPublish:"March 31st 2016",dateEndFourthStepPublish:"April 30th 2016",dateEndFifthStepPublish:"June 30th 2016",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"184413",title:"Dr.",name:"Ming",middleName:"Chih",surname:"Hung",slug:"ming-hung",fullName:"Ming Hung",profilePictureURL:"https://mts.intechopen.com/storage/users/184413/images/4908_n.jpg",biography:"Ming-Chih Hung is a Professor of Geography/GIScience at Northwest Missouri State University. He earned his bachelor degree from National Taiwan University focusing on DEM applications, his MS from the University of Utah focusing on the V-I-S Model and soft classification of TM images, and his Ph.D. also from the University of Utah focusing on remote sensing and GIS on urban areas. His research emphasizes on use of GIScience on urban areas. In addition to urban areas, he is also interested in precision agriculture and environmental issues. At Northwest Missouri State, he teaches courses on remote sensing, GIS, GPS, and cartography.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Northwest Missouri State University",institutionURL:null,country:{name:"United States of America"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"637",title:"Spatial Analysis",slug:"spatial-analysis"}],chapters:[{id:"52302",title:"Application of Spatial Statistics in Transportation Engineering",doi:"10.5772/65051",slug:"application-of-spatial-statistics-in-transportation-engineering",totalDownloads:2450,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"“Everything is related to everything else, but near things are more related than distant things” is the first law of geography. It can be hypothesized that spatially, occurrence of a crash can exhibit similarities. To identify spatial patterns of crashes, this chapter presents spatial autocorrelation techniques such as Moran’s I and the Getis-Ord Gi*statistics; spatial interpolation such as kriging; and nonparametric probability density function and kernel density (K). The aim of this chapter is to provide application of spatial statistics in transportation engineering specifically to identify crash concentrations and patterns of clusters in a study area.",signatures:"Uday R.R. Manepalli and Ghulam H. Bham",downloadPdfUrl:"/chapter/pdf-download/52302",previewPdfUrl:"/chapter/pdf-preview/52302",authors:[{id:"182804",title:"Dr.",name:"Ghulam H.",surname:"Bham",slug:"ghulam-h.-bham",fullName:"Ghulam H. Bham"},{id:"188145",title:"Mr.",name:"Uday",surname:"Manepalli",slug:"uday-manepalli",fullName:"Uday Manepalli"}],corrections:null},{id:"52704",title:"Comparison of Spatial Interpolation Techniques Using Visualization and Quantitative Assessment",doi:"10.5772/65996",slug:"comparison-of-spatial-interpolation-techniques-using-visualization-and-quantitative-assessment",totalDownloads:3774,totalCrossrefCites:12,totalDimensionsCites:25,hasAltmetrics:0,abstract:"Spatial interpolation has been widely and commonly used in many studies to create surface data based on a set of sampled points, such as soil properties, temperature, and precipitation. Currently, there are many commercial Geographic Information System (GIS) or statistics software offering spatial interpolation functions, such as inverse distance weighted (IDW), kriging, spline, and others. To date, there is no “rule of thumb” on the most appropriate spatial interpolation techniques for certain situations, though general suggestions have been published. Many studies rely on quantitative assessment to determine the performance of spatial interpolation techniques. Most quantitative assessment methods provide a numeric index for the overall performance of an interpolated surface. Although it is objective and convenient, there are many facts or trends not captured by quantitative assessments. This study used 2D visualization and 3D visualization to identify trends not evident in quantitative assessment. This study also presented a special case, a closed system in which all interpolated surfaces should sum up to 100%, to demonstrate the interaction between interpolated surfaces that were created separately and independently.",signatures:"Yi-Hwa (Eva) Wu and Ming-Chih Hung",downloadPdfUrl:"/chapter/pdf-download/52704",previewPdfUrl:"/chapter/pdf-preview/52704",authors:[{id:"181853",title:"Dr.",name:"Yi-Hwa",surname:"Wu",slug:"yi-hwa-wu",fullName:"Yi-Hwa Wu"}],corrections:null},{id:"51744",title:"Wage Concentration in Spain: A Spatial Analysis",doi:"10.5772/64441",slug:"wage-concentration-in-spain-a-spatial-analysis",totalDownloads:1582,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this article, the degree of concentration of wages in Spain at the provincial and regional levels is estimated using the latest available micro-data corresponding to the Structure of Earnings Survey 2010 (N = 216.769). From the analysis of the statistics obtained, it is possible to know in detail the spatial distribution of national wage inequality, to identify those areas where inequality is greatest, and to estimate the possible existence of spatial dependence and structure. The analysis focuses not only on the study of global inequality, but delves into the question by extending the analysis from a gender perspective.",signatures:"Beatriz Larraz, Mónica Navarrete and José Manuel Pavía",downloadPdfUrl:"/chapter/pdf-download/51744",previewPdfUrl:"/chapter/pdf-preview/51744",authors:[{id:"183051",title:"Dr.",name:"Beatriz",surname:"Larraz",slug:"beatriz-larraz",fullName:"Beatriz Larraz"},{id:"183056",title:"Prof.",name:"Jose Manuel",surname:"Pavia",slug:"jose-manuel-pavia",fullName:"Jose Manuel Pavia"},{id:"183460",title:"Dr.",name:"Monica",surname:"Navarrete",slug:"monica-navarrete",fullName:"Monica Navarrete"}],corrections:null},{id:"51918",title:"Spatial Optimization of Urban Cellular Automata Model",doi:"10.5772/64788",slug:"spatial-optimization-of-urban-cellular-automata-model",totalDownloads:1947,totalCrossrefCites:3,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Although cellular automata (CA) offer a modelling framework and set of techniques for modelling the dynamic processes of urban growth, determining the optimal value of weights or parameters for elements or factors of urban CA models is challenging. This chapter demonstrates the implementation of a calibration module in a fuzzy cellular urban growth model (FCUGM) for optimizing the weights and parameters of an urban CA model using three types of algorithms: (i) genetic algorithm (GA), (ii) parallel simulated annealing (PSA) and (iii) expert knowledge (EK). It was found that the GA followed by EK produced better and more accurate and consistent results compared with PSA. This suggests that the GA was able to some extent to understand the urban growth process and the underlying relationship between input factors in a way similar to human experts. It also suggests that the two algorithms (GA and EK) have similar agreement about the efficiency of scenarios in terms of modelling urban growth. In contrast, the results of the PSA do not show results corresponding to those of the GA or EK. This suggests that the complexity of the urban process is beyond the algorithm’s capability or could be due to being trapped in local optima. With this satisfactory calibration of the FCUGM for the urban growth of Riyadh city in Saudi Arabia by using CALIB-FCUGM, these calibrated parameters can be passed into the SIM-FCUGM to simulate the spatial patterns of urban growth of Riyadh.",signatures:"Khalid Al-Ahmadi, Mohammed Alahmadi and Sabah Alahmadi",downloadPdfUrl:"/chapter/pdf-download/51918",previewPdfUrl:"/chapter/pdf-preview/51918",authors:[{id:"137051",title:"Dr.",name:"Khalid",surname:"Al-Ahmadi",slug:"khalid-al-ahmadi",fullName:"Khalid Al-Ahmadi"}],corrections:null},{id:"52451",title:"Structural Diversity of Plant Populations: Insight from Spatial Analyses",doi:"10.5772/65320",slug:"structural-diversity-of-plant-populations-insight-from-spatial-analyses",totalDownloads:1855,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Spatial analysis has been one of the most rapidly growing fields in ecology. It is related directly to a growing awareness among researchers that a spatial structure of biosystems, e.g., forests, is important in ecological thinking. The availability of the specific software supports the use of spatial analyses in different fields of the science and forestry science is only one example for this. Many data collected in the forests have the spatial and temporal dimensions and it allows us to use spatial statistics to quantitative description of the spatial structure of forest, which became an important element of modern continuous cover forestry. In this chapter, key elements: data types, null models, and summary statistics, which can be applied in spatial analyses, are briefly described. Real data sets collected from different forests were given to provide examples of spatial analyses. The key elements of spatial analysis in ecology are data type, the appropriate choice of summary statistics and null models. Selecting few of them in a single analysis makes the statements more reliable and realistic in the changing world.",signatures:"Janusz Szmyt",downloadPdfUrl:"/chapter/pdf-download/52451",previewPdfUrl:"/chapter/pdf-preview/52451",authors:[{id:"180608",title:"Dr.",name:"Janusz",surname:"Szmyt",slug:"janusz-szmyt",fullName:"Janusz Szmyt"}],corrections:null},{id:"52429",title:"Practical Value of User‐Centred Spatial Statistics for Responsive Urban Planning",doi:"10.5772/65322",slug:"practical-value-of-user-centred-spatial-statistics-for-responsive-urban-planning",totalDownloads:1760,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This chapter addresses spatial statistics via an alternative perspective, focusing on evidence‐based people‐spatial relationships and related measures, quantifications and qualifications, and by this, it provides rather specific spatial information and spatial statistics about urban environments. It is based on time quality assessment (TQA), a time‐people‐place‐oriented approach for the analysis and simulation of the quality of living environments, backgrounded with the method of behaviour mapping. It shows that the quality of the time spent on a certain activity in a certain place indicates the quality of the living environment. It also shows that the quality of the time spent depends on what a person can afford, and it provides an evaluation of the quality of living environments with a measure of good/bad time. The practical value is in the provision of empirical knowledge to support planning guidance based on user‐centred small‐scale spatial statistics, which is able to inform top‐down and bottom‐up decision‐making processes for people‐friendly living environments.",signatures:"Damjan Marušić and Barbara Goličnik Marušić",downloadPdfUrl:"/chapter/pdf-download/52429",previewPdfUrl:"/chapter/pdf-preview/52429",authors:[{id:"104025",title:"Dr.",name:"Damjan",surname:"Marušić",slug:"damjan-marusic",fullName:"Damjan Marušić"},{id:"184731",title:"Dr.",name:"Barbara",surname:"Goličnik Marušić",slug:"barbara-golicnik-marusic",fullName:"Barbara Goličnik Marušić"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6058",title:"Recent Advances and Applications in Remote Sensing",subtitle:null,isOpenForSubmission:!1,hash:"6c271ba0275d66a79d494e5e0bfe9ebb",slug:"recent-advances-and-applications-in-remote-sensing",bookSignature:"Ming-Chih Hung and Yi-Hwa Wu",coverURL:"https://cdn.intechopen.com/books/images_new/6058.jpg",editedByType:"Edited by",editors:[{id:"184413",title:"Dr.",name:"Ming",surname:"Hung",slug:"ming-hung",fullName:"Ming Hung"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7304",title:"Geospatial Analyses of Earth Observation (EO) data",subtitle:null,isOpenForSubmission:!1,hash:"e90c7cda0e7f94a6620d6ec83db808ae",slug:"geospatial-analyses-of-earth-observation-eo-data",bookSignature:"Antonio Pepe and Qing Zhao",coverURL:"https://cdn.intechopen.com/books/images_new/7304.jpg",editedByType:"Edited by",editors:[{id:"99269",title:"Dr.",name:"Antonio",surname:"Pepe",slug:"antonio-pepe",fullName:"Antonio Pepe"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7262",title:"Spatial Analysis, Modelling and Planning",subtitle:null,isOpenForSubmission:!1,hash:"ed7c7f4193e3951e715569ca454f7077",slug:"spatial-analysis-modelling-and-planning",bookSignature:"Jorge Rocha and José António Tenedório",coverURL:"https://cdn.intechopen.com/books/images_new/7262.jpg",editedByType:"Edited by",editors:[{id:"145918",title:"Ph.D.",name:"Jorge",surname:"Rocha",slug:"jorge-rocha",fullName:"Jorge Rocha"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9246",title:"Satellites Missions and Technologies for Geosciences",subtitle:null,isOpenForSubmission:!1,hash:"f23d04613b089dae40f81342c3e7c7f4",slug:"satellites-missions-and-technologies-for-geosciences",bookSignature:"Vladislav Demyanov and Jonathan Becedas",coverURL:"https://cdn.intechopen.com/books/images_new/9246.jpg",editedByType:"Edited by",editors:[{id:"154597",title:"Prof.",name:"Vladislav",surname:"Demyanov",slug:"vladislav-demyanov",fullName:"Vladislav Demyanov"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9846",title:"Spatial Variability in Environmental Science",subtitle:"Patterns, Processes, and Analyses",isOpenForSubmission:!1,hash:"cfa4fa7b982bbff46ffbe6fbdbffbdf1",slug:"spatial-variability-in-environmental-science-patterns-processes-and-analyses",bookSignature:"John P. 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The rise of Taylorism, standardisation, electrical systems, electronic systems and computing, and now, quantum computing, has given scheduling a whole World of importance.
\r\n\tFrom practice to a mathematical and technological application, scheduling has become another form of art: an algorithmic art, declined in as many OS and hardware constraints, from embedded systems onboard an aircraft or a spacecraft to databases in all financial and Internet servers.
\r\n\tThey have become ubiquitous so that a large part of our civilisational development is supported by their reliability, redundancy, and optimisation capacity. Like all of our civilisational assets, they are benefiting from scientific breakthrough in computational sciences such as evolutionary algorithms, Artificial Intelligence, and quantum computing. If not by using it, by being in need of adapting to the next generation of computing. Space development is also bringing new challenges, especially in redundancy and reliability.
The term cancer is not the name of a single disease, but the name was given to all malignant tumors, the main reason for which is uncontrolled growth. The tumor, which becomes a mass as a result of uncontrolled cell proliferation, also attacks the surrounding cells and tends to spread throughout the body in the later stages of the disease (metastasis). Although cancer is an important health problem, it is not a common disease in childhood. On the other hand, statistics show that cancer affects one in three adults, causes up to 20% of all deaths, and covers about 10% of treatment costs in developed countries [1]. Cancer, which develops as a result of uncontrolled cell growth and development, is a phenomenon that occurs as a result of a complex series of cellular mechanisms working differently from normal. It is known that cancer occurs as a result of mutations in somatic cells and these mutations affect the expression of a series of genes. Cancers can develop in each tissue group depending on age, gender, and environmental factors [2, 3, 4]. Although it is known that cancer develops under the influence of genetic and environmental factors, environmental factors are more prominent in the formation of some types of cancer. It is now known to affect [5, 6]. There are two gene groups known to be involved in cancer formation. These are (1) Tumor suppressor genes and (2) proto-oncogenes [7, 8]. Breast cancers are the leading cancer types known to have tumor suppressor genes in their etiology. BRCA1 and BRCA2 genes are the leading tumor suppressor genes specific to breast cancers [9]. Studies have shown that these two genes are particularly effective in the development of familial breast cancers. While the majority of cancers are sporadic, a small percentage can be hereditary, that is, familial. While the first mutation in the genes involved in hereditary cancers is inherited familial, the fact that the second mutation occurs in a limited number of somatic cells after birth is sufficient for cancerization. These types of cancers occur much earlier than non-familial cancers [9, 10, 11, 12, 13, 14, 15, 16]. According to World Health Organization; When cancer-related deaths in women were investigated between 2019 and 2020 worldwide, the most common type of cancer in all ages and genders is breast cancer, followed by prostate cancer and lung cancer, the least common cancer is thyroid cancer. However, the most common cause of death is lung cancer and breast cancer is the second most common type of cancer. According to International Agency for Research on Cancer of the World Health Organization; new cases and death rates of cancer the worldwide for 2020 are given below (Figure 1) [17, 18, 19, 20], https://gco.iarc.fr/.
Estimated age-standardized incidence and mortality rates (world) in 2020, worldwide, for both sexes, all ages [
Although a lot of important information about the etiology of cancer has been obtained in recent years, the molecular mechanisms that cause cancer formation, that is, the excessive proliferation of a normal cell out of control, are still not fully clarified, and a new mechanism may emerge every year and hereditary factors are known to play a role together. Environmental factors include some chemical agents (nicotine), nutrition, radiation, viruses, living environmental conditions, and lifestyle [16, 21, 22].
There is a threshold value for many carcinogens, amounts that do not exceed this threshold value are harmless. One-third of cancers seen in the USA and Europe are cancers that develop due to the use of cigarettes and other tobacco products. Working conditions and some occupational chemicals are among the other environmental factors that cause cancer. It is known that chemical agents such as asbestos and nicotine cause cancer formation [23, 24, 25, 26].
Ionizing Radiation. Skin cancers were common in the hands of radiologists in the periods when primitive devices were used and prevention methods were not well known. In studies conducted in the following years, it has been shown that bone, thyroid, lung, breast cancer, leukemia, and lymphoma develop with the effect of radiation [27, 28, 29]. Ultraviolet Rays (U.V). U.V rays have been shown to be associated with skin cancers. These include basal cell skin cancer, squamous (stratified squamous epithelium) skin cancer, and skin cancers such as melanoma [30, 31, 32, 33, 34].
Although cancer is a genetic disease, very few cancer cases show hereditary characteristics. Among all cancer types, the rate of hereditary cancers is less than 1%. In families with hereditary cancer cases, cancer occurs more frequently than in the normal population. In families where cancer is inherited; The probability of passing the cancer gene from mother or father to child is 50%. Cancer cases in individuals in such families occur at an earlier age than in the general population. The tissues with the most familial cancer cases are colon, endometrium, ovary, and breast [35, 36, 37]. Two groups are very important in the formation of cancer. These; proto-oncogenes are tumor suppressor genes.
It is known that proto-oncogenes that regulate cell growth and differentiation have important roles in normal cell physiology (30). If a proto-oncogene differentiates or starts to be expressed more than normal as a result of mutation or change in external stimulus; These changes cause uncontrolled growth and therefore malignant formations in the cell. With the mutation of proto-oncogenes, they turn into genes called oncogenes that stimulate continuous cell division [38, 39]. Proto-oncogenes can be grouped into 4 groups according to the biochemical properties of protein products [40, 41].
FGF has also been studied in various animal models; After topical application to the wound in the guinea pig ear, basic FGF has been shown to accelerate epithelialization. Cell number and collagen content increased with subcutaneous injection in guinea pigs. Topical basic FGF has a positive effect on wound healing problems that can be caused by infection and diabetes in mice [46, 47, 48, 49].
Tumor suppressor genes were found for the first time as a result of studies on retinoblastoma, one of the very rare hereditary cancer types. Retinoblastoma is the most common type of cancer among childhood eye cancers and occurs bilaterally in 20–30% of cases [68, 69]. All bilateral cases and 15% of unilateral cases show autosomal dominant inheritance. The gene responsible for this disease is the Rb1 gene located proximal to the long arm of chromosome 13 [70, 71]. As a result of chromosomal changes or point mutations, the functional protein related to this gene is either absent or unable to function in cells in tumor tissue. In such cases, hereditary mutation; is found in only one of the gene pairs and is therefore in a heterozygous state. In order for a tumor to develop in a person carrying the mutant gene, a new mutation must also occur in the normal partner of the mutant gene in the retinal cell(9). As a result of a second mutation, a tumor occurs when the other intact allele is changed or lost. This situation is also called loss of heterozygosity [72, 73], (Figure 2).
Cancer formation model.
In hereditary retinoblastoma cancers, the first mutation occurred in the person either as a result of germline mutations or inherited from one of the parents. In people carrying this gene, retinoblastoma occurs at a very early age [74]. As a result of studies on the localization of many tumor types that show oss of heterozygosity for chromosome 13 and the localization of other tumor suppressor genes, more than 20 tumor suppressor gene regions were identified, the main ones being p53, retinoblastoma, BRCA 1, BRCA 2 (Table 1) [76, 77, 78, 79, 80].
Gene | Cancer | Localization | Function | Hereditary Syndrome |
---|---|---|---|---|
APC | Colon cancer | Cytoplasm | Cellular adhesion | Familial |
DCC | Colon cancer | Cell membrane | Cell adhesion molecule | — |
NF1 | Neurofibromas | Cytoplasm | GTPase activator | Neurofibromatosis Type 1 |
NF2 | Schwannomas and Meningioma | Cell membrane | Cell membrane | Neurofibromatosis Type 2 |
p53 | Colon cancer and many other cancers | Nucleus | Transcription factor | Li-Fraumeni syndrome |
RB | Retinoblastoma | Nucleus | Transcription factor | Retinoblastoma |
RET | Thyroid cancer pheochromocytom | Cell membrane | Tyrosine kinase receptor | Multiple endocrine neoplasm Type 2 |
VHL | Kidney cancer | Cell membrane | Transcription factor | Von Hippel–Lindau disease |
WT-1 | Nephroblastoma | Nucleus | Transcription factor | Wilms tumor |
BRCA1 | Breast cancer | Breast tissue | DNA repair, mismatch repair | Familial breast cancers |
BRCA2 | Breast cancer | Breast tissue epithelium | DNA repair, mismatch repair | Familial breast cancers |
Some tumor suppressor genes and the types of cancer they cause [75].
The p53 gene is located in band 13 of the short arm of human chromosome 17. This gene, which is about 20 kb long; encodes a 2.8 kb mRNA and its product is a core phosphoprotein of 393 amino acids of 53 kD (10). Nucleotide and amino acid sequence analyzes have shown that; The p53 gene contains 5 conserved regions from neopus to human during evolution. This region includes exons 1, 4, 5, 7, and 8. These conserved regions are thought to be essential sites for the p53 wild-type protein. Specifically, the DNA binding region of the p53 gene contains 2 SV40 tumor antigen binding (T-ag), a nuclear localization signal, and multiple phosphorylation sites (Figure 3). The p53 protein controls gene expression positively or negatively by stopping the cell cycle in the G1 phase and binding to specific sequences and transcription factors. Normal p53 protein stops the cell cycle and leads the cell to programmed cell death in the absence of appropriate differentiation or proliferation factors [81, 82, 83, 84, 85].
Schematic structure of the p53 gene; TAS: Transcription activation region, protein binding region (HSP), SV40 wide T-antigen region, adenovirus E1b and papillomavirus E6 binding region, cellular Mdm2 binding region, nuclear localization signal (NLS), oligomerization region (OLIGO) and phosphorylation region (cdc2 and CDK). The 5 conserved regions in evolution are indicated by the letters I, II, III, IV, and V, and the hot spot regions are indicated by the letters A, B, C, D.
The chromosomal location of the BRCA 1 gene (Breast cancer susceptibility gene) was first identified in 1990 and cloned in 1994 [86]. The BRCA1 gene has 24 exons (20) with approximately 100,000 base pairs, occupying 4 cM, located in the q12–21 region of chromosome 17; It is a gene that encodes a tumor suppressor protein. The 11th exon of the BRCA1 gene, which is very large, constitutes 61% of the entire gene. The BRCA1 gene encodes a tumor-suppressing protein with DNA binding properties that negatively affect cancer formation [87]. Recent studies have shown that the product of the BRCA1 gene; It has been shown to be a zing-finger protein with a zinc-binding site at the amino end [87, 88, 89].
Breast tumors occur with the loss of both the wild-type allele of the BRCA1 gene at 17q [90]. Since there are 500 different types and the BRCA 1 gene is a large gene, the frequency of mutation is quite high. Several clinically important mutations have been found in this gene. While approximately 90% of these mutations are frameshift or nonsense mutations, the rest are mutations that cause changes in the stop codon and cause the immature protein to be made at the translation stage [35, 91, 92, 93, 94]. Studies have been ongoing since the gene was cloned to develop a test that could detect familial cancer risk by detecting BRCA 1 mutations. The second most common group of mutations in the BRCA1 gene are 185delAG and 5382insG mutations [95, 96]. These constitute 10% of all mutations in the BRCA1 gene. These two mutations are seen with a frequency of approximately 10% in Ashkenazi and non-Ashkenazi Jews. The carrier rate of these mutations in the same group is 1%. Mutations 185delAG and 5382insG have also been shown to be found in Moroccan and non-Jewish families. The high incidence of deletions in the AG sequence at position 185 of BRCA1 has caused this region to be called the ‘Hotspot’ region. In germ-line mutation studies in all women, the incidence of breast cancer before the age of 40 was found to be 20% in 185delAG carriers [95, 97, 98, 99]. While the 5832insC mutation is most common in Russians and Jews of European origin, it is very low in Israeli Jews [100, 101]. The most common mutation in the Russian population is 4153delA4 (Figure 4) [102].
Mutation distribution in the BRCA1 gene.
The BRCA 1 protein is a ring-finger protein of 1863′ amino acids (45, 46, 47). BRCA 1 is made in the differentiated epithelial cells of developing organs during embryonic development and puberty development. A significant increase in the mRNA level of BRCA 1 has been observed in breast epithelial cells during pregnancy in women without cancer. BRCA 1 expression in humans is stimulated by estrogen and decreases after birth (38,48). Suppression of BRCA 1 expression increases growth in both normal cells and malignant mammary epithelial cells [86, 90, 93]. Since the BRCA1 gene was isolated, its functions have been thought to play a role in transcription, control the cell cycle, and be associated with DNA repair mechanisms. It is a gene that participates in DNA repair mechanisms by interacting with basic transcriptional mechanisms (with RNA polymerase II, Transcription factors TFIIH, TFIIE, and RNA helicase A). BRCA1 and BRCA2 proteins together provide a repair of DNA double-strand breaks in mitotic cells [103, 104] BRCA1 protein interacts with the gamma-tubulin subunits of the centrosome during mitosis, stopping the cell cycle and providing damage control in DNA [105].
BRCA2 is another tumor suppressor gene that was mapped to the long arm of the 13th chromosome by Wooster et al. in 1994 (7). The 13q12-13 region containing BRCA2 is also a region close to the retinoblastoma gene (36, 39). The BRCA2 gene is a 70 kb gene with 27 exons, occupies 6 cM, and the product of the gene is a protein consisting of 3418 amino acids(36). The fact that exon 3 is similar to transcription factors indicates that it may have a function in this direction (33,). BRCA2 has a large 11th exon just like BRCA1(50). This exon makes up about 58% of the whole gene [86, 106, 107, 108]. While the risk of breast cancer and ovarian cancer is higher in patients with germline mutations in this gene, 30–40% loss of heterozygosity is observed in patients with sporadic breast and ovarian cancer [109, 110]. Interestingly, almost all BRCA2 mutations are familial [111]. This theorizes that BRCA mutations can theoretically be traced back to an initial sporadic case and may indicate the presence of a ‘founder effect’. The majority of mutations in the BRCA 2 gene cause a frameshift condition. The most common frameshift mutation is the 999del5 mutation, which is also seen in Iceland. Other than that, the mutations seen in other populations are as follows. Ashkenazi Jewish-6174delT, Dutch-5579insA, Finns- 8555 T > G, 999del5, IVS23-2A > G, French Canadians 8765delAG, 3398delAAAAG, Hungarians-9326insA, Pakistanis-3337C > T, Slovenians-IVS16-2A > G [112]. People with certain mutations of the BRCA2 gene increase the risk of breast cancer by causing hereditary breast-ovarian cancer syndrome. As a result of research, hundreds of mutations in the BRCA2 gene, many of which cause an increased risk of cancer, have been identified. BRCA2 mutations are usually the addition or loss of a small number of DNA base pairs in the gene. As a result of these mutations, the protein product of the BRCA2 gene is abnormal and does not work properly. Research emerges as a result of the inability of the dysfunctional BRCA2 protein to repair the damages in the DNA that make up the genome. As a result, there is an increase in mutations due to this faulty synthesis after unrepaired DNA damages, and some of these mutations can lead to uncontrolled division of cells and the formation of a tumor [107, 113, 114].
By revealing the environmental and genetic factors that are effective in the development of breast cancer, which is a very important social problem, studies to prevent breast cancer gain hope. The incidence of breast cancer differs from country to country in the world. While Hawaii, California, and Canada are in the first place with an incidence of 80–90 per hundred thousand per year, the same value is only between 12 and 15 per hundred thousand in Japan. Although the majority of breast cancers are sporadic cases, 5–10% of all cases are hereditary. BRCA1 and BRCA2 genes are known to be effective in the development of breast cancer. The BRCA1 gene is thought to be responsible for 4–5% of all breast cancers and 45% of hereditary breast cancers. The risk of developing breast cancer up to the age of 70 in BRCA1 gene carriers is 94%. The rate of breast cancer cases occurring before the age of 30 is 25%. The BRCA 1 gene is responsible for half of all familial breast cancer cases and 80–90% of multiple breast and ovarian cancer cases. This shows that due to the importance of BRCA1 and BRCA2 genes in the etiology of breast cancer, detecting both BRCA1 and BRCA2 genes, especially in familial breast cancer cases, is important for public health. As a result, routine applications with rapid, reliable, and inexpensive methods to detect BRCA1 and BRCA2 gene mutations are known to be involved in the etiology of breast cancer in patients and families with multiple breast cancer or ovarian cancer or diagnosed with breast cancer at an early age may need to be seen as potential chemotherapy targets.
There is no conflict of interest.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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