Representative studies of the incidence of t-AML in different primary diagnoses.
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\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
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\\n\\nNote: Edited in October 2021
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\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
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\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
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\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 2021
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Researchers in many different scientific fields all over the world recognized this idea as an inspiring challenge. Robot soccer research is interdisciplinary, complex, demanding but most of all, fun and motivational. Obtained knowledge and results of research can easily be transferred and applied to numerous applications and projects dealing with relating fields such as robotics, electronics, mechanical engineering, artificial intelligence, etc. As a consequence, we are witnesses of rapid advancement in this field with numerous robot soccer competitions and a vast number of teams and team members. The best illustration is numbers from the RoboCup 2009 world championship held in Graz, Austria which gathered around 2300 participants in over 400 teams from 44 nations. Attendance numbers at various robot soccer events show that interest in robot soccer goes beyond the academic and R&D community. \r\n\r\nSeveral experts have been invited to present state of the art in this growing area. It was impossible to cover all aspects of the research in detail but through the chapters of this book, various topics were elaborated. Among them are hardware architecture and controllers, software design, sensor and information fusion, reasoning and control, development of more robust and intelligent robot soccer strategies, AI-based paradigms, robot communication and simulations as well as some other issues such as educational aspect. Some strict partition of chapter in this book hasn’t been done because areas of research are overlapping and interweaving. However, it can be said that chapters at the beginning are more system-oriented with wider scope of presented research while later chapters generally deal with some more particular aspects of robot soccer.",isbn:null,printIsbn:"978-953-307-036-0",pdfIsbn:"978-953-51-5871-4",doi:"10.5772/143",price:139,priceEur:155,priceUsd:179,slug:"robot-soccer",numberOfPages:358,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:null,bookSignature:"Vladan Papić",publishedDate:"January 1st 2010",coverURL:"https://cdn.intechopen.com/books/images_new/3624.jpg",numberOfDownloads:38698,numberOfWosCitations:26,numberOfCrossrefCitations:29,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:43,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:98,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:null,dateEndSecondStepPublish:null,dateEndThirdStepPublish:null,dateEndFourthStepPublish:null,dateEndFifthStepPublish:null,currentStepOfPublishingProcess:1,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"34038",title:"Prof.",name:"Vladan",middleName:null,surname:"Papić",slug:"vladan-papic",fullName:"Vladan Papić",profilePictureURL:"https://mts.intechopen.com/storage/users/34038/images/system/34038.jpg",biography:"Born on 6th August, 1968. in Split, Croatia.\nB. 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Full professor since 2010.\nClasses: Systems theory, Computer graphics, Databases.\n\n\n1993. - 1997. working as a computer software developer in INFO90 and SEM-kompjuteri.\nSince 1998. - 2002. working as young researcher on the projectBiomechanics of human gait, control and rehabilitation",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Split",institutionURL:null,country:{name:"Croatia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1258",title:"Mobile Robot",slug:"anthrobotics-mobile-robot"}],chapters:[{id:"9346",title:"The Real-Time and Embedded Soccer Robot Control System",doi:"10.5772/7352",slug:"the-real-time-and-embedded-soccer-robot-control-system",totalDownloads:3717,totalCrossrefCites:3,totalDimensionsCites:3,hasAltmetrics:0,abstract:null,signatures:"Ce Li, Takahiro Watanabe, Zhenyu Wu, Hang Li and Yijie Huangfu",downloadPdfUrl:"/chapter/pdf-download/9346",previewPdfUrl:"/chapter/pdf-preview/9346",authors:[null],corrections:null},{id:"9347",title:"CAMBADA Soccer Team: from Robot Architecture to Multiagent Coordination",doi:"10.5772/7353",slug:"cambada-soccer-team-from-robot-architecture-to-multiagent-coordination",totalDownloads:2402,totalCrossrefCites:7,totalDimensionsCites:14,hasAltmetrics:0,abstract:null,signatures:"Antonio J. 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Tonissen",dateSubmitted:"December 1st 2011",dateReviewed:"November 22nd 2012",datePrePublished:null,datePublished:"January 23rd 2013",book:{id:"2610",title:"Carcinogenesis",subtitle:null,fullTitle:"Carcinogenesis",slug:"carcinogenesis",publishedDate:"January 23rd 2013",bookSignature:"Kathryn Tonissen",coverURL:"https://cdn.intechopen.com/books/images_new/2610.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"145170",title:"Dr.",name:"Kathryn",middleName:null,surname:"Tonissen",slug:"kathryn-tonissen",fullName:"Kathryn Tonissen"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"145170",title:"Dr.",name:"Kathryn",middleName:null,surname:"Tonissen",fullName:"Kathryn Tonissen",slug:"kathryn-tonissen",email:"k.tonissen@griffith.edu.au",position:null,institution:{name:"Griffith University",institutionURL:null,country:{name:"Australia"}}},{id:"147950",title:"Ph.D. Student",name:"Maneet",middleName:null,surname:"Bhatia",fullName:"Maneet Bhatia",slug:"maneet-bhatia",email:"Maneet.Bhatia@griffithuni.edu.au",position:null,institution:{name:"Griffith University",institutionURL:null,country:{name:"Australia"}}},{id:"147952",title:"Dr.",name:"Therese",middleName:null,surname:"Karlenius",fullName:"Therese Karlenius",slug:"therese-karlenius",email:"therese.karlenius@griffithuni.edu.au",position:null,institution:{name:"Griffith University",institutionURL:null,country:{name:"Australia"}}},{id:"150307",title:"Dr.",name:"Giovanna",middleName:null,surname:"Di Trapani",fullName:"Giovanna Di Trapani",slug:"giovanna-di-trapani",email:"g.ditrapani@griffith.edu.au",position:null,institution:{name:"Griffith University",institutionURL:null,country:{name:"Australia"}}}]},book:{id:"2610",title:"Carcinogenesis",subtitle:null,fullTitle:"Carcinogenesis",slug:"carcinogenesis",publishedDate:"January 23rd 2013",bookSignature:"Kathryn Tonissen",coverURL:"https://cdn.intechopen.com/books/images_new/2610.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"145170",title:"Dr.",name:"Kathryn",middleName:null,surname:"Tonissen",slug:"kathryn-tonissen",fullName:"Kathryn Tonissen"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},ofsBook:{item:{type:"book",id:"10651",leadTitle:null,title:"Machine Learning",subtitle:"Algorithms, Models and Applications",reviewType:"peer-reviewed",abstract:"Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding. In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses–cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real-world, such as stock trading, medical and healthcare systems, and software automation. The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed. The volume will be useful for advanced graduate and doctoral students, researchers, faculty members of universities, practicing data scientists and data engineers, professionals, and consultants working on the broad areas of machine learning, deep learning, and artificial intelligence.",isbn:"978-1-83969-485-1",printIsbn:"978-1-83969-484-4",pdfIsbn:"978-1-83969-486-8",doi:"10.5772/intechopen.94615",price:119,priceEur:129,priceUsd:155,slug:"machine-learning-algorithms-models-and-applications",numberOfPages:152,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"6208156401c496e0a4ca5ff4265324cc",bookSignature:"Jaydip Sen",publishedDate:"December 22nd 2021",coverURL:"https://cdn.intechopen.com/books/images_new/10651.jpg",keywords:null,numberOfDownloads:1869,numberOfWosCitations:0,numberOfCrossrefCitations:2,numberOfDimensionsCitations:3,numberOfTotalCitations:5,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 9th 2021",dateEndSecondStepPublish:"March 9th 2021",dateEndThirdStepPublish:"May 8th 2021",dateEndFourthStepPublish:"July 27th 2021",dateEndFifthStepPublish:"September 25th 2021",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a year",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:5,editedByType:"Edited by",kuFlag:!1,biosketch:"Prof. Sen is a leading scientist in the area of artificial intelligence, machine learning, and cybersecurity, who is listed among the top 2 percent most-cited scientists in the world by Stanford University, USA.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"9",totalChapterViews:"0",totalEditedBooks:"7",institution:null}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"605",title:"Machine Learning",slug:"numerical-analysis-and-scientific-computing-machine-learning"}],chapters:[{id:"79388",title:"Introductory Chapter: Machine Learning in Finance-Emerging Trends and Challenges",slug:"introductory-chapter-machine-learning-in-finance-emerging-trends-and-challenges",totalDownloads:173,totalCrossrefCites:1,authors:[{id:"4519",title:"Prof.",name:"Jaydip",surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen"},{id:"440250",title:"Dr.",name:"Rajdeep",surname:"Sen",slug:"rajdeep-sen",fullName:"Rajdeep Sen"},{id:"440251",title:"Dr.",name:"Abhishek",surname:"Dutta",slug:"abhishek-dutta",fullName:"Abhishek Dutta"}]},{id:"78686",title:"Design and Analysis of Robust Deep Learning Models for Stock Price Prediction",slug:"design-and-analysis-of-robust-deep-learning-models-for-stock-price-prediction",totalDownloads:251,totalCrossrefCites:1,authors:[{id:"4519",title:"Prof.",name:"Jaydip",surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen"},{id:"320071",title:"Dr.",name:"Sidra",surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab"}]},{id:"78753",title:"Articulated Human Pose Estimation Using Greedy Approach",slug:"articulated-human-pose-estimation-using-greedy-approach",totalDownloads:754,totalCrossrefCites:0,authors:[{id:"348818",title:"Assistant Prof.",name:"Pooja",surname:"Kherwa",slug:"pooja-kherwa",fullName:"Pooja Kherwa"},{id:"348833",title:"Mr.",name:"Saheel",surname:"Ahmed",slug:"saheel-ahmed",fullName:"Saheel Ahmed"},{id:"348835",title:"Mr.",name:"Pranay",surname:"Berry",slug:"pranay-berry",fullName:"Pranay Berry"},{id:"348836",title:"Mr.",name:"Sahil",surname:"Khurana",slug:"sahil-khurana",fullName:"Sahil Khurana"},{id:"348839",title:"Ms.",name:"Sonali",surname:"Singh",slug:"sonali-singh",fullName:"Sonali Singh"}]},{id:"79087",title:"Ensemble Machine Learning Algorithms for Prediction and Classification of Medical Images",slug:"ensemble-machine-learning-algorithms-for-prediction-and-classification-of-medical-images",totalDownloads:248,totalCrossrefCites:0,authors:[{id:"416773",title:"M.Sc.",name:"Racheal S.",surname:"Akinbo",slug:"racheal-s.-akinbo",fullName:"Racheal S. 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Rosa",coverURL:"https://cdn.intechopen.com/books/images_new/5191.jpg",editedByType:"Edited by",editors:[{id:"151889",title:"Dr.",name:"Joao Luis Garcia",surname:"Rosa",slug:"joao-luis-garcia-rosa",fullName:"Joao Luis Garcia Rosa"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"44517",title:"Therapy-Related Acute Myeloid Leukemias",doi:"10.5772/52459",slug:"therapy-related-acute-myeloid-leukemias",body:'Therapy-related acute myeloid leukemia (t-AML) is a heterogeneous group of myeloid neoplasms occurring as an overwhelming complication in patients receiving previous cytotoxic chemotherapy and/or radiation therapy used to treat haematopoietic or solid malignancies or associated with immunosuppressive treatment for non-neoplastic rheumatologic/autoimmune diseases or solid organ transplantation (Offman et al., 2004; Kwong, 2010). T-AML is an increasingly recognized condition included in the category of therapy-related myeloid neoplasms in the revised WHO classification of tumours of haematopoietic and lymphoid tissues, together with therapy-related myelodysplastic syndrome (t-MDS) and myelodysplastic/myeloproliferative neoplasm, that constitute a unique clinical syndrome (Vardiman et al., 2009).
The average age of the population in the developed countries is increasing, and cancer incidence increases with age. Both improved early detection of first malignancies and primary oncologic therapy have led to enhanced survival rates, and the risk of t-AML has consequently risen over the last few decades (Travis, 2006; Ries et al., 2008). Thus patients are, in a sense, the fortunate victims of our own success. Secondary leukemias challenge both the understanding of leukemogenesis and the clinical management of these conditions. The disease offers a unique opportunity to study leukaemic transformation by relating specific genetic and molecular abnormalities to the biologic effects of particular agents. The detailed insights into pathogenetic mechanisms will eventually help to establish a more differentiated clinical approach to successfully treat, but hopefully also prevent, these often fatal consequences of cytotoxic therapies. Despite that t-AMLs share common phenotypic features with de novo AML, the prognosis is generally unfavorable.
In general, t-AML are of particular importance to study for several reasons: (i) they represent the most serious long-term complications to current cancer therapy and the understanding would help to identify patients at risk in order to tailor therapy; (ii) they can be directly induced by chemically well-defined agents or irradiation with well-known cellular effects; (iii) they present the same chromosome aberrations and gene mutations as de novo AML, allowing for extrapolation of results from one to the other type of disease thus clarifying the biological processes leading to leukemogenesis; (iv) an early stage of MDS with refractory cytopenia is often diagnosed in therapy-related diseases, because most patients are followed thoroughly after intensive chemotherapy or irradiation, while in
The proportion of therapy-related AMLs varies from 5% to higher than 10% out of all cases of AMLs depending on the primary disease and the applied treatment in regard to chemical structure and dose of the used compounds, as well as to the type and intensity of used physical agent (Schneider et al., 1999). The GIMEMA registry reports an incidence of 5% of AML occurring as a second malignancy in Italy, however this registry includes only patients in whom treatment is feasible. Similarly, t-AML account for about 6% of all new AML cases in the UK, thus corresponding to an incidence rate at around 0.2/100 000/year (reviewed in Seedhouse & Russell, 2007). For a 12-years period, the review of our own data also showed that in 26 out of 407 consecutive cases of adult AML diagnosed and treated in our institution had a history for a previous malignancy treated with chemotherapy and/or radiotherapy which accounts for 6,1% (Balatzenko & Guenova, 2012). Higher values were reported by others as the pooled analysis of a consecutive series of 372 Swedish adult AML cases compared to 4230 unselected cases reported in the literature 1974 – 2001 revealed an incidence of 13% and 14%, respectively (Mauritzson et al.,2002).
All age groups are affected - both children and adults develop AML following treatment with antineoplastic agents. However, children deserve particular consideration, taking into account the long life-expectancy of oncological patients cured by chemo and radiotherapy (Le Deley et al., 2003). As demonstrated in the published literature, the risk of developing AML following chemotherapy is not reliably correlated with the age of the pediatric patient. There is no consistent evidence that indicates that younger children will be at increased risk; in fact, some studies suggest that younger children might actually display a decreased susceptibility. Unlike secondary solid tumors such as breast, central nervous system, bone, and thyroid cancer which are highly dependent on the age of the patient at time of diagnosis and treatment; an age dependency for t-AML risk was not observed in the same pediatric patient populations (reviewed in Pyatt et al., 2007). In addition, though in the Guidelines for Carcinogen Risk Assessment (2005), presented at the Risk Assessment Forum U.S. Environmental Protection Agency a 10-fold higher risk attributable to early-life carcinogenic exposure was assumed, leading to a reasonable expectation that children can be more susceptible to many carcinogenic agents, the available scientific and medical literature does not support the hypothesis that children necessarily possess an increased risk of developing AML following leukemogenic chemical exposure (Pyatt et al., 2007, Barnard et al, 2005).
In adult patients there is a higher risk and shorter latency period for the development of t-AML (Dann et al., 2001). In general, there is no convincing evidence for gender predisposition (Pagano et al., 2001; Smith et al. 2003).
Due to decreasing overall death rates in cancer there is an increasing number of cured patients at risk of developing t-AML. The review of reports on long follow-up of high numbers of patients treated with relatively uniform protocols comprising cytotoxic drugs, growth factors and radiation therapy individually or in combination highlights the major trends, with the greatest likelihood of developing therapy-related myeloid neoplasms following treatment of hematopoietic malignancies and breast cancer in adults, ALL and central nervous system tumors in children, germ cell tumours, lung cancer, etc. A significant proportion of t-AMLs nowadays involve patients treated for non-neoplastic disorders, and those treated with high-dose chemotherapy followed by autologous stem cell transplantation (Mauritzson et al., 2002; Suvajdžić et al. 2012; Ramadan et al., 2012). Representative studies are summarised in Table 1 demonstaring the incidence of t-AML in different primary diseases.
Up to 10% of patients with a preceeding lymphoid neoplasm treated with conventional chemotherapy and especially high-dose therapy and autologous stem cell transplantation may develop a t-AML within 10 years following primary therapy (Table 1). In patients with Hodgkin lymphoma (HL), the risk of t-AML has been reported to range between 1% and 10%, depending on the type of therapy administered, the study population size, and the follow-up duration. In patients with non-Hodgkin’s lymphoma (NHL), an increased risk of secondary malignancies including therapy-related myeloid neoplasms has been reported, in particular when fludarabine-containing regimens or SCT are used. Significant risk factors were older age at the time of diagnosis, male sex, and fludarabine- or nucleoside analogs-containing therapy or SCT.Interestingly, leukemia cases are rarely or never seen in patients treated with radiotherapy alone (Mudie et al. 2006). Secondary carcinogenesis remains a major late complication in patients with acute lymphoblastic leukemia, particularly in children. A retrospective study of the cumulative incidence of secondary neoplasms after childhood ALL over 30 years showed that the risk of t-AML is higher in ALL children who receive a high cumulative dose and prolonged epipodophyllotoxin therapy in weekly or bi-weekly schedules, with short-term use of G-CSF and central nervous system irradiation as additive risk factors (Hijiya et al.,2007).
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t|||||
Acute lymphoblastic leukemia (adults) | \n\t\t\t641 | \n\t\t\t6 (0.9%) | \n\t\t\tCT | \n\t\t\t32 months | \n\t\t\tVerma et al.,2009 | \n\t\t
Acute lymphoblastic leukemia (children) | \n\t\t\t733 | \n\t\t\t13 (1.8%) | \n\t\t\tCT | \n\t\t\t3 years | \n\t\t\tPui et al.,1989 | \n\t\t
Acute lymphoblastic leukemia (children) | \n\t\t\t1290 | \n\t\t\t37 (2,9%) | \n\t\t\tCT | \n\t\t\t3.8 years | \n\t\t\tHijiya et al., 2007 | \n\t\t
Acute lymphoblastic leukemia | \n\t\t\t1494 | \n\t\t\t6 (0.4%) | \n\t\t\tCT | \n\t\t\t1.3 years | \n\t\t\tTavernier et al.,2007 | \n\t\t
CLL | \n\t\t\t521 | \n\t\t\t3 (0.6%) | \n\t\t\tCT | \n\t\t\t34 months | \n\t\t\tMorrison et al.,2002 | \n\t\t
B-NHL; T-NHL; Hodgkin’s lymphoma | \n\t\t\t1347 | \n\t\t\t11 (0.8%) | \n\t\t\tHDCT± MoAbs | \n\t\t\t\n\t\t\t | Tarella et al.,2011 | \n\t\t
NHL | \n\t\t\t230 | \n\t\t\t11 (4.8%) | \n\t\t\tHD CT + RT | \n\t\t\t4.4 years | \n\t\t\tMicallef et al.,2000 | \n\t\t
NHL | \n\t\t\t29153 | \n\t\t\t29 (0.1%) | \n\t\t\tRT ± CT; other | \n\t\t\t61 months | \n\t\t\tTravis et al.,1991 | \n\t\t
Hodgkin’s lymphoma | \n\t\t\t5411 | \n\t\t\t36 (0.7%) | \n\t\t\tRT ± CT | \n\t\t\t5 years | \n\t\t\tJosting et al.,2003 | \n\t\t
Hodgkin’s lymphoma | \n\t\t\t2676 | \n\t\t\t17 (0.6%) | \n\t\t\tRT; CT; RT+CT | \n\t\t\t79.9 months | \n\t\t\tDevereux et al.,1990 | \n\t\t
Hodgkin’s lymphoma | \n\t\t\t29552 | \n\t\t\t143 (0.5%) | \n\t\t\tRT; CT; RT+CT | \n\t\t\tND | \n\t\t\tKaldor et al.,1990 | \n\t\t
Hodgkin’s lymphoma | \n\t\t\t947 | \n\t\t\t23 (2.4%) | \n\t\t\tRT; CT; RT+CT | \n\t\t\t58 months | \n\t\t\tCimino et al. ,1991 | \n\t\t
Hodgkin’s lymphoma | \n\t\t\t32591 | \n\t\t\t169 (0.5%) | \n\t\t\tRT; CT; RT+CT | \n\t\t\tND | \n\t\t\tDores et al.,2002 | \n\t\t
Hodgkin’s lymphoma (children) | \n\t\t\t1380 | \n\t\t\t24 (1.7%) | \n\t\t\tRT; CT; RT+CT | \n\t\t\tND | \n\t\t\tBhatia et al.,1996 | \n\t\t
Hodgkin’s lymphoma | \n\t\t\t794 | \n\t\t\t8 (1.0%) | \n\t\t\tRT; RT+CT | \n\t\t\t5 years | \n\t\t\tMauch et al., 1996 | \n\t\t
Multiple Myeloma | \n\t\t\t8740 | \n\t\t\t39* (0.4%) | \n\t\t\tCH, HDM-ASCT, IMiDs | \n\t\t\t45.3 months | \n\t\t\tMailankody et al.,2011 | \n\t\t
Multiple Myeloma | \n\t\t\t2418 | \n\t\t\t5 (0.2%) | \n\t\t\tCH, HDM-ASCT, IMiDs | \n\t\t\tND | \n\t\t\tBarlogie et al.,2008 | \n\t\t
APL | \n\t\t\t77 | \n\t\t\t3 (3.9%) | \n\t\t\tCT ± ATRA | \n\t\t\t\n\t\t\t | Latagliata et al.,2002 | \n\t\t
\n\t\t\t\t | \n\t\t|||||
Small cell lung carcinoma | \n\t\t\t158 | \n\t\t\t3 (1.9%) | \n\t\t\t\n\t\t\t | 2.7 years | \n\t\t\tChak et al.,1984 | \n\t\t
Germ-cell tumours | \n\t\t\t212 | \n\t\t\t4 (1.9%) | \n\t\t\tCT | \n\t\t\tND | \n\t\t\tPedersen-Bjergaard et al.,1991 | \n\t\t
Germ-cell tumours | \n\t\t\t442 174 124 | \n\t\t\t3 (0.7%) 3 (1.7%) 0 | \n\t\t\tCT RT+CT RT | \n\t\t\tND | \n\t\t\tSchneider et al.,1991 | \n\t\t
Germ-cell tumors (children) | \n\t\t\t716 416 | \n\t\t\t6 (0.84%) 0 | \n\t\t\tCT+RT RT or S | \n\t\t\t101 weeks | \n\t\t\tSchneider et al.,1999 | \n\t\t
Ovarian Cancer | \n\t\t\t63359 | \n\t\t\t109 (0.2%) | \n\t\t\tCT | \n\t\t\t4 years | \n\t\t\tVay et al.,2011 | \n\t\t
Ovarian Cancer | \n\t\t\t99113 | \n\t\t\t95 (0.1%) | \n\t\t\tRT; CT; RT+CT | \n\t\t\t4-5 years | \n\t\t\tKaldor et al.,1990 | \n\t\t
Ovarian Cancer | \n\t\t\t28971 | \n\t\t\t1 (0.003%) 65 (0.2%) 25 (0.09%) | \n\t\t\tRT CT RT+CT | \n\t\t\t3.3 years \n\t\t\t | \n\t\t\tTravis et al.,1999 | \n\t\t
Breast Cancer | \n\t\t\t5299 646 | \n\t\t\t27 (0.5%) 5 (0.8%) | \n\t\t\tCT RT | \n\t\t\tND | \n\t\t\tFisher et al.,1985 | \n\t\t
Breast Cancer | \n\t\t\t82700 | \n\t\t\t74 (0.09%) \n\t\t\t | \n\t\t\tCT; RT; CT+RT | \n\t\t\t5 years | \n\t\t\tCurtis et al.,1992 | \n\t\t
Breast Cancer | \n\t\t\t1474 | \n\t\t\t14 (0.9%) | \n\t\t\tCH ± RT | \n\t\t\t66 months | \n\t\t\tDiamandidou et al.,1996 | \n\t\t
Testicular Cancer | \n\t\t\t1909 | \n\t\t\t3 1 2 | \n\t\t\tCT RT RT+CT | \n\t\t\t7.7 years | \n\t\t\tvan Leeuwen et al., 1993 | \n\t\t
Testicular Cancer | \n\t\t\t28843 | \n\t\t\t27 (0.09%) | \n\t\t\tCH; RT | \n\t\t\tND | \n\t\t\tTravis et al.,1997 | \n\t\t
Prostate Cancer | \n\t\t\t487 | \n\t\t\t3 (0.6%) | \n\t\t\tCH | \n\t\t\t48 months | \n\t\t\tFlaig et al.,2008 | \n\t\t
Prostate Cancer | \n\t\t\t168612 | \n\t\t\t184 (0.1%) | \n\t\t\tRT | \n\t\t\t\n\t\t\t | Ojha et al., 2010 | \n\t\t
\n\t\t\t\t | \n\t\t|||||
Reumatoid arthritis | \n\t\t\t53067 | \n\t\t\t68 (SIR=2,4) | \n\t\t\t\n\t\t\t | ND | \n\t\t\tAskling et al. 2005 | \n\t\t
Reumatoid arthritis | \n\t\t\t4160 | \n\t\t\t0 (SIR=0) | \n\t\t\tTNF antagonist | \n\t\t\tNA | \n\t\t\tAskling et al. 2005 | \n\t\t
Multiple sclerosis | \n\t\t\t2854 | \n\t\t\t21(SIR=1,84) | \n\t\t\t\n\t\t\t | NA | \n\t\t\tMartinelli et al. 2009 | \n\t\t
Systemic lupus erythematodis | \n\t\t\t5715 | \n\t\t\t8(OR=1,2) | \n\t\t\t\n\t\t\t | ND | \n\t\t\tLoststrone et al. 2009 | \n\t\t
Wegener’s granulomatosis | \n\t\t\t293 | \n\t\t\t(SIR=19,6) | \n\t\t\t\n\t\t\t | 6,8-18,5 yrs | \n\t\t\tFaaurschou et al. 2008 | \n\t\t
Ulcerative colitis | \n\t\t\t2012 | \n\t\t\t(OR=3,8) | \n\t\t\t\n\t\t\t | ND | \n\t\t\tJohnson et al. 2012 | \n\t\t
Representative studies of the incidence of t-AML in different primary diagnoses.
Legend: * including terapy-related MDS; ND – no data; CT – chemotherapy; RT – radio therapy; IMiDs – Immunomodulatory drugs; MoAbs – monoclonal antibodies; HD – high dose; ASCT - autologous stem cell transplantation; ND – no data; S – surgery; ATRA - all-trans retinoic acid; NHL – non-Hodgkin’s lymphoma; APL – acute promyelocytic leukaemia; OR – odds ratio; SIR – standardized incidence ratio.
In most studies, an increased risk of t-AML was reported in breast cancer patients treated with chemoradiotherapy ± radiotherapy. Besides, an increased incidence of t-MDS/AML in patients treated with surgery alone and in patients with a family history of breast cancer suggests a possible association between the two diseases.
When looking at solid tumors, an increased risk of t-AML has been reported in breast cancer patients treated with chemoradiotherapy ± radiotherapy (Table 1). Praga et al. analyzed 9796 breast cancer patients treated in 19 randomized trials (Praga et al., 2005). The cumulative 8-year risk of t-AML showed wide variability between patients treated with standard or high cumulative doses of epirubicin (0.37% vs 4.97%, respectively). In almost 400,000 breast cancer patients, significant risk factors were also younger age at the time of breast cancer diagnosis, advanced stage disease with distal involvement and treatment using radiotherapy (Martin et al., 2009).A large proportion of patients with testicular cancer can be cured by radiochemotherapy, including topoisomerase II inhibitors and cisplatin, but t-MDS/AML represents a major problem with a mean cumulative risk of 1.3 to 4.7% at 5 years (Travis et al., 2000). An increased incidence of AML was found in children with non-testicular germ cell tumors after chemoradiotherapy, with a cumulative incidence in patients treated with combined chemotherapy and radiotherapy. No cases of leukemia were found in patients treated with radiotherapy or surgery only (Schneider et al.,1999).
An increased risk of therapy-related myelodysplastic syndrome and t-AML after high-dose therapy and autologous stem-cell transplantation (ASCT) for malignant lymphoma has been described by several studies, reporting a highly variable incidence ranging from 1-3% (Lenz et al., 2004; Howe et al., 2003) to 12% (Micallef et al., 2000). The incidence of therapy-related myeloid neoplasms after SCT is related to the type of conditioning regimens, as patients receiving the combination of TBI and alkylating agents seem to have an especially increased risk, but also to the type of previous chemotherapy, its effects on harvested hematopoietic stem cells and the use of growth factors. The development of t-MN after SCT has been shown to be associated with and preceded by markedly altered telomere dynamics in hematopoietic cells, which may reflect increased clonal proliferation and/or altered telomere regulation in premalignant cells (Chakraborty et al., 2009). In the allogeneic bone marrow or hematopoietic stem cell transplantation setting, donor cell–derived leukemias (DCL) and myelodysplastic neoplasms represent a rare but intriguing form of leukemogenesis. DCL represents a unique form of leukemogenesis in which normal donor cells become transformed into an aggressive leukemia or MDS following engraftment in a foreign host environment (Wang et al., 2011; Sala-Torra et al., 2006).
The risk of developing therapy-related AML also applies to patients with non-malignant conditions, such as autoimmune diseases treated with cytotoxic and/or immunosuppressive agents. There is considerable evidence to suggest an increased occurrence of hematologic malignancies in patients with autoimmune diseases compared to the general population, with a further increase in risk after exposure to cytotoxic therapies. Unfortunately, studies have failed to reveal a clear correlation between leukemia development and exposure to individual agents used for the treatment of autoimmune diseases. The association of t-AML and autoimmune diseases was clearly demonstrated in a recent study reporting for an odds ratio of AML OR=1,29 (95% CI, 1.2–1.39) by comparing 13,486 patients aged over 67 years with myeloid malignancies to 160,086 population-based matched controls using the SEER-Medicare database of Hematopoietic Malignancy Risk Traits (SMAHRT). Specifically, AML was associated with rheumatoid arthritis (OR 1.28), systemic lupus erythematosus (OR 1.92), polymyalgia rheumatica (OR 1.73), autoimmune haemolytic anaemia (OR 3.74), systemic vasculitis (OR 6.23), ulcerative colitis (OR 1.72) and pernicious anaemia (OR 1.57) (Anderson et al., 2009). This was confirmed in a recent study by Kristinsson et al. that included 9,219 patients with AML and 42,878 matched controls from population-based central registries in Sweden and reported for a 1.7-fold (95% CI, 1.5–1.9) increased risk of AML (Kristinsson et al., 2011).
In summary, certain inflammatory medical conditions and a personal history of cancer, independent from therapy, are associated with an increased risk of myeloid leukemia. According to the WHO classification, the distinction of t-AMLs from de novo leukemias is solely based on the patient’s history but not on the specific biomarkers. Interestingly, it has been observed that 20–30% of acute leukemias, occurring as second malignancy, developed in the absence of previous chemo and/or radiotherapy exposure suggesting that besides the proven leukemogenic mechanisms of chemo and immunosuppressive therapy and ionizing radiations, other factors such as genetics, chronic immune stimulation and environment could favour the onset of multiple neoplastic diseases (Pagano et al., 2001; Johnson et al., 2012). We have to admit that there is insufficient evidence to label leukemias that develop in patients who are exposed to cytotoxic agents as ‘therapy-related leukemias’. Further investigation of the underlying mechanisms and defects, including defects in immunity, DNA repair, and apoptosis in these patients are warranted rather than studying only drug mechanisms that lead to leukemogenesis .
Despite that it has been suggested that chemotherapy (CT) and radiotherapy (RT) are associated with a considerable increase in the risk for the development of t-AML compared to the general population, it still only occurs in a relatively small number of patients. The actuarial risk varies from study to study, but an increase in the risk of AML of 0.25 to 1 % per year has been generally observed. The risk is dose dependent and increases exponentially with age after the age of 40 years, paralleling the risk of primary AML in the general population (Pedersen-Bjergaard J., 2005).
It is important to identify risk factors that may confer susceptibility to the development of the condition, including life style, environmental and occupational, as well as host factors, such as differences in drug catabolism, membrane transport or inefficient DNA repair that could explain the predisposition to leukemia. In general chemotherapy confers a greater risk while involved field radiation is associated with very little or no increased risk of leukemia. Characteristic features often relate to the type of previous therapy; alkylating agents or RT; drugs binding to the enzyme DNA-topoisomerase, or antimetabolites.
Lichtman (2007) after a review of 463 618 cases of cancer patients treated with chemotherapy and radiotherapy, reported 741 cases of AML/MDS, or less than 1%. These data clearly demonstrate, that after exposure to chemotherapy and/or radiotherapy only a small proportion of patients develop t-AMLs, which supports the idea, that a host predisposition to the leukemogenic potential of chemotherapy and radiotherapy probably exits (Czader & Orazi, 2009). Understanding individual susceptibility factors is important not only to identify patients at risk in order to tailor therapy, but also to clarify the biological processes leading to leukemogenesis (Leone et al.,2007).
During the last years, a number of factors were identified, that might cause a predisposition to both de novo and t-AML, including several cancer susceptibility syndromes (Knoche et al., 2006).
Similarly,
Some observation also suggest that individuals with constitutional genetic variation in the p53 pathway such as certain allelic variants within the
The
Recently, an oncogenic germline
Over the last years,
A novel concept addresses
DAPK1 was more frequently methylated in t-MDS/AML when compared to de novo MDS and AML (39% vs 15.3% and 24.4%, p=0.0001). Besides, the methylation pattern appeared to be related to the primary tumor, with DAPK1 more frequently methylated in patients with a previous lymphoproliferative disease (75% vs 32%, p=0.006). In patients studied for concurrent methylation of several promoters, t-MDS/AML were significantly more frequently hypermethylated in 2 or more promoter regions than de novo MDS or AML suggesting that promoter hypermethylation of genes involved in cell cycle control, apoptosis and DNA repair pathways is a frequent finding in t-MDS/AML and may contribute to secondary leukemogenesis. These studies support the hypothesis that chemotherapy and individual genetic predisposition have a role in t-MDS/AML development, and the identification of specific epigenetic modifications may explain complexity and genomic instability of these diseases and give the basis for targeted-therapy. The significant association with previous malignancy subtypes may underlie a likely susceptibility to methylation of specific targets and a role for constitutional epimutations as predisposing factors for the development of therapy-related myeloid neoplasm. However, how the epigenetic machinery is disrupted after chemo/radiotherapy and during secondary carcinogenesis is still unknown, warranting further studies (Voso et al., 2010; Greco et al., 2010).
Another probable mechanisms that predispose to t-AML could be related to accumulation of reactive species that escape detoxification mechanisms or are produced in excess due to drug metabolizing enzymes polymorphisms, or due to DNA damage which is inefficiently repaired because of defective DNA-repair (Seedhouse et al., 2004).
Drug or xenobiotic metabolizing enzymes play key roles in the detoxification of xenobiotics, as well as of a number of commonly used chemotherapeutics. Besides, drug metabolizing enzymes display a high degree of polymorphism in the general population. The potential role of the polymorphisms of most of these genes in the etiology of primary or t-AML has been suggested (Perentesis, 2001).
One of the most important compounds of CYP system is a
Glutathione S-transferases (GSTs) detoxify potentially mutagenic and DNA-toxic metabolites of several chemotherapeutic agents, such as adriamycin, BCNU, bleomycin, chlorambucil, cisplatin, etoposide, melphalan, mitomycin C, mitoxantrone, vincristine, cyclophosphamide, etc. The variant allele of
An increased risk of developing t-AML has been observed in breast cancer patients with a 677T/1298A haplotype in
Another mechanism implicated into the t-AML development includes defects of the individual DNA-repair machinery which is genetically determined and is believed to be the result of combinations of multiple genes, each of which may display subtle differences in their activities. Double-strand breaks in DNA lead either to cell death or loss of genetic material resulting in chromosomal aberrations. Insufficient repair results in acquisition and persistence of mutations, whereas elevated levels of repair can inhibit the apoptotic pathway and enable a cell with damaged DNA, attempting repair, to misrepair and survive (Leone et al., 2007).
There is accumulating evidence suggesting a role for
Another possible mechanisms might involve the
By definition t-AMLs occur as late complications of cytotoxic chemotherapy and/or radiation therapy administered for a prior neoplastic or non-neoplastic disorder (Vardiman et al., 2008). Chemotherapy and ionizing radiation cause extensive DNA damage and affect unfortunately not only neoplastic but also normal cells. Presumably if genes controlling growth and differentiation of haematopoietic stem cells are affected, a neoplastic myeloid clone may arise. Further, repeated therapies may facilitate the selection of such a clone due to the inevitable immunosupression.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Alkylating agents \n\t\t\t | \n\t\t\tBusulfan | \n\t\t\tDastugue et al., 1990 | \n\t\t
Carboplatin | \n\t\t\tMiyata et al., 1996 | \n\t\t|
Carmustine | \n\t\t\tPerry et al., 1998 | \n\t\t|
Chlorambucil | \n\t\t\tRosenthal et al., 1996 | \n\t\t|
Cisplatin | \n\t\t\tSamanta et al., 2009 | \n\t\t|
Cyclophosphamide | \n\t\t\tAu et al., 2003 | \n\t\t|
Dacarbazine | \n\t\t\tCollins et al., 2009 | \n\t\t|
Dihydroxybusulfan | \n\t\t\tPedersen-Bjergaard et al.,1980 | \n\t\t|
Lomustine | \n\t\t\tPerry et al., 1998 | \n\t\t|
Mechlorethamine | \n\t\t\tMetayer et al., 2003 | \n\t\t|
Melphalan | \n\t\t\tKyle et al., 1070; Yang et al., 2012 | \n\t\t|
Mitolactol | \n\t\t\tBennett et al., 1994 | \n\t\t|
Mitomycin C | \n\t\t\tNakamori et al., 2003 | \n\t\t|
Procarbazine | \n\t\t\tTravis et al., 1994 | \n\t\t|
Semustine | \n\t\t\tBoice et al., 1983 | \n\t\t|
Temozolomide | \n\t\t\tNoronha et al., 2006 | \n\t\t|
Topoisomerase II inhibitors \n\t\t\t | \n\t\t\t4-Epidoxorubicin | \n\t\t\tRiggi et al., 1993 | \n\t\t
Bimolane | \n\t\t\tXue et al., 1997 | \n\t\t|
Dactinomycin | \n\t\t\tScaradavou et al., 1995 | \n\t\t|
Daunorubicin | \n\t\t\tBlanco et al., 2001 | \n\t\t|
Doxorubicin | \n\t\t\tYonal et al., 2012 | \n\t\t|
Etoposide | \n\t\t\tHaupt et al., 1994 | \n\t\t|
Mitoxantrone | \n\t\t\tColovic et al., 2012 | \n\t\t|
Razoxane | \n\t\t\tBhavnani et al., 1994 | \n\t\t|
Teniposide | \n\t\t\tEzoe et al. 2012 | \n\t\t|
Antimetabolites \n\t\t\t | \n\t\t\t5-fluorouracil | \n\t\t\tTurker et al., 1999 | \n\t\t
Fludarabine | \n\t\t\tSmith et al., 2011 | \n\t\t|
6-Mercaptopurine | \n\t\t\tBo et al., 1999 | \n\t\t|
Methotrexate | \n\t\t\tKolte et al., 2001 | \n\t\t|
Antimicrotubule agents \n\t\t\t | \n\t\t\tDocetaxel | \n\t\t\tGriesinger et al., 2004 | \n\t\t
Paclitaxel | \n\t\t\tSee et al., 2006 | \n\t\t|
Vinblastine - leukemogenic effects were not confirmed | \n\t\t\tCarli et al., 2000 | \n\t\t|
Vincristine - leukemogenic effects were not confirmed | \n\t\t\tCarli et al. 2000 | \n\t\t|
Growth factors \n\t\t\t | \n\t\t\tGranulocyte colony-stimulating factor | \n\t\t\tRelling et al., 2003 | \n\t\t
Granulocyte-macrophage colony-stimulating factor | \n\t\t\tHershman et al., 2007 \n\t\t\t | \n\t\t|
Immunomodulators | \n\t\t\tAzathioprine | \n\t\t\tKwong et al.,2010 | \n\t\t
Cytotoxic agents implicated in t-AML.
Although increased risk of t-AML has been observed after chemotherapy or radiotherapy alone or in combination, chemotherapy generally confers greater risk. Radiation alone is rarely associated with increased risk of t-AML. However, cytotoxic drugs are often given in complex schedules and sometimes in combination with radiotherapy, making it difficult to assess the tumorigenic role of each drug. The most common cytotoxic drugs commonly implicated are listed in the Table 2.
Alkylaing agents were the first chemotherapeutics to be associated with secondary leukaemia development after successful treatment of other solid or haematopoietic neoplasms (Kyle et al., 1970; Smit & Meyler, 1970). The mechanisms of DNA damage include either methylation or DNA inter-stand crosslinking formation. Monofunctional alkylating agents (incl. dacarbasine, procarbasine, temozolomide) have one reactive moiety and generally induce base lesions by transferring alkyl groups (-CH3 or CH2-CH3) to oxygen or nitrogen atoms of DNA bases, resulting in highly mutagenic DNA base lesions (reviewed in Drablos et al., 2004). In contrast, bifunctional alkylating agents (incl. melphalan, cylophosphamide, chlorambucil) have two reactive sites and in addition to DNA base lesions, intra- and interstrand crosslinks can be formed by attacking two bases within the same or on opposing DNA strands which furtheron could result in translocations, inversions, insertions and loss of heterozygosity (reviewed in Helleday et al., 2008).
The latency between treatment and t-MN is generally long, between 5 and 7 years, and overt leukemia is frequently preceeded by a dysplastic phase. These cases are generally characterized by loss or deletion of chromosome 5 and/or 7 [-5/del(5q), -7/del(7q)]. In the University of Chicago\'s series of 386 patients with t-MDS/t-AML, 79 patients (20%) had abnormalities of chromosome 5, 95 patients (25%) had abnormalities of chromosome 7, and 85 patients (22%) had abnormalities of both chromosomes 5 and 7. t-MDS/t-AML with a -5/del(5q) is associated with a complex karyotype, characterized by trisomy 8, as well as loss of 12p, 13q, 16q22, 17p (
Commonly used topoisomerase inhibitors bind to the enzyme/DNA complex at the strand cleavage stage of the topoisomerase reaction, interacting with topoisomerase I (topotecan) or II(doxorubicin, epipodophyllotoxin, e.g. etoposide and teniposide). Topoisomerase II inhibitors block the enzymatic reaction through religation and enzyme release, leaving the DNA with a permanent strand break. Chromosomal breakpoints have been found to be preferential sites of topoisomerase II cleavage, which are believed to be repaired by the nonhomologous end-joining DNA repair pathway to generate chimaeric oncoproteins that underlie the resultant leukaemias (reviewed in Joannides & Grimwade, 2010).
T-AMLs occur after a shorter latency time, ranging between 1 and 3 years from the primary treatment, usually arising without a previous dysplastic phase. Several factors, such as the schedule and the concurrent use of asparaginase, dexrazoxane or G-CSF, are considered very important in determining the relative risk. Exposure to topoisomerase II inhibitors is predominantly associated with t-AML characterized by reciprocal translocations with as many as 40 different partner genes, such as t(9;11), t(19;11) or t(4;11) in 80% of the cases, as well as with internal duplications, deletions, and inversions translocations of the
Antimetabolites (e.g. azathioprine, 6-thioguanine, fludarabine) share structural similarities with nucleotides, and can be incorporated into DNA or RNA, thereby interfering with replication and causing inhibition of cell proliferation. Once placed in the newly synthesized DNA strand, metabolites are prone to methylation and formation of the highly mutagenic base lesions that closely resemble the induced by alkylating agents. Cell cycle arrest and cell death after treatment are triggered by the DNA MMR machinery. However, MMR-deficient cells can tolerate methylated lesions, potentially forming a leukaemic clone (Offman et al., 2004). In line with the cytogenetic aberrations found with alkylating agents, patients with t-AML after antimetabolites treatment frequently harbour partial or complete loss of chromosomes 5 and 7 (Morrison et al., 2002; Smith et al., 2011).
Since some of G-CSF effects include stimulation of the proliferation of granulocytic progenitors and premature release of neutrophils from the bone marrow enhancing their capacity for phagocytosis, ROS (reactive oxygen species) generation and bacterial cell killing, two mechanisms have been implicated in the G-CSF-mediated promotion of therapy-related myeloid neoplasms (Beekman & Touw, 2010). First, G-CSF-induced production and release of ROS by bone marrow neutrophils may result in increased DNA damage and mutation rates in Human hematopoietic stem and progenitor cells (Touw & Bontenbal, 2007). Second, repeated application of G-CSF results in a continuous leaving of these cells from their protective bone marrow niche, which may render them more susceptible to genotoxic stress (Trumpp et al., 2010). In an attempt to evaluate the risk of acute myeloid leukemia or myelodysplastic syndrome in patients receiving chemotherapy with or without G-CSF, Lyman et al., 2010 systematically reviewed 25 randomized controlled trials and identified 6058 and 6746 patients were randomly assigned to receive chemotherapy with and without initial G-CSF support, respectively. An absolute risk of 0.43% was determined, however, the administration of G-CSF showed benefits for a substantial proportion of patients and outweighs the increased risk of secondary leukemias.
The risk of leukemia following radiation is considerably smaller than after chemotherapy, with a relative peak at the 5th to 9th year after radiotherapy exposure showing a slow decline afterwards. The underlying mechanisms refer to the formation of reactive oxygen species through radiolysis of water molecules resulting from the exposure of cells to ionizing radiation, which are highly reactive and capable of oxidizing or deaminating DNA bases and increasing the frequency of DNA double strand breaks (Rassool et al., 2007), on one hand, or can also directly induce strand breaks by disruption of the sugar phosphate backbone of DNA, potentially leading to the formation of large scale chromosomal rearrangements (Klymenko et al., 2005). The radiation-related leukemia risk depends on the dose given to the active bone marrow, the dose rate, and the extent of exposed marrow (Travis L., 2006). Due to cell killing at higher doses the risk of t-AML is considerably larger at low doses: patients in whom high radiation doses to limited fields have been given are associated with little or no increased risk of leukemia (UNSCEAR 2000 Report), while exposure of extended fields of radiotherapy as well as low-dose total body irradiation may result in considerably higher risks (Travis et al., 1996; Travis et al., 2000) of leukemia.
It has been suggested, that t-AML are a direct consequence of mutational events induced by chemotherapy, radiation therapy, immunosuppressive therapy, or a combination of these modalities (Godley & Larson, 2008). Similarly to de novo AML, t-AMLs are complex genetic diseases, requiring cooperating mutations in interacting pathways for disease initiation and progression. Establishing a leukaemic phenotype requires acquisition of crucial genetic aberrations, such as point mutations, fusion genes formation or gene rearrangements, deletion or inactivation of tumor-suppressor genes, or changes in the expression of critical oncogenes or growth factor receptor genes (Larson, 2004). Most probably, multiple events are involved in which DNA damage from exposure to genotoxic stress leads to the secondary abnormalities that cause t-AML (Pedersen-Bjergaard, 2001). A major difference between t-AML and de novo AML is that high doses of mutagenic chemo-/radiotherapy impact on the DNA of haematopoietic stem and precursor cells in the socondary myeloid neoplasms. In contrast, chronic exposure to low doses of occupational/environmental agents over extended periods of time may be operational in the development of high-risk de novo MDS/AML (Sill et al., 2011).
However, these differences are not apparent in all cases and there is a clinical and biological overlap between t-AML and high-risk de novo myelodysplastic syndromes and acute myeloid leukaemia suggesting similar mechanisms of leukaemogenesis. Recently, similarities in therapy-related and elderly acute myeloid leukemia were found in terms of the similar clinical and molecular aspects and unfavorable prognosis. In older individuals prolonged exposure to environmental carcinogens may be the basis for these similarities (D\'Alò et al., 2011). On the other hand, a recently published study reported that AML diagnosed in the past decade in patients after receiving radiotherapy alone differ from therapy-related myeloid neoplasms occurring after cytotoxic chemotherapy/combined-modality therapy and share genetic features and clinical behavior with de novo AML/MDS, suggesting that post-radiotherapy MDS/AML may not represent a direct consequence of radiation toxicity (Nardi et al., 2012). Therefore, other factors might be involved such as genetic variants conferring predisposition to the primary malignacy that may also be of relevance for therapy-related leukaemogenesis and account for subtle biologic differences between t-MNs and high-risk de novo MDS/AML (Sill et al., 2011). Besides, the nature of the causative agent has an important bearing upon the characteristics, biology, time to onset and prognosis of the resultant leukaemia (Joannides & Grimwade, 2010).
Various pathogenetic mechanisms have been elucidated so far and different genetic pathways for the multistep development of t-MDS/t-AML have been proposed, in which particular mechanisms of DNA damage that lead either to chromosomal deletions, balanced translocations or induction of defective DNA-mismatch repair could promote survival of misrepaired cells giving rise to the leukemic clone (Leone at al., 2007). Multiple tumor suppressor genes or oncogenes may need to be mutated to ultimately transform a cell resulting in impaired differentiation of hematopoietic cells and/or in proliferative and survival advantage. Different molecular pathways may cooperate in the genesis of leukemia and at least 8 alternative genetic pathways have been defined based on characteristic recurrent chromosome abnormalities(Pedersen-Bjergaard et al., 2007).
Interestingly, analysis of gene expression in CD34+ cells from patients who developed t-MDS/AML after autologous hematopoietic cell transplantation revealed altered gene expression related to mitochondrial function, metabolism, and hematopoietic regulation and the genetic programs associated with t-MDS/AML are perturbed long before disease onset (Li et al., 2011). Similarly, the gene expression profiles in diagnostic acute lymphoblastic leukemic cells from children treated on protocols that included leukemogenic agents, revealed a signature of 68 probes, corresponding to 63 genes, that was significantly related to risk of t-AML. The distinguishing genes included transcription-related oncogenes (
The comparison of samples from t-AML and de novo AML patients using high resolution array CGH revealed more copy number abnormalities (CNA) in t-AML than in de novo AML cases: 104 CNAs with 63 losses and 41 gains (mean number 3.46 per case) in t-AML, while in de novo-AML, 69 CNAs with 32 losses and 37 gains (mean number of 1.9 per case). The authors suggested that CNA can be classified into several categories: abnormalities common to all AML; those more frequently found in t-AML and those specifically found in de novo AML (Itzhar et al., 2011).
Recently, a growing amount of data suggests that DNA methylation abnormalities may contribute to a multistep secondary leukemogenesis. Two distinct alterations of normal DNA methylation patterns may occur in cancer: (i) a global hypomethylation resulting in chromosomal instability and loss of genetic integrity, and (ii) promoter specific DNA hypermethylation which leads to silencing of tumor suppressor genes. Cytotoxic drugs and radiation have been shown to affect tissue DNA methylation profile. Radiation is able to induce a stable DNA hypomethylation in both target and bystander tissues. Gene promoter methylation is a common finding in t-MDS/AML and has been associated to a shorter latency period from the treatment of the primary tumor. Among the studied genes,
Similarly to de novo AML, therapy-related AMLs comprise an extremely heterogeneous group of biologically different hematologic malignancies and their clinical presentation varies in a significant degree from cases to case, depending on applied chemo- and or radiotherapy for the primary disorder as well as on other factors.
As expected, the most frequent complaints at the presentation of patients with t-AMLs include: fatigue, weakness, and occasionally fever, bleeding complications caused by thrombocytopenia, anemia, and leukopenia. Features that are fairly common in de novo acute leukemia, such as hepatomegaly, splenomegaly, lymphadenopathy, gingival hyperplasia, skin rash, or neurological complications, are notably absent from the presentations of patients with t-MDS/t-AML. Bone marrow biopsies typically reveal hypercellularity with some degree of marrow fibrosis, although hypocellular and even aplastic marrows can be seen (Godley & Le Beau, 2007).
Morphologically, t-AML can present in the broad spectrum of myeloid leukemias. Mostly in patients after previous therapy with alkylating agents multilineage dysplasia can be observed. However, dysplasia can be seen in some patients with balanced translocations as well. Dysgranulopoiesis includes hypogranular neutrophils, with hypo- or hyperlobulated nuclei, nuclear excrescences, and pseudo-Pelger-Huet nuclei. Red cell morphology in most cases is characterised by macrocytosis and poikilocytosis, periodic acid-Schiff-positive normoblasts, dyserythropoiesis with megaloblastoid changes, erythroid hyperplasia, ringed sideroblasts, nuclear budding, karyorrhexis, binuclearity, and nuclear bridging. Megakaryocyte dysplasia within the bone marrow includes micromegakaryocytes, abnormal nuclear spacings, mononuclear forms, giant compound granules, and hypogranular cytoplasm. Cases of therapy-related myeloid neoplasms related to treatment with topoisomerase II inhibitors typically present as overt acute myeloid leukemia without a myelodysplastic prephase. Morphologic features are not unique in therapy-related cases. Although monocytic and monoblastic differentiation is often present, the appearance may be that of de novo cases, including those with recurrent cytogenetic abnormalities (Godley & Le Beau, 2007; Vardiman et al., 2008).
Immunophenotypic studies are not used to distinguish t-AML from de novo cases but rather to clarify abnormal populations, reflecting the heterogeinety of the underlying morphology. The phenotype findings are similar to their de novo counterparts. The myeloblasts are characteristically CD34-positive and express pan-myeloid markers (CD13, CD33) and flow cytometry may be helpful in assessing the proportion of myeloid blasts, as well as aberrant antigenic expression, such as CD7, CD56, CD19, etc. Immunophenotypic maturation patterns of the myeloid and erythroid lineages may also be evaluated. The maturing myeloid cells may show abnormal patterns of antigen expression and/or light scatter properties. However, the relevance of such findings is similar to that in de novo cases (Wood B., 2007; Vardiman et al., 2008).
Clinical and laboratory features of patients with t-AML with recurrent genetic abnormalities have been of particular interest. In some studies, hematologic characteristics of patients with t-AML with t(8;21) and inv(16), are identical to those of de novo AML with the same karyotypes (Quesnel et al., 1993). Simmilarly, according to Duffield et al., 2012, t-APL and de novo APL had abnormal promyelocytes with similar morphologic and immunophenotypic features, comparable cytogenetic findings, and comparable rates of FMS-like tyrosine kinase mutations (Duffield et al., 2012). Interestingly, compared with patients with t-APL, those with de novo APL had a greater median body mass index-BMI (31.33 vs. 28.48), incidence of obesity (60.4% vs. 27.3%), and history of hyperlipidemia (45.3% vs. 18.2%), suggesting that abnormalities in lipid homeostasis may in some way be of pathogenic importance in de novo APL (Elliott et al., 2012). t-AML-t(8;21) shares many features with de novo AML-t(8;21)(q22;q22), however patients with t-AML-t(8;21) are older and had a lower WBC count, substantial morphologic dysplasia, Auer rods are detected only certain patients, an increase in eosinophils is uncommon (Gustafson et al., 2009). The detection of morphologic features characteristic of t(8;21) with associated multilineage dysplasia is fairly unique to t(8;21) t-AML/MDS (Arber et al., 2002). Despite that, some studies reported that t-AML/MDS with t(8;21) may have a high frequency of expression of CD19 and CD34 (Arber et al., 2002), this was not confirmed by others (Gustafson et al., 2009).
Rearrangements involving the
\n\t\t\t\t | \n\t\t\tGIMEMA 2001 n=127 | \n\t\t\t\n\t\t\t\t | \n\t\t\tSerbia 2012 n=42 | \n\t\t\tOur data 2012 n=26 | \n\t\t\tDe novo AML, 2011 n= 2653 | \n\t\t
Age – mean (range) years | \n\t\t\t58 (21-87) | \n\t\t\t57.8 (18.6-79.4) | \n\t\t\t56.07 (23-84) | \n\t\t\t53.5 (22-83) | \n\t\t\t53.2 (16.2-85) | \n\t\t
Male %/female % | \n\t\t\t44/56 | \n\t\t\t32/68 | \n\t\t\t29/71 | \n\t\t\t46/54 | \n\t\t\t53/47 | \n\t\t
Latency median (range) months | \n\t\t\t52 (2-379) | \n\t\t\t48.5 (4-530) | \n\t\t\t54.62 (6-243) | \n\t\t\t48 (3-216) | \n\t\t\tNA | \n\t\t
WBC – mean x109/L | \n\t\t\t6.7 | \n\t\t\t7.4 | \n\t\t\t27.2 | \n\t\t\t24.4 | \n\t\t\t12.5 | \n\t\t
CR rate % | \n\t\t\t55 | \n\t\t\t63 | \n\t\t\t23.8 | \n\t\t\t42 | \n\t\t\t67 | \n\t\t
Median OS months | \n\t\t\t7 | \n\t\t\t12 | \n\t\t\t5.94 | \n\t\t\t6 | \n\t\t\t20 | \n\t\t
Reference | \n\t\t\tPagano et al, 2001 | \n\t\t\tKayser et al, 2011 | \n\t\t\tSuvajdžić et al, 2012 | \n\t\t\tBalatzenko et al., 2012 | \n\t\t\tKayser et al, 2011 | \n\t\t
Major clinical data in t-AML patients’ cohorts.
The analysis of 179 t-AML patients from the GIMEMA Archive of Adult Acute Leukaemia, including 41 treated with surgery only, allowed for the distinction of some differences compared to de novo AML cases. The median age of t-AML was significantly higher than that of other AML (63 years vs. 57 years), the number of men was significantly lower than the number of women [4.8% vs. 7.4%) most probably due to the high incidence in breast cancer patients; as was the number of patients aged <65 years [5.3% vs. 7.5%]. Interestingly, an increased incidence of cancer was observed among first-degree relatives of patients with AML occurring after a primary malignancy [36.9% vs. 27.2% in de novo AML]. Prevalent types of primary malignancies were breast cancer, lymphoma and Hodgkin\'s disease (Pagano et al., 2001). Higher WBC count and females predominance in t-AML had also been observed by others (Schoch et al., 2004).
It is widely accepted, that the spectrum of chromosome aberrations is comparable in t-AML and de novo AML, however the frequencies of distinct cytogenetic categories is different depending on the characteristics of the analyzed patient cohort (reviewed in Schoch et al., 2004). Two are the most striking features of t-AML: the extremely high frequency of abnormal clonal karyotype up to 75%-96% compared to 50%-59% in de novo AML (Schoch et al., 2004; Godley & Larson, 2008; Grimwade et al., 2010; Mauritzson et al., 2002); and a clear predominance of unfavorable cytogenetics, such as deletion or loss of chromosomes 5 and/or 7 or a complex karyotype (Godley & Larson, 2008). However, the frequency and the spectrum of abnormal karyotypes varies depending on the nature of the applied antecedent anti-neoplastic therapy (Rund et al., 2004).
Unbalanced chromosome aberrations such as abnormalities of chromosomes 5 and/or 7 account for 76% of the cases with an abnormal karyotype.Complex karyotypes are seen in 26.9% of t-AML as compared to 11.30% of de novo AML (Schoch et al., 2004). Recurring balanced rearrangements account for 11% of cases (Larson & Le Beau, 2005), with a specific over-presentation of 11q23 abnormalities – 12.9% vs. 3.7% in de novo AML (Schoch et al., 2004). Comparative data on chromosome/molecular aberrations in t-AML and de novo AML are presented in Table 4.
Generally, t-AMLs with unbalanced chromosome abnormalities are developed after exposure to alkylating agents and/or ionizing radiation. This group is considered as a biologically distinct form and the most frequent type of t-AML accounting for approximately 75% of cases. The disease usually follows a long period of latency generally occuring 5–10 years after the drug exposure and is characterized frequently by a preleukemic phase and tri-lineage dysplasia. Typical cytogenetical aberrations comprise loss or deletion of chromosome 5 and/or 7 [-5/del(5q), -7/del(7q)]. Frequently, abnormalities of chromosome 5 are part of a complex karyotype, that additionally includes trisomy 8, as well as loss of 12p, 13q, 16q22, 17p (
The complex and hypodiploid karyotypes with unbalanced chromosome changes results in multiple severe molecular abnormalities with a gene-dosage effect for some of the genes that depend on the nature of the primary chromosome aberration. The loss of the coding regions for tumor suppressor genes from hematopoietic progenitor cells is a particularly unfavorable event, since the remaining allele becomes susceptible to inactivating mutations leading to the leukemic transformation (Leone et al., 2001; Joannides & Grimwade, 2011).
Interestingly, significant proportion of older patients are diagnosed with leukaemia with no antecedent history of exposure, and some of these cases show a remarkably similar phenotype to classic therapy-related leukaemia (D\'Alò et al., 2011). The specific cytogenetic abnormalities common to MDS, alkylating-agent-related AML and poor-prognosis AML [3q-, -5/5q-, -7/7q-, +8, +9, 11q-, 12p-, -18, -19, 20q-, +21, t(1;7), t(2;11)], probably reflect a common pathogenesis distinct from that of other de novo AMLs. Possibly, tumour suppressor genes are implicated and genomic instability may be a cause of multiple unbalanced chromosomal translocations or deletions. Typically, these patients are either elderly or have a history of exposure to alkylating agents or environmental exposure 5-7 years prior to diagnosis (Dann & Rowe, 2001).
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\t1.5% | \n\t\t\t6% | \n\t\t
\n\t\t\t\t | \n\t\t\t7% - 15% | \n\t\t\t0 – 6% | \n\t\t
\n\t\t\t\t | \n\t\t\t2% - 5% | \n\t\t\t1% - 4% | \n\t\t
\n\t\t\t\t | \n\t\t\t18% - 22% | \n\t\t\t16% | \n\t\t
\n\t\t\t\t | \n\t\t\t22% - 35% | \n\t\t\t7% - 12% | \n\t\t
\n\t\t\t\t | \n\t\t\t5% - 8% | \n\t\t\t2% - 2.5% | \n\t\t
\n\t\t\t\t | \n\t\t\t17% - 33% | \n\t\t\t3% -12% | \n\t\t
Inv(16)/t(16;16) / | \n\t\t\t4% - 6% | \n\t\t\t1% - 8% | \n\t\t
Inv(3)/t(3;3) / EVI1 | \n\t\t\t1% - 2% | \n\t\t\t0.2% - 1% | \n\t\t
\n\t\t\t\t | \n\t\t\tRare | \n\t\t\tRare | \n\t\t
\n\t\t\t\t | \n\t\t\t6% | \n\t\t\t2% - 4% | \n\t\t
\n\t\t\t\t | \n\t\t\t19% - 35% | \n\t\t\t12% - 16% | \n\t\t
\n\t\t\t\t | \n\t\t\t6% - 10% | \n\t\t\t11% - 12% | \n\t\t
\n\t\t\t\t | \n\t\t\t3% - 5% | \n\t\t\t4.% | \n\t\t
\n\t\t\t\t | \n\t\t\t5% - 10% | \n\t\t\t4% - 9% | \n\t\t
t(15;17) / | \n\t\t\t4% - 11% | \n\t\t\t2% - 3% | \n\t\t
t(8;21) / | \n\t\t\t5% - 9% | \n\t\t\t2% - 5% | \n\t\t
t(9;11) / | \n\t\t\t1% - 2% | \n\t\t\t6% - 11% | \n\t\t
t(v;11)(v;q23) / | \n\t\t\t2% - 4% | \n\t\t\t4% - 12% | \n\t\t
\n\t\t\t\t | \n\t\t\t8% - 13% | \n\t\t\t9% | \n\t\t
\n\t\t\t\t | \n\t\t\t10-15% | \n\t\t\t18% - 25% | \n\t\t
\n\t\t\t\t | \n\t\t\t4% - 7% | \n\t\t\t17% | \n\t\t
Chromosome and molecular abnornalities in t-AML compared to de novo AML.
References: Abbas et al., 2010; Ahmad et al., 2009; Bacher et al., 2011; Bacher et al., 2007; Christiansen et al., 2005; Christiansen et al., 2004; Christiansen et al.,2007; Fried et al., 2012; Gaidzik et al., 2011; Green et al., 2010; Kayser et al., 2011; Kosmider et al., 2011; Lee et al., 2004; Lin et al., 2005; Marcucci et al., 2010; Mauritzson et al., 2002; Paschka et al., 2010; Pedersen-Bjergaard et al., 2008; Preudhomme et al., 2002; Shen et al., 2011; Takahashi et al., 2000; Thiede et al., 2002; Westman et al., 2011.
The critical genetic consequences of unbalanced chromosome aberrations in MDS and AML have remained unknown (Pedersen-Bjergaard et al., 2007). The genetic consequences of a deletion may be a reduction in the level of one or more critical gene products (haploinsufficiency), or complete loss of function. The latter model, known as the “two-hit model”, predicts that loss of function of both alleles of the target gene would occur, in one instance through a detectable chromosomal loss or deletion and, in the other, as a result of a subtle inactivating mutation, or other mechanisms, such as transcriptional silencing. However, the respective genes on the “intact copy” seem to be not affected, since no submicroscopic deletions or mutations of the remaining allele in any of the genes within the commonly deleted segment (CDS) were detected (reviewed in Le Beau & Olney, 2009). Therefore, most probably loss of only a single copy of a relevant gene (haploinsufficiency) perturbs cell fate. Deletions of putative tumor suppressor genes at chromosomes 5q and 7q are believed to underlie the molecular pathogenesis of alkylating agent- related leukemias. Since similar aberrations occur in de novo MDS/AML, knowledge on potential regions of involvement at chromosomes 5q and 7q derives from de novo and treatment-related cases, but the specific genes in these regions that are important in leukemia pathogenesis continue to remain elusive (Jerez et al., 2011).
On chromosome 5q, two CDSs were identified in 5q31.2 (de novo and t-MDS/t-AML) and 5q33.1 (in 5q− syndrome). The 970 kb CDS within 5q31.2 comprises 20 genes that encoded proteins that take part in regulation of mitosis and G2 checkpoint, transcriptional control, and translational regulation. The second 1.5 Mb CDS is located within 5q33.1, distal to the CDS in 5q31.2 and contains 40 genes, 33 of which are expressed within the CD34+ hematopoietic stem/progenitor cell compartment cells and, therefore, represent candidate genes (Boultwood et al., 2002).The genes that might be involved in leukemogenesis due to gene dosage effect include
Monosomy 7 and del(7q) occur in a variety of clinical contexts including de novo MDS and AML, leukemias associated with a constitutional predisposition, and therapy-related MDS or AML (Luna-Fineman et al., 1995). Several regions with allelic loss were identified in patients with 7q deletions, including entire regions from chromosome 7q22 to 7q31, 7q32-7q35, etc. (Kratz et al., 2001; Le Beau et al., 1996; Dohner et al.,1998). Besides, case analysis of allelic loss at 7q31 and 7q22 loci revealed retention of sequences between these loci or submicroscopic allele imbalance for a different distal locus, suggesting that multiple distinct critical chromosme7q genes are involved in MDS and AML.
Critical genes affected by monosomy 7 and del(7q) are still unknown. Several candidate genes have been suggested as involved in leukemogenesis.
Deletions of chromosome band 17p13 or loss of a whole chromosome 17 harboring the
Application of multicolor fluorescence in situ hybridization (M-FISH) allows better identification of chromosome abnormalities compared to G-banding. A clustering of breakpoints was observed in the centromeric or pericentromeric region of chromosomes 1, 5, 7, 13, 17, 21, and 22 in almost 50% of patients with t-MDS and t-AML and an abnormal karyotype. In most of the patients with chromosome derivatives containing material from 3 or more chromosomes or having “sandwich-like” chromosomes, those made up of several small interchanging layers of material from two chromosomes, showed mutations of
In some patients treated with alkylating agents an amplification or duplication of
Balanced chromosome translocations and inversions have been found in 10.6% of t-AML. These types of aberrations are observed most commonly in patients treated with agents targeting topoisomerase II. Other typical features of t-AML with balances chromosome abnormalities comprise presentation of the disease as an overt leukemia without a myelodysplastic phase and a short latency period (6–36 months). The formation of these chromosome abnormalities is considered as a result of multiple DNA strand breaks following the topoisomerase II inhibitors. Generally, chromosomal breakpoints have been found to be preferential sites of topoisomerase II cleavage that seems to be repaired by the nonhomologous end-joining DNA repair pathway to generate chimaeric oncoproteins that underlie the resultant leukaemias (Joannides & Grimwade, 2010).
Most often, chromosome translocations involve chromosome bands 11q23 or 21q22 with rearrangement of the
It seems, that an association between the nature of the applied drug and the type of translocation exists, since translocations involving 11q23 are more frequent after treatment with epipodophyllotoxins, whereas translocations affecting 21q22, inv(16), and t(15;17) are more common after anthracyclines (Andersen et al., 1998). Other less common, recurrent, balanced cytogenetic abnormalities occurring in myeloid neoplasms associated with previous therapy include 3q21q26, 11p15, t(9;22)(q34;q11), 12p13, and t(8;16)(p11;p13) (Czader et al., 2009).
Recently, translocations involving the
Generally, the recurrent balanced chromosome aberrations lead to the formation of fusion genes, with the participation of hematopoietic transcription factors genes, that encode himeric oncoproteins playing a crtical role in leukemogenesis.
Translocations involving chromosome 11q23, where the
T-AML with balanced 21q22 aberrations has been associated with prior exposure to radiation, epipodophyllotoxins, and anthracyclines. Translocations involving chromosome 21q22 comprise multiple abnormalities, presented as t(8;21) (56%), t(3;21) (20%), and t(16;21) (5%) (Slovak et al., 2002), t(1;21)/
The
A relatively distinct subgroup of t-AML comprises patients bearing “favorable” cytogenetic abnormalities, such as inv(16) and t(15;17) (Andersen MK et al. 2002), and more rarely – t(8;21) (Gustafson et al., 2009). These aberrations have been observed after alkylating agents and/or topoisomerase II inhibitors. High frequency of t(15;17), inv(16) and t(8;21) (18-29%, 21%, and 15% respectively) has also been reported in patients treated with radiotherapy only (Andersen et al., 2002; Yin et al., 2005).
The median latency period after the treatment is 22 months in patients with inv(16), 29 months in patients with t(15;17) and 37 months in patients with t(8;21). More than half of the cases in each group had additional cytogenetic abnormalities. Trisomy of chromosomes 8, 21, 22 and del(7q) are the most frequent additional abnormalities in the inv(16) subgroup, whereas trisomy 8, monosomy 5, and del(16q) are most frequent in the t(15;17) subgroup. Additional abnormalities commonly associated with t(8;21) include loss of a sex chromosome and Trisomy 4 (Andersen et al., 2002; Gustafson et al., 2009; Yin et al., 2005).
Interestingly, some structural differences were observed between patients positive for these aberrations with de novo AML and t-AML.In t-AML with inv(16)/t(16;16), the unusual rare types of fusion
In therapy related t(15;17) APL, a prevalence of short form of
As to
On the other hand, almost all chromosome translocations in leukemia that have been analyzed to date show no consistent homologous sequences at the breakpoint with small deletions and duplications in each breakpoint, and micro-homologies and non-template insertions at genomic junctions of each chromosome translocation. The size of these deletions and duplications in the same translocation is much larger in de novo leukemia than in therapy-related leukemia (Zhang & Rowley, 2006).
Several molecular abnormalities were identified in both de novo AML and t-AML that are not a result of chromosome abnormalities, including mainly point mutations and gene tandem duplications. Significant differences in frequency of some of them were reported in t-AML.
Internal tandem duplications (ITD) and point mutations within the tyrosine kinase domain (TKD) of the FMS-like tyrosine kinase 3 (
In contrast, higher incidence in t-AML was reported for
Point mutations in the
To study the frequency and spectrum of molecular abnormalities with a proven or suggestive role in leukemic transformation in patients with t-AML we analysed 407 consecutive adult AML patients, diagnosed and treated in our institution, for a 12-years period. Among them, 26 cases had history for a previous malignancy treated with chemotherapy and/or radiotherapy which accounts for 6,1% of the cases – 12 (46%) males and 14 (54%) females, at a mean age of 53.5 years (ranging 22-83 years).AML was diagnosed after radio and/or chemotherapy for solid tumours in 16 (61.5%) of the patients and haematopoietic neoplasms – in 10 (38.5%). Qualitative, semi-quantitative or quantitative real-time Reverse transcription polymerase chain reaction (RT-PCR) was applied in all patients for screening of molecular abnormalities, as follows: (i) fusion transcripts
Eight of the patients (30.8%) beared “favourable” fusion transcripts
According to the model proposed by Deguchi & Gilliland (2002), development of AML is the consequence of collaboration between at least two broad classes of mutations: (i) class I mutations which result in constitutively activated tyrosine kinases (gain of function) and confer a proliferative and/or survival advantage without affecting differentiation -
At least 14 different genes have been identified as mutated in t-MDS and t-AML, clustering differently and characteristically in the eight genetic pathways. Class I and Class II mutations are significantly associated, indicating their cooperation in leukemogenesis (Pedersen-Bjergaard et al., 2007). Several examples of such cooperative genetic alterations were reported.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
I n=8 30.8% | \n\t\t\t52/m | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t
62/f | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
49/f | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
23/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t|
27/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
72/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
28/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
22/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
II n=7 26.9% \n\t\t\t | \n\t\t\t67/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t
48/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t|
65/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
50/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
30/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t|
57/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
82/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
III n=11 42.3% \n\t\t\t | \n\t\t\t57/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\tN | \n\t\t\t0 | \n\t\t\t0 | \n\t\t
83/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
74/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\tN | \n\t\t|
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67/f | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t\t1 | \n\t\t\t0 | \n\t\t\t1 | \n\t\t|
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68/m | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\tN | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t\t0 | \n\t\t|
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\n\t\t\t\t | \n\t\t\t0% | \n\t\t\t11.5% | \n\t\t\t11.5% | \n\t\t\t7.7% | \n\t\t\t3.8% | \n\t\t\t0% | \n\t\t\t11.5% | \n\t\t\t7.7% | \n\t\t\t0% | \n\t\t\t23.1% | \n\t\t\t26.9% | \n\t\t\t24.0% | \n\t\t\t15.4% | \n\t\t\t61.5% | \n\t\t\t48.0% | \n\t\t\t0% | \n\t\t\t16% | \n\t\t
Molecular alterations in therapy-related acute myeloid leukemias. Group I - patients with “favourable” fusion transcripts, Group II - patients with overexpression of multiple “unfavourable” genes, Group III - patients without a specific pattern. Abreviations: f – female, m – male, N – not done.
Mutations of
The diagnosis of therapy-related myeloid leukemia (t-MDS/t-AML) identifies a group of high-risk patients with multiple and varied poor prognostic features (Larson, 2007), such as overrepresentation of 11q23 translocations, adverse cytogenetics, including complex and monosomal karyotypes, and
Encouraging results were reported after allogeneic hematopoietic stem cells transplantation (allo-HSCT). The follow-up of 461 patients with t-MDS or t-AML who underwent allo-HSCT detected 3-year RFS and OS rates of 33% and 35%, respectively. In a multivariate analysis, the following risk factors were identified: (1) not being in complete remission at the time of transplantation, (2) abnormal cytogenetics, (3) higher patients\' age and (4) therapy-related MDS. Using age (<40 years), abnormal cytogenetics and not being in complete remission at the time of transplantation as risk factors, three different risk groups with OS of 62%, 33% and 24% could be easily distinguished (Kröger et al., 2009). Similar results were observed by Litzow et al., 2010. The analysis of outcomes in a total of 868 patients, including t-AML (n=545) or t-MDS (n=323), revealed disease-free (DFS) and OS of 32% and 37% at 1 year and 21% and 22% at 5 years, respectively. In a multivariate analysis, 4 risk factors with adverse impacts on DFS and OS were identified: (1) age older than 35 years; (2) poor-risk cytogenetics; (3) t-AML not in remission or advanced t-MDS; and (4) donor other than an HLA-identical sibling or a partially or well-matched unrelated donor. The 5-years survival for subjects with none, 1, 2, 3, or 4 of these risk factors was 50%, 26%, 21%, 10%, and 4%, respectively [Litzow et al.,2010].
T-AMLs with “favorable” genetic abnormalities involving CBF-transcription complex - t(8;21)/
According to some studies these patients have treatment outcome comparable with primary AML patients (de Witte et al., 2002). Complete remission can be obtained in 85% of intensively treated patients with inv(16), and in 69% with t(15;17), with a median OS of 29 months in both cytogenetic subgroups, thus the response rates to intensive chemotherapy are comparable to those of de novo disease (Andersen et al., 2002). Similarly, t-AML with t(15;17) and t(8;21), treated according to standard protocols, had an outcome similar to de novo cases, indicating the dominant prognostic role of good karyotypes (D\'Alò et al., 2011). The comparison of clinical and pathologic findings in therapy-related APL and de novo APL cases revealed abnormal promyelocytes with similar morphologic and immunophenotypic features, comparable cytogenetic findings, comparable rates of FMS-like tyrosine kinase mutations, and similar rates of recurrent disease and death, suggesting that secondary APL is similar to de novo APL and, thus, should be considered distinct from other secondary acute myeloid neoplasms (Duffield et al., 2012).
In contrast, matched analysis (by age, Eastern Cooperative Oncology Group performance status, and additional cytogenetic abnormalities) indicated worse OS and event-free survival (EFS) in patients with therapy-related CBF AML carrying the recurrent chromosomal aberrations inv(16) or t(8;21) – a median OS of 100 weeks compared to 376 weeks in de novo CBF AMLs (Borthakuret al., 2009). In patients with t-AML and t(8;21), the OS is significantly inferior to that of patients with de novo t(8;21) AMLs (19 months vs not reached). These findings suggest that t(8;21) t-AMLs share many features with de novo AML with t(8;21)(q22;q22), but the affected patients have a worse outcome (Gustafson et al., 2009). Interstingly, it has been reported recently that despite that fewer complete remissions are achieved in t-APL (63.6%) compared to de novo APL (92.5%), this was a result of the higher induction mortality rate of 36.4% vs. 7.5%, respectively. No cases of leukemic resistance were seen in either group. However, OS was also inferior in t-APL compared to de novo APL (51% vs. 84%, respectively) (Elliott et al., 2012).
The survival of patients with t-AML is often poor despite prompt diagnosis and treatment. There is a paucity of prospective treatment data since these patients are often excluded from frontline chemotherapy trials and turned to best supportive care. However, despite that the CR rate of t-AML patients (28% up to 50%) has been demonstrated to be inferior to patients with de novo AML (65-80%), this difference can be attributed to the higher number of patients with unfavourable karyotypes. Within cytogenetically defined subgroups, the prognosis of t-AML patients does not differ significantly from patients with de novo AML. Treatment recommendations should be further based on the patient’s performance status, which likely reflects age, comorbidities, the status of the primary disease, and the presence of complications from primary therapy, as well as the clonal abnormalities detected in the t-AML cells. Standard chemotherapy, haematopoietic stem cell transplantation, as well as experimental trials are applied.
Clinical algorythm in the management of t-AML patients.
Intriguingly, several studies found that results after induction therapy were not different between t-AML and de novo AML patients. Furthermore, analyses of CR-rates, OS and DFS, when corrected for the influence of age, cytogenetic abnormalities, performance status and leucocyte count, showed that the presence of a t-AML may even lose prognostic significance and patients with secondary AML should be offered the chance of benefiting from treatment according to current frontline AML protocols (Ostgård et al., 2010). The dosage and modality of treatment during postremission therapy however have a marked impact on the cumulative toxicity of cancer therapy. Therefore, intensive induction therapy should not be withheld for t-AML patients, and dose-reduced regimes for allogeneic HSCT should be considered. In contrast, t-AML patients >60 years show a significantly greater relapse rates probably due to the lower dosage of applied chemotherapy during postremission therapy compared with younger patients (Kayser et al., 2011). Encouraging results are reported after allogeneic transplantation. The identification of relevant risk factors allows for a more precise prediction of outcome and identification of subjects most likely to benefit from allogeneic transplantation.Allogeneic transplantation should be proposed timely to these patients after an accurate analysis of patient history (Litzow et al., 2010; Spina et al., 2012). Novel transplantation strategies using reduced intensity conditioning regimens as well as novel drugs – demethylating agents and targeted therapies, await clinical testing and may improve outcome (de Witte et al., 2002).
As the number of patients with t-AMLs is expected to rise, safety issues of cytotoxic therapies are becoming increasingly important in order to develop strategies to reduce the risk for therapy-related malignancies without compromising success rates for the respective primary disorders. Besides, there is clinical and biological overlap between therapy related and high-risk de novo leukaemias suggesting similar mechanisms of leukaemogenesis. Deeper insights into pathogenetic mechanisms will eventually help to establish a more differentiated clinical approach to successfully treat, but hopefully also prevent, these often fatal consequences of cytotoxic therapies.
The reported own data on therapy-related AML were generated in the Center of Excellence “Translational Research in Haematology” of the National Specialised Hospital for Active Treatment of Hematological Diseases, supported by National Science Fund (grant CVP01-119/D02-35/2009), as follows: morphology and immunophenotype were evaluated at the Laboratory of Haematopathology and Immunology, cytogenetic and molecular studies were performed at the Laboratory of Cytogenetics and Molecular Biology, clinical management was performed at the Haematology Clinic. MG and GB contributed equally to the development of the manuscript. GM was responsible for the treatment section. MG and GB have been supported by EuGESMA COST Action BM0801: European Genetic and Epigenetic Study on AML and MDS.