Cancer: From Genomics to Pharmaceutics

142 THE ROLE OF MIRNAS IN CONTROL OF K-RAS GENE EXPRESSIONmiRNAs as diagnostic and prognostic markers. Clin Chem Lab Med 2019; 57(7):932-953.8. Pisarello MJL, Loarca L, Ivanics T, Morton L, LaRusso N. MicroRNAs in thecholangiopathies: Pathogenesis, diagnosis, and treatment. J Clin Med 2015;4(9):1688-1712.9. Ha M, Kim VN. Regulation of microRNA biogenesis. Nat Rev Mol Cell Biol.2014;15(8): 509-524.10. Yi R, Qin Y, Macara IG, Cullen BR. Exportin5 mediates the nuclear export ofpre-microRNAs and short hair pin RNAs. Genes Dev 2003;17(24):3011–3016.11. Filipowicz W, Bhattacharyya SN, Sonenberg N. Mechanisms of post-transcriptionalregulation by microRNAs: are the answers in sight? Nat Rev Genet 2008;9(2): 102-114.12. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines,indicates that thousands of human genes are microRNA targets. Cell 2005; 120(1):15-20.13. Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer 2006;6(11): 857-866.14. Wiemer EAC. The role of microRNAs in cancer: No small matter. Eur J Cancer2007;43(10): 1529-1544.15. Calin GA, Sevignani C, Dumitru D, Hyslop T, Noch E, Yendamuri S, et al. HumanmicroRNA genes are frequently located at fragile sites and genomic regions involved incancers. Proc Natl Acad Sci U S A 2004; 101(9): 2999-3004.16. Cimmino A, Calin GA, Fabbri M, Iorio MV, Ferracin M, Shimizu M, et al. miR-15 andmiR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci U S A 2006;103(7):2464-2464.17. He L, Thomson JM, Hemann MT, Hernando-Monge E, Mu D, Goodson S, et al.A microRNA polycistron as a potential human oncogene. Nature 2005;435(7043):828-833.18. Mendell JT. miRiad roles for the miR-17-92 cluster in development and disease. Cell2008; 133(2): 217-222.19. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, et al. MicroRNAexpression profiles classify human cancers. Nature 2005; 435(7043): 834-838.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

B¨us¸ra KURT GULTAS¸LAR, Ebru Esin Y ¨ OR¨ UKER ¨ 14320. Volinia S, Calin GA, Liu CG, Ambs S, Cimmino A Petrocca F, et al. A microRNAexpression signature of human solid tumors defines cancer gene targets. Proc Natl AcadSci U S A 2006; 103(7): 2257-2261.21. Lu JL, Deutsch C. Folding zones inside the ribosomal exit tunnel. Nat Struct and MolBiol 2005;12(12): 1123-1129.22. Png KJ, Halberg N, Yoshida M, Tavazoie SF. A microRNA regulon that mediatesendothelial recruitment and metastasis by cancer cells. Nature 2011;481(7380): 90-194.23. Wang B, Zhang Q. The expression and clinical significance of circulating microRNA-21in serum of five solid tumors. J Cancer Res Clin Oncol 2012;138:1659-1666.24. Pan XA, Wang ZX, Wang R. MicroRNA-21 A novel therapeutic target in human cancer.Cancer Biol Ther 2010;10(12): 1224-1232.25. Tsuchida N, Ryder T, Ohtsubo E. Nucleotide-Sequence of the Oncogene Encoding theP21 Transforming Protein of Kirsten Murine Sarcoma-Virus. Science 1982;217(4563):937-939.26. Kranenburg O. The K-RAS oncogene: Past, present, and future. Biochimica EtBiophysica Acta-Reviews on Cancer 2005;1756(2): 81-82.27. Yun JY, Rago C, Cheong I, Pagliarini R, Angenendt P, Rajagopalan H, et al. GlucoseDeprivation Contributes to the Development of K-RAS Pathway Mutations in TumorCells. Science 2009; 325(5947): 1555-1559.28. Ryan MB, Corcoran RB. Therapeutic strategies to target RAS-mutant cancers. Nat RevClin Oncol 2018;15(11): 709-720.29. Misale S, Yaeger R, Hobor S, Scala E, Janakiraman M, Liska D, et al. Emergence ofK-RAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer.Nature 2012; 486(7404): 532-536.30. Rosty C, Young JP, Walsh MD, Clendenning M, Walters RJ, Pearson S, et al. Colorectalcarcinomas with K-RAS mutation are associated with distinctive morphological andmolecular features. Mod Pathol 2013;26(6): 825-834.31. Raponi M, Winkler H, Dracopoli NC. K-RAS mutations predict response to EGFRinhibitors. Curr Opin Pharmaco 2008; 8(4): 413-418.32. McCormick F. Progress in targeting RAS with small molecule drugs. BiochemicalJournal 2019;476: 65-374.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

144 THE ROLE OF MIRNAS IN CONTROL OF K-RAS GENE EXPRESSION33. Zafra, MP, Parsons MJ, Kim J, Curbelo DA, Goswami S, Schatoff EM, et al. An InVivo Kras Allelic Series Reveals Distinct Phenotypes of Common Oncogenic Variants.Cancer Discov 2020; 10: 1654–1671.34. Chen X, Guo X, Zhang H, Xiang Y, Chen J, Yin Y, et al. Role of miR-143 targetingK-RAS in colorectal tumorigenesis. Oncogene 2009;28(10):1385-1392.35. Kent OA, Chivukula RR, Mullendore M, Wentzel EA, Feldmann G, Lee KH, et al.Repression of the miR-143/145 cluster by oncogenic Ras initiates a tumor-promotingfeed-forward pathway. Genes Dev 2010;24(24): 2754-2759.36. Iliopoulos, D, Rotem A, Struhl K. Inhibition of miR-193a Expression by Max andRXR alpha Activates K-RAS and PLAU to Mediate Distinct Aspects of CellularTransformation. Cancer Res 2011;71(15): 5144-5153.37. Rodriguez-Aguayo C, Monroig PC, Redis RS, Bayraktar E, Almeida MI, Ivan C,et al. Regulation of hnRNPA1 by microRNAs controls the miR-18a-K-RAS axis inchemotherapy-resistant ovarian cancer. Ann Oncol 2018. 29.38. Gong, B., W.W. Liu, W.J. Nie, D.F. Li, Z.J. Xie, C. Liu, et al., MiR-21/RASA1 axisaffects malignancy of colon cancer cells via RAS pathways. Cell Discov 2017;3: 17029.39. Edmonds MD, Boyd KL, Moyo TK, Mitra R, Duszynski RJ, Arrate MP, et al.MicroRNA-31 initiates lung tumorigenesis and promotes mutant K-RAS-driven lungcancer. J Clin Invest 2016;126(1):349-64.40. Kent OA, Mendell JT, Rottapel R., Transcriptional Regulation of miR-31 by OncogenicK-RAS Mediates Metastatic Phenotypes by Repressing RASA1. Mol Cancer Res 2016;14(3): 267-277.41. Xiao W, Wang XG, Wang T, Xing JC. MiR-223-3p promotes cell proliferation andmetastasis by downregulating SLC4A4 in clear cell renal cell carcinoma. Aging-Us2019;11(2): 615-633.42. Ota T, Doi K, Fujimoto T, Tanaka Y, Ogawa M, Matsuzaki H, et al. K-RAS Up-regulatesthe Expression of miR-181a, miR-200c and miR-210 in a Three-dimensional-specificManner in DLD-1 Colorectal Cancer Cells. Anticancer Res 2012; 32(6): 2271-2275.43. Shin KH, Bae SD, Hong HS, Kim RH, Kang MK, Park NH. miR-181a shows tumorsuppressive effect against oral squamous cell carcinoma cells by downregulating K-RAS.Biochem Biophys Res Commun 2011;(4): 896-902.44. Shi L, Middleton J, Jeon YJ, Magee P, Veneziano D, Lagana A, et al. K-RAS induceslung tumorigenesis through microRNAs modulation. Cell Death Dis 2018; 9:219.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

B¨us¸ra KURT GULTAS¸LAR, Ebru Esin Y ¨ OR¨ UKER ¨ 14545. Hiraki M, Nishimura J, Takahashi H, Wu X, Takahashi Y, Miyo M, et al. ConcurrentTargeting of K-RAS and AKT by MiR-4689 Is a Novel Treatment Against Mutant K-RASColorectal Cancer. Mol Ther Nucleic Acids 2015;4:e231.46. Okudela K, Suzuki T, Umeda S, Tateishi Y, Mitsui H, Miyagi Y, et al. Acomprehensive search for microRNAs with expression profiles modulated by oncogenicK-RAS: Potential involvement of miR-31 in lung carcinogenesis. Oncol Rep 2014;32(4):1374-1384.47. Shui B, La Rocca G, Ventura A, Haigis KM. Interplay between K-RAS and miRNAs.Trends Cancer 2022;8(5):384-396.48. Johnson L, Mercer K, Greenbaum D, Bronson RT, Crowley D, Tuveson DA, et al,Somatic activation of the K-RAS oncogene causes early onset lung cancer in mice.Nature 2001; 410(6832): 1111-1116.49. Jackson EL, Willis N, Mercer K, Bronson RT, Crowley D, Montoya R, et al. Analysis oflung tumor initiation and progression using conditional expression of oncogenic K-RAS.Genes Dev 2001;15(24): 3243-3248.50. Hingorani SR, Petricoin EF, Maitra A, Rajapakse V, King C, Jacobetz MA, et al.Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse.Cancer Cell 2004; 5(1): 103-103.51. Braun BS, Tuveson DA, Kong N, Le DT, Kogan SC, Rozmus J, et al. Somatic activationof oncogenic K-RAS in hematopoietic cells initiates a rapidly fatal myeloproliferativedisorder. Proc Natl Acad Sci U S A 2004; 101(2): 597-602.52. Yu SN, Lu ZH, Liu CZ, Meng YX, Ma YH, Zhao WG, et al. miRNA-96 SuppressesK-RAS and Functions as a Tumor Suppressor Gene in Pancreatic Cancer. Cancer Res2010;70(14): 6015-6025.53. Tanic M, Yanowsky K, Rodriguez-Antona C, Andres R, Marquez-Roda I, Osorio A, etal. Deregulated miRNAs in Hereditary Breast Cancer Revealed a Role for miR-30c inRegulating K-RAS Oncogene. Plos One 2012;7(6):e38847.54. Gastaldi C, Bertero T, Xu N, Bourget-Ponzio I, Lebrigand K, Fourre S, et al.miR-193b/365a cluster controls progression of epidermal squamous cell carcinoma.Carcinogenesis 2014; 35(5): 1110-1120.55. Liao WT, Ye YP, Zhang NJ, Li TT, Wang SY, Cui YM, et al. MicroRNA-30b functionsas a tumour suppressor in human colorectal cancer by targeting K-RAS, PIK3CD andBCL2. J Pathol 2014; 232(4): 415-427.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

146 THE ROLE OF MIRNAS IN CONTROL OF K-RAS GENE EXPRESSION56. Kasinski AL, Slack FJ. miRNA-34 Prevents Cancer Initiation and Progressionin a Therapeutically Resistant K-RAS and p53-Induced Mouse Model of LungAdenocarcinoma. Cancer Res 2012;72(21): 5576-5587.57. Morris JP, Greer R, Russ HA, von Figura G, Kim GE, Busch A, et al. Dicer RegulatesDifferentiation and Viability during Mouse Pancreatic Cancer Initiation. Plos One2014;9(5): e95486.58. Chin LJ, Ratner E, Leng SG, Zhai RH, Nallur S, Babar I, et al. A SNP in a let-7 microRNAComplementary Site in the K-RAS 3 ’ Untranslated Region Increases Non-Small CellLung Cancer Risk. Cancer Res 2008;68(20): 8535-8540.59. Kim, M, Chen XW, Chin LJ, Paranjape T, Speed WC, Kidd KK, et al. Extensive sequencevariation in the 3 ’ untranslated region of the K-RAS gene in lung and ovarian cancercases. Cell Cycle 2014;13(6): 1030-1040.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

CANCER: FROM GENOMICS TO PHARMACEUTICSCHAPTER 6GERMLINE PREDISPOSITION TO CHILDHOODCANCERSTugc¸e SUDUTAN ˘1,2, Yucel ERB ¨˙ILG˙IN31Ph.D. Candidate, ˙Istanbul University, Institute of Health Sciences, ˙Istanbul, T¨urkiye2˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Department of Genetics, ˙Istanbul, T¨urkiyeE-mail: [email protected]. Prof., ˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Department of Genetics,˙Istanbul, T¨urkiyeE-mail: [email protected]: 10.26650/B/LSB28LSB48LSB56.2024.019.006ABSTRACTPediatric cancers are rare, yet they are the common cause of cancer-related death in childhood. Childhoodcancer predisposition refers to an increased risk of cancer development at a young age due to inherited mutations orother genetic factors. Recent genomic studies in children and young adults have led to discovery of new pathogenicvariants in previously unknown susceptibility genes that indicate the germline predisposition to cancer has beenunderestimated and more pediatrics and young adults may be affected by cancer predisposition syndromes. Cancerpredisposition syndromes account for approximately 10% of childhood cancers. However, predisposing germlinevariant frequencies are vary between cancer types, ∼ 69% for adrenocortical tumors and ∼ 4% for leukemia.Predisposing germline variant carriers may exhibit distinct characteristics regarding age at manifestation, tumortype, family history, prognostic differences, and therapy toxicity. Recognizing childhood cancer due to germlinepredisposition is important in many ways; to mitigate potential acute toxicities and avoid long-term side effectsof therapy, and possible secondary malignancies, potential use of targeted therapies, prenatal diagnosis and earlydetection of possible carriers of other family members. Genetic testing is a powerful diagnostic tool but also haschallenges and caveats. Both clinical and scientific expertize is essential for evaluating of variants and implicationsof the knowledge in diagnosis and clinical management of patients. In this chapter, we summarized the review of themost common childhood hereditary cancer predisposition malignancies and syndromes.Keywords: Predisposition, cancer, pediatricsCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

148 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERS1. IntroductionCancer is the leading cause of death among children and approximately 400.000 childrenand adolescents (age 0-19) are diagnosed with cancer worldwide every year (1). Optimizedconventional therapies and improved diagnostic procedures have led to an increase in thecure rates of childhood cancer to about 80% in developed countries, but in many low-andmiddle-income countries it is less than 30% (2). Furthermore, in the long term many childrencancer survivors suffer from side effects of therapies such as mental disabilities, toxicities,and secondary cancers (3).The distribution of cancer types and biological characteristics differ among adolescentsand children. Leukemia is the most common cancer in childhood (∼30%), and followedby brain and other nervous system tumors (26%), and soft tissue sarcoma (∼6%). On theother hand, in adolescents, brain and other nervous system tumors are most common (21%)and followed by lymphoma (20%) (2, 4). The cancer etiology between pediatrics and adultsis different. Unlike later-onset cancers, environmental and lifestyle factors can be largelyexcluded in childhood cancers. Despite some chronic infections like HIV, Epstein-Barr virus(EBV) can be counted as a risk factor for childhood cancers, the etiology of childhood cancersis not well understood.Diagnostic of childhood cancers are challenging, and classification of tumors requiresa multistage approach that includes morphological evaluation, immunohistochemistry, andmolecular analysis (4). High-throughput technologies enabled the analysis of cancer genomemore accurately, better classification of molecular subtypes and paved the way to personalizedmedicine. Childhood tumors are typically presented by a block of cell differentiation duringcell type maturation steps. Except for DNA repair deficiencies, childhood cancers harborrelatively lower numbers of somatic mutations than adult cancers. On the other hand, pediatriccancer genomes harbor copy number alterations, gene fusions, and other structural variationssuch as chromoplexy, chromothripsis. In many pediatric cancer driver mutations occur duringthe developmental stage of tumor tissues such as hematopoietic stem cells or muscle stemcells etc. (5). The most common mutant genes in childhood cancers are TP53, APC, BRCA2,NF1, PMS2, RB1, and RUNX1 (6).Recent studies have shown that germline predisposition to cancer is about 10% ofchildhood cancers (5-7). Based on the function of the affected gene, germline geneticvariations including point nucleotide variations, translocations, trisomies, and epigeneticchanges can cause cancer predisposition (8). Several syndromes and malignancies areassociated with cancer in children, such as Li-Fraumeni syndrome (LFS), adrenocorticalcarcinomas, hypodiploid B cell acute lymphoblastic leukemia (B-ALL), retinoblastoma,neurofibromatosis. DNA repair genes; mismatch repair genes MSH2, MSH6, PMS2 anddouble-stranded break repair genes TP53, BRCA2, CHEK2 are the genes that harbour themost known germline cancer susceptibility variants (9). Germline TP53 carriers haveCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 149significantly increased risk of early onset cancer and treatment-induced secondary oncogenes(10). Therefore, germline genetic testing strategies are critical to determine cases withincreased cancer development risk. Although some families may have a history of multiplecancer cases, which indicates an inherited predisposition to cancer, most of the time familyhistory did not reveal a prediction of predisposition syndrome. Earlier diagnosis of cancerpredisposition syndromes (CPS) gives chances for personalized targeted therapies, reducedtoxicity, clinical follow-up, and appropriate genetic counseling for family members.In this chapter, we reviewed childhood CPS by giving the most common examples andhow to approach family with CPS.1.1. Tumors of Hematopoietic and Lymphoid TissuesLeukemia comprises approximately one fourth of all malignancies in children and youngadults (CAYA), with 80% ALL, 15% AML, and 2% CML (4). Hematopathology haspioneered the adoption of newly available molecular techniques and large clinical programswith genomic approaches led to massive accumulation of information on leukemia. DNArepair defects, bone marrow failure disorders, constitutional chromosomal aberrations, andinherited mutations are predisposed to hematological malignancies (11).1.1.1. Predisposition to Acute Lymphoblastic LeukemiaALL is a malignancy with aggressive proliferation of immature lymphocytes in the bonemarrow. ALL cases are characterized with recurrent genetic abnormalities that have prognosticsignificance such as ETV6::RUNX1, TCF3::PBX1 and hyperdiploidy (≻60 chromosomes)is associated with a favorable prognosis, whereas hypodiploidy (≺44 chromosomes),KMT2A rearrangements, and IKZF1 deletions are poor prognostic markers (4). Germlinepredisposition variant frequency in ALL varies according to subtypes. Compared to othercancer, patients with B-ALL have a lower incidence of predisposition variants. Accordingto genome-wide association studies (GWAS) results, common polymorphisms are mostlylocated in hematopoietic transcription factor genes such as ARID5B, IKZF1 and GATA3 andare associated with low-penetrance of ALL susceptibility and limited clinical significance(12). However, harboring more than one of the common variants may increase the risk ofALL development up to 9-fold (13). Besides the common variants, rare germline variationsof TP53, ETV6, IKZF1, PAX5, RUNX1 genes have been reported in families with ALL andprone to develop ALL at a high frequency (14). Germline variants of TP53 are reported in∼65% of childhood hypodiploid B-ALL and discussed under Li-Fraumeni syndrome (LFS).PAX5 is an essential transcription factor for B-cell differentiation, and somatic alterationsincluding translocations, copy number variations, and SNVs are found in ∼30% of ALL.Germline PAX5 p.Gly183Ser/Arg/His missense variants have been associated with familialB-ALL. These families exhibited 9p loss, which causes the retention of the variant PAX5 alleleand CDKN2A (15, 16). Biallelic inactivation of PAX5 is required for leukemic transformationCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

150 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSof the cell, and germline PAX5 p.Gly183Ser alone leads to partial reduction in transcriptionactivity and can be tolerated in germline. Another germline PAX5 variant p.Arg38His wasreported in two families with several B-ALL cases (17, 18). PAX5 p.Arg38His variant wasdetected at an older age of onset with normal karyotype (17).ETV6 is a transcription regulator of platelet development, highly expressed inhematopoietic stem cells and important for hematopoiesis. Somatic alterations of ETV6,including translocations, deletions, and SNVs are common in leukemia and recent studiesindicate it as a general cancer predisposition gene. Decreased expression and monoallelicexpression of ETV6 contribute to leukemia development and germline pathogenic variationsof ETV6 are associated with familial ALL, nonsyndromic genetic disorder ETV6-relatedthrombocytopenia 5, myeloid malignancies and solid tumors (6, 19). Almost all patientswho harbor a pathogenic ETV6 variant also show thrombocytopenia but only 30% of themare diagnosed with a hematological malignancy, especially high hyperdiploid and older agepatients with B-ALL. Therefore, geneting testing for ETV6 should be considered for patientswith unexplained thrombocytopenia and cumulative hematological malignancy history in thefamily.IKZF1 is a zinc finger transcription factor and essential for the lineage commitmentof lymphocytes. IKZF1 encodes IKAROS protein and eight IKAROS isoforms withDNA-binding and non-binding forms have been published. IK6 is a non-DNA-bindingIKAROS isoform that is frequently highly expressed in ALL (12, 14, 20). Somaticinactivating IKZF1 alterations are mostly observed in Philadelphia (Ph) positive or Ph-like andDUX4-rearranged B-ALL. On the other hand, germline IKZF1 variants are observed in ∼1%of B-ALL and are associated with specific immunological phenotypes rather than Ph or Ph-likeALL subtypes. Germline variants of IKZF1 cause impairment of protein function, null ormissense variants in the DNA-binding domain are associated with common variable immunedeficiency, dominant negative variants are associated with combine immune deficiency (CID)and dimerization domain variants are haploinsufficient and associated with ALL (14, 21, 22).For clinical interpretation of germline IKZF1 variants, it should be kept in mind that 30% ofgermline IKZF1 variant carriers are asymptomatic.RUNX1 encodes a transcription factor that plays a role in hematopoietic stem cellsdifferentiation and maturation. Somatic alterations of RUNX1 have been reported in lymphoid(especially T cell lineage) and myeloid leukemia and myelodysplastic syndrome (MDS) (23).Germline RUNX1 variants are detected in familial platelet disorder and thrombocytopenia byleading to aberrant protein activity. These patients mostly developed MDS/AML and lesscommonly ALL. The somatic acquisition of RUNX1, GATA2 or JAK3 variants in additionto germline RUNX1 variants are necessary to drive the malignant transformation of the cells(14). Li et al. screened germline samples of 6190 childhood ALL and identified RUNX1Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 151variants in 1.25% of B-ALL and 1.92% of T-ALL. Furthermore, functional analysis wasrevealed that B-ALL patients were mostly carrying missense variants that were not disruptingprotein function. However, T-ALL patients had truncating RUNX1 variants that caused theloss of function (24). Therefore, germline RUNX1 variant testing can be considered in ALLcases with thrombocytopenia or cumulation of hematological malignancies in families withplatelet defects (14).Germline IKZF1 variants have been associated with decreased drug response but noneof the germline variants of PAX5, RUNX1, ETV6 have been associated with therapy toxicity(22). On the other hand, detection of germline variants in these genes is important for optimaldonor selection when choosing a family donor for hematopoietic stem cell transplantation(HSCT).SH3B3 is important for effective stem cell homeostasis and is a negative regulator ofJAK-STAT pathway. Rare germline variations of SH3B3 have been reported in B-ALL (25).ALL patients exceeded 90-95% treatment response. Besides that, therapy toxicitymay cause organ dysfunction, impaired growth, decreased fertility and second primarymalignancies as long-term side effects of therapy. Chemotherapy (CT) is used as a first-linetreatment approach in ALL, and allogeneic HSCT is used in specific conditions. IntrathecalCT is required if central nervous system (CNS) involvement or prophylaxis are observed.Intrathecal CT and particularly external beam radiation therapy (EBRT) highly increase therisk of second primary CNS tumors (90% of patients who received cranial EBRT) (26).1.1.2. Predisposition to Myelodysplastic Syndrome and Acute Myeloid LeukemiaAML and MDS are rare heterogeneous entities in pediatrics, and AML constitutes 15-20%of childhood leukemia. It is estimated that an inherited AML and/or MDS accounts for 30-50%of children with AML/MDS and 10-20% of young adults (6). A familial disorder should besuspected in any child with MDS with positive findings from a screening history, physicalexaminations and genetic tests. Stem cell transplantation is a crucial option in childhoodMDS/AML treatment protocols. It is important to screen relatives for predisposition variantswhile selecting donors.MDS is a diverse group of clonal bone marrow disorders and tends to transform into AML.The age of diagnosis can be one to above 50 years in cases with familial AML/MDS. CAYAand older-adults with MDS are biologically and clinically distinct forms of the disorder. CAYAwith MDS are more likely to harbor variations in genetic predisposition genes. Early-onsetMDS patients are mostly characterized with severe presentation of specific syndromes inchildhood (27, 28). RUNX1, GATA2, CEBPA, ETV6, ANKRD26, DDX41, SAMD9 andSAMD9L variations have been detected in familial AML/MDS (29).Sporadic and germline mutations of RUNX1 are detected in AML, ALL, MDS, and familialplatelet disorder/ myeloid malignancy (FPD/MM). RUNX1 translocations are commonlyCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

152 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSobserved in sporadic AML cases. On the other hand, inherited mutations of RUNX1 aremostly nonsense or frameshift SNVs resulting in haploinsufficiency or larger deletions (25).Approximately 35% of RUNX1 variant carriers developed MDS/AML. Therefore, variableexpressivity of inherited RUNX1 variants should be considered while evaluating family history(11).CEBPA encodes the granulocytic differentiation factor C/EBP? that is important formyeloid differentiation. CEBPA deficiency has been shown to cause pure AML, andapproximately 10% of AML patients with a biallelic mutation in CEBPA also carry a germlineCEBPA variation (30). Germline CEBPA variants (especially frameshift variants affecting5’ end of the gene) predispose to AML with an autosomal dominant inheritance pattern.Somatic alterations of CEBPA are observed in AML as a favorable prognostic factor, butgermline CEBPA variants have been associated with a higher relapse incidence (11).DNMT3A is a highly conserved methyltransferase involved in epigenetic mechanisms.DNMT3A alterations that cause reduced methyltransferase activity, appear as a foundermutation in myeloid malignancies. However, DNMT3A mutations alone are insufficientfor developing malignancy. Pathogenic variants of DNMT3A frequently co-occur with TET2,IDH1, or IDH2 (31).GATA2 is a zinc-finger transcription factor in stem cell maintenance and promoteshematopoietic stem cell generation and function. GATA2 variations mostly affect thezinc finger region and cause haploinsufficiency. GATA2 deficiency is a heterogeneousimmunodeficiency syndrome and is associated with autosomal dominant predisposition tofamilial MDS/AML (32). GATA2 variations have been detected in 7% of pediatric MDS.Monosomy 7 is associated with de novo GATA2 aberrations, and monosomy 7 or partialloss of chromosome 7 is presented as a poor prognostic marker in MDS/AML. Furthermore,30% of patients with germline GATA2 variations also acquire somatic variations in ASXL1,suggesting a “second hit” for AML transformation (33).Germline screening tests for familial predisposition syndrome should not be limited toCAYA cases. Inherited pathogenic variants of RNA helicase gene DDX41 predispose to MDSand AML that can be presented in adulthood. Moreover, DDX41, SAMD9 and SAMD9L playroles in innate immunity, and antiviral response that new mechanisms for predisposition tohematological malignancies (25).AML is commonly observed in several syndromes; Down syndrome, Noonan syndrome,neurofibromatosis type 1, Ollier disease, Weaver syndrome and Sotos syndrome or trisomy8 in children (34, 35). Additionally, patients with Fanconi anemia (FA), Bloom syndrome,Shwachman-Diamond syndrome, congenital neutropenia, dyskeratosis congenita, MIRAGEsyndrome and Werner syndrome predispose to MDS/AML (36-40).Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 1531.1.3. Predisposition to LymphomaFamilial predisposition to lymphoma includes non-Hodgkin lymphoma (NHL), Hodgkinlymphoma and chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma.Childhood lymphomas have distinct biology from adult lymphomas. Furthermore, somelymphoma types such as pediatric type follicular lymphoma, pediatric nodal marginal zonelymphoma, large B-cell lymphoma with IRF4 rearrangement, systemic EBV positive T-celllymphoma of childhood and “hydroa vacciniforme” lymphoproliferative disorder are observedexclusively in CAYA group. A subset of childhood lymphomas is observed with congenitalimmunodeficiencies or EBV infection; however, the etiology and predisposing factors ofchildhood lymphomas are not well understood (4).Twin studies and case control studies have shown that a family history of lymphoma canpredispose to an elevated risk of lymphoma. Monozygotic twins of patients with HL have ahighly increased risk for developing HL, whereas dizygotic twins do not. An elevated NHLrisk has been found in both monozygotic and dizygotic twins, and cases with first-degreerelatives with HL (41). Common polymorphic variants, rare germline variations and severalsyndromes predispose to lymphoma. GWAS have found the HLA region and 8q24 as candidategene loci for lymphoma subtypes (42). Rare germline variants of CD70, KDR, KLDHC8B,NPAT, ACAN, CHECK2 and DICER1 genes have been identified in high-risk HL families aswell as de novo pathogenic variants that can contribute to lymphoma pathogenesis in childrenwithout family history (43). DICER1 p.Ile1711Met and p.His1767MetfsTer71 variants havebeen detected in a rare type of HL (44). DICER1, KDR, KLHDC8B, NPAT, POT1 andCHECK2 variants showed dominant inheritance of lymphoma, whereas ETV6 and ACANvariants inherited in a recessive mode (43).Patients with DNA repair disorders, immune deficiencies, and lymphoproliferativedisorders have approximately 8-10 times increased lymphoma risk compared with age-matchcontrols (43, 45).1.2. Genetic Predisposition to Solid TumorsCentral nervous system (CNS) tumors are the second most common type of cancerin CAYA. Medulloblastoma (MB), ependymoma (EP), and astrocytoma (AS) are thefrequent tumors of the CNS. Molecular diagnostics highly contribute to understanding thepredisposition to nervous system tumors (46).MB is a tumor of cerebellum and represents 15-20% of all CNS neoplasms. TheSonic hedgehog (SHH) and WNT pathways play prominent roles in the pathogenesis ofMB subtypes. SHH activated MB, has been associated with Gorlin syndrome resulting fromgermline mutations of PTCH1 and SUFU (47, 48). WNT pathway activation occurs throughsomatic mutation of CTNNB1 and germline variants of APC in patients with WNT-activatedMB (49, 50). Waszak et al. suggested APC, BRCA2, PALB2, PTCH1, SUFU, and TP53 genesCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

154 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSas MB predisposition genes by comparing the prevalence of germline mutations in their cohortwith data from the Exome Aggregation Consortium (ExAC) (49). Germline variants of ELP1have recently been associated with SHH activated MB. Furthermore, MB is associated withseveral syndromes such as LFS, AT, Bloom syndrome, and Greig’s cephalopolysyndactylysyndrome (47).EP is a tumor of the ventricular system, one of the low-grade glioma types and the secondmost common type in children with CNS tumors. Multiple EP formation has been reportedin patients who had germline APC mutations and NF2 (51). Patients with Kabuki syndromecarrying KMT2S variants have an increased risk of developing EP (52).High-grade glioma includes various heterogeneous lesions with different histologies.The most common histologies are anaplastic astrocytoma and glioblastoma (53). Germlinepredisposition to AS is associated with mutations in MUTYH, ERCC, TP53, PMS2, NF1,BRCA2, FANCA, RECQL4, DHCR7, WT1 and GJB2 (46).Neuroblastoma (NB) is a tumor of the sympathetic nervous system that develops fromneural crest cells. NB is the third-most common cancer and most common extracranial solidtumor in children and infants. A majority of NBs are observed sporadically, but germlinesusceptibility is described in 2% of patients with NB. Familial NB patients are presentedat a young age and tend to have multifocal tumors. A transcription factor gene PHOX2Bis the first gene reported in familial NB. PHOX2B variations are detected in congenitalcentral hypoventilation syndrome and/or Hirschsprung’s disease. However, regardless ofthese diseases, germline pathogenic variants of PHOX2B have been reported in NB patients(54). The proto-oncogenic ALK gene is the second gene reported in familial NB patients.Because of the incomplete penetrance of ALK variants, NB development is not detected in allgermline ALK variant carriers (55, 56). RASopathies are another predisposition condition inNB. In addition to sequencing studies, GWAS was able to detect several increased likelihoodsof developing NB loci, including CASC15, BARD1, LMO1, HACE1 and LIN28B (6).“Wilms tumor” (WT) is the most common renal tumor of childhood with an underlyinggermline predisposition in approximately 15% of cases. Patients with syndromic WT cancommonly present bilateral tumors compared to non-syndromic patients and tend to be seenat a younger age. Germline changes in the WT1 gene and epigenetic changes affecting 11p15locus are linked with an elevated risk of WT. Moreover, WT is associated with FanconiAnemia (FA), DICER1 syndrome, LFS and Bloom syndrome (BS) (57). Up to 80% ofpatients with “Beckwith-Wiedemann syndrome” (BWS) harbor causal germline methylationdefects at locus 11p15 (58). New pathogenic germline variants have been identified in theCTR9, REST, and TRIM28 genes associated with WT (59-61).Soft tissue sarcomas account for 7% of children’s tumors. Rhabdomyosarcoma (RMS)is a rare aggressive cancer that originates from mesenchymal cells and is the most commonCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 155soft tissue sarcoma. Although most children with RMS are sporadic, several syndromesare associated with RMS development such as LFS, NF1 and BWS. Inherited TP53 variantcarriers have an increased risk of developing RMS before age 5 (46, 62).Retinoblastoma (RB) is a malignancy of the neural retina and familial patients can harborgermline or mosaic variants that are detected in the RB1 gene. 25% of germline variants ofRB1 are inherited in autosomal dominant mode and often follow the ”two-hit” tumor modelfor tumorigenesis, while epigenetic silencing by methylation or two independent somaticmutations is required in non-hereditary cases (63, 64). The parent of origin effects or partialfunctional RB1 alleles lead to variable expressivity and penetrance in familial RB cases.Therefore, they need to be carefully evaluated for predisposition to cancer. Patients withgermline RB1 mutation have an increased risk of secondary cancer, especially soft tissuesarcomas, after the treatment phase (6, 65).1.3. Cancer Predisposition SyndromesCPS are genetic/epigenetic conditions and patients with these syndromes have an increasedrisk of developing cancer. Several CPSs show germline mosaicism and the frequency ofunderlying germline genetic variants are variable among different populations (4). CPS forhematologic malignancies can be reviewed under bone marrow failure syndromes, tumorsuppressor gene syndromes, DNA repair defects, immunodeficiency syndromes and Downsyndrome with hematological malignancies. Typical pediatric cancers and associated CPSare given in Table 1.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

156 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSTable 1: Cancer Predisposition SyndromesCancer PredispositionSyndromesRelated genesReported MalignanciesDNA repair disorders (66)Ataxia Telangiectasia ATM● Lymphoma (B cell)● Leukemia (ALL/T cell)● Gastric cancer● Melanoma● Sarcoma● LeiomyomaBloom Syndrome BLM● ALL-AML● Lymphoma● MDS● Brain tumor● Sarcoma● Retinoblastoma● Epithelial carcinomas● CUP syndromeFanconi anemiaFANCA, FANCB, FANCC,FANCD1/BRCA2, FANCD2, FANCE,FANCF, FANCG, FANCI,FANCJ/BRIP1/BACH1, FANCL,FANCM, FANCN/PALB2,FANCO/RAD51C, FANCP/SLX4,FANCQ/XPF/ERCC4,FANCR/RAD51, FANCES/BRCA1,FANCT/UBE2T,FANCU/XRCC2, REV7/MAD2L2● AML● MDS● Solid tumors● Cancers in the skin andgenitourinary tractNijmegen fracturesyndromeNBN● Mainly lymphomas● Solid tumors (for instancemedulloblastoma, gliomaand rhabdomyosarcoma)Rothmund–ThomsonsyndromeRECQL4● Osteosarcoma● Lymphoma● Skin CancerXeroderma PigmentosumDDB2, ERCC1, ERCC2, ERCC3,ERCC4, ERCC5, POLH, XPA, XPC● Malignant skin tumorLi-Fraumeni syndrome TP53● Soft tissue sarcoma● Osteosarcoma● Adrenocortical carcinoma(ACC)● Leukemia● Premenopausal breast cancer● Brain tumors● Choroid plexus carcinoma(CPC)Constitutional mismatchrepair deficiencyMLH1, MSH2, MSH6, PMS2,EPCAM● Brain tumors in childhood● Leukemias in childhood● Colorectal cancer in the2nd/3rd life decadeSyndromes predisposing to bone marrow failure/leukemia (11,17, 25, 32, 39, 67-76)Kostmann syndrome ELA2, HAX1● MDS● Acute myelogenousleukemiaConstitutionalthrombocytopeniaANKRD26● AML● CML● MDSMIRAGE syndrome SAMD9 ● MDS● AMLCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 157Table 1: ContinuedAtaxia-pancytopeniasyndromeSAMD9L● MDS● AMLFamilial AML with mutatedDDX41DDX41● MDS● AMLCongenital thrombocytopenia MECOM● CML● MelanomaBone marrow failuresyndromeERCC6L2● MDS● AMLCongenital amegakaryocyticthrombocytopenia type I/IIMPL● Leukemia● Colorectal cancerFamilial platelet disorder withassociated myeloid malignancyRUNX1● AML● ALL● MDSFamilial AML CEBPA● Lung adenocarcinoma● AMLGATA2-spectrum disorders GATA2● MDS● AMLPredisposition to ALL PAX5● Lymphoma● Lung cancerThrombocytopenia ETV6● MDS● CMML● Skin cancerDiamond blackfan anemiaRPS7, RPS10, RPS17, RPS19,RPS24, RPS26, RPL5, RPL11,RPL19, RPL35A● AML● MDS● Osteosarcoma● Colon cancerShwachman–DiamondsyndromeSBDS● AML● MDSDyskeratosis congenitaDKC1, TERC, TERT, TINF2,NHP2, NOP10, WRAP53● MDS● AML● Solid tumor● Squamous cell carcinoma (skinor mucosa)● Hodgkin disease● Pancreatic carcinomaRASopaties (39)Neurofibromatosis Type 1 NF1● Leukemia● (Optic nerve) Glioma● Brain tumors● Gastrointestinal stromal tumors● Retinal vasoproliferative tumors● Breast cancer before age 50years in women● Many other common cancers● Peripheral nerve sheath tumorand other soft● Tissue sarcomasNoonan syndromePTPN11, SOS1, RAF1, RIT1,KRAS, NRAS, SHOC2● Juvenile myelomonocyticleukemia (JMML)● ALL● AML● Solid tumors (such asrhabdomyosarcoma andneuroblastoma)Arteriovenous malformationsyndromeRASA1● Colon adenocarcinoma● Lung adenocarcinoma● Endometrial endometrioidAdenocarcinoma● Squamous cell lung carcinomaCostello syndrome HRAS ● Solid tumors of early childhoodCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

158 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSTable 1: Continued● Neuroblastoma● RhabdomyosarcomaCardio-fascio-cutaneoussyndromeBRAF, MAP2K1 (MEK1),MAP2K2 (MEK2)● Melanoma● Lung cancer● Bone cancer● Skin cancer● Stomach cancerLegius syndrome SPRED1● AML● B cell acute lymphoblasticleukemiaCBL syndrome CBL● AML● Lung cancerFamilial Cancer Syndromes (77-81)Familial adenomatouspolyposis syndromeAPC, MUTYH● Medulloblastoma● Hepatoblastoma● Small bowel/ Colon carcinoma● Pancreatic-cancer● Papillary thyroid carcinoma● Adenocarcinoma of stomach orbile ductsJuvenile polyposis syndrome SMAD4, BMPR1A● Colon cancer● Cancers of the stomach andupper GI tract● Pancreatic cancerPeutz–Jeghers syndrome STK11● Colorectal carcinoma● Gastric carcinoma● Pancreatic cancer● Mamma carcinoma● Ovarian carcinoma● Adenoma malign of the cervixMYTH-associated polyposis MUTYH● Thyroid cancer● Ovarian cancer● Bladder cancerLynch syndromeMSH2, MSH6, MLH1, PMS2,EPCAM● Brain tumors in childhood● Leukemias in childhood● Colorectal cancer in the 2nd/3rdlife decadeMultiple endocrine neoplasiatype IMEN1● Parathyroid tumors● Pituitary tumors● Well-differentiated endocrinetumors of the● Gastro-Entero-Pancreatic (82)tract● Carcinoid tumors● Adrenocortical tumors● • EpendymomaMultiple endocrine neoplasiatype IIARET● Medullary thyroid carcinoma(MTC)● Pheochromocytoma● Parathyroidadenoma/hyperplasia.Multiple endocrine neoplasiatype IIBRET● Only medullary thyroidcarcinoma (MTC)Multiple endocrine neoplasiatype IVCDKN1B● Breast invasive ductalcarcinoma● Prostate adenocarcinoma● Lung adenocarcinoma● Colon adenocarcinoma● Testicular mixed germ celltumorCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 159Table 1: ContinuedVon Hippel–Lindau VHL● Clear Cell Renal carcinoma● Pheochromocytoma● Neuroendocrine tumors● Endolymphatic sac tumorsFamilial thyroid cancer RET, NTRK1● Only medullary thyroidcarcinomaHyperparathyroidism-jawtumor syndromeCDC73● Parathyroid cancerPTEN hamartoma tumorsyndromePTEN● Breast cancer● Non-medullary thyroid cancer● Endometrial cancer● Colorectal cancer● Renal cell carcinoma● Melanoma● Brain tumorsPleuropulmonary blastomasyndromeDICER1● Kidney● Thyroid● Ovary● Cervix● Testicle● BrainGorlin syndrome PTCH1, SUFU● Medulloblastoma● Multiple basal cell carcinomasRubinstein–Taybi syndrome CREBBP, EP300● Brain tumors● Medulloblastoma● Neuroblastoma)● Hematologic malignancies(leukemia)Schinzel–Giedion syndrome SETBP1● Lung adenocarcinoma● Colon adenocarcinoma● Melanoma● Myelodysplastic syndromesNKX2-1 syndrome NKX2-1 ● Non-small cell lung cancerHereditary leiomyomatosis andrenal cancer syndromeFH● Lung adenocarcinomaTuberous sclerosis complex(TSC)TSC1, TSC2● Bladder cancerNeurofibromatosis Type II NF2● Meningiomas● EpendymomasPredisposition to Meningioma SMARCE1 ● Breast cancerNon-syndromic hereditaryWilms tumorWT1, CTR9● Leukemia● MDSHereditary retinoblastoma RB1 ● Small cell lung cancerHereditary neuroblastoma ALK, PHOX2B ● Lung cancer1.3.1. Li Fraumeni SyndromeLi Fraumeni syndrome (LFS) is a rare disease but the most commonly seen CPS in children.LFS predisposes to various tumors such as sarcomas, CNS tumors, adrenocortical carcinoma,and breast cancer and leukemia (25). Inherited pathogenic variants of TP53 are hallmarksof the LFS and inherited in an autosomal dominant mode. Tumor suppressor genes playroles in the regulation of cell cycle and apoptosis. Biallelic inactivation of tumor suppressorgenes is required for malign transformation. TP53 is a well-known tumor suppressor gene andgermline variation of TP53 was found in approximately 50% of childhood low-hypodiploidALL patients. Low-hypodiploid ALL with germline TP53 variants has a poor prognosis.Therefore, TP53 variant analysis is routinely suggested to children with hypodiploid ALL.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

160 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSAlthough lymphomas are not the common malignancies in LFS, these patients also have anincreased risk of lymphoma (83).1.3.2. Down Syndrome“Down syndrome” (DS) has an increased susceptibility for developing leukemia and DShas an almost 150-fold increased risk of AML before age 5. DS related myeloid proliferationsare commonly megakaryoblastic and are defined as transient myelopoiesis (TAM) and myeloidleukemia (ML-DS). TAM is observed mostly in newborns, and a large proportion of themshow spontaneous remission. Most patients with ML-DS harbor GATA1 and additional genevariants that encode cohesion components, signal transducers, and epigenetic regulators (4).Children with DS who developed ALL frequent harbor alterations in cytokine receptors orkinase signaling pathways, JAK2 variants and overexpression of CRLF2 (25).1.3.3. Bone Marrow Failure Syndromes“Inherited bone marrow failure syndromes” (IBMFS) are a heterogeneous groupof diseases including telomere syndromes, Diamond Blackfan anemia (DBA), FA,Shwachman-Diamond syndrome (SDS) and others. IBMFS is characterized by aplasticanemia and predisposition to cancer. More than 80 genes that play roles in senescence, cellcycle regulation, ribosome synthesis and telomere function have been associated with IBMFS(11, 85). Patients with IBMFS have an increased risk of toxicity; therefore, diagnosis andsyndrome-based management are important to decrease morbidity.1.3.3.1. Fanconi AnemiaAbout 60% of patients with FA develop early onset bone marrow failure and about 33%of cases with FA develop a hematological malignancy, most commonly AML and MDS.Germline biallelic BRCA1 mutations in FA was reported in a family study with an elevatedrisk of developing leukemia by the age of 5 years (86). Biallelic germline variants of ERCC2in FA are associated with xeroderma pigmentosum in childhood (87).1.3.3.2. Diamond Blackfan AnemiaDBA is a rare congenital erythroid aplasia that is usually observed at the early onset. DBAcan be inherited in both autosomal dominant and recessive form and causes macrocytic anemiaand distinct anomalies. Nearly half of DBA patients harbor pathogenic variants in ribosomalor non-ribosomal protein genes. GATA1 variants may rarely lead to the DBA phenotype inboys. Patients with DBA have increased predisposition to MDS and AML, and rare ALL andlymphoma cases have also been reported with DBA (11, 88).1.3.3.3. Shwachman-Diamond SyndromeSDS is a rare autosomal recessive IBMF disorder that is presented with low WBC count,developmental delay and skeletal abnormalities. Biallelic variants of SBDS are reported in90% of patients with SDS. SBDS protein affects cell proliferation, mitosis, maintenance ofCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 161the stromal microenvironment and ribosomal subunit joining. Chromosomal instability dueto SBDS aberrations may contribute to predisposition to MDS or leukemia in children (89).1.3.3.4. Congenital Amegakaryocytic Thrombocytopenia“Congenital amegakaryocytic thrombocytopenia” (CAMT) and thrombocytopenia withabsent radius syndrome (TAR) are two-well described thrombocytopenia syndromes. CAMTis inherited in an autosomal recessive mode and characterized by a severely low number ofmegakaryocytes and progression to pancytopenia. Pathogenic variants of the thrombopoietinreceptor gene MPL are associated with CAMT (73). Patients with CAMT have a higher riskof developing MDS and AML. TAR syndrome is inherited as an autosomal recessive disorderand is associated with deletion or missense variants of RBM8A gene. A small proportion ofpatients (four from 300 patients) with TAR may develop leukemia (84).1.3.4. DNA Repair DisordersDNA repair disorders are characterized by constitutional pathogenic variants in key genesthat are related to DNA replication and cellular response to DNA damage. Patients withDNA repair syndromes are commonly predisposed to malignant lymphoproliferative diseases.Increased DNA damage during lymphocyte maturation, impaired response to infectious agentsdue to reduced immune repertoire, and dysregulated immune development contribute tolymphoma development (43, 90).1.3.4.1. Nijmegen Breakage Syndrome“Nijmegen breakage syndrome” (NBS) is a rare chromosomal instability syndromeinherited in an autosomal recessive mode and associated with the dysfunction of NBNgene. The NBN gene encodes nibrin protein, which is important for the maintenanceof chromosomal integrity through double-strand break (DSB) repair, DNA recombination,maintenance of telomere integrity, and cell cycle checkpoint control. Among all chromosomalbreakage and immunodeficiency syndromes, NBS patients are prone to develop lymphomawith an increased risk, especially diffuse large B cell lymphoma (DLBCL) and peripheralT-cell lymphoma and more rarely BCP-ALL and AML. Reduced immune response and viralinfections may contribute to malignant proliferation with impaired balance of cell maturationand apoptosis. NBS patients suffer from side effects of chemotherapy related toxicities andimmunodeficiency. Furthermore, 13% of NBS patients develop a secondary cancer (43, 92).1.3.4.2. Ataxia-Telengiectasia“Ataxia-telangiectasia” (AT) is an autosomal recessive syndrome characterized byprogressive ataxia, immune dysregulation, impairing DSB repair mechanism and increasedsusceptibility to cancer development. Approximately 20% of AT patients develophematological malignancies with a mean age of 11 years. ATM gene located on chromosome11q22 encodes a cell cycle checkpoint kinase that is cruical for the cellular response toCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

162 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSDNA damage in cells (93). Biallelic mutations in ATM are exclusively related to oncogenicprocesses in AT. Based on variant profile AT is distinguished in two classes; pathogenicvariants of ATM that cause loss of function are observed in “classic AT”, missense, inframe orsplice site variants of ATM that lead to reduced levels of kinase activity classified as “variantAT”. Approximately 85% of patients with AT develop lymphoid malignancies, 15% of ATdevelop leukemia, but solid tumors have also been observed. During the treatment of cancer,it should be kept in mind that ionizing radiation can cause increased toxicity due to impairedDNA repair (11, 94).1.3.4.3. Bloom SyndromeBS is a rare autosomal recessive disorder characterized by growth retardation,photosensitivity rashes, and increased early-onset cancer risk. BLM gene is located at 15q26.1and encodes an evolutionary conserved protein RecQ helicase. RecQ helicase is essential tomaintain genomic stability during DNA replication, plays important roles in HR-mediatedDSB repair, and protects the genome from illegitimate recombination during mitosis (11).In contrast to other DNA repair syndromes, BS patients develop various types of cancer, butmost commonly they develop acute leukemias (21%) and lymphomas (23%). BS treatment iscomplicated and the prognosis is poor (43).1.3.4.4. Constitutional Mismatch Repair Deficiency SyndromeBiallelic inherited mutations in mismatch repair (MMR) genes such as MSH2, MSH6,MLH1, PMS2 and EPCAM cause an autosomal recessive DNA repair syndrome, constitutionalmismatch repair syndrome (CMMRD). Leukemia/lymphoma is the most commonly observedhematological malignancy in CMMRD patients with a mean age of 6-10 years at diagnosis(95). Contrary to other DNA damage repair syndromes, an increased risk of therapy toxicityis not expected in cases with CMMRD. The chemotherapeutic agents mercaptopurine andtemozolomide demonstrate antitumor efficiency through active MMR; therefore, these typesof drugs would not be efficient in CMMRD treatment (95).1.3.5. Primary Immune DeficienciesPrimary inherited immunodeficiency (PID) is a spectral disorder with defective immunesystem components. Patients with PIDs may have high rates of infections. So far, more than300 forms of PIDs and related genes have been identified. Patients with PID have an increasedrisk of infections and childhood cancer. EBV positivity is a predisposition event to developlymphoma in patients with PIDs (96).“Wiskott-Aldrich syndrome” (WAS) is an X-linked combined immune deficiency thatusually presents with thrombocytopenia and progressive immunodeficiency. Absent ortruncated forms of WASP variant cause the WAS phenotype. Approximately 13% of patientswith WAS present a malignancy and lymphoma are the most prevalent subtype of malignancy(11, 96).Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 163The BTK gene is involved in B-cell maturation and missense mutations of BTK causeaberrant enzymatic function that were reported in X-linked agammaglobulinemia (XLA).XLA have higher rates of acute leukemia and lymphoma (11).1.3.6. RASopathiesUncontrolled activation of the RAS-MAPK pathway is a common entity in hematologiccancers especially for juvenile myelomonocytic leukemia (JMML). RAS pathway membersNF1, PTPN11, NRAS, KRAS and CBL variants have been detected in approximately 90% ofJMML. Pathogenic NF1 variants cause autosomal dominant disorder neurofibromatosis type1 that affects the nervous system. Children with neurofibromatosis type 1 are prone to developJMML and typically carry loss of wild type NF1 allele and duplication of mutant allele dueto uniparental isodisomy. Furthermore, inherited variants of CBL are detected in 10 to 15%of JMML (97, 98).Noonan Syndrome (NS) is one of the common RASopathies and 50% of patients with NScarry germline variations in PTPN11 gene. Somatic variations of PTPN11 are also seen inJMML and indicate poor prognosis with increased relapse rate. Patients with NS who harborinherited PTPN11 variants commonly develop JMML-like disease. Beside that, patients withNS are also prone to ALL development. Germline variants of other RAS pathway members,RIT1, RRAS and SOS1 have been detected in patients with NS as well (25, 99).1.4. Recognizing Predisposition to Childhood CancersExtended availability of genetic testing and increased awareness of germline inheritanceof cancer predisposition genes have led to better stratification of patients at risk. Patientswith CPS may benefit from modified treatment strategies to decrease treatment-based toxicityand earlier clinical follow-up for the risk of secondary malignancy. Furthermore, for familiesto know the reason for cancer, gives opportunities for better genetic counseling and prenataldiagnosis (100). Therefore, it is mandatory to develop and integrate tools and pipelines forgenetic predisposition screening, diagnosis and management of affected children and theirfamilies.Identification of cases with cancer predisposition mainly rely on family history and type ofmalignancy. CPS are inherited mostly in autosomal dominant patterns; therefore, cumulationof malignancy in a family particularly indicates predisposition to cancer. However, due tosmall family size, recessive or de novo variants, incomplete penetrance, or expressivity makeit difficult to recognize cancer susceptibility in daily clinical practice (101).Several guidelines were developed to improve recognition of predisposition to cancer,management and counseling of pediatric patients. “The McGill Interactive PediatricOncoGenetic Guidelines” (MIPOGG), Jongmans (both original and modified) criteria (JC),and “the Childhood Cancer Screening checklist” (CCSC) are the most studied clinical.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

164 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERSguidelines (102,103) (Table 2). The guidelines indicate the need for an interdisciplinaryapproach with clinical experts and human geneticists.CCSC tool basically relies on the physical examination, and requires the use ofphotographs, personal and family history (104).Jongmans et al. generated a tool for recognition of genetic predisposition in pediatriccancer patients based on family history, type of malignancy, multiple, specific features, andincreased toxicity. JC also advises genetic counseling as a difference from other tools (100).The updated version of JC includes a wider list of CPS-associated tumors (105).MIPOGG is another well studied, and freely available interactive tool for the selectionof CPS with respect to “high risk features for CPS” and “tumor specific criteria”. MIPOGGincludes both malignant solid tumors and CPS-associated benign tumors (106).Usual indicatives of cancer predisposition syndrome are the presence of adult typetumors or metastases, multiple primary tumors, unusual therapy resistance or toxicity,presence of molecular aberrations, and family members with certain tumor syndromes.Next-generation sequencing allows identification of new candidate gene variants for cancerpredisposition. Besides that, reanalysis of genetic data may be required for certaincases. Therefore, comprehensive phenotype description, appropriate genetic testing, andstandardized documentation are not only mandatory for understanding of phenotype-genotypecorrelation but also important for further evaluations and follow-up. From this perspective,Hoyer J. et al. generated a structured questionnaire “the Pediatric Cancer Predisposition ToolPERCEPT” as a joint work of “SIOPE’s Host Genome Working Group”, “the I-BFM HostGenetic Variation Working Group”, “the Working Group Tumor Genetics of the GermanSociety of Human Genetics” and the COST Action CA16223 ”LEukaemiaGENe Discoveryby data sharing, mining and collaboration (LEGEND)”. PERCEPT can be used by geneticconsultation, and trained physicians and it’s intended to be applied as a second line care thatfocuses on systematic assignment and documentation of clinical characteristics of patientswith childhood cancer who have confirmed or suspected cancer predisposition variants. Inthis questionnaire, patients are evaluated according to their primer and secondary malignancyrecords, pregnancy and birth records, clinical examinations, morphological abnormalities,previous genetic counseling and testing, family history, and pedigrees (101).2. ConclusionIn conclusion, the rarity, heterogeneity, and strong impact of germline predisposition arechallenges of pediatric cancers. Combinational use of functional and genetic testing leadsto more accurate diagnosis and clinical management of childhood cancers. Understandingof the germline predisposition to pediatric cancer is increasing, but much remains to belearned. Currently, universal gene screening and targeted analysis approaches are used in theroutine diagnosis of inherited cancers. Careful analysis of genetic tests is crucial, and highCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 165throughput screening methods are vulnerable tools for identifying new predisposition genes.However, several challenges exist in predisposition studies, such as numbers of variants withunknown significance, small cohort studies, and lack of informative family history. Largecohort studies and better design of disease models will enable better clinical classificationof new pathogenic variants and give more proper genetic counseling to families suspected ofcancer predisposition syndromes.Table 2: Clinical screening tools for cancer predisposition in childhoodJongmans’ criteria (100) McGill Interactive PediatricOncoGenetic Guidelines (106)Childhood CancerScreening checklist (104)Criteria 1Familyhistory- Presence of ≥ 2malignancies (≤ 18 yearsof age) in childhood- Having a first-degreerelative (parent or sibling)with cancer younger than45 years of age- If there are ≥ 2 seconddegree relatives withcancer under the age of<45 on the same side of thefamily, the parents of thecancer index are related.- Presence of known cancerpredisposition syndrome in thefamily-Having a close relative (parent,sibling/half-sibling, aunt/uncle,cousin, grandparent) withcancer ≤ 18 years or having aparent/sibling/half-sibling ≤ 50years with cancer-Having the same type of cancerin a close relative or the sameorgan affected by cancer at anyage- Presence of multiple primarytumors in close relatives- ≥ 2 times the presenceof the same specifickind of cancer (on oneside of the family tillthe third degree), whichcould be associated withthe malignancy of thechild- Another familymember with childhoodcancer, which could beassociated with themalignancy of the child- 2 family members withcancer <45 years old,which could beassociated with themalignancy of the child- A first-degree familymember of this childwith cancer has (had)cancer themselvesCriteria 2 The pediatric case with twomalignancies;- One of age at onset <18years and (if 2ndmalignancy is notcompatible with expectedtime and/or tissue typefrom treatment regimens)- >1 primary tumor- Bilateral/multifocal primarytumors- Dysmorphic features/congenitalabnormalities that the cliniciandeems to be related to cancerpredisposition- Prior primarymalignancy Perinatal data,learning anddevelopmentaldifficulties, or possiblygrowth retardation presentin the context of a CPSCriteria 3 Cancer and congenitalanomalies or other specificsymptoms; for example;- Congenital anomalies,- Facial dysmorphisms,- Mental retardation,- Abnormal growth (height,head circumference, birthweight, asymmetric growth),- Skin anomalies (aberrantpigmentation, > 2 coffee aulait spots, vascular skinchanges, hypersensitivity tosunlight, skin many benigntumors,- Hematological disorders(Pancytopenia, anemia,thrombocytopenia,neutropenia),Immunodeficiency- Abnormalities suggestiveof a cancer predispositionsyndrome;a) found during physicalexamination;-Head (scalp tumors)-Eyes (cataract, visiblenerve fibers on cornea,photosensitivity)-Mouth (leukoplakia,abnormal tongue, oralpigmentation, oral tumors,abnormal oral mucosa,mucosal neurinomas,papilloma periorificial)-Ears: crease/pits of earlobule, helical pits of earhelixb) 2D photographic seriesc) 3D photographCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

CANCER: FROM GENOMICS TO PHARMACEUTICSTable 2: ContinuedCriteria 4 Case of pediatric cases withextreme treatment toxicity;-Criteria 5 Having one of the followingtumors in childhood such as;- Adrenocortical carcinoma,- Atypical teratoid rhabdoidtumor,- Cerebellar gangliocytoma,- Choroid plexus carcinoma,- Endolymphatic sac tumors,- Hemangioblastoma,- Hepatoblastoma,- JMML,- Low hypodiploid ALL,- Malignant peripheral nervesheath tumor,- Medullary thyroid-celltumor,- Medulloblastic carcinoma,- Medulloblastoma,- Pleuropulmonary blastoma,- Pituitary blastoma,- Pineoblastoma,- Retinoblastoma,- Schwannoma,- Subependymal giant celltumorTypes of tumors in which morethan 10% of patients carry agermline mutation and thereforeshould be referred for geneticconsultation are listed below;- Atypical teratoid/rhabdoidtumor,- small cell carcinoma of theovary-hypercalcemic type,- Choroid plexus carcinoma- Dysplastic cerebellargangliocytoma,- Endolymphatic sac tumor,- Hemangioblastoma,- Optic pathway glioma,- Pineoblastoma,- Pituitary blastoma,- Retinoblastoma,- Subependymal giant cell tumor,- Vestibular schwannoma,- Cystic nephroma,- Renal angiomyolipoma,- Renal cell carcinoma,- Renal rhabdoid tumor,- Desmoid tumor, Extrarenalrhabdoid tumor,- Gardner fibroma,- Malignant peripheral nervesheath tumor,- Nasal chondromesenchymalhamartoma,- Adrenocortical carcinoma,- Cardiac rhabdomyoma,-Colorectal carcinoma,- Gastrointestinal stromal tumor,- Hepatoblastoma,- Medullary thyroid cancer,- Ovarian Sertoli-Leydig celltumor,- Parathyroid tumor,- Pheochromocytoma,- Paraganglioma,- Pleuropulmonary blastoma,- TrichilemmomaREFERENCES1. Steliarova-Foucher E, Colombet M, Ries LAG, Moreno F, Dolya A, Bray F, et al.International incidence of childhood cancer, 2001-10: a population-based registry study.Lancet Oncol. 2017;18(6):719-31.2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin.2020;70(1):7-30.3. Kopp LM, Gupta P, Pelayo-Katsanis L, Wittman B, Katsanis E. Late effects in adultCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 167survivors of pediatric cancer: a guide for the primary care physician. Am J Med.2012;125(7):636-41.4. Pfister SM, Reyes-M´ugica M, Chan JKC, Hasle H, Lazar AJ, Rossi S, et al. A Summaryof the Inaugural WHO Classification of Pediatric Tumors: Transitioning from the Opticalinto the Molecular Era. Cancer Discov. 2022;12(2):331-55.5. Sweet-Cordero EA, Biegel JA. The genomic landscape of pediatric cancers: Implicationsfor diagnosis and treatment. Science. 2019;363(6432):1170-5.6. Zhang MY, Churpek JE, Keel SB, Walsh T, Lee MK, Loeb KR, et al. GermlineETV6 mutations in familial thrombocytopenia and hematologic malignancy. Nat Genet.2015;47(2):180-5.7. Gambale A, Russo R, Andolfo I, Quaglietta L, De Rosa G, Contestabile V, et al. Germlinemutations and new copy number variants among 40 pediatric cancer patients suspectedfor genetic predisposition. Clin Genet. 2019;96(4):359-65.8. Ishida H, Iguchi A, Aoe M, Takahashi T, Tamefusa K, Kanamitsu K, et al. Panel-basednext-generation sequencing identifies prognostic and actionable genes in childhood acutelymphoblastic leukemia and is suitable for clinical sequencing. Ann Hematol. 2018.9. Bouffet E, Larouche V, Campbell BB, Merico D, de Borja R, Aronson M, et al. ImmuneCheckpoint Inhibition for Hypermutant Glioblastoma Multiforme Resulting FromGermline Biallelic Mismatch Repair Deficiency. J Clin Oncol. 2016;34(19):2206-11.10. Sorrell AD, Espenschied CR, Culver JO, Weitzel JN. Tumor protein p53 (TP53) testingand Li-Fraumeni syndrome: current status of clinical applications and future directions.Mol Diagn Ther. 2013;17(1):31-47.11. Stieglitz E, Loh ML. Genetic predispositions to childhood leukemia. Ther Adv Hematol.2013;4(4):270-90.12. Mullighan CG, Goorha S, Radtke I, Miller CB, Coustan-Smith E, Dalton JD, et al.Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia. Nature.2007;446(7137):758-64.13. Xu H, Yang W, Perez-Andreu V, Devidas M, Fan Y, Cheng C, et al. Novel susceptibilityvariants at 10p12.31-12.2 for childhood acute lymphoblastic leukemia in ethnicallydiverse populations. J Natl Cancer Inst. 2013;105(10):733-42.14. Wagener R, Elitzur S, Brozou T, Borkhardt A. Functional damaging germline variants inETV6, IKZF1, PAX5 and RUNX1 predisposing to B-cell precursor acute lymphoblasticleukemia. Eur J Med Genet. 2023;66(4):104725.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

168 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERS15. Shah S, Schrader KA, Waanders E, Timms AE, Vijai J, Miething C, et al. A recurrentgermline PAX5 mutation confers susceptibility to pre-B cell acute lymphoblasticleukemia. Nat Genet. 2013;45(10):1226-31.16. Escudero A, Takagi M, Auer F, Friedrich UA, Miyamoto S, Ogawa A, et al. Clinical andimmunophenotypic characteristics of familial leukemia predisposition caused by PAX5germline variants. Leukemia. 2022;36(9):2338-42.17. Duployez N, Jamrog LA, Fregona V, Hamelle C, Fenwarth L, Lejeune S, et al. GermlinePAX5 mutation predisposes to familial B-cell precursor acute lymphoblastic leukemia.Blood. 2021;137(10):1424-8.18. Yazdanparast S, Khatami SR, Galehdari H, Jaseb K. One missense mutation in exon 2of the PAX5 gene in Iran. Genet Mol Res. 2015;14(4):17768-75.19. Noetzli L, Lo RW, Lee-Sherick AB, Callaghan M, Noris P, Savoia A, et al. Germlinemutations in ETV6 are associated with thrombocytopenia, red cell macrocytosis andpredisposition to lymphoblastic leukemia. Nat Genet. 2015;47(5):535-8.20. Olsson L, Johansson B. Ikaros and leukaemia. Br J Haematol. 2015;169(4):479-91.21. Kuehn HS, Nunes-Santos CJ, Rosenzweig SD. IKAROS-Associated Diseases in 2020:Genotypes, Phenotypes, and Outcomes in Primary Immune Deficiency/Inborn Errorsof Immunity. J Clin Immunol. 2021;41(1):1-10.22. Churchman ML, Qian M, Te Kronnie G, Zhang R, Yang W, Zhang H, et al. GermlineGenetic IKZF1 Variation and Predisposition to Childhood Acute LymphoblasticLeukemia. Cancer Cell. 2018;33(5):937-48.e8.23. Grossmann V, Kern W, Harbich S, Alpermann T, Jeromin S, Schnittger S, et al.Prognostic relevance of RUNX1 mutations in T-cell acute lymphoblastic leukemia.Haematologica. 2011;96(12):1874-7.24. Li Y, Yang W, Devidas M, Winter SS, Kesserwan C, Dunsmore KP, et al. GermlineRUNX1 variation and predisposition to childhood acute lymphoblastic leukemia. J ClinInvest. 2021;131(17).25. Klco JM, Mullighan CG. Advances in germline predisposition to acute leukaemias andmyeloid neoplasms. Nat Rev Cancer. 2021;21(2):122-37.26. Zahnreich S, Schmidberger H. Childhood Cancer: Occurrence, Treatment and Risk ofSecond Primary Malignancies. Cancers (Basel). 2021;13(11).Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 16927. Avagyan S, Shimamura A. Lessons From Pediatric MDS: Approaches to GermlinePredisposition to Hematologic Malignancies. Front Oncol. 2022;12:813149.28. Furutani E, Shimamura A. Genetic predisposition to MDS: diagnosis and management.Hematology Am Soc Hematol Educ Program. 2019;2019(1):110-9.29. Godley LA, Shimamura A. Genetic predisposition to hematologic malignancies:management and surveillance. Blood. 2017;130(4):424-32.30. Pabst T, Eyholzer M, Haefliger S, Schardt J, Mueller BU. Somatic CEBPA mutationsare a frequent second event in families with germline CEBPA mutations and familialacute myeloid leukemia. J Clin Oncol. 2008;26(31):5088-93.31. Yang L, Rau R, Goodell MA. DNMT3A in haematological malignancies. Nat RevCancer. 2015;15(3):152-65.32. Hahn CN, Chong CE, Carmichael CL, Wilkins EJ, Brautigan PJ, Li XC, et al. HeritableGATA2 mutations associated with familial myelodysplastic syndrome and acute myeloidleukemia. Nat Genet. 2011;43(10):1012-7.33. Wlodarski MW, Hirabayashi S, Pastor V, Stary J, Hasle H, Masetti R, et al. Prevalence,clinical characteristics, and prognosis of GATA2-related myelodysplastic syndromes inchildren and adolescents. Blood. 2016;127(11):1387-97; quiz 518.34. Chantrain CF, Jijon P, De Raedt T, Vermylen C, Poirel HA, Legius E, et al.Therapy-related acute myeloid leukemia in a child with Noonan syndrome and clonalduplication of the germline PTPN11 mutation. Pediatr Blood Cancer. 2007;48(1):101-4.35. Kratz CP, Antonietti L, Shannon KM, Dole MG, Friebert SE. Acute myeloid leukemiaassociated with t(8;21) or trisomy 8 in children with neurofibromatosis, type 1. J PediatrHematol Oncol. 2003;25(4):343.36. Usemann J, Ernst T, Schafer V, Lehmberg K, Seeger K. EZH2 mutation in anadolescent with Weaver syndrome developing acute myeloid leukemia and secondaryhemophagocytic lymphohistiocytosis. Am J Med Genet A. 2016;170A(5):1274-7.37. Alter BP. Fanconi anemia and the development of leukemia. Best Pract Res ClinHaematol. 2014;27(3-4):214-21.38. Freedman MH, Alter BP. Risk of myelodysplastic syndrome and acute myeloid leukemiain congenital neutropenias. Semin Hematol. 2002;39(2):128-33.39. Alter BP, Giri N, Savage SA, Rosenberg PS. Cancer in dyskeratosis congenita. Blood.2009;113(26):6549-57.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

170 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERS40. Seiter K, Qureshi A, Liu D, Galvin-Parton P, Arshad M, Agoliati G, et al. Severetoxicity following induction chemotherapy for acute myelogenous leukemia in a patientwith Werner’s syndrome. Leuk Lymphoma. 2005;46(7):1091-5.41. Morton LM, Slager SL, Cerhan JR, Wang SS, Vajdic CM, Skibola CF, et al. Etiologicheterogeneity among non-Hodgkin lymphoma subtypes: the InterLymph Non-HodgkinLymphoma Subtypes Project. J Natl Cancer Inst Monogr. 2014;2014(48):130-44.42. Cerhan JR, Slager SL. Familial predisposition and genetic risk factors for lymphoma.Blood. 2015;126(20):2265-73.43. Szmyd B, Mlynarski W, Pastorczak A. Genetic predisposition to lymphomas: Overviewof rare syndromes and inherited familial variants. Mutat Res Rev Mutat Res.2021;788:108386.44. Kuhlen M, Honscheid A, Schemme J, Merz H, Mauz-K ¨ orholz C, Borkhardt A, et al. ¨Hodgkin lymphoma as a novel presentation of familial DICER1 syndrome. Eur J Pediatr.2016;175(4):593-7.45. Khodzhaev K, Bay SB, Kebudi R, Altindirek D, Kaya A, Erbilgin Y, et al. LymphomaPredisposing Gene in an Extended Family: CD70 Signaling Defect. J Clin Immunol.2020;40(6):883-92.46. Capasso M, Montella A, Tirelli M, Maiorino T, Cantalupo S, Iolascon A. GeneticPredisposition to Solid Pediatric Cancers. Front Oncol. 2020;10:590033.47. Carta R, Del Baldo G, Miele E, Po A, Besharat ZM, Nazio F, et al. Cancer PredispositionSyndromes and Medulloblastoma in the Molecular Era. Front Oncol. 2020;10:566822.48. Northcott PA, Jones DT, Kool M, Robinson GW, Gilbertson RJ, Cho YJ, et al.Medulloblastomics: the end of the beginning. Nat Rev Cancer. 2012;12(12):818-34.49. Grobner SN, Worst BC, Weischenfeldt J, Buchhalter I, Kleinheinz K, RudnevaVA, et al. The landscape of genomic alterations across childhood cancers. Nature.2018;555(7696):321-7.50. Attard TM, Giglio P, Koppula S, Snyder C, Lynch HT. Brain tumors in individuals withfamilial adenomatous polyposis: a cancer registry experience and pooled case reportanalysis. Cancer. 2007;109(4):761-6.51. Torres CF, Korones DN, Pilcher W. Multiple ependymomas in a patient with Turcot’ssyndrome. Med Pediatr Oncol. 1997;28(1):59-61.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 17152. Barry KK, Tsaparlis M, Hoffman D, Hartman D, Adam MP, Hung C, et al. FromGenotype to Phenotype-A Review of Kabuki Syndrome. Genes (Basel). 2022;13(10).53. Fangusaro J. Pediatric high grade glioma: a review and update on tumor clinicalcharacteristics and biology. Front Oncol. 2012;2:105.54. McConville C, Reid S, Baskcomb L, Douglas J, Rahman N. PHOX2B analysis innon-syndromic neuroblastoma cases shows novel mutations and genotype-phenotypeassociations. Am J Med Genet A. 2006;140(12):1297-301.55. Mosse YP, Laudenslager M, Khazi D, Carlisle AJ, Winter CL, Rappaport E, etal. Germline PHOX2B mutation in hereditary neuroblastoma. Am J Hum Genet.2004;75(4):727-30.56. Trochet D, Bourdeaut F, Janoueix-Lerosey I, Deville A, de Pontual L, SchleiermacherG, et al. Germline mutations of the paired-like homeobox 2B (PHOX2B) gene inneuroblastoma. Am J Hum Genet. 2004;74(4):761-4.57. Maciaszek JL, Oak N, Nichols KE. Recent advances in Wilms’ tumor predisposition.Hum Mol Genet. 2020;29(R2):R138-R49.58. Choufani S, Shuman C, Weksberg R. Beckwith-Wiedemann syndrome. Am J Med GenetC Semin Med Genet. 2010;154C(3):343-54.59. Hanks S, Perdeaux ER, Seal S, Ruark E, Mahamdallie SS, Murray A, et al. Germlinemutations in the PAF1 complex gene CTR9 predispose to Wilms tumour. Nat Commun.2014;5:4398.60. Mahamdallie SS, Hanks S, Karlin KL, Zachariou A, Perdeaux ER, Ruark E, et al.Mutations in the transcriptional repressor REST predispose to Wilms tumor. Nat Genet.2015;47(12):1471-4.61. Halliday BJ, Fukuzawa R, Markie DM, Grundy RG, Ludgate JL, Black MA, et al.Germline mutations and somatic inactivation of TRIM28 in Wilms tumour. PLoS Genet.2018;14(6):e1007399.62. Ognjanovic S, Olivier M, Bergemann TL, Hainaut P. Sarcomas in TP53 germlinemutation carriers: a review of the IARC TP53 database. Cancer. 2012;118(5):1387-96.63. Dimaras H, Corson TW, Cobrinik D, White A, Zhao J, Munier FL, et al. Retinoblastoma.Nat Rev Dis Primers. 2015;1:15021.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

172 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERS64. Kamihara J, Bourdeaut F, Foulkes WD, Molenaar JJ, Mosse YP, Nakagawara A, et al.Retinoblastoma and Neuroblastoma Predisposition and Surveillance. Clin Cancer Res.2017;23(13):e98-e106.65. Kleinerman RA, Tucker MA, Abramson DH, Seddon JM, Tarone RE, Fraumeni JF,Jr. Risk of soft tissue sarcomas by individual subtype in survivors of hereditaryretinoblastoma. J Natl Cancer Inst. 2007;99(1):24-31.66. Sharma R, Lewis S, Wlodarski MW. DNA Repair Syndromes and Cancer: Insights IntoGenetics and Phenotype Patterns. Front Pediatr. 2020;8:570084.67. Kostmann R. Infantile genetic agranulocytosis; agranulocytosis infantilis hereditaria.Acta Paediatr Suppl (Upps). 1956;45(Suppl 105):1-78.68. Noris P, Favier R, Alessi MC, Geddis AE, Kunishima S, Heller PG,et al. ANKRD26-related thrombocytopenia and myeloid malignancies. Blood.2013;122(11):1987-9.69. Narumi S, Amano N, Ishii T, Katsumata N, Muroya K, Adachi M, et al. SAMD9mutations cause a novel multisystem disorder, MIRAGE syndrome, and are associatedwith loss of chromosome 7. Nat Genet. 2016;48(7):792-7.70. Russell AJ, Gray PE, Ziegler JB, Kim YJ, Smith S, Sewell WA, et al. SAMD9Lautoinflammatory or ataxia pancytopenia disease mutations activate cell-autonomoustranslational repression. Proc Natl Acad Sci U S A. 2021;118(34).71. Germeshausen M, Ancliff P, Estrada J, Metzler M, Ponstingl E, Rutschle H, etal. MECOM-associated syndrome: a heterogeneous inherited bone marrow failuresyndrome with amegakaryocytic thrombocytopenia. Blood Adv. 2018;2(6):586-96.72. Shabanova I, Cohen E, Cada M, Vincent A, Cohn RD, Dror Y. ERCC6L2-associatedinherited bone marrow failure syndrome. Mol Genet Genomic Med. 2018;6(3):463-8.73. Germeshausen M, Ballmaier M. CAMT-MPL: congenital amegakaryocyticthrombocytopenia caused by MPL mutations - heterogeneity of a monogenic disorder -a comprehensive analysis of 56 patients. Haematologica. 2021;106(9):2439-48.74. Song WJ, Sullivan MG, Legare RD, Hutchings S, Tan X, Kufrin D, et al.Haploinsufficiency of CBFA2 causes familial thrombocytopenia with propensity todevelop acute myelogenous leukaemia. Nat Genet. 1999;23(2):166-75.75. Sellick GS, Spendlove HE, Catovsky D, Pritchard-Jones K, Houlston RS. Furtherevidence that germline CEBPA mutations cause dominant inheritance of acute myeloidleukaemia. Leukemia. 2005;19(7):1276-8.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 17376. Di Paola J, Porter CC. ETV6-related thrombocytopenia and leukemia predisposition.Blood. 2019;134(8):663-7.77. Rahner N, Steinke V. Hereditary cancer syndromes. Dtsch Arztebl Int.2008;105(41):706-14.78. Blatter R, Tschupp B, Aretz S, Bernstein I, Colas C, Evans DG, et al. Disease expressionin juvenile polyposis syndrome: a retrospective survey on a cohort of 221 Europeanpatients and comparison with a literature-derived cohort of 473 SMAD4/BMPR1Apathogenic variant carriers. Genet Med. 2020;22(9):1524-32.79. Chae HD, Jeon CH. Peutz-Jeghers syndrome with germline mutation of STK11. AnnSurg Treat Res. 2014;86(6):325-30.80. Kamilaris CDC, Stratakis CA. Multiple Endocrine Neoplasia Type 1 (MEN1): AnUpdate and the Significance of Early Genetic and Clinical Diagnosis. Front Endocrinol(Lausanne). 2019;10:339.81. Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al.NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res.2013;41(Database issue):D991-5.82. Kim SJ, Dix DJ, Thompson KE, Murrell RN, Schmid JE, Gallagher JE, et al. Effects ofstorage, RNA extraction, genechip type, and donor sex on gene expression profiling ofhuman whole blood. Clin Chem. 2007;53(6):1038-45.83. Holmfeldt L, Wei L, Diaz-Flores E, Walsh M, Zhang J, Ding L, et al. The genomiclandscape of hypodiploid acute lymphoblastic leukemia. Nat Genet. 2013;45(3):242-52.84. Alter BP, Giri N, Savage SA, Peters JA, Loud JT, Leathwood L, et al. Malignanciesand survival patterns in the National Cancer Institute inherited bone marrow failuresyndromes cohort study. Br J Haematol. 2010;150(2):179-88.85. Narla A, Ebert BL. Ribosomopathies: human disorders of ribosome dysfunction. Blood.2010;115(16):3196-205.86. Wagner JE, Tolar J, Levran O, Scholl T, Deffenbaugh A, Satagopan J, et al. Germlinemutations in BRCA2: shared genetic susceptibility to breast cancer, early onset leukemia,and Fanconi anemia. Blood. 2004;103(8):3226-9.87. Bogliolo M, Schuster B, Stoepker C, Derkunt B, Su Y, Raams A, et al. Mutations inERCC4, encoding the DNA-repair endonuclease XPF, cause Fanconi anemia. Am JHum Genet. 2013;92(5):800-6.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

174 GERMLINE PREDISPOSITION TO CHILDHOOD CANCERS88. Vlachos A, Rosenberg PS, Atsidaftos E, Alter BP, Lipton JM. Incidence of neoplasiain Diamond Blackfan anemia: a report from the Diamond Blackfan Anemia Registry.Blood. 2012;119(16):3815-9.89. Donadieu J, Leblanc T, Bader Meunier B, Barkaoui M, Fenneteau O, Bertrand Y, etal. Analysis of risk factors for myelodysplasias, leukemias and death from infectionamong patients with congenital neutropenia. Experience of the French Severe ChronicNeutropenia Study Group. Haematologica. 2005;90(1):45-53.90. Bomken S, van der Werff Ten Bosch J, Attarbaschi A, Bacon CM, Borkhardt A, BoztugK, et al. Current Understanding and Future Research Priorities in Malignancy AssociatedWith Inborn Errors of Immunity and DNA Repair Disorders: The Perspective of anInterdisciplinary Working Group. Front Immunol. 2018;9:2912.91. Sun Y, Jiang X, Price BD. Tip60: connecting chromatin to DNA damage signaling. CellCycle. 2010;9(5):930-6.92. Wolska-Kusnierz B, Pastorczak A, Fendler W, Wakulinska A, Dembowska-BaginskaB, Heropolitanska-Pliszka E, et al. Hematopoietic Stem Cell Transplantation PositivelyAffects the Natural History of Cancer in Nijmegen Breakage Syndrome. Clin CancerRes. 2021;27(2):575-84.93. Rothblum-Oviatt C, Wright J, Lefton-Greif MA, McGrath-Morrow SA, Crawford TO,Lederman HM. Ataxia telangiectasia: a review. Orphanet J Rare Dis. 2016;11(1):159.94. Hecht F, Hecht BK. Cancer in ataxia-telangiectasia patients. Cancer Genet Cytogenet.1990;46(1):9-19.95. Tabori U, Hansford JR, Achatz MI, Kratz CP, Plon SE, Frebourg T, et al. ClinicalManagement and Tumor Surveillance Recommendations of Inherited Mismatch RepairDeficiency in Childhood. Clin Cancer Res. 2017;23(11):e32-e7.96. Verhoeven D, Stoppelenburg AJ, Meyer-Wentrup F, Boes M. Increased risk ofhematologic malignancies in primary immunodeficiency disorders: opportunities forimmunotherapy. Clin Immunol. 2018;190:22-31.97. Niemeyer CM. JMML genomics and decisions. Hematology Am Soc Hematol EducProgram. 2018;2018(1):307-12.98. Stiller CA, Chessells JM, Fitchett M. Neurofibromatosis and childhoodleukaemia/lymphoma: a population-based UKCCSG study. Br J Cancer.1994;70(5):969-72.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Tugc¸e SUDUTAN, Y¨ucel ERB ˘˙ILG˙IN 17599. Kratz CP, Niemeyer CM, Castleberry RP, Cetin M, Bergstrasser E, Emanuel PD, et al. ¨The mutational spectrum of PTPN11 in juvenile myelomonocytic leukemia and Noonansyndrome/myeloproliferative disease. Blood. 2005;106(6):2183-5.100. Jongmans MC, Loeffen JL, Waanders E, Hoogerbrugge PM, Ligtenberg MJ, Kuiper RP,et al. Recognition of genetic predisposition in pediatric cancer patients: An easy-to-useselection tool. Eur J Med Genet. 2016;59(3):116-25.101. Hoyer Juliane BIB, Ripperger Tim , Karow Axel , Borkhardt Arndt ,, Brozou TriantafylliaCG, Ebinger Martin , Farah Roula , Obregon Susana Garc ´ ´ıa ,, Hauer Julia KA, KronnieGeertruijte , Kuhlen Michaela , Lazic Jelena ,, Lohi Olli OU, P ¨ erez-Mart ´ ´ınez Antonio,Rieß Olaf , Schneider Dominik T ,, Schrappe Martin SC, Zimmermann Stefanie , ThielChristian ,, Schroeck Evelin , et al. Pediatric Cancer Predisposition Documentation Tool- Standardized Reporting Form for Children and Adolescents with Suspected CancerPredisposition Syndrome 2021; 6(1844)1-9102. Byrjalsen A, Hansen TVO, Stoltze UK, Mehrjouy MM, Barnkob NM, Hjalgrim LL,et al. Nationwide germline whole genome sequencing of 198 consecutive pediatriccancer patients reveals a high incidence of cancer prone syndromes. PLoS Genet.2020;16(12):e1009231.103. Rossini L, Durante C, Bresolin S, Opocher E, Marzollo A, Biffi A. DiagnosticStrategies and Algorithms for Investigating Cancer Predisposition Syndromes inChildren Presenting with Malignancy. Cancers (Basel). 2022;14(15).104. Postema FAM, Hopman SMJ, de Borgie CAJM, Aalfs CM, Anninga JK, Berger LPV, etal. Clinical value of a screening tool for tumor predisposition syndromes in childhoodcancer patients (TuPS): a prospective, observational, multi-center study. Fam Cancer.2021;20(4):263-71.105. Ripperger T, Bielack SS, Borkhardt A, Brecht IB, Burkhardt B, Calaminus G, et al.Childhood cancer predisposition syndromes-A concise review and recommendations bythe Cancer Predisposition Working Group of the Society for Pediatric Oncology andHematology. Am J Med Genet A. 2017;173(4):1017-37.106. Goudie C, Coltin H, Witkowski L, Mourad S, Malkin D, Foulkes WD. The McGillInteractive Pediatric OncoGenetic Guidelines: An approach to identifying pediatriconcology patients most likely to benefit from a genetic evaluation. Pediatr Blood Cancer.2017;64(8).Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

CANCER: FROM GENOMICS TO PHARMACEUTICSCHAPTER 7BIG DATA / MULTIOMIC APPROACHES IN CANCERRESEARCHSeda SUSG ¨ UN¨ 1,2, Barıs¸ SALMAN3,4, Sibel Aylin UGUR ˘ ˙IS¸ER˙I51PhD Candidate, ˙Istanbul University, Institute of Graduate Studies in Health Sciences, Genetics Department,˙Istanbul, T¨urkiye2˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Genetics Department, ˙Istanbul, T¨urkiyeE-mail: [email protected] Candidate, ˙Istanbul University, Institute of Graduate Studies in Health Sciences, Genetics Department,˙Istanbul, T¨urkiye4˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Genetics Department, ˙Istanbul, T¨urkiyeE-mail: [email protected]. Dr., ˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Genetics Department, ˙Istanbul,T¨urkiyeE-mail: [email protected]: 10.26650/B/LSB28LSB48LSB56.2024.019.007ABSTRACTThe development and causes of cancer are related to complex cellular and environmental processes. In orderto resolve this layered complexity, high resolution and high throughput molecular approaches are required, whichmay improve patient care via early diagnosis, prognosis and/or actionable clinical impact. Cancer related data canbe obtained using a series of cutting-edge omics technologies involving genomics, epigenomics, transcriptomics,proteomics and metabolomics. The big data obtained from these platforms may be integrated via bioinformatic tools,which may help patient based clinical decisions.Keywords: Multiomics, genomics, transcriptomics, proteomics, metabolomics, single cell, bigdata, biodata,bioinformaticsCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Seda SUSG ¨ UN, Barıs¸ SALMAN, Sibel Aylin U ¨ GUR ˘ ˙IS¸ER˙I 1771. IntroductionMolecular mechanisms of carcinogenesis are spatiotemporally complex and requireintegration of multiple levels of data through high resolution technologies. Multiomicsinvolving next generation sequencing (NGS) and proteomic technologies along withbioinformatic approaches in this sense have the potential to untangle this complexity andprovide personalized patient care in cancer treatment. Single omics approaches have longbeen used for many aspects of cancer such as cataloging the mutational landmark of cancer cellsvia exome or genome sequencing, identifying alterations in gene expression, and detectingaberrant gene fusions through RNA sequencing and targeting epigenetic alterations viaepigenomic approaches. There is now a shift towards integration of these kinds of dataalong with proteomic and metabolomic findings, which eventually serves as an interface touncover complex pathology in cancer. The new era of ‘Big Data and Multiomics’ providesthe opportunity to improve health outcomes.2. Omics Technologies and Relevant ApplicationsOmics technologies refer to holistic high-throughput assessments of biological data(1). They may globally be used to interrogate physiological states together with molecularalterations leading to Mendelian and/or complex disorders (2). These technologies can targeta variety of molecules, including DNA, RNA, proteins and metabolites; which is then namedaccordingly as genomics, epigenomics, transcriptomics, proteomics, and metabolomics.Recently, immunomics and microbiomics have been also added to extend the comprehensivepicture of the biological system (1, 3).Initially, omics technologies had been conducted separately by focusing on one type ofmolecule, however, currently multi-omics have emerged as a valuable approach to generatehigh-dimensional datasets and gain deep insights into diseases (4). Indeed, two main toolsare used in omics assays, these are NGS and mass spectrometry (MS). While NGS enablesinvestigating genome, epigenome, transcriptome, and their interactions with each other (DNA,RNA), MS provides evaluating proteome, metabolome, and their interactomes (protein,metabolite) (1). In the following sections, firstly the main omics approaches will be detailedseparately, and then, the utility of multi-omics approaches will be mentioned.2.1. GenomicsThe human genome can be described as the complete profile of nuclear and mitochondrialDNA sequences together with various RNA and protein molecules complexed with thisDNA. Accordingly, genomics is the most studied omics field and it mainly focuses on thegenetic variations in the DNA sequence, which potentially cause transcriptomic and proteomicalterations (5).Genetic variations in the DNA may be grouped according to their sizes:Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

178 BIG DATA / MULTIOMIC APPROACHES IN CANCER RESEARCH(i) Small size variations include changes in the base content of the DNA affecting a fewbase pairs. If this kind of variation is observed within the coding sequence of the gene itmay result in missense, nonsense or frameshift alterations in the polypeptide chain encodedfrom this gene. These kinds of variations can sometimes interfere with the splicing pattern ofprimary mRNA transcripts or result in increased or decreased expression from these genes.Microsatellite variations which are regions in the genomic sequence containing short tandemrepeats of 2-10 base pairs are also classified as small sized variations.(ii) Middle sized variations, which are known as structural variations are considered tobe larger than 1000 kb. A subgroup of these variations is known as copy number variations(CNVs) as they may cause decreased or increased DNA content through insertions and/ordeletions. Translocations and inversions on the other hand cause locational and orientationalchanges in the genome, respectively. Philadelphia chromosome associated with chronicmyelogenous leukemia is an example of a cancer related chromosomal abnormality generatedas a result of translocation of the long arm of chromosomes 9 and 22. The translocationbreakpoint brings two unrelated DNA sequences together, namely Abelson murine leukemia(ABL1) gene from chromosome 9q34 and breakpoint cluster gene (BCR) on chromosome22q11. The resulting fusion gene called BCR-ABL1 in the constitutive activation of thetyrosine kinase activity of ABL1 (6). High resolution sequencing technologies may detectCNVs especially in the terminal regions of the translocations and inversions.(iii) The largest variation type causes anomalies in the count of chromosomes, especiallyaneuploidies. Trisomy of chromosome 21 leading to Down Syndrome is an example for suchaberrations.Genomics may be considered as a tool set of molecular applications. A proper tool shouldbe selected to detect the particular variation that may be associated with the disease. Everygenomic technique has its limitations and advantages to detect a particular variation subtype inthe genome. For example, a balanced inversion will not be detected with a genomic techniquedeveloped for detecting only CNVs. DNA variations are also grouped according to their tissueof origin. Germline variations may be inherited to next generations, while somatic variationsoccur de novo in tissues other than the germline. Therefore, somatic variations are onlyfound in a subset of cells/tissues of an organism, which are not inherited to the succeedinggenerations. In cancer research, it is crucial to identify somatic only variations in tumor cellsvia comparing their presence in noncancerous tissue. Yet pathogenic germline variations incertain genes including BRCA1 may be associated with an increased risk of developing certaintypes of cancers. Especially in the presence of positive family history, identifying this kindof actionable variation is highly important to serve proper patient care (7). Thus, genomicsapproaches lead us to characterize the mutational landscapes for complex diseases such ascancer.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Seda SUSG ¨ UN, Barıs¸ SALMAN, Sibel Aylin U ¨ GUR ˘ ˙IS¸ER˙I 179Genomic scale genetic approaches include array based technologies, next generationsequencing and optical mapping. SNP arrays and array Comparative Genomic Hybridization(aCGH) give the opportunity to mainly analyze genome wide structural variations. SNP arraysadditionally can be used for genotyping to perform loss-of-heterozygosity (LOH) analysis andgenome-wide association studies (GWAS) in complex diseases (8, 9). In this chapter, the termNGS will be used as an umbrella term for all massively parallel sequencing technologies.Essentially all NGS technologies are different from each other when variables such as thechemistry, instrument and/or targeted regions are considered. Most NGS approaches to dateare short-read, in which the regions to be sequenced are up to 500 base pairs. These shortreads are aligned to the reference genome and variations from the reference genome are calledand annotated in a separate file for further analyses. The NGS approach is named according tothe regions selected for sequencing: (i) Targeted/panel sequencing: certain genes are selectedfor NGS; (ii) Whole exome sequencing (WES): mainly the protein coding regions of genesare selected for NGS; (iii) Whole genome sequencing (WGS): Whole genome is sequenced.WGS should further be considered if it is performed with a short or long read technology.Long reads will aid better resolution of complex structural variations, repetitive regions andphasing of variants. It is also important to consider the genome annotation used for alignment.For example, approximately 140 and 170 de novo mutations (DNMs) have been reported forthe same individual using short and long read WGS, respectively. The number of DNMsapproaches 190, when the same long read WGS data is mapped to more complete humangenome reference performed by Telomere-to-telomere (T2T) consortium, instead of using theconventional hg38 reference genome (10).Genomic studies based on quantitative microarray technologies including aCGH and SNParrays can be used to analyze the genome especially for CNV detection. These high resolutiontechnologies rely on almost millions of probes that target specific DNA regions. SNP arrayshave the advantage of creating genotyping data along with signal intensity detection. Thisproperty of SNP arrays aids finding loci with loss of heterozygosity, which may be extremelyimportant in cancer (11). However, complex cytogenetic abnormalities, which may havea clinical impact may be overlooked by conventional techniques involving aCGH and SNParray. A complementary high-resolution genome-wide technique, known as optical genomemapping (OGM) can analyze high molecular weight DNA to detect large and complex genomicrearrangements including balanced translocations (12).Genomics studies have allowed large-scale analyses of copy number alterations, structuralvariants, and short nucleotide variations in various cancer types. These collective efforts led tothe generation of several publicly available data portals, including The Cancer Genome Atlas(TCGA) and the International Cancer Genome Consortium (ICGC) portal. Data availablethrough these databases have seeded cutting edge research on cancer biology (13). Table 1Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

180 BIG DATA / MULTIOMIC APPROACHES IN CANCER RESEARCHhas been curated to present links to valuable databases, knowledge bases and consortiums thatdistribute data, tools and/or educational materials for researchers, clinicians and patients toimprove patient care in cancer.Table 1: Curated list of databases, knowledge bases, consortiums and studies that produce and distributedata, tools and/or educational materials for cancer studiesTitle Abbrevation URL ImpactA database ofsomaticmutations innormal humantissuesSomaMutDB https://vijglab.einsteinmed.org/SomaMutDB/somatic mutations innormal human tissuesCancer DriverLogCanDL https://candl.osu.edu/catalog of potentiallyactionable cancermutationsCancer GenomeInterpreterCGI https://www.cancergenomeinterpreter.org/the uploaded list of tumorspecific variations isreannotated by CGI toidentify driver mutationsand alterations that may beused as biomarkers forpatient care.Catalogue ofSomaticMutations inCancerCOSMIC https://cancer.sanger.ac.uk/cosmic/impact of somaticmutations in humancancer.ClinicalInterpretation ofVariants inCancerCIViC https://civicdb.org/knowledgebase for variantinterpretation in cancerEuropean SocietyFor MedicalOncologyESMO https://www.esmo.orginternational organisationfor medical oncologyInternationalCancer GenomePortalICGC https://dcc.icgc.org/Cancer genomics datavisualization, analysis anddownload. Not updatedsince February, 2021My CancerGenome- https://www.mycancergenome.org/precision cancer medicineknowledge resource forclinicians, patients andresearchersOncologyKnowledge BaseOncoKBTM https://www.oncokb.org/curated knowledgebase ofsomatic mutations andstructural alterationspresent in tumorsPediatric Cancer(PeCan)Knowledge BasePeCan https://pecan.stjude.cloud/A genomics knowledgebase that presents curateddata of pediatric cancergenomes includingmutational, geneexpression and histologicaldata. Various tools for dataanalysis and vizualisiationare also present.PersonalizedCancer Therapy- https://pct.mdanderson.org/knowledge base forprecisiononcology thathelps clinicians andpatients to assess potentialtherapy options based onspecific tumor biomarkers.The Atlas ofGenetics andCytogenetics inOncology andHaematology- https://atlasgeneticsoncology.orga peer reviewed on-linejournal, encyclopaedia anddatabase in free access onthe Internet, devoted togenes, cytogenetics, andclinical entities in cancer,and cancer-prone diseasesCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Seda SUSG ¨ UN, Barıs¸ SALMAN, Sibel Aylin U ¨ GUR ˘ ˙IS¸ER˙I 181Table 1: ContinuedThe CancerGenome AtlasTCGA https://portal.gdc.cancer.gov/archive of genomic,epigenomic,transcriptomic, andproteomic data includingpan-cancer atlasThe cBioPortalfor CancerGenomicscBioPortal https://www.cbioportal.org/archive ofmultidimensional cancergenomics data setsThe CirculatingCell-freeGenome AtlasStudyCCGA https://clinicaltrials.gov/ct2/show/NCT02889978Ongoing study to profilecirculating cell-freenucleic acids (cfNAs)associated with variouscancer typesThe ClinicalKnowledgebaseCKB https://ckb.jax.org/knowledgebase fornterpreting cancergenomics with respect toprotein impact, therapies,and clinical trialsThe NationalComprehensiveCancerNetwork®NCCN® https://www.nccn.org/homemultidisciplinary teamfrom various cancercenters that develop anddistribute resorces forpatient careThe PrecisionMedicineKnowledgebasePMKB https://pmkb.weill.cornell.edu/knowledgebase for clinicalcancer variants andinterpretationsThe VariantInterpretation forCancerConsortiumVICC https://cancervariants.organ international expectconsortium working onstandardizing of cancervariant annotationTumorPortal - http://www.tumorportal.org/a portal for cancer genes,mutations and annotationsRecently, analyses of cell-free DNA (cfDNA) especially in the blood plasma usingaforementioned genomics applications have been of importance to researchers as the deathof growing tumor cells release tumor cell-derived DNA into the circulation. The fractionof cfDNA that is derived from tumor cells is named circulating tumor DNA (ctDNA). Thisapproach relying on ctDNA is also known as liquid biopsy and it may be used in earlyscreening and/or diagnosis of cancer, predicting treatment response and monitoring diseaseprogression (14). Similarly, tumor derived cell-free RNA (cfRNA) has been used to developeffective cancer biomarkers via transcriptomic profiling of cfRNA may detect effective cancerbiomarkers (15). However, due to the complexity of the cancer genome profile, innovativegenomics approaches are still required (16).2.2. EpigenomicsThe cells in a multicellular organism have essentially the same DNA content. Yet, variableexpression of this DNA controlled spatiotemporally determines both tissue specificity andflexibility of cells to respond to varying environmental conditions. This spastic utilizationof DNA depends on the regulation of the epigenome. The complex repertoire of chemicalcompounds, proteins and non-coding functional RNA molecules make up the cell epigenome.The epigenome collectively has several functions including deciding which genes will beturned on or off and controlling the cell specific production of proteins. These moleculesmost of the time mark the DNA without changing the actual base sequence of the DNA. TheseCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

182 BIG DATA / MULTIOMIC APPROACHES IN CANCER RESEARCHmarks can sometimes be inherited through cell divisions or inherited vertically from parentto offspring. Epigenome is also quite plastic; epigenetic marks can be written or erased uponenvironmental signals. DNA methylation at CpG loci, chemical alterations of histone tailssuch as acetylation and methylation, control of chromatin architecture and binding of RNAmolecules to DNA as in X-chromosome inactivation are examples of epigenomic regulation(17).Epigenomic applications mainly involve array or sequencing based technologies as ingenomics. Treating DNA with bisulfite (BS-DNA) results in conversion of all unmethylatedcytosines to uracil by deamination without any effect on methylated cytosines (5mC).BS-DNA then can be applied on arrays similar to SNP arrays to perform locus baseddifferential methylation analysis (18). Whole genome or targeted BS-DNA profile can alsobe obtained through a suitable NGS strategy. Long-read NGS involving single-moleculereal-time sequencing and nanopore sequencing can directly identify chemical modificationson DNA nucleotides including 5mC directly without any prior modifications unlike BS-DNAsequencing (19).Histone modifications are commonly detected by analyzing DNA-protein interactionsusing chromatin immunoprecipitation (ChIP). Antibodies with affinity to specific histonemodifications are used to capture associated DNA regions in ChIP assays. ChIP may befollowed with NGS (ChIP-Seq), which maps the genome-wide distribution of this specifichistone based epigenetic mark (1, 3). The most recent technique to reveal regions ofopen chromatin is known as Assay for Transposase Accessible Chromatin using Sequencing(ATAC-seq) (19).To date, epigenomics applications, evaluating genome-wide histone modification marksand DNA methylation profiles by comparing cancer and normal tissues has revealed anassociation between epigenetic deregulation and the onset, development, and progression ofcancer (3). Moreover, it has been enlightened that tumorigenesis is related to epigeneticreprogramming. Hence, genome-wide epigenetic differentiation including DNA methylation,histone modifications, and chromatin remodeling is one of the hallmarks of cancer. Inconclusion, epigenomics is an indispensable part of multi-omics approaches in cancer studies(20).2.3. TranscriptomicsTranscriptomics focuses on analysis of cell specific RNA profiles in a spatiotemporalmanner (21). Transcriptomic studies have traditionally focused solely on mRNA, butnow they have extended to cover other types of RNA molecules including long and shortnon-coding RNAs and circular RNAs. Transcriptome approaches have been initiated viausing RNA microarrays, which had several limitations such as dependence to prior knowledgeof genomic data to design probes and high background signal levels (1, 5). AdvancementsCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Seda SUSG ¨ UN, Barıs¸ SALMAN, Sibel Aylin U ¨ GUR ˘ ˙IS¸ER˙I 183in NGS technology allowed RNA sequencing (RNA-seq) to become a key approach to assesswhole-transcriptome in a high-throughput manner. RNA-seq can identify both coding andnoncoding RNA transcripts de novo, detect novel isoforms and give insights for cryptic splicing(2, 3). As RNA-seq both gives differential gene expression and genotyping data, it has been anindispensable tool in cancer research. Like NGS, RNA-seq is a general term that correspondsto a number of techniques. For example, as long-read RNA-seq can sequence full-lengthtranscripts, it enables proper quantification of isoform specific gene expression. Isoform levelmapping is limited in short-read RNA-seq (22). Most RNA-seq data is produced from cDNAlibraries. The ultimate long read direct RNA-seq can additionally detect nucleotide and endmodifications, which are important for RNA structure and function (23).The aforementioned advancements have led to aid deep comprehension of the humantranscriptome concept as well as the underlying mechanisms of complex diseases such ascancer (1, 21). In terms of cancer research, transcriptomics has provided tools to identifynovel fusion transcripts, alternative splicing products, and new noncoding RNAs, thus it hasenabled the understanding of tumorigenesis mechanisms and revealed potential treatmenttargets or diagnostic markers (24).2.4. ProteomicsProteomics yields information about all expressed proteins in the context of expressionprofile, post-translational modifications, their interactions, structures, and functions at agiven time in a cell, tissue, or organism. Reliable assessment of the proteome is quiteimportant since mainly proteins conduct cellular functions. Improvement in MS technologiesprovides high-throughput proteome profiles, however, there are still some limitations due tothe complexity and dynamicity of proteins (2, 3, 25).To date, individual proteomics studies in cancer have unveiled some biomarkers andtherapeutic targets for tumor growth and metastasis. Additionally, now there are variouscancer proteome databases worldwide, and this obtained massive data can be utilized to moreprecisely interrogate tumor classification, prognosis, prediction, and therapeutic targets (25)2.5. MetabolomicsMetabolites are defined as small molecules with size less than 1.5 kDa. Metabolomicsquantifies metabolites in cells, tissues, or organisms in high-throughput manner.Metabolomics studies need interdisciplinary work with metabolic biology, chemistry, andbioinformatics. As metabolites are the final output of the phenotype, metabolomics isas important as other omics in understanding the phenotypes of interest (26). Further,metabolomics profile is more diverse, and more complex physically and chemically thanother omics due to it containing various biological molecules (5).Metabolism is found to be dysregulated in cancer cells to accomplish the requirementsof uncontrolled proliferation. This altered metabolome profile can be used as biomarkers forCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

184 BIG DATA / MULTIOMIC APPROACHES IN CANCER RESEARCHdiagnosis, prognosis, and precision medicine treatments in cancer. Therefore, metabolomicsstudies have become valuable and precise tools to determine drivers of tumorigenesis andcancer biomarkers (26, 27).3. Multi-omics Approaches to Cancer ResearchOver decades after determining the central dogma of molecular biology, it is now knownthat the information flow of DNA-RNA-protein is not static and straightforward. Therefore,focusing on just one biological data may be insufficient for complex diseases such as cancer.For instance, studying the epigenome along with the transcriptome will give better insights oncontrol of gene expression. Several RNA based mechanisms including alternative splicing,regulation of mRNA stability via target miRNAs and nonsense-mediated mRNA decay areonly functionally validated when proteomics data is studied in parallel. Genome basedstudies, namely genomics, transcriptomics and DNA methylation level based epigenomics willoverlook the proteome and specific posttranslational modifications. Taken together, insteadof a single dimensional approach to biological processes, multi-omics can be considered asvarious instruments performing in the orchestra. In this context, the multi-omics approachyields such high-dimensional information (3, 28). So far, merged multi-omics datasets havebeen successful in numerous clinical cancer studies and have aided to determine clinicalsubtypes of cancer, cancer pathophysiology, drug resistance or target discovery, revealbiomarkers thanks to unbiased and rapid measurements of biological datasets in a singleexperiment (28).There are different approaches to multi-omics, Hasin and colleagues have categorizedthem into three groups “genome first”, “phenotype first”, and “environment first” approachesaccording to the initial reason for the research. In the “genome first” approach, firstly geneticvariants that contribute to diseases are defined. Based on that defined causal variants throughgenomics, additional omics data can be used to understand how this gene and involvedpathway led to phenotype. Moreover, GWAS generally identifies locus related to disease, butit cannot determine the main causal gene. In this instance, within GWAS locus there are manycandidate genes, and causative genes can be prioritized by using other omics data such astranscriptomics or epigenomics. In the “phenotype first” approach, multi-omics datasets aremerged to reveal contributors of a phenotype of interest. Obtained data that include alteredpathways and factors give insights to us into disease nature. In brief, it may be summarizedas ”genome first” is an inductive approach while ”phenotype first” is deductive approach. Onthe other hand, in the “environment first” approach, an environmental factor such as diet is putat the center of research. In this approach, predominantly animal models are used to revealreliable effects of factors on phenotype. After the animal is exposed to the interested factor,multi-omics datasets are evaluated to figure out the effect of that factor on disease (2).Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Seda SUSG ¨ UN, Barıs¸ SALMAN, Sibel Aylin U ¨ GUR ˘ ˙IS¸ER˙I 1853.1. Single-Cell Omics in Cancer ResearchCancer is a heterogeneous disease and cells within the tumor microenvironment can havedistinct genetic and epigenetic alterations or different functions. The tumor microenvironmentrefers to the surroundings of cancer cells along with immune cells, stromal cells, and manyothers. The tumor microenvironment plays a critical role in tumor growth, progression, andresponse to therapy. Understanding the tumor microenvironment is essential for developingeffective cancer treatments that can target specific components of this complex ecosystem.Therefore, traditional omics approaches which examine average information of whole cellsobtained from patient samples may overlook molecular features of rare cell populationsthat could be critical for tumor growth and response to therapy. Thanks to advancementsof single-cell techniques, the multi-omics profile of the tumor microenvironment can bedelineated at a single-cell resolution (29, 30).Despite the enormous contributions of the multi-omics approach to understanding cancerbiology, nowadays, the single-cell multi-omics approach has emerged as a valuable trend inrecent cancer research. Developing such innovative techniques will keep providing crucialinsights into cancer biology and will result in the developing of new approaches to cancerdiagnosis and treatment.4. Differentiating germline and somatic variations in cancer tissueOmics technologies, especially genomics may be used to discriminate between tumorspecific somatic variations from germ-line variations. NGS based analysis of matched samplesfrom tumor and normal paired analyses will reveal tumor related somatic alterations for sure.Additionally, tumor only approaches may overlook germline variations in cancer-predisposinggenes, which may be important both for their clinical impact and genetic counseling (31).Variant allele frequency (VAF) for a germline variant can in theory be either 50%(heterozygous) or 100 % (homozygous or hemizygous). Tumor associated somatic variationson the other hand create a level of mosaicism for the isolated biological sample and mayhave varied VAF levels. Moreover, the VAF level will drop significantly in highly targetedapproaches such as liquid biopsy, tumor subclones and single cell analysis. ConventionalNGS applications and related bioinformatic tools may fail to detect these low-VAF somaticvariations (32).Another challenge is to classify detected somatic variations according to guidelines. Forgermline variants, American College of Medical Genetics (ACMG) guidelines have been usedextensively to collect variant related evidence via protein level impact, familial segregationdata, functional studies, allele frequency, phasing and computational modeling (33). Theseevidences collectively locate the variant into one of the five classes: pathogenic, likelypathogenic, variant of unknown significance (VUS), likely benign, benign. Somatic variants incancer are classified further for their significance in cancer diagnosis, prognosis, and treatmentCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

186 BIG DATA / MULTIOMIC APPROACHES IN CANCER RESEARCHby another guideline published by Association for Molecular Pathology (AMP) (34). TheAMP guideline classifies the variants into four tiers, named I to IV, with further evidencecategorization from A to D. Tier I is variants with strong clinical significance with pieces ofevidence A and B; tier II is variants with potential clinical significance with evidence C andD; tier III is variants with unknown clinical significance (VUCS); tier IV is variants classifiedas benign or likely benign. Evidence level A categorizes variants that have FDA-approvedtherapies, and in the professional guidelines; evidence level B categorizes variants predictingresponse or resistance to therapies that have extensive cohort studies and consensus of expertsin the field; level C categorizes variants that have FDA-approved treatments for different tumortype or smaller studies and consensus; level D classifies variants that have preclinical trialsand case reports without consensus.Somatic variants in cancer are further categorized to be either driver or passengermutations. Genomic instability together with a high mutation rate results in accumulationof many variants in tumor genomes. Most of these variants are passengers as they are notrelated to the cancer phenotype. Rare driver mutations give cells the evolutionary advantageof tumor initiation, growth, survival and proliferation (35). Differentiating between driverand passenger mutations has been one of the challenging questions in cancer biology. Severalcomputational and experimental methods may be used to detect driver mutations from NGSdata. Initially, a driver gene should be found more frequently to be mutated in differentgenomes compared to random passenger mutations. If it is a tumor subtype hallmark drivermutation, obviously it is expected to be mutated highly frequently in multiple unrelatedsamples from the same cancer type. Secondly, the functional impact of the variant on proteinshould probably be significant which can be analyzed by conventional algorithms. Third,machine-learning based methods can come up with predictive results. Finally, the biologicalsignificance of the candidate driver gene/mutation can be supported by functional studiesand/or in silico pathway analyses (36).5. ConclusionMulti-omic technologies have the potential to revolutionize our understanding ofbiological systems and provide new insights into disease mechanisms, drug development,and personalized medicine. However, the integration of multiple types of omic data and thestandardization of data collection and analysis methods remain significant challenges thatmust be overcome to fully realize the potential of these technologies.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

CANCER: FROM GENOMICS TO PHARMACEUTICSREFERENCES1. Dai X, Shen L. Advances and Trends in Omics Technology Development. Front Med(Lausanne). 2022;9:911861.2. Hasin Y, Seldin M, Lusis A. Multi-omics approaches to disease. Genome Biol.2017;18(1):83.3. Chakraborty S, Hosen MI, Ahmed M, Shekhar HU. Onco-Multi-OMICS Approach: ANew Frontier in Cancer Research. Biomed Res Int. 2018;2018:9836256.4. Conesa A, Beck S. Making multi-omics data accessible to researchers. Sci Data.2019;6(1):251.5. Horgan RP, Kenny LC. ‘Omic’ technologies: genomics, transcriptomics, proteomicsand metabolomics. The Obstetrician & Gynaecologist. 2011;13(3):189-95.6. Haider MZ, Anwer F. Genetics, Philadelphia Chromosome. [Updated 2022 Jul 18]. In:StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2023 Jan-. Availablefrom: https://www.ncbi.nlm.nih.gov/books/NBK560689/7. Miller DT, Lee K, Chung WK, Gordon AS, Herman GE, Klein TE, et al. ACMG SFv3.0 list for reporting of secondary findings in clinical exome and genome sequencing: apolicy statement of the American College of Medical Genetics and Genomics (ACMG).Genet Med. 2021 Aug;23(8):1381-1390.8. Tam V, Patel N, Turcotte M, Bosse Y, Pare G, Meyre D. Benefits and limitations ofgenome-wide association studies. Nat Rev Genet. 2019;20(8):467-84.9. Mao X, Young BD, Lu YJ. The application of single nucleotide polymorphismmicroarrays in cancer research. Curr Genomics. 2007;8(4):219-28.10. Noyes MD, Harvey WT, Porubsky D, Sulovari A, Li R, Rose NR, et al. Familiallong-read sequencing increases yield of de novo mutations. Am J Hum Genet. 2022Apr 7;109(4):631-646.11. Ryland GL, Doyle MA, Goode D, Boyle SE, Choong DYH, Rowley SM, et al. Loss ofheterozygosity: what is it good for?. BMC Med Genomics 8, 45 (2015).12. Lestringant V, Duployez N, Penther D, Luquet I, Derrieux C, Lutun A, et al. Opticalgenome mapping, a promising alternative to gold standard cytogenetic approachesCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

188 BIG DATA / MULTIOMIC APPROACHES IN CANCER RESEARCHin a series of acute lymphoblastic leukemias. Genes Chromosomes Cancer. 2021Oct;60(10):657-667.13. Fonseca-Montano MA, Blancas S, Herrera-Montalvo LA, Hidalgo-Miranda A. CancerGenomics. Arch Med Res. 2022;53(8):723-31.14. Yan YY, Guo QR, Wang FH, Adhikari R, Zhu ZY, Zhang HY, et al. Cell-Free DNA:Hope and Potential Application in Cancer. Front Cell Dev Biol. 2021 Feb 22;9:639233.15. Larson MH, Pan W, Kim HJ, Mauntz RE, Stuart SM, Pimenrel M, et al. A comprehensivecharacterization of the cell-free transcriptome reveals tissue- and subtype-specificbiomarkers for cancer detection. Nat Commun 12, 2357 (2021).16. Berger MF, Mardis ER. The emerging clinical relevance of genomics in cancer medicine.Nat Rev Clin Oncol. 2018;15(6):353-65.17. Cavalli G, Heard E. Advances in epigenetics link genetics to the environment and disease.Nature. 2019 Jul;571(7766):489-499.18. Ozdemir O, Egemen E, Ugur Iseri SA, Sezerman OU, Bebek N, Baykan B, etal. Identification of epilepsy related pathways using genome-wide DNA methylationmeasures: A trio-based approach. PLoS One. 2019 Feb 8;14(2):e0211917.19. Mehrmohamadi M, Sepehri MH, Nazer N, Norouzi MR. A Comparative Overview ofEpigenomic Profiling Methods. Front Cell Dev Biol. 2021 Jul 22;9:714687.20. Carlberg C, Velleuer E, SpringerLink. Cancer Biology: How Science Works. 1st 2021.ed. Cham: Springer International Publishing : Imprint: Springer; 2021.21. Williams CG, Lee HJ, Asatsuma T, Vento-Tormo R, Haque A. An introduction to spatialtranscriptomics for biomedical research. Genome Med. 2022;14(1):68.22. Stark R, Grzelak M, Hadfield J. RNA sequencing: the teenage years. Nat Rev Genet.2019 Nov;20(11):631-656.23. Jain M, Abu-Shumays R, Olsen HE, Akeson M. Advances in nanopore direct RNAsequencing. Nat Methods. 2022 Oct;19(10):1160-1164.24. Tsimberidou AM, Fountzilas E, Bleris L, Kurzrock R. Transcriptomics and solid tumors:The next frontier in precision cancer medicine. Semin Cancer Biol. 2022;84:50-9.25. Kwon YW, Jo HS, Bae S, Seo Y, Song P, Song M, et al. Application of Proteomicsin Cancer: Recent Trends and Approaches for Biomarkers Discovery. Front Med(Lausanne). 2021;8:747333.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

Seda SUSG ¨ UN, Barıs¸ SALMAN, Sibel Aylin U ¨ GUR ˘ ˙IS¸ER˙I 18926. Cheung PK, Ma MH, Tse HF, Yeung KF, Tsang HF, Chu MKM, et al. The applicationsof metabolomics in the molecular diagnostics of cancer. Expert Rev Mol Diagn.2019;19(9):785-93.27. Schmidt DR, Patel R, Kirsch DG, Lewis CA, Vander Heiden MG, Locasale JW.Metabolomics in cancer research and emerging applications in clinical oncology. CACancer J Clin. 2021;71(4):333-58.28. Heo YJ, Hwa C, Lee GH, Park JM, An JY. Integrative Multi-Omics Approachesin Cancer Research: From Biological Networks to Clinical Subtypes. Mol Cells.2021;44(7):433-43.29. Liu J, Qu S, Zhang T, Gao Y, Shi H, Song K, et al. Applications of Single-Cell Omicsin Tumor Immunology. Front Immunol. 2021;12:697412.30. Nam AS, Chaligne R, Landau DA. Integrating genetic and non-genetic determinants ofcancer evolution by single-cell multi-omics. Nat Rev Genet. 2021;22(1):3-18.31. Jones S, Anagnostou V, Lytle K, Parpart-Li S, Nesselbush M, Riley DR, et al.Personalized genomic analyses for cancer mutation discovery and interpretation. SciTransl Med. 2015 Apr 15;7(283):283ra53.32. Kim J, Kim D, Lim JS, Maeng JH, Son H, Kang HC, et al. The use of technicalreplication for detection of low-level somatic mutations in next-generation sequencing.Nat Commun. 2019 Mar 5;10(1):1047. doi: 10.1038/s41467-019-09026-y.33. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards andguidelines for the interpretation of sequence variants: a joint consensus recommendationof the American College of Medical Genetics and Genomics and the Association forMolecular Pathology. Genet Med. 2015 May;17(5):405-24.34. Li MM, Datto M, Duncavage EJ, Kulkarni S, Lindeman NI, Roy S, et al. Standards andGuidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A JointConsensus Recommendation of the Association for Molecular Pathology, AmericanSociety of Clinical Oncology, and College of American Pathologists. J Mol Diagn.2017 Jan;19(1):4-23. doi: 10.1016/j.jmoldx.2016.10.002. PMID: 27993330; PMCID:PMC5707196.35. Martincorena I, Campbell PJ. Somatic mutation in cancer and normal cells. Science.2015 Sep 25;349(6255):1483-9.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

190 BIG DATA / MULTIOMIC APPROACHES IN CANCER RESEARCH36. Zhang J, Liu J, Sun J, Chen C, Foltz G, Lin B. Identifying driver mutations fromsequencing data of heterogeneous tumors in the era of personalized genome sequencing.Brief Bioinform. 2014 Mar;15(2):244-55.Cancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.

CANCER: FROM GENOMICS TO PHARMACEUTICSCHAPTER 8NEW THERAPEUTIC APPROACHES IN GENOME˙Ildeniz USLU- BIC¸ AK1,2, Bus¸ra YAS¸A-C¸ EV ¨˙IK3,4, Selc¸uk SOZER TOKDEM ¨ ˙IR51PhD, ˙Istanbul University, Institute of Graduate Studies in Health Sciences, Genetics Department, ˙Istanbul, T¨urkiye2˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Genetics Department, ˙Istanbul, T¨urkiyeE-mail: [email protected] Candidate, ˙Istanbul University, Institute of Graduate Studies in Health Sciences, Genetics Department,˙Istanbul, T¨urkiye4˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Genetics Department, ˙Istanbul, T¨urkiyeE-mail: [email protected]. Dr., ˙Istanbul University, Aziz Sancar Institute of Experimental Medicine, Genetics Department, ˙Istanbul,T¨urkiyeE-mail: ssozer@˙Istanbul.edu.trDOI: 10.26650/B/LSB28LSB48LSB56.2024.019.008ABSTRACTTo date, science has dramatically resolved many unknowns about the pathobiology of diseases and successfullycurated many of them. Even the most terrible illnesses have treatment modalities now. The power of scienceand technology finds instant solutions to evolving needs and requirements by eradicating diseases. More to fight.The rapid advancement of genome editing in recent years has changed the study of the human genome, allowingresearchers to gain a deeper understanding of how a single gene product contributes to a site of action of an organism.Delivering the editing machinery in situ, which effectively adds, deletes, and ”corrects” genes and carries out otherprecise genomic alterations, allows genome editing. The ultimate goal of such complex and troublesome gene editingcapability is to treat diseases. Near future, easy accessibility to such personalized treatment options in the clinic willbe for everyone.Keywords: Genome Editing, Gene Therapy, Crispr/Cas Systems, Gene Delivery SystemsCancer: from Genomics to Pharmaceutics, edited by Zeynep Karakas, et al., Istanbul University Press, 2024. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/uitm-ebooks/detail.action?docID=31789562.Created from uitm-ebooks on 2025-12-02 14:42:18. Copyright © 2024. Istanbul University Press. All rights reserved.