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 DNA methylation in T-ALL
   Additionally, MS-MLPA has the advantage of requiring lit- tle DNA and does not require DNA bisulfite conversion or immunoprecipitation. MS-MLPA is readily compatible with clinical routine and could enhance prognostication and precision medicine.
However, array analysis or methylation analysis at the whole genome level would be relevant in T-ALL to gain information and investigate how aberrant methylation patterns are involved in leukemogenesis. We have observed that aberrant methylation profiles were mostly associated with the driver oncogene involved. In particu- lar, a hypoM subgroup with unfavorable outcome is main- ly enriched in SIL-TAL1+ cases and also in cases negative for the main oncogenes TLX1, TLX3, SIL-TAL1 and HOXA. Deciphering the molecular mechanism of aber- rant methylation and the relationship with driver onco- genes could identify new deregulated pathways for adapt- ed-therapy.
Acknowledgments
We thank all French, Swiss and Belgian participants, clini- cians, biologists and clinical research assistants, in the LALA-94 and GRAALL 2003-2005 trials, for collecting and providing data and samples.
Funding
MeDIP experiments were supported by the INCA-project PAIR-Lymphomes. Work in SS laboratory was supported by Ligue contre le Cancer (Equipe labellisée). Work in the Necker hematology department and SS laboratory was supported by grants from ITMO (Institut Thématique Multi-Organisme) épigénétique et cancer. The GRAALL was supported by grants P0200701 and P030425/AOM03081 from Le Programme Hospitalier de Recherche Clinique, Ministère de l’Emploi et de la Solidarité, France and the Swiss Federal Government in Switzerland. AT was supported by a grant from the French pro- gram CARPEM (CAncer Research for PErsonalized Medicine).
References
1. Chessells JM, Hall E, Prentice HG, et al. The impact of age on outcome in lymphoblastic leukaemia; MRC UKALL X and XA com- pared: a report from the MRC Paediatric and Adult Working Parties. Leukemia. 1998; 12(4):463-473.
2. Teitell MA, Pandolfi PP. Molecular genetics of acute lymphoblastic leukemia. Ann Rev Pathol. 2009;4:175-198.
3. Van Vlierberghe P, Pieters R, Beverloo HB, Meijerink JP. Molecular-genetic insights in paediatric T-cell acute lymphoblastic leukaemia. Br J Haematol. 2008;143(2):153- 168.
4. Ferrando AA, Neuberg DS, Staunton J, et al. Gene expression signatures define novel oncogenic pathways in T cell acute lym- phoblastic leukemia. Cancer Cell. 2002; 1(1):75-87.
5. Homminga I, Pieters R, Langerak AW, et al. Integrated transcript and genome analyses reveal NKX2-1 and MEF2C as potential oncogenes in T cell acute lymphoblastic leukemia. Cancer Cell. 2011;19(4):484-497.
6. Soulier J, Clappier E, Cayuela JM, et al. HOXA genes are included in genetic and biologic networks defining human acute T- cell leukemia (T-ALL). Blood. 2005; 106(1):274-286.
7. Flavahan WA, Gaskell E, Bernstein BE. Epigenetic plasticity and the hallmarks of cancer. Science. 2017;357(6348).
8. Nordlund J, Backlin CL, Wahlberg P, et al. Genome-wide signatures of differential DNA methylation in pediatric acute lym- phoblastic leukemia. Genome Biol. 2013; 14(9):r105.
9. Borssen M, Haider Z, Landfors M, et al. DNA methylation adds prognostic value to minimal residual disease status in pediatric T-cell acute lymphoblastic leukemia. Pediatr Blood Cancer. 2016;63(7):1185-1192.
10. Borssen M, Palmqvist L, Karrman K, et al. Promoter DNA methylation pattern identi-
fies prognostic subgroups in childhood T- cell acute lymphoblastic leukemia. PLoS One. 2013;8(6):e65373.
11. Haider Z, Larsson P, Landfors M, et al. An integrated transcriptome analysis in T-cell acute lymphoblastic leukemia links DNA methylation subgroups to dysregulated TAL1 and ANTP homeobox gene expres- sion. Cancer Med. 2019;8(1):311-324.
12. Huguet F, Leguay T, Raffoux E, et al. Pediatric-inspired therapy in adults with Philadelphia chromosome-negative acute lymphoblastic leukemia: the GRAALL-2003 study. J Clin Oncol. 2009;27(6):911-918.
13. Maury S, Chevret S, Thomas X, et al. Rituximab in B-lineage adult acute lym- phoblastic leukemia. N Engl J Med. 2016; 375(11):1044-1053.
14. Asnafi V, Buzyn A, Le Noir S, et al. NOTCH1/FBXW7 mutation identifies a large subgroup with favorable outcome in adult T-cell acute lymphoblastic leukemia (T-ALL): a Group for Research on Adult Acute Lymphoblastic Leukemia (GRAALL) study. Blood. 2009;113(17):3918-3924.
15. Bergeron J, Clappier E, Radford I, et al. Prognostic and oncogenic relevance of TLX1/HOX11 expression level in T-ALLs. Blood. 2007;110(7):2324-2330.
16. Bond J, Marchand T, Touzart A, et al. An early thymic precursor phenotype predicts outcome exclusively in HOXA-overexpress- ing adult T-cell acute lymphoblastic leukemia: a Group for Research in Adult Acute Lymphoblastic Leukemia study. Haematologica. 2016;101(6):732-740.
17. Jia J, Pekowska A, Jaeger S, et al. Assessing the efficiency and significance of Methylated DNA Immunoprecipitation (MeDIP) assays in using in vitro methylated genomic DNA. BMC Res Notes. 2010;3:240.
18. Cornen S, Guille A, Adelaide J, et al. Candidate luminal B breast cancer genes identified by genome, gene expression and DNA methylation profiling. PLoS One. 2014;9(1):e81843.
19. Benoukraf T, Cauchy P, Fenouil R, et al. CoCAS: a ChIP-on-chip analysis suite. Bioinformatics. 2009;25(7):954-955.
20. Saeed AI, Sharov V, White J, et al. TM4: a free, open-source system for microarray data management and analysis. Biotechniques. 2003;34(2):374-378.
21. Reich M, Tabor T, Liefeld T, et al. The GenePattern Notebook environment. Cell Syst. 2017;5(2):149-151.
22. Trinquand A, Tanguy-Schmidt A, Ben Abdelali R, et al. Toward a NOTCH1/FBXW7/RAS/PTEN-based onco- genetic risk classification of adult T-cell acute lymphoblastic leukemia: a group for research in adult acute lymphoblastic leukemia study. J Clin Oncol. 2013; 31(34):4333-4342.
23. Castro M, Grau L, Puerta P, et al. Multiplexed methylation profiles of tumor suppressor genes and clinical outcome in lung cancer. J Transl Med. 2010;8:86.
24. Molinari C, Casadio V, Foca F, et al. Gene methylation in rectal cancer: predictive marker of response to chemoradiotherapy? J Cell Physiol. 2013;228(12):2343-2349.
25. Moelans CB, de Groot JS, Pan X, van der Wall E, van Diest PJ. Clonal intratumor het- erogeneity of promoter hypermethylation in breast cancer by MS-MLPA. Mod Pathol. 2014;27(6):869-874.
26. Garcia-Baquero R, Puerta P, Beltran M, et al. Methylation of tumor suppressor genes in a novel panel predicts clinical outcome in paraffin-embedded bladder tumors. Tumour Biol. 2014;35(6):5777-5786.
27. Gurioli G, Salvi S, Martignano F, et al. Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach. J Transl Med. 2016;14(1):249.
28. Jouinot A, Assie G, Libe R, et al. DNA Methylation is an independent prognostic marker of survival in adrenocortical cancer. J Clin Endocrinol Metab. 2017;1 02(3):923- 932.
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