Multidisciplinary insight into clonal expansion of HTLV-1–infected cells in adult T-cell leukemia via modeling by deterministic finite automata coupled with high-throughput sequencing

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• 作者：Amir Farmanbar ; Sanaz Firouzi ; Sung-Joon Park ; Kenta Nakai…
• 关键词：Mathematical computational modeling ; Deterministic finite state automata (DFA) ; State ; transition diagram ; Adult T ; cell leukemia ; Human T ; cell leukemia virus ype ; 1 ; Integration site ; Clonal expansion ; Next ; generation sequencing
• 刊名：BMC Medical Genomics
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：10
• 期：1
• 全文大小：903KB
• 刊物主题：Human Genetics; Microarrays; Gene Expression;
• 出版者：BioMed Central
• ISSN：1755-8794
• 卷排序：10

文摘

BackgroundClonal expansion of leukemic cells leads to onset of adult T-cell leukemia (ATL), an aggressive lymphoid malignancy with a very poor prognosis. Infection with human T-cell leukemia virus type-1 (HTLV-1) is the direct cause of ATL onset, and integration of HTLV-1 into the human genome is essential for clonal expansion of leukemic cells. Therefore, monitoring clonal expansion of HTLV-1–infected cells via isolation of integration sites assists in analyzing infected individuals from early infection to the final stage of ATL development. However, because of the complex nature of clonal expansion, the underlying mechanisms have yet to be clarified. Combining computational/mathematical modeling with experimental and clinical data of integration site–based clonality analysis derived from next generation sequencing technologies provides an appropriate strategy to achieve a better understanding of ATL development.