利用三阶段随机模型研究慢性髓性白血病的发病年龄和检测方法

IF 1.3 4区 数学 Q3 BIOLOGY Journal of Biological Systems Pub Date : 2024-04-20 DOI:10.1142/s0218339024500190
SURYADEEPTO NAG, ANANDA SHIKHARA BHAT, SIDDHARTHA P. CHAKRABARTY
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引用次数: 0

摘要

慢性髓性白血病(CML)是一种双相恶性克隆性疾病,其发展过程为先进入慢性期,此时细胞只具有增殖能力,然后进入爆发期,此时细胞具有自我更新能力。众所周知,费城染色体(包含 BCR-ABL 融合基因)是 "CML 的标志"。然而,实证研究表明,仅仅存在 BCR-ABL 基因可能并不是发展成 CML 的充分条件,可能还需要与肿瘤抑制因子相关的进一步修饰。因此,我们建立了一个 CML 进展的三突变随机模型,三个阶段分别对应 BCR-ABL 存在的非恶性细胞、慢性期的恶性细胞和爆发期的恶性细胞。我们证明该模型的预测结果与美国的年龄发病率数据一致。最后,我们建立了一个框架,用于从检测到癌症的时间开始追溯估算恶性肿瘤的发病时间。
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STUDYING THE AGE OF ONSET AND DETECTION OF CHRONIC MYELOID LEUKEMIA USING A THREE-STAGE STOCHASTIC MODEL

Chronic Myeloid Leukemia (CML) is a biphasic malignant clonal disorder that progresses, first with a chronic phase, where the cells have enhanced proliferation only, and then to a blast phase, where the cells have the ability of self-renewal. It is well recognized that the Philadelphia chromosome (which contains the BCR-ABL fusion gene) is the “hallmark of CML”. However, empirical studies have shown that the mere presence of BCR-ABL may not be a sufficient condition for the development of CML, and further modifications related to tumor suppressors may be necessary. Accordingly, we develop a three-mutation stochastic model of CML progression, with the three stages corresponding to the non-malignant cells with BCR-ABL presence, the malignant cells in the chronic phase, and the malignant cells in the blast phase. We demonstrate that the model predictions agree with age incidence data from the United States. Finally, we develop a framework for the retrospective estimation of the time of onset of malignancy, from the time of detection of the cancer.

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来源期刊
CiteScore
2.80
自引率
12.50%
发文量
31
审稿时长
1 months
期刊介绍: The Journal of Biological Systems is published quarterly. The goal of the Journal is to promote interdisciplinary approaches in Biology and in Medicine, and the study of biological situations with a variety of tools, including mathematical and general systems methods. The Journal solicits original research papers and survey articles in areas that include (but are not limited to): Complex systems studies; isomorphies; nonlinear dynamics; entropy; mathematical tools and systems theories with applications in Biology and Medicine. Interdisciplinary approaches in Biology and Medicine; transfer of methods from one discipline to another; integration of biological levels, from atomic to molecular, macromolecular, cellular, and organic levels; animal biology; plant biology. Environmental studies; relationships between individuals, populations, communities and ecosystems; bioeconomics, management of renewable resources; hierarchy theory; integration of spatial and time scales. Evolutionary biology; co-evolutions; genetics and evolution; branching processes and phyllotaxis. Medical systems; physiology; cardiac modeling; computer models in Medicine; cancer research; epidemiology. Numerical simulations and computations; numerical study and analysis of biological data. Epistemology; history of science. The journal will also publish book reviews.
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