Foo Jasmine, Leder Kevin, Ryser Marc D
School of Mathematics, University of Minnesota, Minneapolis, MN, United States.
Industrial and Systems Engineering, University of Minnesota, Minneapolis, MN, United States.
J Theor Biol. 2014 Aug 21;355:170-84. doi: 10.1016/j.jtbi.2014.02.042. Epub 2014 Apr 13.
Primary tumors often emerge within genetically altered fields of premalignant cells that appear histologically normal but have a high chance of progression to malignancy. Clinical observations have suggested that these premalignant fields pose high risks for emergence of recurrent tumors if left behind after surgical removal of the primary tumor. In this work, we develop a spatio-temporal stochastic model of epithelial carcinogenesis, combining cellular dynamics with a general framework for multi-stage genetic progression to cancer. Using the model, we investigate how various properties of the premalignant fields depend on microscopic cellular properties of the tissue. In particular, we provide analytic results for the size-distribution of the histologically undetectable premalignant fields at the time of diagnosis, and investigate how the extent and the geometry of these fields depend upon key groups of parameters associated with the tissue and genetic pathways. We also derive analytical results for the relative risks of local vs. distant secondary tumors for different parameter regimes, a critical aspect for the optimal choice of post-operative therapy in carcinoma patients. This study contributes to a growing literature seeking to obtain a quantitative understanding of the spatial dynamics in cancer initiation.
原发性肿瘤通常出现在组织学上看似正常但有很高进展为恶性肿瘤几率的癌前细胞的基因改变区域内。临床观察表明,如果在手术切除原发性肿瘤后遗留这些癌前区域,它们会对复发性肿瘤的出现构成高风险。在这项工作中,我们开发了一种上皮癌发生的时空随机模型,将细胞动力学与癌症多阶段基因进展的通用框架相结合。使用该模型,我们研究癌前区域的各种特性如何依赖于组织的微观细胞特性。特别是,我们给出了诊断时组织学上不可检测的癌前区域大小分布的分析结果,并研究这些区域的范围和几何形状如何取决于与组织和遗传途径相关的关键参数组。我们还针对不同参数范围得出了局部与远处继发性肿瘤相对风险的分析结果,这是癌症患者术后治疗最佳选择的一个关键方面。这项研究有助于越来越多旨在定量理解癌症起始空间动态的文献。