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在克隆扩增过程中,随着转移驱动基因的改变,肿瘤转移的演变。

The evolution of tumor metastasis during clonal expansion with alterations in metastasis driver genes.

作者信息

Yamamoto Kimiyo N, Nakamura Akira, Haeno Hiroshi

机构信息

Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka 812-8581, Japan.

Department of Radiation Oncology and Image-Applied Therapy, Kyoto University, Kyoto, Japan.

出版信息

Sci Rep. 2015 Oct 30;5:15886. doi: 10.1038/srep15886.

Abstract

Metastasis is a leading cause of cancer-related deaths. Carcinoma generally initiates at a specific organ as a primary tumor, but eventually metastasizes and forms tumor sites in other organs. In this report, we developed a mathematical model of cancer progression with alterations in metastasis-related genes. In cases in which tumor cells acquire metastatic ability through two steps of genetic alterations, we derive formulas for the probability, the expected number, and the distribution of the number of metastases. Moreover, we investigate practical pancreatic cancer disease progression in cases in which both one and two steps of genetic alterations are responsible for metastatic formation. Importantly, we derive a mathematical formula for the survival outcome validated using clinical data as well as direct simulations. Our model provides theoretical insights into how invisible metastases distribute upon diagnosis with respect to growth rates, (epi)genetic alteration rates, metastatic rate, and detection size. Prediction of survival outcome using the formula is of clinical importance in terms of determining therapeutic strategies.

摘要

转移是癌症相关死亡的主要原因。癌通常在特定器官作为原发性肿瘤起始,但最终会发生转移并在其他器官形成肿瘤位点。在本报告中,我们开发了一个具有转移相关基因改变的癌症进展数学模型。在肿瘤细胞通过两步基因改变获得转移能力的情况下,我们推导了转移概率、预期转移数以及转移灶数量分布的公式。此外,我们研究了在一步和两步基因改变均导致转移形成的情况下胰腺癌的实际疾病进展。重要的是,我们推导了一个使用临床数据以及直接模拟验证的生存结果数学公式。我们的模型为关于生长速率、(表观)遗传改变率、转移率和检测大小的诊断时不可见转移灶如何分布提供了理论见解。使用该公式预测生存结果在确定治疗策略方面具有临床重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e7c/4626809/72aa7b667875/srep15886-f1.jpg

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