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理解癌症发生率的单峰分布:癌症的发生需要两个因素。

Understanding the unimodal distributions of cancer occurrence rates: it takes two factors for a cancer to occur.

机构信息

Cancer Systems Biology Center, China-Japan Union Hospital of Jilin University.

Zhejiang Sci-Tech University.

出版信息

Brief Bioinform. 2021 Jul 20;22(4). doi: 10.1093/bib/bbaa349.

Abstract

Data from the SEER reports reveal that the occurrence rate of a cancer type generally follows a unimodal distribution over age, peaking at an age that is cancer-type specific and ranges from 30+ through 70+. Previous studies attribute such bell-shaped distributions to the reduced proliferative potential in senior years but fail to explain why some cancers have their occurrence peak at 30+ or 40+. We present a computational model to offer a new explanation to such distributions. The model uses two factors to explain the observed age-dependent cancer occurrence rates: cancer risk of an organ and the availability level of the growth signals in circulation needed by a cancer type, with the former increasing and the latter decreasing with age. Regression analyses were conducted of known occurrence rates against such factors for triple negative breast cancer, testicular cancer and cervical cancer; and all achieved highly tight fitting results, which were also consistent with clinical, gene-expression and cancer-drug data. These reveal a fundamentally important relationship: while cancer is driven by endogenous stressors, it requires sufficient levels of exogenous growth signals to happen, hence suggesting the realistic possibility for treating cancer via cleaning out the growth signals in circulation needed by a cancer.

摘要

SEER 报告中的数据显示,癌症类型的发生率通常随着年龄呈单峰分布,在特定的癌症类型中达到峰值,范围在 30 岁以上到 70 岁之间。先前的研究将这种钟形分布归因于老年时期增殖能力的降低,但未能解释为什么有些癌症的发生率峰值出现在 30 岁或 40 岁以上。我们提出了一个计算模型,为这种分布提供了一个新的解释。该模型使用两个因素来解释观察到的与年龄相关的癌症发生率:器官的癌症风险和循环中所需的生长信号的可用性水平,前者随着年龄的增长而增加,后者随着年龄的增长而减少。我们对三阴性乳腺癌、睾丸癌和宫颈癌的已知发生率进行了针对这些因素的回归分析;所有这些分析都得到了高度拟合的结果,这也与临床、基因表达和癌症药物数据一致。这些结果揭示了一个重要的关系:虽然癌症是由内源性应激源驱动的,但它需要足够水平的外源性生长信号才能发生,因此提示通过清除癌症所需的循环中的生长信号来治疗癌症是一种现实的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1df/8294564/3550cc40b0cc/bbaa349f1.jpg

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