Merajver Sofia, Phadke Sameer, Soellner Matthew
ANN ARBOR, MICHIGAN.
Trans Am Clin Climatol Assoc. 2017;128:169-179.
The advent of rapid and progressively more affordable sequencing and gene expression studies have spurred research on therapies for cancer targeted to specific gene alterations. With few exceptions, such as those cancers with either a paucity of mutations or major chromosomal rearrangements driving the neoplastic transformation, the approaches based on one mutational target-one drug have achieved only modest outcomes in cancer. Using the paradigm of aggressive breast cancers, we will show the mathematical explanation that predicts our failures and indicates a plausible way forward. An integrated network modeling approach to intracellular signaling, metabolism, and microenvironment interactions, coupled with the use of synthetic devices engineered to understand phenotypic heterogeneity of cancer lesions, may form the basis for selection of the next-generation of personalized therapies for cancer. Academia can play a larger role in bringing effective drugs to first-in-human trials in this context.
快速且价格日益亲民的测序和基因表达研究的出现,推动了针对特定基因改变的癌症治疗研究。除了少数例外情况,比如那些驱动肿瘤转化的突变极少或存在主要染色体重排的癌症,基于一个突变靶点一种药物的方法在癌症治疗中仅取得了有限的成果。以侵袭性乳腺癌为例,我们将展示一种数学解释,它能预测我们的失败并指明一条可行的前进道路。一种整合细胞内信号传导、代谢和微环境相互作用的网络建模方法,再结合使用经过设计以了解癌症病灶表型异质性的合成装置,可能为选择下一代癌症个性化疗法奠定基础。在这种情况下,学术界在将有效药物推进到首次人体试验方面可以发挥更大的作用。