Genetic Modifiers of Intitiation and Progression of Mammary Cancer

我们实验室最近取得了重大进展。在过去的几年里，我们发表了第一项关于体质多态性影响转移的研究结果。我们证明，Sipa1 基因中的单个氨基酸多态性可以将小鼠乳腺肿瘤的转移能力调节多达十倍。此外，我们通过人类流行病学试点研究证明，该基因 SIPA1 的人类直系同源物的多态性与人类乳腺癌的淋巴结状态相关。这些发现是第一个发表的例子，证明基因遗传而不是肿瘤内的突变在人类癌症的进展中发挥着重要作用。最近，我们一直在扩展这些结果，以研究其他基因在建立转移易感性中的作用。正在采取两种互补的方法。首先，使用 Sipa1 分子作为核，我们正在识别和表征与转移修饰蛋白 Sipa1 物理相互作用的基因产物，特别关注那些与多态性 PDZ 结构域相互作用的蛋白质结合伴侣。目前的研究表明，至少三种假定的候选蛋白质在实验系统中表现出对转移的显着影响，并且在试点流行病学研究中也有证据表明其在人类乳腺癌中发挥作用。第二个研究途径是基于表达数量性状图谱。利用我们的高度转移小鼠模型和复杂的性状遗传学策略，我们鉴定了另外 5 个基因，这些基因证明了与乳腺肿瘤进展的实验关联。对表达阵列数据的分析表明，这些基因中至少有 4 个可能在人类乳腺癌转移易感性中发挥作用，其中 3 个新基因抑制肿瘤进展，而 1 个可能增加转移易感性。使用这些补充方法，我们计划继续对与乳腺癌肿瘤进展相关的基因组结构进行遗传和基因组分析。这些研究中生成的数据将通过最先进的计算方法进行进一步分析，以进一步阐明与转移进展相关的复杂的相互作用网络。

Recent progress in our laborabory has been significant. During the past years we published the results of our first study of the effect of constitutional polymorphism influencing metastasis. We demonstrated that a single amino acid polymorphism in the gene Sipa1 could modulate the metastatic capacity of mouse mammary tumors by as much as ten-fold. Furthermore we demonstrated, using pilot human epidemiology studies, that polymorphisms in the human ortholog of this gene, SIPA1, were associated with lymph node status in human breast cancer. These findings were the first published example that genetic inheritance rather that mutation within tumors, plays a major role in progression of human cancer. More recently we have been extending these results to investigate the role of additional genes in the establishment of metastasis susceptibility. Two complementary approaches are being pursued. First, using the Sipa1 molecule as a nucleus, we are identifying and characterizing gene products that physically interact with the metastasis modifying protein Sipa1, with particular focus on those protein binding partners that interact with the polymorphic PDZ domain. Current efforts have revealed that at least three of the putative collection of candidate proteins demonstrate significant effects on metastasis in experimental systems, as well as evidence of a role in human breast cancer in pilot epidemiology studies. The second avenue of research is based on expression quantitative trait mapping. Using our highly metastatic mouse model and a complex trait genetics strategy, we have identified an additional 5 genes that demonstrated experimental associations with mammary tumor progression. Analysis of expression array data suggests that at least 4 of these genes may play a role in human breast cancer metastasis susceptibility, with 3 of the novel genes suppressing tumor progression, and one potentially increasing metastasis susceptbility. Using these complementary methodologies, we plan to continue our genetic and genomic analysis of the genome architecture associated with breast cancer tumor progression. The data generated in these studies will be further analyzed by state-of-the-art computational methods to further elucidate the complex interacting networks associated with metastatic progression.