Determining PTEN Functional Status by Network Component Deduced Transcription Factor Activities

PTEN-controlled PI3K-AKT-mTOR pathway represents one of the most deregulated signaling pathways in human cancers. With many small molecule inhibitors that target PI3K-AKT-mTOR pathway being exploited clinically, sensitive and reliable ways of stratifying patients according to their PTEN functional status and determining treatment outcomes are urgently needed. Heterogeneous loss of PTEN is commonly associated with human cancers and yet PTEN can also be regulated on epigenetic, transcriptional or post-translational levels, which makes the use of simple protein or gene expression-based analyses in determining PTEN status less accurate. In this study, we used network component analysis to identify 20 transcription factors (TFs) whose activities deduced from their target gene expressions were immediately altered upon the re-expression of PTEN in a PTEN-inducible system. Interestingly, PTEN controls the activities (TFA) rather than the expression levels of majority of these TFs and these PTEN-controlled TFAs are substantially altered in prostate cancer mouse models. Importantly, the activities of these TFs can be used to predict PTEN status in human prostate, breast and brain tumor samples with enhanced reliability when compared to straightforward IHC-based or expression-based analysis. Furthermore, our analysis indicates that unique sets of PTEN-controlled TFAs significantly contribute to specific tumor types. Together, our findings reveal that TFAs may be used as “signatures” for predicting PTEN functional status and elucidate the transcriptional architectures underlying human cancers caused by PTEN loss.受PTEN调控的PI3K-AKT-mTOR信号通路（PTEN-controlled PI3K-AKT-mTOR pathway）是人类癌症中最常发生失调的信号通路之一。目前已有多款靶向该通路的小分子抑制剂投入临床应用，因此亟需建立灵敏且可靠的方法，以根据患者的PTEN功能状态进行分层，并辅助判断治疗预后。PTEN的异质性缺失普遍存在于人类癌症中，而PTEN本身还可通过表观遗传、转录及翻译后水平受到调控，这使得基于简单蛋白或基因表达分析来判定PTEN状态的准确性大幅降低。本研究借助网络组分分析（network component analysis），在PTEN诱导表达系统中，鉴定出20个转录因子（transcription factors, TFs）——其基于靶基因表达推导得到的活性，会在PTEN重新表达后即刻发生改变。有趣的是，PTEN主要调控的是多数此类转录因子的活性（转录因子活性，transcription factor activity, TFA），而非其蛋白或基因表达水平；且在前列腺癌小鼠模型中，这些受PTEN调控的TFA发生了显著改变。重要的是，相较于传统的基于免疫组化（immunohistochemistry, IHC）或基因表达的分析方法，利用这些转录因子的活性可更为可靠地预测人类前列腺癌、乳腺癌及脑肿瘤样本中的PTEN功能状态。此外，本研究分析还发现，不同的受PTEN调控的TFA特征集，可显著参与特定肿瘤类型的发生发展。综上，本研究揭示转录因子活性可作为预测PTEN功能状态的"特征标签"，并阐明了PTEN缺失所驱动的人类癌症的转录调控架构。