Institute for Molecular Medicine and Crump Institute for Molecular Imaging and Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095.
Proc Natl Acad Sci U S A. 2013 Nov 19;110(47):19160-5. doi: 10.1073/pnas.1316991110. Epub 2013 Oct 7.
Toward identifying a cancer-specific gene signature we applied surprisal analysis to the RNAs expression behavior for a large cohort of breast, lung, ovarian, and prostate carcinoma patients. We characterize the cancer phenotypic state as a shared response of a set of mRNA or microRNAs (miRNAs) in cancer patients versus noncancer controls. The resulting signature is robust with respect to individual patient variability and distinguishes with high fidelity between cancer and noncancer patients. The mRNAs and miRNAs that are implicated in the signature are correlated and are known to contribute to the regulation of cancer-signaling pathways. The miRNA and mRNA networks are common to the noncancer and cancer patients, but the disease modulates the strength of the connectivities. Furthermore, we experimentally assessed the cancer-specific signatures as possible therapeutic targets. Specifically we restructured a single dominant connectivity in the cancer-specific gene network in vitro. We find a deflection from the cancer phenotype, significantly reducing cancer cell proliferation and altering cancer cellular physiology. Our approach is grounded in thermodynamics augmented by information theory. The thermodynamic reasoning is demonstrated to ensure that the derived signature is bias-free and shows that the most significant redistribution of free energy occurs in programming a system between the noncancer and cancer states. This paper introduces a platform that can elucidate miRNA and mRNA behavior on a systems level and provides a comprehensive systematic view of both the energetics of the expression levels of RNAs and of their changes during tumorigenicity.
为了确定癌症特异性基因特征，我们对一大组乳腺癌、肺癌、卵巢癌和前列腺癌患者的 RNA 表达行为应用了惊讶分析。我们将癌症表型状态描述为一组 mRNA 或 microRNAs (miRNAs) 在癌症患者与非癌症对照中的共同反应。该特征对于个体患者的变异性具有稳健性，并且能够高度准确地区分癌症患者和非癌症患者。涉及该特征的 mRNA 和 miRNAs 相关，并且已知它们有助于癌症信号通路的调控。miRNA 和 mRNA 网络在非癌症和癌症患者中是共同的，但疾病调节了连通性的强度。此外，我们还实验评估了癌症特异性特征作为可能的治疗靶点。具体来说，我们在体外重新构建了癌症特异性基因网络中单一占主导地位的连通性。我们发现了从癌症表型的偏离，显著降低了癌细胞的增殖并改变了癌症细胞的生理。我们的方法基于热力学，并通过信息论进行了增强。热力学推理被证明可以确保导出的特征是无偏差的，并表明在将系统编程为非癌症和癌症状态之间，自由能的最大重新分配发生。本文介绍了一个平台，可以在系统水平上阐明 miRNA 和 mRNA 的行为，并提供了关于 RNA 表达水平的能量学及其在肿瘤发生过程中的变化的全面系统观点。
