Ptitsyn Andrey A, Weil Michael M, Thamm Douglas H
Center for Bioinformatics, Department of Microbiology, Immunology and Pathology, Colorado State University, Colorado, USA.
BMC Bioinformatics. 2008 Aug 12;9 Suppl 9(Suppl 9):S8. doi: 10.1186/1471-2105-9-S9-S8.
Metastases are responsible for the majority of cancer fatalities. The molecular mechanisms governing metastasis are poorly understood, hindering early diagnosis and treatment. Previous studies of gene expression patterns in metastasis have concentrated on selection of a small number of "signature" biomarkers.
We propose an alternative approach that puts into focus gene interaction networks and molecular pathways rather than separate genes. We have reanalyzed expression data from a large set of primary solid and metastatic tumors originating from different tissues using the latest available tools for normalization, identification of differentially expressed genes and pathway analysis. Our studies indicate that regardless of the tissue of origin, all metastatic tumors share a number of common features related to changes in basic energy metabolism, cell adhesion/cytoskeleton remodeling, antigen presentation and cell cycle regulation. Analysis of multiple independent datasets indicates significantly reduced oxidative phosphorylation in metastases compared to primary solid tumors.
Our methods allow identification of robust, although not necessarily highly expressed biomarkers. A systems approach relying on groups of interacting genes rather than single markers is also essential for understanding the cellular processes leading to metastatic progression. We have identified metabolic pathways associated with metastasis that may serve as novel targets for therapeutic intervention.
转移是大多数癌症死亡的原因。控制转移的分子机制了解甚少，这阻碍了早期诊断和治疗。先前关于转移中基因表达模式的研究集中在少数“标志性”生物标志物的选择上。
我们提出了一种替代方法，该方法关注基因相互作用网络和分子途径而非单个基因。我们使用最新的可用工具进行标准化、差异表达基因的鉴定和途径分析，重新分析了来自大量源自不同组织的原发性实体瘤和转移性肿瘤的表达数据。我们的研究表明，无论起源组织如何，所有转移性肿瘤都具有一些与基本能量代谢、细胞粘附/细胞骨架重塑、抗原呈递和细胞周期调控变化相关的共同特征。对多个独立数据集的分析表明，与原发性实体瘤相比，转移灶中的氧化磷酸化显著降低。
我们的方法能够识别出可靠的生物标志物，尽管不一定是高表达的。依赖于相互作用基因群而非单个标志物的系统方法对于理解导致转移进展的细胞过程也至关重要。我们已经确定了与转移相关的代谢途径，这些途径可能成为治疗干预的新靶点。
