Evidence for systems-level molecular mechanisms of tumorigenesis

<p>Abstract</p> <p>Background</p> <p>Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth.</p> <p>Results</p> <p>Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs") defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree) and global (betweenness and closeness) measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis.</p> <p>Conclusion</p> <p>Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.</p

Characterization of protein-interaction networks in tumors

<p>Abstract</p> <p>Background</p> <p>Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be formally represented as graphs, and approximating PINs as undirected graphs allows the network properties to be characterized using well-established graph measures.</p> <p>This paper outlines features of PINs derived from 29 studies on differential gene expression in cancer. For each study the number of differentially regulated genes was determined and used as a basis for PIN construction utilizing the Online Predicted Human Interaction Database.</p> <p>Results</p> <p>Graph measures calculated for the largest subgraph of a PIN for a given differential-gene-expression data set comprised properties reflecting the size, distribution, biological relevance, density, modularity, and cycles. The values of a distinct set of graph measures, namely <it>Closeness Centrality</it>, <it>Graph Diameter</it>, <it>Index of Aggregation</it>, <it>Assortative Mixing Coefficient</it>, <it>Connectivity</it>, <it>Sum of the Wiener Number</it>, <it>modified Vertex Distance Number</it>, and <it>Eigenvalues </it>differed clearly between PINs derived on the basis of differential gene expression data sets characterizing malignant tissue and PINs derived on the basis of randomly selected protein lists.</p> <p>Conclusion</p> <p>Cancer PINs representing differentially regulated genes are larger than those of randomly selected protein lists, indicating functional dependencies among protein lists that can be identified on the basis of transcriptomics experiments. However, the prevalence of hub proteins was not increased in the presence of cancer. Interpretation of such graphs in the context of robustness may yield novel therapies based on synthetic lethality that are more effective than focusing on single-action drugs for cancer treatment.</p

Translational Oncogenomics and Human Cancer Interactome Networks

An overview of translational, human oncogenomics, transcriptomics and cancer interactomic networks is presented together with basic concepts and potential, new applications to Oncology and Integrative Cancer Biology. Novel translational oncogenomics research is rapidly expanding through the application of advanced technology, research findings and computational tools/models to both pharmaceutical and clinical problems. A self-contained presentation is adopted that covers both fundamental concepts and the most recent biomedical, as well as clinical, applications. Sample analyses in recent clinical studies have shown that gene expression data can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, &#x2018;personalized medicine&#x2019;. Several cancer detection techniques are currently under development both in the direction of improved detection sensitivity and increased time resolution of cellular events, with the limits of single molecule detection and picosecond time resolution already reached. The urgency for the complete mapping of a human cancer interactome with the help of such novel, high-efficiency / low-cost and ultra-sensitive techniques is also pointed out

Aberrant Mitochondrial Homeostasis at the Crossroad of Musculoskeletal Ageing and Non-Small Cell Lung Cancer

Cancer cachexia is accompanied by muscle atrophy, sharing multiple common catabolic pathways with sarcopenia, including mitochondrial dysfunction. This study investigated gene expression from skeletal muscle tissues of older healthy adults, who are at risk of age-related sarcopenia, to identify potential gene biomarkers whose dysregulated expression and protein interference were involved in non-small cell lung cancer (NSCLC). Screening of the literature resulted in 14 microarray datasets (GSE25941, GSE28392, GSE28422, GSE47881, GSE47969, GSE59880 in musculoskeletal ageing; GSE118370, GSE33532, GSE19804, GSE18842, GSE27262, GSE19188, GSE31210, GSE40791 in NSCLC). Differentially expressed genes (DEGs) were used to construct protein-protein interaction (PPI) networks and 35 retrieve clustering gene modules. Overlapping module DEGs were ranked based on 11 topological algorithms and were correlated with prognosis, tissue expression, and tumour purity in NSCLC. The analysis revealed that the dysregulated expression of the mammalian mitochondrial ribosomal proteins, MRPS26, MRPS17, MRPL18, and MRPL51 were linked to reduced survival and tumour purity in NSCLC while tissue expression of the same genes followed an opposite direction in healthy older adults. These results support a potential link between the mitochondrial microenvironment in ageing muscle and NSLC. Further studies comparing changes in sarcopenia and NSCL associated cachexia are warranted

Cancer systems biology: exploring cancer-associated genes on cellular networks

Genomic alterations lead to cancer complexity and form a major hurdle for a comprehensive understanding of the molecular mechanisms underlying oncogenesis. In this review, we describe the recent advances in studying cancer-associated genes from a systems biological point of view. The integration of known cancer genes onto protein and signaling networks reveals the characteristics of cancer genes within networks. This approach shows that cancer genes often function as network hub proteins which are involved in many cellular processes and form focal nodes in the information exchange between many signaling pathways. Literature mining allows constructing gene-gene networks, in which new cancer genes can be identified. The gene expression profiles of cancer cells are used for reconstructing gene regulatory networks. By doing so, the genes, which are involved in the regulation of cancer progression, can be picked up from these networks after which their functions can be further confirmed in the laboratory.Comment: More similar papers at http://www.bri.nrc.ca/wan