Dataset Information

Network Rewiring in Cancer: Applications to Melanoma Cell Lines and the Cancer Genome Atlas Patients.

ABSTRACT: Genes do not work in isolation, but rather as part of networks that have many feedback and redundancy mechanisms. Studying the properties of genetic networks and how individual genes contribute to overall network functions can provide insight into genetically-mediated disease processes. Most analytical techniques assume a network topology based on normal state networks. However, gene perturbations often lead to the rewiring of relevant networks and impact relationships among other genes. We apply a suite of analysis methodologies to assess the degree of transcriptional network rewiring observed in different sets of melanoma cell lines using whole genome gene expression microarray profiles. We assess evidence for network rewiring in melanoma patient tumor samples using RNA-sequence data available from The Cancer Genome Atlas. We make a distinction between "unsupervised" and "supervised" network-based methods and contrast their use in identifying consistent differences in networks between subsets of cell lines and tumor samples. We find that different genes play more central roles within subsets of genes within a broader network and hence are likely to be better drug targets in a disease state. Ultimately, we argue that our results have important implications for understanding the molecular pathology of melanoma as well as the choice of treatments to combat that pathology.

SUBMITTER: Ding KF

PROVIDER: S-EPMC6048451 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Network Rewiring in Cancer: Applications to Melanoma Cell Lines and the Cancer Genome Atlas Patients.

Ding Kuan-Fu KF Finlay Darren D Yin Hongwei H Hendricks William P D WPD Sereduk Chris C Kiefer Jeffrey J Sekulic Aleksandar A LoRusso Patricia M PM Vuori Kristiina K Trent Jeffrey M JM Schork Nicholas J NJ

Frontiers in genetics 20180710

Genes do not work in isolation, but rather as part of networks that have many feedback and redundancy mechanisms. Studying the properties of genetic networks and how individual genes contribute to overall network functions can provide insight into genetically-mediated disease processes. Most analytical techniques assume a network topology based on normal state networks. However, gene perturbations often lead to the rewiring of relevant networks and impact relationships among other genes. We appl ...[more]

PMID: 30042785

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Project description:Metastatic melanoma patients have a poor prognosis, mainly attributable to the underlying heterogeneity in melanoma driver genes and altered gene expression profiles. These characteristics of melanoma also make the development of drugs and identification of novel drug targets for metastatic melanoma a daunting task. Systems biology offers an alternative approach to re-explore the genes or gene sets that display dysregulated behaviour without being differentially expressed. In this study, we have performed systems biology studies to enhance our knowledge about the conserved property of disease genes or gene sets among mutually exclusive datasets representing melanoma progression. We meta-analysed 642 microarray samples to generate melanoma reconstructed networks representing four different stages of melanoma progression to extract genes with altered molecular circuitry wiring as compared to a normal cellular state. Intriguingly, a majority of the melanoma network-rewired genes are not differentially expressed and the disease genes involved in melanoma progression consistently modulate its activity by rewiring network connections. We found that the shortlisted disease genes in the study show strong and abnormal network connectivity, which enhances with the disease progression. Moreover, the deviated network properties of the disease gene sets allow ranking/prioritization of different enriched, dysregulated and conserved pathway terms in metastatic melanoma, in agreement with previous findings. Our analysis also reveals presence of distinct network hubs in different stages of metastasizing tumor for the same set of pathways in the statistically conserved gene sets. The study results are also presented as a freely available database at http://bioinfo.icgeb.res.in/m3db/. The web-based database resource consists of results from the analysis presented here, integrated with cytoscape web and user-friendly tools for visualization, retrieval and further analysis.

Project description:BACKGROUND:Recent evidence suggests a subset of cells within a tumor with "stem-like" characteristics. These cells are able to transplant tumors in immunodeficient hosts. Distinct from non-malignant stem cells, cancer stem cells (CSC) show low proliferative rates, high self-renewing capacity, propensity to differentiate into actively proliferating tumor cells, and resistance to chemotherapy or radiation. They are often characterized by elevated expression of stem cell surface markers, in particular CD133, and sets of differentially expressed stem cell-associated genes. CSC are usually rare in clinical specimens and hardly amenable to functional studies and gene expression profiling. In this study, a panel of heterogenous melanoma cell lines was screened for typical CSC features. METHODS:Nine heterogeneous metastatic melanoma cell lines including D10 and WM115 were studied. Cell lines were phenotyped using flow cytometry and clonogenic assays were performed by limiting dilution analysis on magnetically sorted cells. Spheroidal growth was investigated in pretreated flasks. Gene expression profiles were assessed by using real-time rt-PCR and DNA microarrays. Magnetically sorted tumor cells were subcutaneously injected into the flanks of immunodeficient mice. Comparative immunohistochemistry was performed on xenografts and primary human melanoma sections. RESULTS:D10 cells expressed CD133 with a significantly higher clonogenic capacity as compared to CD133- cells. Na8, D10, and HBL cells formed spheroids on poly-HEMA-coated flasks. D10, Me39, RE, and WM115 cells expressed at least 2 of the 3 regulatory core transcription factors SOX2, NANOG, and OCT4 involved in the maintenance of stemness in mesenchymal stem cells. Gene expression profiling on CD133+ and CD133- D10 cells revealed 68 up- and 47 downregulated genes (+/-1.3 fold). Two genes, MGP and PROM1 (CD133), were outstandingly upregulated. CD133+ D10 cells formed tumors in NSG mice contrary to CD133- cells and CD133 expression was detected in xenografts and primary human melanoma sections using immunohistochemistry. CONCLUSIONS:Established melanoma cell lines exhibit, to variable extents, the typical features of CSCs. The tumorigenic cell line D10, expressing CD133 and growing in spheroids and might qualify as a potential model of melanoma CSCs.

Dataset Information

Network Rewiring in Cancer: Applications to Melanoma Cell Lines and the Cancer Genome Atlas Patients.

Publications

Network Rewiring in Cancer: Applications to Melanoma Cell Lines and the Cancer Genome Atlas Patients.

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