A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy

Dreyer F, Cantone M, Eberhardt M, Jaitly T, Walter L, Wittmann J, Gupta S, Khan FM, Wolkenhauer O, Puetzer BM, Jäck HM, Heinzerling L, Vera J (2018)

Publication Status: Published

Publication Type: Journal article, Original article

Publication year: 2018

Journal

Biochimica et Biophysica Acta - Molecular Basis of Disease Elsevier

Publisher: Elsevier B.V.

Book Volume: 1864

Pages Range: 2315-2328

Journal Issue: 6

DOI: 10.1016/j.bbadis.2018.01.020

Abstract

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients.

Authors with CRIS profile

Florian Dreyer Department of Dermatology Martina Cantone Department of Dermatology Martin Eberhardt Department of Dermatology Tanushree Jaitly Juniorprofessur für Bioinformatik Lisa Walter Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Jürgen Wittmann Department of Molecular Immunology Hans-Martin Jäck Professur für Immunologie Lucie Heinzerling Department of Dermatology Julio Vera González Professur für Tumorimmunologie (Schwerpunkt Systembiologie)

Additional Organisation(s)

Machine Learning and Data Analytics Lab

Involved external institutions

University of Stellenbosch / Universiteit van Stellenbosch ZA South Africa (ZA) CSIR Indian Institute of Toxicology Research IN India (IN) Universität Rostock DE Germany (DE)

How to cite

APA:

Dreyer, F., Cantone, M., Eberhardt, M., Jaitly, T., Walter, L., Wittmann, J.,... Vera, J. (2018). A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy. Biochimica et Biophysica Acta - Molecular Basis of Disease, 1864(6), 2315-2328. https://doi.org/10.1016/j.bbadis.2018.01.020

MLA:

Dreyer, Florian, et al. "A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy." Biochimica et Biophysica Acta - Molecular Basis of Disease 1864.6 (2018): 2315-2328.

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