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Review
. 2017 Jul 26:16:1176935117721691.
doi: 10.1177/1176935117721691. eCollection 2017.

Immuno-Oncology Integrative Networks: Elucidating the Influences of Osteosarcoma Phenotypes

Affiliations
Review

Immuno-Oncology Integrative Networks: Elucidating the Influences of Osteosarcoma Phenotypes

Ankush Sharma et al. Cancer Inform. .

Abstract

In vivo and in vitro functional phenotyping characterization was recently obtained with reference to an experimental pan-cancer study of 22 osteosarcoma (OS) cell lines. Here, differentially expressed gene (DEG) profiles were recomputed from the publicly available data to conduct network inference on the immune system regulatory activity across the characterized OS phenotypes. Based on such DEG profiles, and for each phenotype that was analyzed, we obtained coexpression networks and bio-annotations for them. Then, we described the immune-modulated influences in phenotype-specific networks' integrating pathway, transcription factor, and microRNA regulations. Overall, this approach seems suitable for representing heterogeneity in OS tumorigenesis.

Keywords: Osteosarcoma; immune-mediated regulation; networks; phenotypes.

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Conflict of interest statement

Declaration of Conflicting Interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Profiles showing distinct and shared differentially expressed genes across phenotypes.
Figure 2.
Figure 2.
Molecular functions of differentially expressed genes: tumorigenic vs nontumorigenic (top-left panel), invasive vs noninvasive (top-right panel), colony forming vs non–colony forming (bottom-left panel), and proliferative vs nonproliferative (bottom-right panel).
Figure 3.
Figure 3.
Immune-modulated networks. Phenotype-driven Gene Ontology biological processes. Node size varies according to significance, from smallest circle (p-value >.1, to the largest circle, p-value <.0005). The majority of nodes present significance between p-value intervals (.05-0.1) and (.005-.05) (source: ClueGO, http://apps.cytoscape.org/apps/cluego).
Figure 4.
Figure 4.
Regulation influences from transcription factors and microRNAs (miRNAs) across pathway landscapes. Tumorigenic phenotype (top network) followed by invasive and colony-forming phenotypes, followed by proliferative phenotype (bottom network). The Weighted Gene Co-Expression Network Analysis (WGCNA) package was used. Blue labels indicate pathway terms, circles indicate miRNAs, rhomboids and hexagons indicate mutations (missense and coding silent), and red links indicate the presence as a connector of a transcription factor.

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