Abstract
Background: Multiple myeloma (MM) is a clonal B cell neoplasia that comes from growth of malignant B cells in the bone marrow. Stromal cells, including inflammatory cells, in the bone marrow enable MM persistence and growth. MM is characterized by an uncoordinated cytokine system with an increase in proinflammatory cytokines. While proinflammatory cytokines are essential in mounting an anti-tumor response, they can also drive cancer progression. Ultimately, it is the effects of the cytokine milieu in the immune microenvironment that help determine MM development. While the role of IFNγ in MM remains mixed and unclear, our analysis suggests IFNγ plays an oncogenic role in MM and offers other insights to MM pathology.
Methods: The National Center for Biotechnology Information (NCBI) GEO is an open database of more than 2 million samples of functional genomics experiments. The Search Tag Analyze Resource for GEO (STARGEO) platform allows for meta-analysis of genomic signatures of disease and tissue. We employed the STARGEO platform to search the Gene Expression Omnibus and performed meta-analysis on 517 peripheral blood samples from multiple myeloma patients using 97 healthy peripheral blood samples as a control. We then analyzed the signature in Ingenuity Pathway Analysis (IPA) to help define the genomic signature of MM and identify disease pathways. We analyzed genes that showed statistical significance disease and control samples (p<0.05) and an absolute experimental log ratio of at least 0.1.
Results: We identified IFNγ signaling, primary immunodeficiency signaling, B cell development, and antigen presentation as the top canonical pathways. Top regulators included IFNγ, TNF, the oncogenic transcription regulator SMARC4, and CNOT7 (with predicted inhibition). We found inhibition of Wnt-signaling through stark upregulation of DKK1 (correlated with osteolytic lesions in MM) and the Wnt-binding protein antagonist FRZB. We also noted increased B cell survival through upregulation of the ADP-ribonyltransferase and B cell survival regulator PAPR14 and CPEB4, a gene required for cell cycle progression. Additionally, apoptotic signaling was diminished through downregulation of CNOT7 (limits B cell proliferation), genes involved in lysosomal disruption during apoptosis such as cathepsin H and lysozymes, the apoptotic Bcl-2 family protein BNIP3, and the pattern recognition receptor NOD2 (involved in autophagy). B cell development was impaired through downregulation of essential genes such as BLNK, a linker protein involved in B cell receptor signaling. Epigenetic changes were reflected by upregulation of the histone genes such as histone 1 genes HIST1H1C/1H2BD. Among histone 1's related pathways are E2F-mediated DNA replication and hypoxia-independent gene expression. Additionally, we found upregulation of tumorigenic genes such as neuron derived neurotrophic factor, NDNF, and hepatocyte growth factor, HGF, which has yet to be described in MM. Interestingly, pathway analysis demonstrated that this diverse set of disease processes are downstream of IFNγ signaling (see figure 1).
Conclusion: MM pathogenesis reflects several disease processes that remain largely obscure. Our analysis clarifies the role of several mechanisms in MM such as inhibition of Wnt-signaling, defective B cell apoptosis, increased proliferation, loss of epigenetic integrity, and impaired B cell development. Activation of the antigen presentation pathway in our analysis may seem paradoxical to MM progression but recent evidence illustrates increased antigen presentation to T-regulatory cells, leading to immune tolerance. Most importantly, we are beginning to clarify the multifactorial, oncogenic qualities of IFNγ signaling in MM and are working to validate these results with analysis of our patient samples.
No relevant conflicts of interest to declare.
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