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Combinatorial treatment with polyI:C and anti-IL6 enhances apoptosis and suppresses metastasis of lung cancer cells

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      Abstract

      Activation of TLR3 stimulates cancer cell apoptosis and triggers secretion of inflammatory cytokines. PolyI:C, a TLR3 agonist, activates immune cells and regresses metastatic lung cancer in vivo. Although polyI:C reportedly kills lung carcinomas, the mechanism remains elusive. Here, we demonstrated that polyI:C suppressed the proliferation and survival of metastatic (NCI-H358 and NCI-H292) and non-metastatic (A549) lung cancer cells. Notably, A549, NCI-H292 and NCI-H358 which are inducible by polyI:C, expressed low-to-medium level of TLR3 protein, and were susceptible to polyI:C treatment. By contrast, NCI-H1299, which endogenously expresses high level of TLR3 protein, was insensitive to polyI:C. We showed that polyI:C stimulated pro-inflammatory cytokines associated with survival and metastasis in a cell type-specific manner. While A549 and NCI-H292 released high levels of IL6, IL8 and GRO, the NCI-H358 cells endogenously secretes abundant levels of these cytokines, and was not further induced by polyI:C. Thus, NCI-H358 was resistant to the inhibition of cytokine-dependent metastasis. NCI-H1299, which was unresponsive to polyI:C, did not produce any of the pro-inflammatory cytokines. Treatment of A549 with a combination of polyI:C and anti-IL6 antibody significantly decreased IL6 production, and enhanced polyI:C-mediated killing and suppression of oncogenicity and metastasis. While polyI:C stimulated the phosphorylation of STAT3 and JAK2, blockade of these proteins enhanced polyI:C-mediated suppression of survival and metastasis. Taken together, polyI:C alone provoked apoptosis of lung cancer cells that express low-to-medium levels of functional TLR3 protein. The combinatorial treatment with polyI:C and anti-IL6 enhanced polyI:C-mediated anticancer activities through IL6/JAK2/STAT3 signalling, and apoptosis via TLR3-mediated caspase 3/8 pathway.

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      The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Author and article information

            Affiliations
            1 Department of Biological Sciences, Faculty of Science, National University of Singapore, Singapore 117543, Singapore
            2 Taipei Medical University, College for Medical Science and Technology, Taipei 110, Taiwan
            Author notes
            Correspondence to: Jeak Ling Ding, dbsdjl@ 123456nus.edu.sg
            Journal
            Oncotarget
            Oncotarget
            Oncotarget
            ImpactJ
            Oncotarget
            Impact Journals LLC
            1949-2553
            16 May 2017
            2 March 2017
            : 8
            : 20
            : 32884-32904
            28427199 5464836 15862 10.18632/oncotarget.15862
            Copyright: © 2017 Lau et al.

            This article is distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.

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