Gefitinib, an EGFR tyrosine kinase inhibitor, is used as FDA approved drug in breast cancer and non-small cell lung cancer treatment. However, this drug has certain side effects and complications for which the underlying molecular mechanisms are not well understood. By systems biology based in silico analysis, we identified off-targets of gefitinib that might explain side effects of this drugs. The crystal structure of EGFR-gefitinib complex was used for binding pocket similarity searches on a druggable proteome database (Sc-PDB) by using IsoMIF Finder. The top 128 hits of putative off-targets were validated by reverse docking approach. The results showed that identified off-targets have efficient binding with gefitinib. The identified human specific off-targets were confirmed and further analyzed for their links with biological process and clinical disease pathways using retrospective studies and literature mining, respectively. Noticeably, many of the identified off-targets in this study were reported in previous high-throughput screenings. Interestingly, the present study reveals that gefitinib may have positive effects in reducing brain and bone metastasis, and may be useful in defining novel gefitinib based treatment regime. We propose that a system wide approach could be useful during new drug development and to minimize side effect of the prospective drug.

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Purpose Extracellular matrix remodeling is essential for extravillous trophoblast (EVT) cell migration and invasion during placental development and regulated by matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteases (TIMPs). Sphingosine kinases (SPHK1 and SPHK2) synthesize sphingosine‐1‐phosphate (S1P), which works either intracellularly or extracellularly via its receptors S1PR1‐5 in an autocrine or paracrine manner. The role of SPHKs/S1P in regulating the expression of MMPs and TIMPs in EVT is mostly unknown and forms the primary objective of the study. Methods HTR‐8/SVneo cells were used as a model of EVT. To inhibit the expression of SPHKs, cells were treated with specific inhibitors, SK1‐I and SKI‐II, or gene‐specific siRNAs. The expressions of MMPs and TIMPs were estimated by qPCR. Results We demonstrated that SPHK1, MMP1‐3, and TIMP1‐3 were highly expressed in HTR‐8/SVneo cells. We found that treatment of cells with SK1‐I, SKI‐II, and knockdown of SPHK1 or SPHK2 increased the expression of MMP1, MMP3, and TIMP3. The addition of extracellular S1P inhibits the upregulation of MMPs and TIMPs in treated cells. Conclusions SPHKs negatively regulate the expression of MMP1, MMP3, and TIMP3. The level of intracellular S1P acts as a negative feedback switch for MMP1, MMP3, and TIMP3 expression in EVT cells.

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