alexa Implications of increased tissue transglutaminase (TG2) expression in drug-resistant breast cancer (MCF-7) cells.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): Herman JF, Mangala LS, Mehta K

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Abstract The development of resistance to chemotherapeutic drugs is a major obstacle to the successful treatment of breast cancer. Ways to block or overcome this resistance are objects of intense research. We have previously shown that cancer cells selected for resistance against chemotherapeutic drugs or isolated from metastatic tumor sites have high levels of a calcium-dependent protein crosslinking enzyme, tissue transglutaminase (TG2) but no direct link between TG2 and resistance was established. As TG2 can associate with the beta members of the integrin family of proteins, we hypothesized that TG2 promotes cell survival signaling pathways by activating integrins on the surface of these cells. To test this hypothesis, we studied the expression of TG2 and its interaction with various integrins in drug-resistant MCF-7 breast cancer cells. TG2 closely associated with beta1 and beta5 integrins on the surface of drug-resistant MCF-7 (MCF-7/Dox and MCF-7/RT) cells. The incubation of TG2-expressing drug-resistant MCF-7 cells on fibronectin (Fn)-coated surfaces strongly activated focal adhesion kinase, an event that leads to the activation of several downstream signaling pathways and, in turn, can confer apoptosis-resistant phenotype to cancer cells. The role of TG2 in Fn-mediated cell attachment, cell growth, and cell survival functions was further analysed by small interfering RNA (siRNA) approach. Inhibition of TG2 by siRNA-inhibited Fn-mediated cell attachment and cell survival functions in drug-resistant MCF-7 cells. We conclude that the expression of TG2 in breast cancer cells contributes to the development of the drug-resistance phenotype by promoting interaction between integrins and Fn. This article was published in Oncogene and referenced in Journal of Computer Science & Systems Biology

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