Anti-DR4 Antibody [DR-4-02] - Low endotoxin, Azide free (A86119)

Many cancer entities and their associated cell line models are highly heterogeneous in their responsiveness to apoptosis inducers and, despite a detailed understanding of the underlying signaling networks, cell death susceptibility currently cannot be predicted reliably from protein expression profiles. Here, we demonstrate that an integration of quantitative apoptosis protein expression data with pathway knowledge can predict the cell death responsiveness of melanoma cell lines. By a total of 612 measurements, we determined the absolute expression (nM) of 17 core apoptosis regulators in a panel of 11 melanoma cell lines, and enriched these data with systems-level information on apoptosis pathway topology. By applying multivariate statistical analysis and multi-dimensional pattern recognition algorithms, the responsiveness of individual cell lines to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) or dacarbazine (DTIC) could be predicted with very high accuracy (91 and 82% correct predictions), and the most effective treatment option for individual cell lines could be pre-determined in silico. In contrast, cell death responsiveness was poorly predicted when not taking knowledge on protein-protein interactions into account (55 and 36% correct predictions). We also generated mathematical predictions on whether anti-apoptotic Bcl-2 family members or x-linked inhibitor of apoptosis protein (XIAP) can be targeted to enhance TRAIL responsiveness in individual cell lines. Subsequent experiments, making use of pharmacological Bcl-2/Bcl-xL inhibition or siRNA-based XIAP depletion, confirmed the accuracy of these predictions. We therefore demonstrate that cell death responsiveness to TRAIL or DTIC can be predicted reliably in a large number of melanoma cell lines when investigating expression patterns of apoptosis regulators in the context of their network-level interplay. The capacity to predict responsiveness at the cellular level may contribute to personalizing anti-cancer treatments in the future.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) plays an important role in immune surveillance and preferentially induces apoptosis in cancer cells over normal cells, suggesting its potential in cancer therapy. However, the molecular basis for its selective killing of cancer cells is not well understood. Recent studies have identified the CCN family of integrin-binding matricellular proteins as important regulators of cell behavior, including cell adhesion, proliferation, migration, differentiation, and survival. We show here that CCN1 (CYR61) supports the adhesion of prostatic carcinoma cells as an adhesion substrate through integrins and heparan sulfate proteoglycans. Knockdown of CCN1 expression in PC-3 and DU-145 androgen-independent prostate cancer cells strongly inhibited their proliferation without causing apoptosis, indicating that CCN1 promotes their growth. However, CCN1 also significantly enhances TRAIL-induced apoptosis through interaction with integrins alphavbeta3 and alpha6beta4 and the cell-surface heparan sulfate proteoglycan syndecan-4, acting through a protein kinase Calpha-dependent mechanism without requiring de novo protein synthesis. Knockdown of CCN1 expression in PC-3, DU-145, and LNCaP cells severely blunted their sensitivity to TRAIL, an effect that was reversed by exogenously added CCN1 protein. These findings reveal a functional dichotomy for CCN1 in prostate carcinoma cells, because it contributes to both cell proliferation and TRAIL-induced cell death and suggest that CCN1 expression status may be an important parameter in assessing the efficacy of TRAIL-dependent cancer therapy.