Transcriptional Landscape of PARs in Epithelial Malignancies

G protein-coupled receptors (GPCRs), the largest family of cell receptors, act as important regulators of diverse signaling pathways. Our understanding of the impact of GPCRs in tumors is emerging, yet there is no therapeutic platform based on GPCR driver genes. As cancer progresses, it disrupts normal epithelial organization and maintains the cells outside their normal niche. The dynamic and flexible microenvironment of a tumor contains both soluble and matrix-immobilized proteases that contribute to the process of cancer advancement. An example is the activation of cell surface protease-activated receptors (PARs). Mammalian PARs are a subgroup of GPCRs that form a family of four members, PAR_1⁻4, which are uniquely activated by proteases found in the microenvironment. PAR₁ and PAR₂ play central roles in tumor biology, and PAR₃ acts as a coreceptor. The significance of PAR₄ in neoplasia is just beginning to emerge. PAR₁ has been shown to be overexpressed in malignant epithelia, in direct correlation with tumor aggressiveness, but there is no expression in normal epithelium. In this review, the involvement of key transcription factors such as Egr1, p53, Twist, AP2, and Sp1 that control PAR₁ expression levels specifically, as well as hormone transcriptional regulation by both estrogen receptors (ER) and androgen receptors (AR) are discussed. The cloning of the human protease-activated receptor 2; Par2 (hPar2) promoter region and transcriptional regulation of estrogen (E₂) via binding of the E₂⁻ER complex to estrogen response elements (ERE) are shown. In addition, evidence that TEA domain 4 (TEAD₄) motifs are present within the hPar2 promoter is presented since the YAP oncogene, which plays a central part in tumor etiology, acts via the TEAD₄ transcription factor. As of now, no information is available on regulation of the hPar3 promoter. With regard to hPar4, only data showing CpG methylation promoter regulation is available. Characterization of the PAR transcriptional landscape may identify powerful targets for cancer therapies.