Given an abstract from a research paper, your task is to identify and label relationships between chemical compounds and genes mentioned in the abstract.

The relationship type must be one of ['DOWNREGULATOR', 'SUBSTRATE', 'INDIRECT-REGULATOR', 'PART-OF', 'MODULATOR-ACTIVATOR', 'REGULATOR', 'INHIBITOR', 'COFACTOR', 'UPREGULATOR', 'ACTIVATOR', 'ANTAGONIST', 'NOT', 'INDIRECT-DOWNREGULATOR', 'SUBSTRATE_PRODUCT-OF', 'INDIRECT-UPREGULATOR', 'AGONIST', 'PRODUCT-OF', 'MODULATOR', 'DIRECT-REGULATOR', 'UNDEFINED', 'AGONIST-INHIBITOR', 'AGONIST-ACTIVATOR', 'MODULATOR-INHIBITOR'].

Please format your output as a JSON array. Each entry in the array should express a single relation, formatted as ["<Entity_A>", "<RELATION_A_B>", "<Entity_B>"]. If no relations can be found, please output an empty JSON array [].

Abstract:

Conditional activation of Pik3ca (H1047R) in a knock-in mouse model promotes mammary tumorigenesis and emergence of mutations. Oncogenic mutations in PIK3CA, which encodes the phosphoinositide-3-kinase (PI3 K) catalytic subunit p110α, occur in ∼25% of human breast cancers. In this study, we report the development of a knock-in mouse model for breast cancer where the endogenous Pik3ca allele was modified to allow tissue-specific conditional expression of a frequently found Pik3ca (H1047R) (Pik3ca (e20H1047R)) mutant allele. We found that activation of the latent Pik3ca (H1047R) allele resulted in breast tumors with multiple histological types. Whole-exome analysis of the Pik3ca (H1047R) -driven mammary tumors identified multiple mutations, including Trp53 mutations that appeared spontaneously during the development of adenocarinoma and spindle cell tumors. Further, we used this model to test the efficacy of GDC-0941, a PI3 K inhibitor, in clinical development, and showed that the tumors respond to PI3 K inhibition.
[["GDC-0941", "INHIBITOR", "PI3 K"]]