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Papers of the Week


Papers: 7 Mar 2020 - 13 Mar 2020


Animal Studies, Pharmacology/Drug Development


2020 Feb 27


Pain

Editor's Pick

Non-surgical mouse model of endometriosis-associated pain that responds to clinically active drugs.

Authors

Fattori V, Franklin NS, Gonzalez-Cano R, Peterse D, Ghalali A, Madrian E, Verri WA, Andrews N, Woolf CJ, Rogers MS
Pain. 2020 Feb 27.
PMID: 32132396.

Abstract

Endometriosis is an estrogen-dependent inflammatory disease that affects approximately 10% of women. Debilitating pelvic or abdominal pain is one of its major clinical features. Current animal models of endometriosis-associated pain require surgery either to implant tissue or to remove the ovaries. Moreover, existing models do not induce spontaneous pain, which is the primary symptom of patients with chronic pain, including endometriosis. A lack of models that accurately recapitulate the disease phenotype must contribute to the high failure rate of clinical trials for analgesic drugs directed at chronic pain, including those for endometriosis. We set out to establish a murine model of endometriosis-associated pain. Endometriosis was induced non-surgically by injecting a dissociated uterine horn into a recipient mouse. The induced lesions exhibited histological features that resemble human lesions along with an increase in pro-inflammatory cytokines and recruitment of immune cells. We also observed the presence of CGRP-, TRPA1-, and TRPV1-expressing nerve fibers in the lesions. This model induced mechanical allodynia, spontaneous abdominal pain, and changes in thermal selection behavior that indicate discomfort. These behavioral changes were reduced by drugs used clinically for endometriosis, specifically letrozole (aromatase inhibitor) and danazol (androgen). Endometriosis also induced neuronal changes as evidenced by activation of the NF-κB signaling pathway in TRPA1- and TRPV1-expressing DRG neurons. In conclusion, we have established a model of endometriosis-associated pain that responds to clinically active drugs and can, therefore, be used to identify novel therapies.