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October 01, 2020
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Psoriatic microenvironment may help predict treatment response

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A psoriatic microenvironment score could help predict how some psoriatic lesions will respond to certain treatments, allowing practitioners to reduce exposure to ineffective therapies, according to a study.

“In this study, analysis of whole-genome mRNA expression in skin biopsies identified two different immune profiles that correlate with psoriatic lesional and nonlesional skin; with systemic treatment, the immune phenotype of psoriatic lesional skin reverted to a nonlesional pattern,” study author Gaofeng Wang, MD, PhD, told Healio. “The PME score is a bioinformatic metric that encompasses these changes and correlates with future clinical responses 8 weeks prior to apparent clinical differences.”

In the retrospective study, the CIBERSORT algorithm was used to define and classify psoriatic lesions, and then psoriatic microenvironment (PME) signature genes were estimated.

Cohorts from 12 retrospective psoriasis studies were used, including 1,145 skin samples.

Twenty-two immune cell subtypes were identified, differentiating psoriatic lesions from healthy skin. Thirty-three PME signature genes defined two immune phenotypes, according to the study.

Those with a high PME score had a better treatment response, as defined by a reduction in Psoriasis Area and Severity Index score, compared with those with a lower PME score. At week 16, those with a higher PME had an average reduction in PASI of 75.8% (95% CI, 69.4%-82.2%; P = .03). Those with a lower PME score had a reduction of 53.5% (95% CI, 45.3%-61.7%; P = .03).

“The PME score can be viewed as part of a novel and an emerging movement in medicine to tailor individual treatments to an individual’s genetic expression profile. This approach could be used to identify responders and nonresponders before clinical changes to more rapidly switch therapeutic strategies in nonresponders,” Wang said. “Rather than using a uniform therapy for all patients or disease subtypes, our approach used molecular information belonging to an individual patient to develop a personalized treatment. This could improve psoriatic clinical practice through enhanced patient drug evaluation/treatment, clinical trial conduct and drug development design.”