Psoriatic Microenvironment Score May Predict Clinical Efficacy of Systemic Psoriasis Therapy

Researchers used the CIBERSORT algorithm to develop a bioinformatic gene signature score to predict outcomes of psoriasis treatment.

The psoriatic microenvironment (PME) score, based on a bioinformatic analysis of the psoriatic microenvironment, may predict the clinical efficacy of systemic psoriasis therapy in advance of clinical responses, according to study data published in JAMA Dermatology.

Researchers sought to develop a bioinformatic gene signature score that was derived from skin mRNA to help predict outcomes of psoriasis treatment. To define the PME, they used CIBERSORT, an algorithm that identifies specific individual immune cell subsets. The analysis involved 1145 skin samples from different cohorts of 12 retrospective psoriasis studies. A total of 157, 71, 89, and 90 psoriasis lesions were treated with etanercept, tofacitinib, adalimumab, and methotrexate, respectively. The main outcome measure was the number of weeks after treatment was initiated that responders and nonresponders could be predicted.

The investigators found that 22 immune cell subtypes formed infiltration patterns that differentiated psoriasis lesions from healthy skin. Among the lesions, the expression of 33 PME signature genes defined 2 immune phenotypes and could be simplified to a numerical PME score. A high PME score, characterized by keratinocyte differentiation, correlated with a better treatment response (Psoriasis Area and Severity Index [PASI] reduction, 75.8%; 95% CI, 69.4%-82.2%; P =.03). A low PME score demonstrated an immune activation signature and was associated with a worse response (PASI reduction, 53.5%; 95% CI, 45.3%-61.7%; P =.03).

“The PME score at week 4 after treatment initiation correlated with future responder versus nonresponder to treatment status 8 to 12 weeks earlier than PASI reduction for etanercept, methotrexate plus adalimumab, and tofacitinib,” the researchers noted.

The study has several limitations, including the use of public data sets, and the investigators could not obtain or verify clinical findings on each participant. Also, investigators used PASI75 as their indicator to identify ifthe patient was a responder or nonresponder; many therapies can now reach PASI90 or PASI100.

“We have defined a novel biometric score, the PME score, that characterizes the psoriatic microenvironment for psoriasis treatment response and provides new insights into psoriasis pathogenesis,” the researchers concluded. “The PME score is a possible platform to predict psoriasis treatment responses before they are detectable clinically. As an example of personalized medicine for psoriasis, this tool has the potential to shorten the treatment duration of ineffective medications and limit drug development time, health care costs, medication adverse effects, and general patient burden.”


Wang G, Miao Y, Kim N, et al. Association of the psoriatic microenvironment with treatment response. Published online September 2, 2020. JAMA Dermatol. doi:10.1001/jamadermatol.2020.2118