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Durable psoriasis improvement has been reported in a subset of psoriasis patients after treatment withdrawal of biologics blocking IL-23/Type 17 T-cell (T17) autoimmune axis. However, it is not well understood if systemic blockade of the IL-23/T17 axis promotes immune tolerance in psoriasis skin. The purpose of the study was to find translational evidence that systemic IL-17A blockade promotes regulatory transcriptome modification in human psoriasis skin immune cell subsets. We analyzed human psoriasis lesional skin 6 mm punch biopsy tissues before and after systemic IL-17A blockade using the muti-genomics approach integrating immune cell-enriched scRNA-seq (n = 18), microarray (n = 61), and immunohistochemistry (n = 61) with repository normal control skin immune cell-enriched scRNA-seq (n = 10) and microarray (n = 8) data. For the T17 axis transcriptome, systemic IL-17A blockade depleted 100% of IL17A + T-cells and 95% of IL17F + T-cells in psoriasis skin. The expression of IL23A in DC subsets was also downregulated by IL-17A blockade. The expression of IL-17-driven inflammatory mediators (IL36G, S100A8, DEFB4A, and DEFB4B) in suprabasal keratinocytes was correlated with psoriasis severity and was downregulated by IL-17A blockade. For the regulatory DC transcriptome, the proportion of regulatory semimature DCs expressing regulatory DC markers of BDCA-3 (THBD) and DCIR (CLEC4A) was increased in posttreatment psoriasis lesional skin compared to pretreatment psoriasis lesional skin. In addition, IL-17A blockade induced higher expression of CD1C and CD14, which are markers of CD1c+ CD14+ dendritic cell (DC) subset that suppresses antigen-specific T-cell responses, in posttreatment regulatory semimature DCs compared to pretreatment regulatory semimature DCs. In conclusion, systemic IL-17A inhibition not only blocks the entire IL-23/T17 cell axis but also promotes regulatory gene expression in regulatory DCs in human psoriasis skin.

Physician rating of cutaneous erythema is central to clinical dermatological assessment as well as quantification of outcome measures in clinical trials in a number of dermatologic conditions. However, issues with inter-rater reliability and variability in the setting of higher Fitzpatrick skin types make visual erythema assessment unreliable. We developed and validated a computer-assisted image-processing algorithm (EQscore) to reliably quantify erythema (across a range of skin types) in the dermatology clinical setting. Our image processing algorithm evaluated erythema based upon green light suppression differentials between affected and unaffected skin. A group of four dermatologists used a 4-point Likert scale as a human evaluation of similar erythematous patch tests. The algorithm and dermatologist scores were compared across 164 positive patch test reactions. The intra-class correlation coefficient of groups and the correlation coefficient between groups were calculated. The EQscore was validated on and independent image set of psoriasis, minimal erythema dose testing and steroid-induced blanching images. The reliability of the erythema quantification method produced an intra-class correlation coefficient of 0.84 for the algorithm and 0.67 for dermatologists. The correlation coefficient between groups was 0.85. The EQscore demonstrated high agreement with clinical scoring and superior reliability compared with clinical scoring, avoiding the pitfalls of erythema underrating in the setting of pigmentation. The EQscore is easily accessible (http://lab.rockefeller.edu/krueger/EQscore), user-friendly, and may allow dermatologists to more readily and accurately rate the severity of dermatological conditions and the response to therapeutic treatments.

Simple Summary: Early detection of melanoma and differentiation from benign nevi can be challenging even for the most experienced dermatologists. To improve melanoma detection, artificial intelligence algorithms incorporating dermoscopy have been developed, but lack transparency and therefore have limited training value for healthcare providers. To address this, an automated approach utilizing imaging biomarker cues (IBCs), logical features extracted from images that mimic expert dermatologists' dermoscopic pattern recognition skills, was developed. This study excluded deep learning approaches to which IBCs are complementary or alternative. Ten participants assessed 78 dermoscopic images (39 melanomas and 39 nevi) first without IBCs and then with IBCs. Using IBCs significantly improved diagnostic accuracy: sensitivity increased significantly from 73.69% to 81.57% (p = 0.0051) and specificity increased from 60.50% to 67.25% (p = 0.059). These results indicate that incorporating IBCs can significantly enhance melanoma diagnosis, with potential implications for improved screening practices. Further research is needed to confirm these findings across a variety of healthcare providers. Incorporation of dermoscopy and artificial intelligence (AI) is improving healthcare professionals' ability to diagnose melanoma earlier, but these algorithms often suffer from a "black box" issue, where decision-making processes are not transparent, limiting their utility for training healthcare providers. To address this, an automated approach for generating melanoma imaging biomarker cues (IBCs), which mimics the screening cues used by expert dermoscopists, was developed. This study created a one-minute learning environment where dermatologists adopted a sensory cue integration algorithm to combine a single IBC with a risk score built on many IBCs, then immediately tested their performance in differentiating melanoma from benign nevi. Ten participants evaluated 78 dermoscopic images, comprised of 39 melanomas and 39 nevi, first without IBCs and then with IBCs. Participants classified each image as melanoma or nevus in both experimental conditions, enabling direct comparative analysis through paired data. With IBCs, average sensitivity improved significantly from 73.69% to 81.57% (p = 0.0051), and the average specificity improved from 60.50% to 67.25% (p = 0.059) for the diagnosis of melanoma. The index of discriminability (d′) increased significantly by 0.47 (p = 0.002). Therefore, the incorporation of IBCs can significantly improve physicians' sensitivity in melanoma diagnosis. While more research is needed to validate this approach across other healthcare providers, its use may positively impact melanoma screening practices. [ABSTRACT FROM AUTHOR]

Hidradenitis suppurativa (HS) is an inflammatory skin disease characterized by painful nodules, abscesses and purulent secretions in intertriginous regions. Intense pruritus frequently accompanies HS lesions, adding further discomfort for patients. While Th17 pathway activation is implicated in HS pathogenesis, disease mechanisms are still not fully understood, and therapeutics are lacking. Previous reports raise a potential role for eosinophils in HS, showing a strong association of eosinophil levels with disease severity. To investigate eosinophils in HS, we recruited patients and matched healthy controls and then performed flow‐cytometry studies, eosinophil stimulation assays, and lesional skin staining for eosinophils. We found that HS patients reported similar levels of pain and itch. Compared to matched controls, HS blood exhibited decreased mature eosinophils and increased numbers of immature eosinophils, coupled with a significant increase in dermal eosinophilic infiltrates. Additionally, IL‐17RA+ eosinophils were highly and significantly correlated with multiple HS‐related clinical scores. In both stimulated and unstimulated conditions, HS eosinophils showed an inflammatory phenotype versus controls, including an increase in costimulatory T‐ and B‐cell markers (e.g. CD5 and CD40) following all stimulations (TNFα/IL‐17A/IL‐17F). These findings highlight the significance of pruritus in HS and suggest a higher turnover of eosinophils in HS blood, potentially due to the consumption of eosinophils in skin lesions. Our data delineate the features and functions of eosinophils in HS and suggest that eosinophils participate in disease pathogenesis, advancing Th17‐related inflammation. Further studies are needed to investigate eosinophils' response to current HS treatments and their potential as a therapeutic target in the disease. [ABSTRACT FROM AUTHOR]

Melanoma accounts for the majority of skin cancer‐related mortality, highlighting the need to better understand melanoma initiation and progression. In‐depth molecular analysis of neoplastic melanocytes in whole tissue biopsies may be diluted by inflammatory infiltration, which may obscure gene signatures specific to neoplastic cells. Thus, a method is needed to precisely uncover molecular changes specific to tumor cells from a limited sample of primary melanomas. Here, we performed laser capture microdissection (LCM) and gene expression profiling of patient‐derived frozen sections of pigmented lesions and primary cutaneous melanoma. Compared to bulk tissue analysis, analysis of LCM‐derived samples identified 9528 additional differentially expressed genes (DEGs) including melanocyte‐specific genes like PMEL and TYR, with enriched of pathways related to cell proliferation. LCM methodology also identified potentially targetable kinases specific to melanoma cells that were not detected by bulk tissue analysis. Taken together, our data demonstrate that there are marked differences in gene expression profiles depending on the method of sample isolation. We found that LCM captured higher expression of melanoma‐related genes while whole tissue biopsy identified a wider range of inflammatory markers. Taken together, our data demonstrate that LCM is a valid approach to identify melanoma‐specific changes using a relatively small amount of primary patient‐derived melanoma sample. [ABSTRACT FROM AUTHOR]

Interleukin (IL)‐23–independent IL‐17A production has been suggested to be involved in persistent manifestations of psoriatic disease, including anti–IL‐12/23–refractory psoriatic plaques; this study aimed to test this hypothesis by investigating the clinical and molecular effects of direct IL‐17A (with secukinumab) versus selective IL‐23 inhibition (with guselkumab) in patients with anti–IL‐12/23 (ustekinumab)–refractory psoriatic plaques. A 16‐week, randomized, open‐label, parallel‐group, Phase IIa study (ARROW, NCT03553823) was conducted in patients with ≥1 active psoriatic plaque (total clinical score [TCS] ≥6) at screening despite treatment with ustekinumab, and a Psoriasis Area and Severity Index (PASI) score 1–10. Patients were randomized 1:1 to receive secukinumab 300 mg (n = 20) or guselkumab 100 mg (n = 20). Biopsies from one refractory ('target plaque') were obtained at baseline and Week 16. The primary endpoint was the proportion of patients whose ustekinumab‐refractory target plaque achieved clear/almost clear status (TCS 0–2) at Week 16. Transcriptomic and histological analyses were conducted on target plaques to determine the molecular effects of direct IL‐17A versus selective IL‐23 inhibition. At Week 16, target plaque clear/almost clear status was achieved in 60.0% of patients treated with secukinumab versus 40.0% of patients treated with guselkumab (p = 0.1715). Molecular analyses identified that secukinumab modulated a greater proportion of psoriasis disease transcriptome genes (72.1% vs. 48.0%) and resulted in more histological responders (72.2% vs. 53.3%) compared with guselkumab. Secukinumab demonstrated a greater clinical and molecular effect on ustekinumab‐refractory psoriatic plaques versus guselkumab. These results are consistent with the hypothesis that IL‐23–independent IL‐17 mechanisms may be relevant to the inflammation driving refractory manifestations of psoriasis. [ABSTRACT FROM AUTHOR]

Durable psoriasis improvement has been reported in a subset of psoriasis patients after treatment withdrawal of biologics blocking IL-23/Type 17 T-cell (T17) autoimmune axis. However, it is not well understood if systemic blockade of the IL-23/T17 axis promotes immune tolerance in psoriasis skin. The purpose of the study was to find translational evidence that systemic IL-17A blockade promotes regulatory transcriptome modification in human psoriasis skin immune cell subsets. We analyzed human psoriasis lesional skin 6 mm punch biopsy tissues before and after systemic IL-17A blockade using the mutigenomics approach integrating immune cell-enriched scRNA-seq (n = 18), microarray (n = 61), and immunohistochemistry (n = 61) with repository normal control skin immune cell-enriched scRNA-seq (n = 10) and microarray (n = 8) data. For the T17 axis transcriptome, systemic IL-17A blockade depleted 100% of IL17A+ T-cells and 95% of IL17F+ T-cells in psoriasis skin. The expression of IL23A in DC subsets was also downregulated by IL-17A blockade. The expression of IL-17-driven inflammatory mediators (IL36G, S100A8, DEFB4A, and DEFB4B) in suprabasal keratinocytes was correlated with psoriasis severity and was downregulated by IL-17A blockade. For the regulatory DC transcriptome, the proportion of regulatory semimature DCs expressing regulatory DC markers of BDCA-3 (THBD) and DCIR (CLEC4A) was increased in posttreatment psoriasis lesional skin compared to pretreatment psoriasis lesional skin. In addition, IL-17A blockade induced higher expression of CD1C and CD14, which are markers of CD1c+ CD14+ dendritic cell (DC) subset that suppresses antigen-specific T-cell responses, in posttreatment regulatory semimature DCs compared to pretreatment regulatory semimature DCs. In conclusion, systemic IL-17A inhibition not only blocks the entire IL-23/T17 cell axis but also promotes regulatory gene expression in regulatory DCs in human psoriasis skin. [ABSTRACT FROM AUTHOR]

Background: The mechanisms driving alopecia areata (AA) are still unclear, hindering development of targeted therapeutics. Specific Th2 targeting with dupilumab in AA provides a unique opportunity to dissect its pathogenesis and explore the role of Th2 pathway. Methods: We evaluated changes in scalp biomarkers in AA patients (with and without concomitant atopy) randomized to weekly dupilumab or placebo for 24 weeks, followed by open‐label dupilumab for 24 weeks. Changes in biomarker levels were measured at weeks 12, 24, and 48 and were also correlated with clinical hair regrowth. Results: At week 24, preceding clinical hair regrowth outcomes, only dupilumab‐treated patients presented significant suppression of cellular infiltrates, and multiple Th2‐related, markers (CCL13/MCP‐4, CCL18/PARC, CCL26/eotaxin‐3, CCL24/Eotaxin‐2), coupled with significant upregulation in the hair keratins. Th1‐related suppression was evident later (week 48) when all patients received open‐label dupilumab. Results were more pronounced in atopic AA patients, that showed 48% and 97% improvements in the lesional AA scalp profile at weeks 24 and 48, respectively, while 2% worsening was seen in the placebo arm at week 24. Moreover, placebo‐treated patients presented 54% worsening in hair keratins when compared with baseline at week 24. At week 24, increases in hair keratins showed significant correlations only with decreases in Th2‐related markers. Conclusions: Scalp biomarkers provide evidence of dupilumab efficacy in AA, detected even prior to clinical response, with exclusive correlations between early suppression of Th2 markers and increased hair keratins. These findings strengthen previous reports suggesting a possible role for Th2 cytokines as AA drivers. [ABSTRACT FROM AUTHOR]