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Kathryn Haran,1,* Allison Kranyak,1,* Chandler E Johnson,2 Payton Smith,2 Aaron S Farberg,3,4 Tina Bhutani,1 Wilson Liao1,2 1Department of Dermatology, University of California San Francisco, San Francisco, CA, USA; 2Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA; 3Baylor Scott & White Health System, Dallas, TX, USA; 4Bare Dermatology, Dallas, TX, USA*These authors contributed equally to this workCorrespondence: Kathryn Haran, Department of Dermatology, University of California San Francisco, 2340 Sutter St N414, San Francisco, CA, 94115, USA, Tel +1 (415) 944-7618, Email Kathryn.haran@ucsf.eduAbstract: While psoriasis and atopic dermatitis (AD) are two common dermatological conditions, their diagnosis and therapeutic decision-making pathways are often complex. As a result, there has been increased focus on the development of precision medicine approaches for psoriasis and AD. Two companies at the forefront of dermatology precision medicine research are Mindera Health and Castle Biosciences. Here, we review the technologies developed by these two companies using a dermal diagnostic patch and superficial skin scrapings, respectively, their research published to date, and their future research goals. Research from both companies shows promise in predicting the response of inflammatory skin disease to biologics using minimally invasive techniques. However, challenges to adoption include insurance coverage and patient trust in the technologies. While there are several differences between Mindera Health and Castle Biosciences, they have a shared goal of utilizing minimally invasive technologies to sample skin and predict response to biologic treatments using a panel of optimized biomarkers.Keywords: machine learning, genetics, technology, diagnosis

Samantha J Palomares, Aaron S Farberg Bare Dermatology, Dallas, TX, USACorrespondence: Aaron S Farberg, Tel +1 847 721 2725, Email aaron.farberg@gmail.comAbstract: Necrobiosis lipoidica (NL) is a chronic granulomatous disorder of the skin which usually presents with red papules and plaques on the lower extremities. Diabetes mellitus has been found to be associated with NL, but the pathophysiology of the disease is unknown. Based on a Doppler flowmetry study showing increased blood flow at NL lesions and the macrophage upregulation of granulomatous disorders, it is reasonable to conclude that there is an inflammatory component to it. NL is extremely challenging to manage. The initial treatment of choice is usually topical or intralesional corticosteroids, and if this fails to work, many dermatologists depend on the small number of case reports for more treatment options. We present a pre-diabetic patient with nonulcerative NL who was successfully treated with the first-in-class therapeutic aryl hydrocarbon receptor (AHR)-modulating agent tapinarof cream (VTAMA, Dermavant). Following the case presentation is a discussion of this topical novel agent and its unique anti-inflammatory mechanism of action. Tapinarof specifically binds to and activates AHR leading to downregulation of TNF-α/IL-23/IL-17 and inhibition of IL-4/IL-13 mediated STAT6 activation. Anti-TNF-α agents and JAK-inhibitors have also been found to be beneficial in treating NL; tapinarof seems to target both these pathways without the risk of their serious adverse reactions.Keywords: aryl hydrocarbon receptor, AHR, granulomatous disease, JAK-STAT pathway, macrophage activation disorder, necrobiosis lipoidica diabeticorum, therapeutic aryl hydrocarbon receptor-modulating agent, TAMA, tumor necrosis factor-alpha antagonists, TNF-α antagonists

Gaurav Singh,1 Stanislav N Tolkachjov,2– 5 Aaron S Farberg5– 7 1Gaurav Singh MD, Milwaukee, WI, USA; 2Epiphany Dermatology, Dallas, TX, USA; 3University of Texas at Southwestern, Dallas, TX, USA; 4Baylor University Medical Center, Dallas, TX, USA; 5Texas A&M College of Medicine, Dallas, TX, USA; 6Bare Dermatology, Dallas, TX, USA; 7Baylor Scott & White Health System, Dallas, TX, USACorrespondence: Aaron S Farberg, Bare Dermatology, 2110 Research Row, Dallas, TX, 75235, USA, Tel +1 847-721-2725, Email aaron.farberg@gmail.comAbstract: Cutaneous squamous cell carcinoma (cSCC) has become a significant public health issue due to its rapidly rising incidence and an estimated 1.8 million newly diagnosed cases annually. As with other cancers, treatment decisions for patients with cSCC are based primarily on a patient’s risk for poor outcomes. There has been improvement in clinicopathologic factor-based risk assessment approaches, either through informal methods or ever evolving staging approaches. However, these approaches misidentify patients who will eventually have disease progression as low-risk and conversely, over classify patients as high-risk who do not experience relapse. To improve the accuracy of risk assessment for patients with cSCC, the 40-gene expression profile (40-GEP) test has been validated to show statistically significant stratification of a high-risk cSCC patient’s risk of nodal or distant metastasis, independent of currently available risk-assessment methods. The 40-GEP test allows for a more accurate classification of metastatic risk for high-risk cSCC patients, with the aim to influence appropriate allocation of clinician time and therapeutic resources to those patients who will most benefit. The objective of this article is to present a treatment algorithm in which clinicians can easily integrate the results of the 40-GEP test into their current treatment approaches to tailor patient care based on individual tumor biology. The following modalities were considered: surveillance imaging, sentinel lymph node biopsy (SLNB), adjuvant radiation therapy (ART), and clinical follow-up. The authors have contributed their own cases for discussion as to how they have seen the beneficial impact of 40-GEP test results in their own practice. Overall, clinicians can identify risk-aligned treatment pathway improvements with the use of the 40-GEP test for challenging to manage, high-risk cSCC patients.Keywords: 40-gene expression profile, 40-GEP, cutaneous squamous cell carcinoma, cSCC, metastasis, patient management, clinician algorithm, prognostic, risk-stratification

While psoriasis and atopic dermatitis (AD) are two common dermatological conditions, their diagnosis and therapeutic decision-making pathways are often complex. As a result, there has been increased focus on the development of precision medicine approaches for psoriasis and AD. Two companies at the forefront of dermatology precision medicine research are Mindera Health and Castle Biosciences. Here, we review the technologies developed by these two companies using a dermal diagnostic patch and superficial skin scrapings, respectively, their research published to date, and their future research goals. Research from both companies shows promise in predicting the response of inflammatory skin disease to biologics using minimally invasive techniques. However, challenges to adoption include insurance coverage and patient trust in the technologies. While there are several differences between Mindera Health and Castle Biosciences, they have a shared goal of utilizing minimally invasive technologies to sample skin and predict response to biologic treatments using a panel of optimized biomarkers.

Simple Summary: Patients with skin lesions suspicious for skin cancer or atypical melanocytic nevi of uncertain malignant potential often present to dermatologists, who may have variable dermoscopy triage clinical experience. We evaluated the clinical utility of a digital dermoscopy image-based artificial intelligence algorithm (DDI-AI device) on the diagnosis and management of skin cancers. Thirty-six United States board-certified dermatologists evaluated 50 cases with clinical images and DDI of the same skin lesions (25 malignant and 25 benign), first without and then with knowledge of the DDI-AI device output. We identified that when using the DDI-AI device, management sensitivity, management specificity, diagnostic sensitivity, and diagnostic specificity all increased over baseline use of clinical images and dermoscopy images. Hence, the use of the DDI-AI device may quickly, safely, and effectively improve dermoscopy performance, skin cancer diagnosis, and management when used by dermatologists, independent of training and experience. Background: Patients with skin lesions suspicious for skin cancer or atypical melanocytic nevi of uncertain malignant potential often present to dermatologists, who may have variable dermoscopy triage clinical experience. Objective: To evaluate the clinical utility of a digital dermoscopy image-based artificial intelligence algorithm (DDI-AI device) on the diagnosis and management of skin cancers by dermatologists. Methods: Thirty-six United States board-certified dermatologists evaluated 50 clinical images and 50 digital dermoscopy images of the same skin lesions (25 malignant and 25 benign), first without and then with knowledge of the DDI-AI device output. Participants indicated whether they thought the lesion was likely benign (unremarkable) or malignant (suspicious). Results: The management sensitivity of dermatologists using the DDI-AI device was 91.1%, compared to 84.3% with DDI, and 70.0% with clinical images. The management specificity was 71.0%, compared to 68.4% and 64.9%, respectively. The diagnostic sensitivity of dermatologists using the DDI-AI device was 86.1%, compared to 78.8% with DDI, and 63.4% with clinical images. Diagnostic specificity using the DDI-AI device increased to 80.7%, compared to 75.9% and 73.6%, respectively. Conclusion: The use of the DDI-AI device may quickly, safely, and effectively improve dermoscopy performance, skin cancer diagnosis, and management when used by dermatologists, independent of training and experience. [ABSTRACT FROM AUTHOR]

Background/Objectives: Basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) are non-melanoma skin cancers (NMSCs) and the most prevalent cancers in the United States. Image-guided superficial radiotherapy (IGSRT) is a relatively new treatment option that uses high-resolution dermal ultrasound integrated with superficial radiotherapy to improve tumor visualization. IGSRT is a clinically equivalent non-surgical alternative to Mohs micrographic surgery at 2 years of follow-up in early-stage NMSC, but larger cohort studies with longer follow-up periods that allow for analysis of patient outcomes by demographic and disease characteristics are needed. Methods: This large, retrospective cohort study was conducted to determine the effect of risk factors (tumor location, tumor stage, and sex) on 2-, 4-, and 6-year freedom from recurrence rates in 19,988 NMSC lesions treated with IGSRT, including lesions with complete treatment courses. Results: Overall freedom from recurrence rates were 99.68% at 2 years, 99.54% at 4 years, and 99.54% at 6 years; rates did not differ significantly by tumor location (head/neck versus other locations, p = 0.9) or sex (male versus female, p = 0.4). In contrast, there was a significant difference in freedom from recurrence rates when analyzed by tumor stage (p = 0.004). Conclusions: There was no significant effect of tumor location or sex on freedom from recurrence in IGSRT-treated NMSC. Although there was a significant difference according to tumor stage, freedom from recurrence rates exceeded 99% at all stages. [ABSTRACT FROM AUTHOR]

Abstract Background To improve identification of patients with cutaneous squamous cell carcinoma (SCC) at high risk for metastatic disease, the DecisionDx-SCC assay, a prognostic 40-gene expression profile (40-GEP) test, was developed and validated. The 40-GEP assay utilizes RT-PCR gene expression analysis on primary tumor biopsy tissue to evaluate the expression of 34 signature gene targets and 6 normalization genes. The test provides classifications of low risk (Class 1), moderate risk (Class 2A), and high risk (Class 2B) of metastasis within 3 years of diagnosis. The primary objective of this study was to validate the analytical performance of the 40-gene expression signature. Methods The repeatability and reproducibility of the 40-GEP test was evaluated by performance of inter-assay, intra-assay, and inter-operator precision experiments along with monitoring the reliability of sample and reagent stability for class call concordance. The technical performance of clinical orders from September 2020 through July 2021 for the 40-GEP test was assessed. Results Patient hematoxylin and eosin (H&E) stained slides were reviewed by a board-certified pathologist to assess minimum acceptable tumor content. Class specific controls (Class 1 and Class 2B) were evaluated with Levey-Jennings analysis and demonstrated consistent and reproducible results. Inter-assay, inter-operator and intra-assay concordance were all ≥90%, with short-term and long-term RNA stability also meeting minimum concordance requirements. Of the 2586 orders received, 93.5% remained eligible for testing, with 97.1% of all tested samples demonstrating actionable class call results. Conclusion DecisionDx-SCC demonstrates a high degree of analytical precision, yielding high concordance rates across multiple performance experiments, along with exhibiting robust technical reliability on clinical samples.

Background/Study Aim: A multispectral digital skin lesion analysis (MSDSLA) device has proven to be sensitive and specific for malignant melanoma (MM) detection by dermatologists and may have other useful applications. This study aimed to develop and test objective quantitative Asymmetry, Border irregularity, Color, and Diameter (qABCD) parameters for MSDSLA and correlate them with the presence of clinical ABCD features to aid the decision to biopsy a suspicious pigmented skin lesions (PSLs).Methods: 1632 benign and malignant [175 MM/High Grade Dysplastic Nevi (HGDN)] were evaluated for their qABCD parameters. Quantitative characteristics were correlated with the presence of clinical ABCD features identified by independent dermatologists.Results: qA, qB, qC, and qD had correlations of 78%, 73%, 76%, and 86%, respectively, for non-MM/HGDN lesions. The correlations for qA, qB, qC, and qD for MM/HGDN lesions was 86.3%, 83%, 89%, and 89%, respectively. All repeatability parameters were statistically significant.Conclusions: This study demonstrates qABCD values are repeatable and strongly correlate with the clinical ABCD features. qABCD characteristics provide an additional objective and reliable means of identifying PSLs that need further evaluation to rule out MM and, in combination with the clinical ABCDs, may allow for improved assessment when evaluating the malignant potential of PSLs.