Immunologic Profiling of Immune-Related Cutaneous Adverse Events with Checkpoint Inhibitors Reveals Polarized Actionable Pathways

Purpose: Immune-related cutaneous adverse events (ircAEs) occur in ≥50% of patients treated with checkpoint inhibitors (CPI), but mechanisms are poorly understood. Experimental Design: Phenotyping/biomarker analyses were conducted in 200 patients on CPIs (139 with ircAEs, 61 without, control) to characterize their clinical presentation and immunologic endotypes. Cytokines were evaluated in skin biopsies, skin tape strip (STS) extracts and plasma using real-time PCR and Meso Scale Discovery multiplex cytokine assays. Results: Eight ircAE phenotypes were identified: pruritus (26%), maculopapular rash (MPR; 21%), eczema (19%), lichenoid (11%), urticaria (8%), psoriasiform (6%), vitiligo (5%), and bullous dermatitis (4%). All phenotypes showed skin lymphocyte and eosinophil infiltrates. Skin biopsy PCR revealed the highest increase in IFN-gamma mRNA in patients with lichenoid (p<0.0001) and psoriasiform dermatitis (p<0.01) as compared to patients without ircAEs, while the highest IL-13 mRNA levels were detected in the eczema (p<0.0001, compared to control). IL-17A mRNA was selectively increased in psoriasiform (p<0.001), lichenoid (p<0.0001), bullous dermatitis (p<0.05) and MPR (p<0.001), compared to control. Distinct cytokine profiles were confirmed in STS and plasma. Analysis determined increased skin/plasma IL-4 cytokine in pruritus, skin IL-13 in eczema, plasma IL-5 and IL-31 in eczema and urticaria, and mixed-cytokine pathways in MPR. Broad inhibition via corticosteroids or type 2-cytokine targeted inhibition resulted in clinical benefit in these ircAEs. In contrast, significant skin upregulation of type 1/type 17 pathways was found in psoriasiform, lichenoid, bullous dermatitis, and type 1 activation in vitiligo. Conclusions: Distinct immunologic ircAE endotypes suggest actionable targets for precision medicine-based interventions

CoC: A database of universally conserved residues in protein folds.

Summary: The Conservatism of Conservatism (CoC) database presents statistically analyzed information about the conservation of residue positions in folds across protein families. Availability: On the web a

Prevalence and Age-Related Patterns in Health Information–Seeking Behaviors and Technology Use Among Skin Cancer Survivors: Survey Study

BackgroundInformation is an unmet need among cancer survivors. There is a paucity of population-based data examining the health information–seeking behaviors and attitudes of skin cancer survivors. ObjectiveWe aimed to identify the prevalence and patterns of health information–seeking behaviors and attitudes among skin cancer survivors across age groups. MethodsWe analyzed population-based data from the 2019 Health Information National Trends Survey 5 (Cycle 3). ResultsThe 5438 respondents included 346 (6.4%) skin cancer survivors (mean age 65.8 years); of the 346 skin cancer survivors, the majority were White (96.4% [weighted percentages]), and 171 (47.8%) were men. Most reported having ever looked for health- (86.1%) or cancer-related (76.5%) information; 28.2% stated their last search took a lot of effort, and 21.6% were frustrated. The internet was most often cited as being the first source that was recently used for health or medical information (45.6%). Compared to skin cancer survivors younger than 65 years old, those 65 years of age or older were more likely to see a doctor first for important health information (≥65 years: 68.3%;<65 years: 36.2%; P<.001) and less likely to have health and wellness apps (≥65 years: 26.4%; <65 years: 54.0%, P=.10), to have watched a health-related YouTube video (≥65 years: 13.3%; <65 years: 27.4%; P=.02), and to have used electronic means to look for information (≥65 years: 61.4%;<65 years: 82.3%, P<.001) ConclusionsSearches for health information are common among skin cancer survivors, but behaviors and attitudes are associated with age, which highlights the importance of access to doctors and personalized information sources

Pancreatic cancer: Cutaneous metastases, clinical descriptors and outcomes

Abstract Background Cutaneous metastases in pancreatic cancer (PC) are rare. Herein, we evaluate the clinical, genomic, and other descriptors of patients with PC and cutaneous metastases. Methods Institutional databases were queried, and clinical history, demographics, PC cutaneous metastasis details, and overall survival (OS) from cutaneous metastasis diagnosis were abstracted. OS was estimated using Kaplan–Meier methods. Results Forty patients were identified, and median age (Q1–Q3, IQR) of PC diagnosis was 66.0 (59.3–72.3, 12.9) years. Most patients had Stage IV disease at diagnosis (n = 26, 65%). The most common location of the primary tumor was the tail of the pancreas (n = 17, 43%). The most common cutaneous metastasis site was the abdomen (n = 31, 78%), with umbilical lesions occurring in 74% (n = 23) of abdominal lesions. The median OS (95% CI) was 11.4 months (7.0, 20.4). Twenty‐three patients had umbilical metastases (58%), and 17 patients had non‐umbilical metastases (43%). The median OS (95% CI) was 13.7 (7.0, 28.7) months in patients with umbilical metastases and 8.9 (4.1, Not reached) months in patients with non‐umbilical metastases (p = 0.1). Sixteen of 40 (40%) patients underwent somatic testing, and findings were consistent with known profiles. Germline testing in 12 (30%) patients identified pathogenic variants in patients: CHEK2, BRCA1, and ATM. Conclusion Cutaneous metastases from PC most frequently arise from a pancreas tail primary site and most frequently occur in the umbilicus. Cutaneous metastases may generally be categorized as umbilical or non‐umbilical metastases

ISIC2018_Task1-2_Training_Input.zip

 To comply with the attribution requirements of the CC-BY-NC license , the aggregate "ISIC 2018: Training" data must be cited as: HAM10000 Dataset: (c) by ViDIR Group, Department of Dermatology, Medical University of Vienna; https://doi.org/10.1038/sdata.2018.161 MSK Dataset: (c) Anonymous; https://arxiv.org/abs/1710.05006; https://arxiv.org/abs/1902.03368 When referencing this dataset in your own manuscripts and publications, please use the following full citations: [1] Noel Codella, Veronica Rotemberg, Philipp Tschandl, M. Emre Celebi, Stephen Dusza, David Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael Marchetti, Harald Kittler, Allan Halpern: "Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)", 2018; https://arxiv.org/abs/1902.03368 [2] Tschandl, P., Rosendahl, C. & Kittler, H. The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. Sci. Data 5, 180161 doi:10.1038/sdata.2018.161 (2018).</blockquote

Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working Group

IMPORTANCE The use of artificial intelligence (AI) is accelerating in all aspects of medicine and has the potential to transform clinical care and dermatology workflows. However, to develop image-based algorithms for dermatology applications, comprehensive criteria establishing development and performance evaluation standards are required to ensure product fairness, reliability, and safety. OBJECTIVE To consolidate limited existing literature with expert opinion to guide developers and reviewers of dermatology AI. EVIDENCE REVIEW In this consensus statement, the 19 members of the International Skin Imaging Collaboration AI working group volunteered to provide a consensus statement. A systematic PubMed search was performed of English-language articles published between December 1, 2008, and August 24, 2021, for “artificial intelligence” and “reporting guidelines,” as well as other pertinent studies identified by the expert panel. Factors that were viewed as critical to AI development and performance evaluation were included and underwent 2 rounds of electronic discussion to achieve consensus. FINDINGS A checklist of items was developed that outlines best practices of image-based AI development and assessment in dermatology. CONCLUSIONS AND RELEVANCE Clinically effective AI needs to be fair, reliable, and safe; this checklist of best practices will help both developers and reviewers achieve this goal

Activating mutations in CSF1R and additional receptor tyrosine kinases in histiocytic neoplasms

Histiocytoses are clonal hematopoietic disorders frequently driven by mutations mapping to the BRAF and MEK1 and MEK2 kinases. Currently, however, the developmental origins of histiocytoses in patients are not well understood, and clinically meaningful therapeutic targets outside of BRAF and MEK are undefined. In this study, we uncovered activating mutations in CSF1R and rearrangements in RET and ALK that conferred dramatic responses to selective inhibition of RET (selpercatinib) and crizotinib, respectively, in patients with histiocytosis

Sebaceous carcinoma: evidence-based clinical practice guidelines

Sebaceous carcinoma usually occurs in adults older than 60 years, on the eyelid, head and neck, and trunk. In this Review, we present clinical care recommendations for sebaceous carcinoma, which were developed as a result of an expert panel evaluation of the findings of a systematic review. Key conclusions were drawn and recommendations made for diagnosis, first-line treatment, radiotherapy, and post-treatment care. For diagnosis, we concluded that deep biopsy is often required; furthermore, differential diagnoses that mimic the condition can be excluded with special histological stains. For treatment, the recommended first-line therapy is surgical removal, followed by margin assessment of the peripheral and deep tissue edges; conjunctival mapping biopsies can facilitate surgical planning. Radiotherapy can be considered for cases with nerve or lymph node involvement, and as the primary treatment in patients who are ineligible for surgery. Post-treatment clinical examination should occur every 6 months for at least 3 years. No specific systemic therapies for advanced disease can be recommended, but targeted therapies and immunotherapies are being developed