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Malignant T lymphocyte proliferation in mycosis fungoides (MF) is largely restricted to the skin, implying that malignant cells are dependent on their specific cutaneous tumor microenvironment (TME), including interactions with non-malignant immune and stromal cells, cytokines, and other immunomodulatory factors. To explore these interactions, we performed a comprehensive transcriptome analysis of the TME in advanced-stage MF skin tumors by single-cell RNA sequencing. Our analysis identified cell-type compositions, cellular functions, and cell-to-cell interactions in the MF TME that were distinct from those from healthy skin and benign dermatoses. While patterns of gene expression were common among patient samples, high transcriptional diversity was also observed in immune and stromal cells, with dynamic interactions and crosstalk between these cells and malignant T lymphocytes. This heterogeneity mapped to processes such as cell trafficking, matrix interactions, angiogenesis, immune functions, and metabolism that affect cancer cell growth, migration, and invasion, as well as antitumor immunity. By comprehensively characterizing the transcriptomes of immune and stromal cells within the cutaneous microenvironment of individual MF tumors, we have identified patterns of dysfunction common to all tumors that represent a resource for identifying candidates with therapeutic potential as well as patient-specific heterogeneity that has important implications for personalized disease management.

Coccidioidomycosis is a fungal infection that primarily manifests as an asymptomatic condition caused by inhalation of fungal spores. Less commonly, patients can develop dissemination to extrapulmonary locations such as the skin or primary cutaneous inoculation of the fungus at a site of trauma. These cutaneous complications are primarily found among immunosuppressed individuals. Here, we present a patient with no relevant past medical history that, after living in an area to which Coccidioides is endemic, developed a slowly growing, pruritic plaque on his right thigh with well‐demarcated areas of hypopigmentation and lichenification with erythematous borders; after several inconclusive biopsies, fungal spherules characteristic of coccidioidomycosis were found on pathology. Along with morphologic evidence of trauma at the site of the infection, the most likely diagnosis was determined to be primary cutaneous coccidioidomycosis. This case is notable for several reasons. First, the patient had a persistent cutaneous coccidioidomycosis infection, with a rare clinical presentation, despite no history of immunocompromising conditions or medications. Second, the patient experienced disease progression while on an empiric trial of a Janus Kinase (JAK) inhibitor. Taken together, these findings may suggest a clinical distinction between the presentation of cutaneous fungal infections in immunocompetent and immunocompromised patients.

Decision paralysis (DP) can be defined as a patient’s inability to commit to a physician and/or initiate appropriate treatment for their condition. An incessant search for greater physician opinions often leads to treatment delay, disease progression, and initiation of care at more advanced stages. Despite the harms associated with DP, a dearth of research on the issue remains. There are no guidelines that assist in both recognition and rectification of DP, leaving patients with chronic illnesses and diagnoses without well-characterized treatment algorithms especially vulnerable. This paper analyzes why patients are inclined toward DP and the clinical implications. Review of the literature affirms that the patient–physician relationship holds considerable influence; physicians identifying DP can improve therapeutic outcomes for their patients. Using these findings, we then propose a framework for broaching this topic with a method that supports patients while respecting their autonomy. A practical approach to both recognition and patient-centered discourse is introduced, providing a foundation for physicians to host these conversations and understand their patients’ perspectives. This approach toward recognition and discourse on DP holds clinical importance, given that there is a paucity of established guidance. A future uniform approach may generate optimal patient care recommendations, which will hold far-reaching impact on both the patient–physician relationship and overall patient outcomes.

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient’s disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.

The presence of actinic keratoses (AKs) increases a patient’s risk of developing squamous cell carcinoma by greater than six-fold. We evaluated the effect of topical treatment with imiquimod on the tumor microenvironment by measuring transcriptomic differences in AKs before and after treatment with imiquimod 3.75%. Biopsies were collected prospectively from 21 patients and examined histologically. RNA was extracted and transcriptomic analyses of 788 genes were performed using the nanoString assay. Imiquimod decreased number of AKs by study endpoint at week 14 ( p  < 0.0001). Post-imiquimod therapy, levels of CDK1, CXCL13, IL1B, GADPH, TTK, ILF3, EWSR1, BIRC5, PLAUR, ISG20, and C1QBP were significantly lower (adjusted p  < 0.05). Complete responders (CR) exhibited a distinct pattern of inflammatory gene expression pre-treatment relative to incomplete responders (IR), with alterations in 15 inflammatory pathways ( p  < 0.05) reflecting differential expression of 103 genes ( p  < 0.05). Presence of adverse effects was associated with improved treatment response. Differences in gene expression were found between pre-treatment samples in CR versus IR, suggesting that higher levels of inflammation pre-treament may play a part in regression of AKs. Further characterization of the immune micro-environment in AKs may help develop biomarkers predictive of response to topical immune modulators and may guide therapy.

BackgroundImmune checkpoint blockade has emerged as a highly effective treatment for patients with metastatic melanoma and cutaneous squamous cell carcinoma. Nivolumab blocks the interactions between programmed cell death protein 1 and programmed death ligand 1 allowing for activation of a latent immune response against the malignancy. Ipilimumab binds to and blocks cytotoxic T-lymphocyte-associated protein 4, alleviating the negative regulation of T-cell activation that is mediated by that checkpoint. Combination therapy with nivolumab and ipilimumab is associated with longer overall survival at 5 years compared with nivolumab monotherapy. Solid organ transplant recipients have a significantly higher risk of malignancies compared with the general population. There is limited data surrounding the efficacy of combination immunotherapy in solid organ transplant recipients, as these patients were excluded from seminal trials due to risk of organ rejection.Case presentationsHere we present four cases of combination immunotherapy in kidney transplant recipients. Three patients had metastatic melanoma, and one patient had metastatic cutaneous squamous cell carcinoma. Two patients had radiographic responses from immunotherapy, one patient had stable disease, and one patient had disease progression. Only one patient had biopsy-proven rejection. At last follow-up, three patients had functioning grafts, though one required hemodialysis after treatment, and one patient succumbed to disease, but graft function remained intact throughout her course.ConclusionsThese cases describe the use of ipilimumab and nivolumab combination immunotherapy for cutaneous malignancies in kidney transplant recipients. They highlight the potential to preserve kidney graft function while effectively treating the disease.

Abstract Background Cancer and its treatments frequently compromise skin integrity, leading to xerosis, pruritus, dermatitis, radiation-induced skin damage, and secondary infections. These cutaneous adverse events (cAEs) are not merely superficial; they profoundly impact patient quality of life (QoL), contributing to physical discomfort, psychosocial distress, and poorer treatment adherence. Even mild skin toxicities elevate dermatology-specific QoL measures, affecting mood and social function. Additionally, new targeted therapies, such as daraxonrasib—a KRAS inhibitor under development for pancreatic cancer—can cause a dose-limiting acneiform facial rash. Methods In this study, relevant literature on skin care in cancer patients was identified using PubMed. Evidence from clinical studies, reviews, and expert guidelines was summarized. Results Evidence supports proactive skincare with gentle pH-balanced cleansers, ceramide- or urea-based moisturizers, and broad-spectrum photoprotection to lessen symptom severity and improve QoL. Sun protection remains essential because chemotherapy and immunomodulatory therapies increase photosensitivity, accelerate photoaging, and raise the risk of secondary skin cancers. Supportive skincare interventions have also shown emotional and functional benefits, including improved mood and self-image during chemotherapy and radiation treatment. Conclusion Despite strong data supporting moisturization, barrier repair, and photoprotection, oncologic treatment plans often overlook these interventions. By integrating dermatologic education and skincare maintenance into standard oncologic practice, we can minimize cAEs, foster treatment compliance, and enhance patients’ physical comfort and psychosocial well-being. This narrative review synthesizes mechanistic insights, clinical evidence, and practical recommendations for oncologists to champion comprehensive skincare in all cancer patients, whether directly affected by skin issues or not.

Reports describe lymphoproliferative disorders after COVID-19 vaccination. We analyse world literature to report on remarkable consistencies such as reactions to the same vaccines and shared clinical and pathological findings. COVID-19 vaccination may be associated with reactive and indolent lymphoproliferative disorders, thus unusual reactions merit diagnostic biopsies. Reactions occur based on vaccine type proportionally to global market share. Abstract Background Individual reports have described lymphoproliferative disorders (LPDs) and cutaneous lymphomas emerging after administration of the COVID-19 vaccine; however, the relationship between reactions and vaccine types has not yet been examined. Objective Determine if there are cases of cutaneous LPDs associated with certain COVID-19 vaccines and their outcomes. Methods We analysed PubMed, the Vaccine Adverse Events Reporting System (VAERS), and our database for instances of biopsy-proven LPDs following COVID-19 vaccines. Results Fifty cases of biopsy-proven LPDs arising after COVID-19 vaccination were found: 37 from medical literature, 11 from VAERS and two from our institution. Geographical distribution revealed the most cases in the United States, Italy, and Greece, with single cases in Spain, Colombia, Canada, Japan, and Romania. The average age of patients was 53; with a slight male predominance (male-to-female ratio of 1.5:1). The Pfizer-BioNTech vaccine was associated with LPDs in 36/50 (72%) cases, aligning with its 70% share of the global vaccine market. Histopathology revealed CD30+ in 80% of cases. The most prevalent form of LPD was lymphomatoid papulosis (LyP, 30%). All reported cases produced favourable outcomes (either complete or near-complete remission). Therapeutic approaches ranged from observation to treatment with steroids, methotrexate, or excision. Conclusion LPDs after COVID-19 vaccination appear in the context of the same vaccines (proportionally to their global market shares), share clinical and pathological findings, and have indolent, self-limited character.

Skin cancer mortality rates continue to rise, and survival analysis is increasingly needed to understand who is at risk and what interventions improve outcomes. However, current statistical methods are limited by inability to synthesize multiple data types, such as patient genetics, clinical history, demographics, and pathology and reveal significant multimodal relationships through predictive algorithms. Advances in computing power and data science enabled the rise of artificial intelligence (AI), which synthesizes vast amounts of data and applies algorithms that enable personalized diagnostic approaches. Here, we analyze AI methods used in skin cancer survival analysis, focusing on supervised learning, unsupervised learning, deep learning, and natural language processing. We illustrate strengths and weaknesses of these approaches with examples. Our PubMed search yielded 14 publications meeting inclusion criteria for this scoping review. Most publications focused on melanoma, particularly histopathologic interpretation with deep learning. Such concentration on a single type of skin cancer amid increasing focus on deep learning highlight growing areas for innovation; however, it also demonstrates opportunity for additional analysis that addresses other types of cutaneous malignancies and expands the scope of prognostication to combine both genetic, histopathologic, and clinical data. Moreover, researchers may leverage multiple AI methods for enhanced benefit in analyses. Expanding AI to this arena may enable improved survival analysis, targeted treatments, and outcomes.