Background: Melanoma, the most lethal form of skin cancer, has undergone a transformative treatment shift with the advent of checkpoint blockade immunotherapy (CBI). Understanding the intricate network of immune cells infiltrating the tumor and orchestrating the control of melanoma cells and the response to CBI is currently of utmost importance. There is evidence underscoring the significance of tissue-resident memory (TRM) CD8 T cells and classic dendritic cell type 1 (cDC1) in cancer protection. Transcriptomic studies also support the existence of a TCF7+ (encoding TCF1) T cell as the most important for immunotherapy response, although uncertainty exists about whether there is a TCF1+TRM T cell due to evidence indicating TCF1 downregulation for tissue residency activation. Methods: We used multiplexed immunofluorescence and spectral flow cytometry to evaluate TRM CD8 T cells and cDC1 in two melanoma patient cohorts: one immunotherapy-naive and the other receiving immunotherapy. The first cohort was divided between patients free of disease or with metastasis 2 years postdiagnosis while the second between CBI responders and non-responders. Results: Our study identifies two CD8+TRM subsets, TCF1+ and TCF1−, correlating with melanoma protection. TCF1+TRM cells show heightened expression of IFN-γ and Ki67 while TCF1− TRM cells exhibit increased expression of cytotoxic molecules. In metastatic patients, TRM subsets undergo a shift in marker expression, with the TCF1− subset displaying increased expression of exhaustion markers. We observed a close spatial correlation between cDC1s and TRMs, with TCF1+TRM/cDC1 pairs enriched in the stroma and TCF1− TRM/cDC1 pairs in tumor areas. Notably, these TCF1− TRMs express cytotoxic molecules and are associated with apoptotic melanoma cells. Both TCF1+ and TCF1− TRM subsets, alongside cDC1, prove relevant to CBI response. Conclusions: Our study supports the importance of TRM CD8 T cells and cDC1 in melanoma protection while also highlighting the existence of functionally distinctive TCF1+ and TCF1− TRM subsets, both crucial for melanoma control and CBI response.

Melanoma is the deadliest form of skin cancer. Due to its high mutation rates, melanoma is a convenient model to study antitumor immune responses. Dendritic cells (DCs) play a key role in activating cytotoxic CD8⁺ T lymphocytes and directing them to kill tumor cells. Although there is evidence that DCs infiltrate melanomas, information about the profile of these cells, their activity states, and potential antitumor function remains unclear, particularly for conventional DCs type 1 (cDC1). Approaches to profiling tumor-infiltrating DCs are hindered by their diversity and the high number of signals that can affect their state of activation. Multiplexed immunofluorescence (mIF) allows the simultaneous analysis of multiple markers, but image-based analysis is time-consuming and often inconsistent among analysts. In this work, we evaluated several machine learning (ML) algorithms and established a workflow of nine-parameter image analysis that allowed us to study cDC1s in a reproducible and accessible manner. Using this workflow, we compared melanoma samples between disease-free and metastatic patients at diagnosis. We observed that cDC1s are more abundant in the tumor infiltrate of the former. Furthermore, cDC1s in disease-free patients exhibit an expression profile more congruent with an activator function: CD40^highPD-L1^low CD86⁺IL-12⁺. Although disease-free patients were also enriched with CD40⁻PD-L1⁺ cDC1s, these cells were also more compatible with an activator phenotype. The opposite was true for metastatic patients at diagnosis who were enriched for cDC1s with a more tolerogenic phenotype (CD40^lowPD-L1^highCD86⁻IL-12⁻IDO⁺). ML-based workflows like the one developed here can be used to analyze complex phenotypes of other immune cells and can be brought to laboratories with standard expertise and computer capacity.

Acral melanoma (AM) is the most common melanoma in non-Caucasian populations, yet it remains largely understudied. As AM lacks the UV-radiation mutational signatures that characterize other cutaneous melanomas, it is considered devoid of immunogenicity and is rarely included in clinical trials assessing novel immunotherapeutic regimes aiming to recover the antitumor function of immune cells. We studied a Mexican cohort of melanoma patients from the Mexican Institute of Social Security (IMSS) (n = 38) and found an overrepresentation of AM (73.9%). We developed a multiparametric immunofluorescence technique coupled with a machine learning image analysis to evaluate the presence of conventional type 1 dendritic cells (cDC1) and CD8 T cells in the stroma of melanoma, two of the most relevant immune cell types for antitumor responses. We observed that both cell types infiltrate AM at similar and even higher levels than other cutaneous melanomas. Both melanoma types harbored programmed cell death protein 1 (PD-1⁺) CD8 T cells and PD-1 ligand (PD-L1⁺) cDC1s. Despite this, CD8 T cells appeared to preserve their effector function and expanding capacity as they expressed interferon-γ (IFN-γ) and KI-67. The density of cDC1s and CD8 T cells significantly decreased in advanced stage III and IV melanomas, supporting these cells’ capacity to control tumor progression. These data also argue that AM could respond to anti-PD-1-PD-L1 immunotherapy.

Psoriasis is a chronic inflammatory autoimmune skin disease characterized by keratinocyte hyperproliferation, primarily driven by the IL-23/IL-17 axis. In addition to immune response, various skin components, including the epidermal barrier and the skin microbiota, have been individually implicated in the disease pathogenesis. Here, we aimed to investigate the interplay between epidermal tight junctions, Staphylococcus aureus enterotoxin B (SEB), and CD4 T cell-mediated immune responses. By immunofluorescence analyses of skin biopsies, we observed that claudin-1 distribution was significantly altered in psoriatic patients, which correlated with the localization of Staphylococcus aureus and SEB across skin layers and with disease severity. Furthermore, functional CD4 TCRvβ17 cells were associated with SEB presence in patients skin and positively correlated with psoriasis severity. Notably, in patients with SEB detected in the dermis, CD4 TCRvβ17 IL-17 cells were linked to barrier abnormalities.