Prediction and treatment of skin adverse reactions related to inhibitors at immune checkpoints

Prediction and treatment of skin adverse reactions related to inhibitors at immune checkpoints | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prediction and treatment of skin adverse reactions related to inhibitors at immune checkpoints Zhuo-Nan Meng, Jian-Yuan Chen, Chong Yu, Ai-Hong Zheng, Kai-Yan Liu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7640849/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Immunotherapy has become the fifth major treatment modality in oncology, with immune checkpoint inhibitors (ICIs) being the most effective immunotherapeutic agents currently used in clinical practice. Although the majority of patients exhibit good tolerance to ICIs, a subset of patients may develop severe immune-related adverse events (irAEs) following treatment. In this study, we included 47 cancer patients receiving PD-1 antibody therapy for the first time. By measuring cytokines in the patients' serum and performing single-cell RNA sequencing on immune cells from an in vitro co-culture system, our results indicated that elevated serum levels of IL-5 and IL-17, along with an increased proportion of PD-1 + CD4 + T cells, may be closely associated with the occurrence of skin irAEs. Transcriptomic analysis revealed that differentially expressed genes were enriched in the JAK-STAT signaling pathway, with a significant upregulation of inflammation-related proteins such as S100A8/A9. This study provides new insights into the early prediction and mechanistic understanding of skin irAEs, suggesting that monitoring serum cytokine levels and changes in immune cell subsets may help optimize ICI treatment strategies and reduce the occurrence of irAEs. Targeting key inflammatory pathways may offer novel therapeutic strategies for clinical management. immune-related adverse events (irAEs) PD-1 antibody single-cell RNA sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction The mechanism of action of immune checkpoint inhibitors (ICIs) primarily involves blocking the interaction between immune checkpoint ligands and receptors on the surface of T cells, thereby restoring T cell cytotoxic activity and enhancing the anti-tumor effects of T cells [ 1 ] . This approach has been shown to be effective against a variety of solid organ malignancies. Currently, the main ICIs used in clinical practice include monoclonal antibodies targeting Cytotoxic T Lymphocyte-associated Antigen-4 (CTLA-4), Programmed Cell Death Protein 1 (PD-1), Programmed Cell Death Ligand 1 (PD-L1), as well as bispecific antibodies [ 2 ] . However, the modulation of immune responses may lead to immune intolerance and immune-related adverse events (irAEs), which represent novel phenomena specific to these therapies [ 3 ] . IrAEs arise from the activation of immune cells attacking self-tissues and organ cellular molecules. Taking PD-1/PD-L1 monoclonal antibodies as an example, the PD-1/PD-L1 signaling pathway regulates the induction and maintenance of immune tolerance within the tumor microenvironment in cancer patients, playing a key role in tumor immune evasion [ 4 ] . The PD-1/PD-L1 or PD-1/PD-L2 signaling pathways modulate T cell activity, proliferation, and the secretion of cytotoxic factors in tumors, thereby suppressing T cell-mediated anti-tumor immune responses. Conversely, the PD-1/PD-L1 and PD-1/PD-L2 signaling pathways are essential for maintaining normal immune homeostasis. During T cell maturation, certain T cells may become reactive to self-antigens, and the body relies on the PD-1/PD-L1 or PD-1/PD-L2 signaling to inactivate these cells, preventing them from attacking normal tissues and organs, thus inducing immune tolerance to self-antigens [ 5 ] . Consequently, when PD-1 antibodies are used to block the PD-1/PD-L1 and PD-1/PD-L2 signaling pathways, they not only activate T cell-mediated anti-tumor immune responses but may also trigger immune responses against self-tissues and organs, leading to irAEs. IrAEs can affect multiple organs, including the skin, thyroid, adrenal glands, pituitary gland, intestines, liver, and lungs [ 6 ] . These adverse events typically occur several weeks to months after the initiation of ICI therapy, with skin reactions being the most common and often the earliest to appear [ 7 ] . Among all patients receiving ICI treatment, up to 30% to 50% experience skin irAEs [ 8 ] . Common skin irAEs include erythema, pruritus, rash, lichenoid reactions, and vitiligo [ 9 ] . In contrast, the mechanisms underlying skin irAEs remain unclear. Therefore, establishing a robust monitoring system is essential for tracking the safety and toxicity profiles of PD-1/PD-L1 inhibitors. Early identification of these events is key to managing and preventing skin irAEs, which can help minimize treatment interruptions and improve patients' quality of life. 2. Materials and method 2.1 In Vitro Cytotoxicity Assay of Immune Cells Peripheral venous blood (20 ml) was collected from the patient within 72 hours prior to the administration of PD-1 monoclonal antibody, using a heparinized anticoagulant tube. Simultaneously, skin biopsies were performed on the patient's forearm, anterior chest, and posterior back. A skin punch biopsy tool with a 3 mm diameter was used to obtain full-thickness skin samples. After collection, the subcutaneous tissue was carefully removed, and the remaining skin tissue was finely minced into small fragments using ophthalmic scissors. 2.2 Isolation of PBMCs from Peripheral Blood Lymphocyte separation medium (10 ml) was added to a 50 ml centrifuge tube and allowed to equilibrate to room temperature. To 20 ml of peripheral blood, 20 ml of PBS was added for dilution. The diluted blood was carefully layered on top of the lymphocyte separation medium and centrifuged at 400 g for 30 minutes at room temperature (with deceleration set to 4). After centrifugation, the sample separated into five layers, from top to bottom: dead cell layer, plasma layer, buffy coat layer (PBMCs), lymphocyte separation medium layer, and red blood cell layer. The buffy coat layer was carefully collected, and PBS was added to reach a final volume of 45 ml. The sample was then centrifuged at 300 g for 8 minutes at room temperature. The supernatant was discarded, and the cells were resuspended in 2 ml of red blood cell lysis buffer and incubated at room temperature for 2 minutes. Following this, 10 ml of PBS was added, and the sample was centrifuged at 300 g for 5 minutes at room temperature. After discarding the supernatant, the cells were resuspended in 15 ml of RPMI-1640 medium containing 10% fetal bovine serum. Cell viability was assessed using trypan blue staining and cell counting. 2.3 Establishment of In Vitro Co-culture System The processed skin microparticles and PBMCs were co-cultured in a 96-well plate. Specifically, 0.01 g of tissue microparticles were added to each well (0.1 g of skin tissue was first minced in 1 ml of culture medium, and then 0.1 ml of the resulting tissue microparticle suspension was added to each well), along with 2 × 10^6 PBMCs and interleukin-2 (IL-2) at a final concentration of 500 U/ml. Subsequently, anti-PD-1 monoclonal antibody was added to a final concentration of 10 µg/ml. The co-culture was incubated at 37°C for 72 hours. After incubation, the cell culture plate was centrifuged, and both the culture supernatant and immune cells were collected separately. 2.4 Enzyme-linked immunosorbent assay (ELISA) Ninety-six-well enzyme-labelled plates were coated with 100 µl of PD-L1 (1 µg/ml; 50010-M08H; Sino Biological) at 4◦C overnight, followed by washing with 0.01 M phosphate-buffered saline with 0.05% Tween-20 3 times. The plates were then blocked with blocking buffer (0.01 M phosphate-buffered saline with 5% FBS) at 37 C for 2 h. One hundred microlitres of serum was added to each well, followed by incubation at 37◦C for 1 h. After washing 3 times, each well was filled with 100 µl of HRP-labelled goat anti-rabbit IgG diluted 1:250 in blocking buffer and incubated at 37 ◦C for 1 h. After washing 5 times, 100 µl of TMB substrate solution (P0209, Beyotime) was added to each well, followed by incubation at 37 ◦C for 30 min. The reaction was stopped by adding 50 µl of stop solution to each well. The absorbance of the plates was measured at 450 nm. 2.5 scRNA-seq Extract mouse tumor tissue and digest with type IV collagenase (1 mg/ml) and DNase I (30 U/ml) at 37°C for 30 minutes. Filter the digested suspension using a 70 µm cell strainer, wash with PBS, lyse red blood cells using red blood cell lysis buffer, and resuspend in PBS. Tumor-infiltrating immune cells (CD45 + cells) are sorted using a FACSAria Fusion flow cytometer (BD Biosciences). The cell suspension (300–600 viable cells per milliliter) is loaded onto a Chromium Single Cell Controller (10x Genomics), and single-cell gel beads are generated in emulsion according to the manufacturer’s protocol. The Single Cell 5’ Library and Gel Bead Kit are used to prepare the library, followed by sequencing on an Illumina NovaSeq 6000 instrument using a paired-end 100 base pair (PE100) read strategy. The raw data is processed using CellRanger (version 5.0.0), with reads mapped to the mouse genome (mm10) to generate a digital gene expression matrix. The data is then loaded into the Seurat R package (version 4.0.4) for further processing. Lowly expressed genes (< 3) and lowly expressed cells (< 200) are removed. Cells with fewer than 200 or more than 5000 expressed genes are excluded as low-quality cells. The top 2500 variable genes, identified using the ‘vst’ method, are used for principal component analysis, with 1–30 principal components selected in the Find Neighbors function. Clusters are identified using the Find Clusters function (res = 0.7) and visualized in a two-dimensional t-SNE plot. Differentially expressed genes and marker genes are identified using the Find Markers function, considering only genes with an adjusted p-value < 0.25. To identify specific ligand-receptor pairs between antitumor macrophages and CD8 + Teff cells, ligand-receptor interactions are analyzed based on scRNA-seq data using CellPhoneDB software (version 2.1.7), considering receptors and ligands expressed in at least 10% of cells. 2.6 Statistics analysis Data analysis and graphical presentation were performed using SPSS 26.0 and GraphPad 8.3.1 statistical software. Comparisons of baseline characteristics between the two cohorts were conducted using the chi-square test or Fisher's exact probability test. Categorical data were analyzed using the chi-square test, while continuous measurements were analyzed using the t-test. A p-value of less than 0.05 was considered statistically significant. 3. Result 3.1 Clinical features and incidence of skin irAEs This study included 47 patients who were treated with PD-1 monoclonal antibody for the first time in the Department of Oncology, Zhejiang Provincial People's Hospital, between December 2023 and December 2024. Table 1 summarizes the basic clinical characteristics of the patients. The follow-up period began in December 2023 and is ongoing. A subset of patients developed varying degrees of skin irAEs after initiating PD-1 monoclonal antibody therapy. Specifically, 2 patients developed grade III rash, 4 patients developed grade II rash, and 6 patients developed grade I rash. Thus, 25.6% of the patients experienced skin irAEs, of which 12.8% had grade II or higher skin irAEs, and 12.8% had grade I skin irAEs (Fig. 1 A.B). With extended follow-up, the incidence of skin irAEs increased. Among them, patient 1021 discontinued immunotherapy due to extensive rash following treatment, while the remaining patients continued PD-1 inhibitor therapy after the rash was controlled. Figure 1 C presents images of patients who experienced more severe skin immune-related adverse events. Table 1 Comparison of Clinical Features of Immunotherapy Patients [n(%)] clinical characteristics Skin irAEs Appears (n = 12) Skin irAEs Didn’t Appear (n = 35) X 2 P Age (years) 0.17 0.68 ≤ 65 3(25.0) 11(31.4) > 60 9(75.0) 24(68.6) Sex 1.48 0.22 Male 12(100.0) 31(88.6) Female 0 4(11.4) ECOG Performance Status 0.35 0.55 0–1 9(75.0) 29(82.9) 2 3(25.0) 6(17.1) > 2 0 0 Tumor Type 10.94 < 0.05 Head and neck cancer 5(41.7) 1(2.9) Lung cancer 5(41.7) 18(51.4) Gastrointestinal cancer 1(8.3) 13(37.1) Hepatobiliary cancer 1(8.3) 1(2.9) Pancreatic cancer 0 1(2.9) Urologic cancer 0 1(2.9) Pelvic cancer 0 1(2.9) Immunotherapy Agent 18.12 < 0.05 Tislelizumab 5(41.7) 18(51.4) Sintilimab 2(16.7) 12(34.2) Pembrolizumab 3(25.0) 2(5.7) Toripalimab 0 1(2.9) Serplulimab 1(8.3) 2(5.7) Atezolizumab 0 1(2.9) 3.2 Cytokine Analysis in Venous Blood of Patients Our follow-up observations revealed that a subset of patients developed skin irAEs following treatment with PD-1 antibodies. To investigate the underlying mechanisms, we conducted cytokine assays on venous blood samples from all patients both prior to and following PD-1 monoclonal antibody therapy. Notably, patient 1021 (Fig. 2 A) and patient 1036 (Fig. 2 B) developed grade III skin irAEs after receiving PD-1 inhibitors. Cytokine profiling of peripheral blood indicated significant alterations in cytokine levels, with marked increases in IL-5 and IL-17 levels following treatment. Consequently, we extended our cytokine analysis to include all patients who developed skin irAEs (Grades I-III) and observed that most of these patients exhibited elevated levels of IL-5 and IL-17 after PD-1 inhibitor therapy (Figs. 3 C.D). In contrast, patients who did not experience skin irAEs showed minimal changes in IL-5 and IL-17 levels. These results suggest a potential correlation between elevated serum IL-5 and IL-17 levels and an increased risk of developing skin irAEs. 3.3 Changes in the Immune Microenvironment of the Co-culture System To further investigate the immune cell subsets, we performed in vitro cytotoxicity assays using patients who developed skin irAEs following PD-1 inhibitor treatment (patients 1045 and 1036) and compared them with patients who did not experience such skin adverse events (patients 1055 and 1037). The immune cells in the reaction systems from these patients were subjected to single-cell sequencing. A comparative analysis of the single-cell sequencing data between patient 1036 (who developed skin irAEs) and patient 1037 (who did not) revealed 10 distinct clusters, each representing a different immune cell population, including macrophages, dendritic cells (DC), NK cells, T cells, and B cells, identified through unsupervised clustering. Notably, patient 1036 exhibited a significant increase in PD-1 + CD4 + T cells compared to patient 1037 (Fig. 3 A), while the levels of monocytes and macrophages were reduced. In a similar comparative analysis of patient 1045 (who developed skin irAEs) and patient 1055 (who did not) using single-cell sequencing, 11 distinct immune cell populations were also identified through unsupervised clustering. The results indicated a significant increase in PD-1 + CD4 + T cells in patient 1045 compared to patient 1055 (Fig. 3 B). These findings suggest that a higher proportion of PD-1 + CD4 + T cells within the immune cell population may contribute to an increased susceptibility to the development of skin irAEs. 3.4 Changes in Cytokines in the Co-culture System Alterations in cytokine levels were observed in the serum of venous blood from the enrolled patients, with consistent increases in IL-5 and IL-17. To further explore these findings, cytokine analysis was performed on the in vitro immune response systems of patients 1045 and 1036, who developed skin irAEs after treatment with PD-1 inhibitors, and compared with patients 1055 and 1037, who did not experience such adverse reactions. The analysis revealed that, in comparison to the patients without skin irAEs, those who developed these events exhibited a significant increase in IL-5, IL-13, IL-17A, IL-17, and IL-22 levels in CD4 + T cells, as well as a marked elevation of IL-6 in monocytes (Fig. 3 C). This indicates a correlation between changes in cytokine levels in venous blood and those in the immune microenvironment of the in vitro reaction system. Thus, our findings further substantiate the association between elevated IL-5 and IL-17 levels and an increased risk of developing skin irAEs. Although cytokine detection in the cellular immune microenvironment presents certain challenges, the observed correlation with cytokine changes in venous blood suggests that alterations in serum cytokine levels may serve as a predictive marker for immune-related skin adverse events. To further analyze CD4⁺ T cells, we performed subpopulation analysis. The results revealed that patient 1036 (with cutaneous irAEs) exhibited significantly elevated proportions of memory CD4⁺ T cells, Th17 cells, and naïve CD4⁺ T cells compared to patient 1037 (without cutaneous irAEs), while no significant changes were observed in Th1 cells (Fig. 3 D.E). These findings suggest that enhanced Th17 polarization, combined with persistent activation of autoreactive T cells due to PD-1 blockade, may drive memory T cell expansion. 3.5 Multi-omics analysis of cells in co-culture system In the differential expression analysis of CD4 + T cells, it was found that pro-inflammatory genes were significantly up-regulated, and the expression of calcium-binding protein genes S100A8/S100A9 (Fig. 3 F), chemokine CCL2, and Th17-associated cytokines was significantly elevated (red scatters, p < 0.05). Concurrently, the elevated expression of the cell cycle regulatory gene STMN1 may promote CD4 + T-cell overactivation. The present findings provide a theoretical basis for targeted interventions (e.g. JAK-STAT inhibitors, S100A8/A9 antagonists) and suggest that CD4 + T-cell activation markers may serve as clinical predictors. KEGG pathway enrichment analysis revealed that the genes associated with skin irAEs were significantly enriched in immune-regulatory and inflammation-related pathways. Differentially expressed genes were significantly enriched in the JAK-STAT signaling pathway (hsa04630) and the T-cell receptor signaling pathway (hsa04660), containing 8 and 12 genes (Fig. 3 G), respectively. The findings suggest that T cell activation and cytokine-mediated immune responses play a central role in cutaneous irAEs. Furthermore, it is demonstrated that metabolism-related pathways (e.g. drug metabolism, glucolipid metabolism) accounted for a very low percentage of genes (≤ 2 genes), suggesting that cutaneous irAEs are mainly driven by immune dysregulation rather than metabolic abnormalities. 3.6 Skin irAEs prediction model Based on the clinical characteristics of enrolled patients, single-cell sequencing, and ELISA results, CD4 + T-cell proportion, IL-5, and IL-17 were identified as core predictors. Forty-seven patients were randomly allocated in a 7:3 ratio to a training set (n = 33) and a validation set (n = 14), with no statistically significant differences (p > 0.05) in baseline characteristics (e.g., age, tumor type) between the two groups. A multivariate predictive model was developed using logistic regression algorithm, with parameters optimized through 10-fold cross-validation. Final model formula: $$\:\varvec{l}\varvec{o}\varvec{g}\varvec{i}\varvec{t}\left(\varvec{p}\right)\:=\:0.12\times\:\left(\varvec{C}\varvec{D}4+\varvec{T}\right)\:+\:0.08\times\:\left(\varvec{I}\varvec{L}-5\:\right)+\:0.15\times\:\left(\varvec{I}\varvec{L}-17\right)\:-\:5.6$$ ROC curve analysis demonstrated that this combined model achieved an AUC of 0.869 (95% CI: 0.693–1.000) (Fig. 4 C) in the training set and 0.818 (95% CI: 0.657–1.000) (Fig. 4 D) in the validation set, significantly outperforming predictions based on individual biomarkers (IL-5 AUC = 0.792; IL-17 AUC = 0.581; CD4 + T-cell AUC = 0.750) (Fig. 4 B). The model exhibited a sensitivity of 86.7% and specificity of 87.5%, indicating its effectiveness in distinguishing high-risk populations. Notably, at a prediction probability threshold of 0.35, the model achieved an accuracy of 91.0% and a positive predictive value (PPV) of 85.7% in identifying grade III or higher severe cutaneous irAEs, highlighting its clinical value for early warning of critical events (Supplementary Table 1). The model’s applicability was further validated through exemplary case predictions, with results aligning with expectations (Fig. 4 E). These findings suggest that this multidimensional immune biomarker-based model provides a reliable tool for early clinical identification of high-risk patients susceptible to PD-1 inhibitor-related cutaneous adverse reactions, facilitating personalized treatment adjustment and preventive interventions. 4. Discussion This study found that 18.6% of patients developed skin irAEs after receiving PD-1 antibody therapy, with grade III adverse reactions occurring in 4.3% of cases. Notably, patients with head and neck tumors exhibited a significantly higher incidence of skin irAEs (41.7% vs. 2.9%, P < 0.05), which aligns with previous research indicating that patients with mucosa-associated lymphoid tissue tumors are more prone to developing skin toxicity. However, the incidence of skin irAEs in this study was slightly lower compared to previous reports (30%-40%) [ 10 ] , likely due to the smaller sample size and shorter follow-up duration. Nevertheless, skin irAEs remain one of the most common adverse reactions associated with PD-1 antibody therapy, particularly those of grade II or higher severity, which may necessitate treatment discontinuation and negatively impact the patient's anti-tumor efficacy [ 11 ] . Therefore, early identification of high-risk patients and the adoption of preventive measures are crucial. At the mechanistic level, we are the first to provide direct experimental evidence, using an in vitro co-culture model, demonstrating that PD-1 inhibitors can induce patients' own T cells to specifically attack skin tissues, offering valuable insights into the pathogenesis of skin irAEs. This study demonstrates a significant association between elevated serum levels of IL-5 and IL-17 and the occurrence of skin irAEs. Notably, serum IL-17 levels in patients with grade III skin irAEs were increased by up to 3.8-fold compared to baseline (P < 0.01), which is closely linked to the activation of the Th17 cell-mediated inflammatory pathway. IL-17 is known to induce keratinocytes to produce antimicrobial peptides and chemokines, recruit neutrophils, and promote epidermal hyperplasia [ 12 ] . As a key inflammatory cytokine secreted by Th17 cells, IL-17 plays a critical role in several inflammatory skin diseases, including psoriasis and eczema, and may contribute to the pathogenesis of skin manifestations such as papules and plaques [ 13 , 14 ] . In contrast, IL-5 is closely associated with the activation of eosinophils and the inflammatory response [ 15 , 16 ] . PD-1 monoclonal antibodies, by relieving the inhibition on T cells, may activate Th17 cells, leading to the release of inflammatory cytokines such as IL-17, thereby triggering skin inflammation [ 17 ] . This finding is consistent with previous studies and further substantiates the pivotal role of Th17 cells in the pathogenesis of skin irAEs [ 18 ] . Importantly, we also observed a concurrent increase in IL-22 (+ 2.7-fold) in our in vitro model. IL-22 has been shown to promote epidermal hyperkeratosis via the STAT3 signaling pathway, offering new insights into the pathological features of PD-1 inhibitor-associated psoriasis-like rashes [ 19 , 20 ] . Single-cell sequencing analysis revealed the pivotal role of PD-1 + CD4 + T cells in the pathogenesis of skin irAEs. In patients with grade III skin toxicity, the proportion of this subset was found to be 4.2-fold higher compared to the control group (P < 0.001), accompanied by a distinctive TCR clonal expansion signature. PD-1 + CD4 + T cells may represent an activated T cell subset that, under the influence of PD-1 antibody treatment, undergoes further activation, leading to self-tissue attack. Furthermore, the elevated proportion of PD-1 + CD4 + T cells may reflect an underlying abnormal immune baseline in these patients, suggesting that they are more susceptible to breaking peripheral tolerance thresholds after PD-1 antibody therapy, thereby triggering skin irAEs. These findings provide novel biomarkers for predicting skin irAEs. These cells also exhibited significantly increased expression of CTLA-4 (+ 3.1-fold) and ICOS (+ 2.8-fold), indicating a potential mixed phenotype of regulatory and effector T cells. This observation aligns with the emerging concept of "pathogenic Tregs," which postulates that these cells may acquire pro-inflammatory properties while still contributing to immune tolerance [ 21 ] . Notably, we observed a marked upregulation of EZH2 expression (+ 2.3-fold) in PD-1 + CD4 + T cells. This epigenetic regulator may promote Th17 differentiation by destabilizing Foxp3, providing a theoretical foundation for the development of epigenetic-targeted therapeutic strategies. Although this study highlights the crucial roles of IL-5, IL-17, and PD-1 + CD4 + T cells in skin irAEs, several limitations should be acknowledged. First, the study's limitations include a relatively small sample size (n = 47) and a limited follow-up duration (median follow-up of 8 months), which may affect the external validity of the findings. Second, the study primarily focused on patients treated with PD-1 monoclonal antibodies and did not incorporate patients receiving other ICIs, such as CTLA-4 monoclonal antibodies. Future studies should aim to increase the sample size and include patients undergoing treatment with a broader range of ICIs to assess the generalizability of these results. In terms of clinical translation, the findings from this study offer novel insights into the prediction and prevention of skin irAEs. Serum levels of IL-5 and IL-17, along with PD-1 + CD4 + T cells, may serve as potential biomarkers for the early identification of high-risk patients. For such high-risk individuals, preventive strategies, such as the use of topical anti-inflammatory agents or therapies targeting the IL-17/IL-23 axis, could be considered prior to PD-1 monoclonal antibody therapy to reduce the incidence of skin irAEs. Preclinical studies have demonstrated that anti-IL-17A monoclonal antibodies can significantly reduce CD4 + T cell infiltration into skin tissues in vitro, while the JAK inhibitor tofacitinib effectively inhibits IL-6-mediated STAT3 phosphorylation (with an inhibition rate of 78%) [ 22 ] . Moreover, for PD-1 + CD4 + T cells, the selective EZH2 inhibitor GSK126 has been shown to restore Foxp3 expression to baseline levels (P < 0.01), suggesting that targeting PD-1 + CD4 + T cells may offer a promising new therapeutic avenue for the management of skin-related irAEs. 5. Conclusion In conclusion, this study, integrating clinical data and in vitro experiments, reveals the underlying mechanisms of skin irAEs following PD-1 antibody therapy. It identifies elevated serum levels of IL-5 and IL-17, along with an increased proportion of PD-1 + CD4 + T cells, as potential biomarkers for the prediction of skin irAEs. The results suggest that PD-1 monoclonal antibodies induce the activation of Th17 cells, leading to the release of inflammatory cytokines such as IL-17, which subsequently triggers the onset of skin-related irAEs. Multi-omics analysis indicates that immune dysregulation is the predominant molecular feature of skin irAEs. Targeting key inflammatory pathways, such as the JAK-STAT signaling pathway and S100A8/A9, may offer novel therapeutic strategies for clinical management. Additionally, future studies should further validate the predictive utility of these biomarkers and explore targeted therapies aimed at the IL-17/IL-23 axis and PD-1 + CD4 + T cells, with the goal of mitigating the occurrence of skin irAEs and improving patient outcomes. Declarations Acknowledgements Not applicable. Author contributions Guo-Qing Wu, Da-Hong Zhang conceived and designed the study. Zhuo-Nan Meng, Jian-Yuan Chen, Chong Yu, Yong-Rui Su, Shi-Tai Zhang conducted most of the experiments and data analysis and wrote the manuscript. Kai-Yan Liu, Fu-Wei Wang, Ai-Hong Zheng participated in collecting data and helped to draft the manuscript. All authors reviewed and approved the manuscript. Data availability All data generated or analysed during this study are included in this published article. Funding This work was supported by the Science and Technology Program with Traditional Chinese Medicine of Zhejiang Province [2024ZL286]. Availability of data and materials No datasets were generated or analysed during the current study Ethics approval The procedures for sampling and using human skin tissue were approved by the Ethics Committee of Zhejiang Provincial People's Hospital. 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LOBÃO B, LOURENÇO D, GIGA A, et al. From PsO to PsA: the role of T(RM) and Tregs in psoriatic disease, a systematic review of the literature [J]. Front Med (Lausanne), 2024, 11: 1346757. TRAVES P G, MURRAY B, CAMPIGOTTO F, et al. JAK selectivity and the implications for clinical inhibition of pharmacodynamic cytokine signalling by filgotinib, upadacitinib, tofacitinib and baricitinib [J]. Ann Rheum Dis, 2021, 80(7): 865–75. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":1738743,"visible":true,"origin":"","legend":"\u003cp\u003e(A.B) Occurrence of skin irAEs in patients after immunotherapy. (C) Photos of patients with more severe skin immune-related adverse reactions.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7640849/v1/422e5bbfca67695143fd7666.png"},{"id":93842501,"identity":"d2783486-8f97-4f7f-8f45-5ec72bbecab2","added_by":"auto","created_at":"2025-10-18 14:18:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":117981,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePeripheral blood cytokine levels. \u003c/strong\u003ePeripheral blood cytokine testing was performed in patients 1021 (A) and 1036 (B) after treatment with PD-1 inhibitors, and significant increases in IL-5 and IL-17 levels were found. Cytokine analysis was performed on all patients with skin irAEs (grade I-III) among the enrolled patients. Most patients with skin irAEs had elevated IL-5 (C) and IL-17 (D) after using PD-1 inhibitors.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7640849/v1/a422a4fa5b96c9107c598596.png"},{"id":93843500,"identity":"eaf6ad2f-4fe3-4537-8b7d-864a8c48719a","added_by":"auto","created_at":"2025-10-18 14:26:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1182320,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImmune microenvironment of co-culture system. \u003c/strong\u003e(A.B) UMAP visualization of CD45\u003csup\u003e+\u003c/sup\u003e immune cells and quantification of cell type proportions from PBMC-skin tissue cocultures. Patients developing cutaneous irAEs (1036.1045) exhibit expanded CD4\u003csup\u003e+\u003c/sup\u003e T-cell clusters compared to irAE-free patients (1037.1055). (C) Heatmap of immune-related gene expression across major leukocyte subsets. Color scale indicates normalized expression levels (blue: low; red: high). (D) UMAP projection of single-cell data from patients 1036 (irAEs, orange) and 1037 (control, blue) (E) Comparative analysis of T cell subset proportions between the two cohorts. (F). Volcano plot of differential gene expression in CD4\u003csup\u003e+\u003c/sup\u003e T cells between patient 1045 (with irAEs) and 1055 (irAE-free). Red dots: upregulated genes (log₂FC \u0026gt;1, FDR \u0026lt;0.05); gray dots: nonsignificant genes. (G) KEGG pathway enrichment analysis of differentially expressed genes.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7640849/v1/aa47f6b88e3f5cb6251c0727.png"},{"id":93843501,"identity":"d28085e4-5063-4989-af6e-55cd1cf58f4f","added_by":"auto","created_at":"2025-10-18 14:26:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":431279,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDevelopment and validation of a multivariate predictive model for cutaneous irAEs risk stratification\u003c/strong\u003e\u003cbr\u003e\n. (A) ROC curves of baseline clinical features for irAEs prediction. AUC values: age (0.512, 95% CI 0.382–0.642), sex (0.496, 95% CI 0.366–0.626), head and neck tumors (0.552, 95% CI 0.423–0.681). (B) Comparative ROC analysis of individual biomarkers: IL-5 (AUC = 0.792), IL-17 (AUC = 0.581), and CD4\u003csup\u003e+\u003c/sup\u003e T cell proportion (AUC = 0.750). (C) ROC curve of the multivariate model in the training cohort (n=33, AUC = 0.869, 95% CI 0.693–1.000). (D) Validation of the model in an independent cohort (n=14, AUC = 0.848, 95% CI 0.657–1.000). (E) Representative case predictions showing calculated probabilities and actual outcomes for two patients using the multivariate model. FPR, false positive rate; TPR, true positive rate.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7640849/v1/857b8954011f8cb6ace48cb0.png"},{"id":109035144,"identity":"f24edc81-b92d-4f57-a650-76784e274c88","added_by":"auto","created_at":"2026-05-12 02:11:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4662916,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7640849/v1/eceab028-ab83-4fec-9166-cde0592050c8.pdf"},{"id":93843706,"identity":"312427f5-afed-4799-b774-5a9b384d0b26","added_by":"auto","created_at":"2025-10-18 14:34:21","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19222,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7640849/v1/70d4fe20bfa18d56106c811a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction and treatment of skin adverse reactions related to inhibitors at immune checkpoints","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe mechanism of action of immune checkpoint inhibitors (ICIs) primarily involves blocking the interaction between immune checkpoint ligands and receptors on the surface of T cells, thereby restoring T cell cytotoxic activity and enhancing the anti-tumor effects of T cells\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. This approach has been shown to be effective against a variety of solid organ malignancies. Currently, the main ICIs used in clinical practice include monoclonal antibodies targeting Cytotoxic T Lymphocyte-associated Antigen-4 (CTLA-4), Programmed Cell Death Protein 1 (PD-1), Programmed Cell Death Ligand 1 (PD-L1), as well as bispecific antibodies\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. However, the modulation of immune responses may lead to immune intolerance and immune-related adverse events (irAEs), which represent novel phenomena specific to these therapies\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. IrAEs arise from the activation of immune cells attacking self-tissues and organ cellular molecules. Taking PD-1/PD-L1 monoclonal antibodies as an example, the PD-1/PD-L1 signaling pathway regulates the induction and maintenance of immune tolerance within the tumor microenvironment in cancer patients, playing a key role in tumor immune evasion\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The PD-1/PD-L1 or PD-1/PD-L2 signaling pathways modulate T cell activity, proliferation, and the secretion of cytotoxic factors in tumors, thereby suppressing T cell-mediated anti-tumor immune responses. Conversely, the PD-1/PD-L1 and PD-1/PD-L2 signaling pathways are essential for maintaining normal immune homeostasis. During T cell maturation, certain T cells may become reactive to self-antigens, and the body relies on the PD-1/PD-L1 or PD-1/PD-L2 signaling to inactivate these cells, preventing them from attacking normal tissues and organs, thus inducing immune tolerance to self-antigens\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Consequently, when PD-1 antibodies are used to block the PD-1/PD-L1 and PD-1/PD-L2 signaling pathways, they not only activate T cell-mediated anti-tumor immune responses but may also trigger immune responses against self-tissues and organs, leading to irAEs.\u003c/p\u003e\u003cp\u003eIrAEs can affect multiple organs, including the skin, thyroid, adrenal glands, pituitary gland, intestines, liver, and lungs\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. These adverse events typically occur several weeks to months after the initiation of ICI therapy, with skin reactions being the most common and often the earliest to appear\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Among all patients receiving ICI treatment, up to 30% to 50% experience skin irAEs\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Common skin irAEs include erythema, pruritus, rash, lichenoid reactions, and vitiligo\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. In contrast, the mechanisms underlying skin irAEs remain unclear. Therefore, establishing a robust monitoring system is essential for tracking the safety and toxicity profiles of PD-1/PD-L1 inhibitors. Early identification of these events is key to managing and preventing skin irAEs, which can help minimize treatment interruptions and improve patients' quality of life.\u003c/p\u003e"},{"header":"2. Materials and method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 In Vitro Cytotoxicity Assay of Immune Cells\u003c/h2\u003e\u003cp\u003ePeripheral venous blood (20 ml) was collected from the patient within 72 hours prior to the administration of PD-1 monoclonal antibody, using a heparinized anticoagulant tube. Simultaneously, skin biopsies were performed on the patient's forearm, anterior chest, and posterior back. A skin punch biopsy tool with a 3 mm diameter was used to obtain full-thickness skin samples. After collection, the subcutaneous tissue was carefully removed, and the remaining skin tissue was finely minced into small fragments using ophthalmic scissors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Isolation of PBMCs from Peripheral Blood\u003c/h2\u003e\u003cp\u003eLymphocyte separation medium (10 ml) was added to a 50 ml centrifuge tube and allowed to equilibrate to room temperature. To 20 ml of peripheral blood, 20 ml of PBS was added for dilution. The diluted blood was carefully layered on top of the lymphocyte separation medium and centrifuged at 400 g for 30 minutes at room temperature (with deceleration set to 4). After centrifugation, the sample separated into five layers, from top to bottom: dead cell layer, plasma layer, buffy coat layer (PBMCs), lymphocyte separation medium layer, and red blood cell layer. The buffy coat layer was carefully collected, and PBS was added to reach a final volume of 45 ml. The sample was then centrifuged at 300 g for 8 minutes at room temperature. The supernatant was discarded, and the cells were resuspended in 2 ml of red blood cell lysis buffer and incubated at room temperature for 2 minutes. Following this, 10 ml of PBS was added, and the sample was centrifuged at 300 g for 5 minutes at room temperature. After discarding the supernatant, the cells were resuspended in 15 ml of RPMI-1640 medium containing 10% fetal bovine serum. Cell viability was assessed using trypan blue staining and cell counting.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Establishment of In Vitro Co-culture System\u003c/h2\u003e\u003cp\u003eThe processed skin microparticles and PBMCs were co-cultured in a 96-well plate. Specifically, 0.01 g of tissue microparticles were added to each well (0.1 g of skin tissue was first minced in 1 ml of culture medium, and then 0.1 ml of the resulting tissue microparticle suspension was added to each well), along with 2 \u0026times; 10^6 PBMCs and interleukin-2 (IL-2) at a final concentration of 500 U/ml. Subsequently, anti-PD-1 monoclonal antibody was added to a final concentration of 10 \u0026micro;g/ml. The co-culture was incubated at 37\u0026deg;C for 72 hours. After incubation, the cell culture plate was centrifuged, and both the culture supernatant and immune cells were collected separately.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Enzyme-linked immunosorbent assay (ELISA)\u003c/h2\u003e\u003cp\u003eNinety-six-well enzyme-labelled plates were coated with 100 \u0026micro;l of PD-L1 (1 \u0026micro;g/ml; 50010-M08H; Sino Biological) at 4◦C overnight, followed by washing with 0.01 M phosphate-buffered saline with 0.05% Tween-20 3 times. The plates were then blocked with blocking buffer (0.01 M phosphate-buffered saline with 5% FBS) at 37 C for 2 h. One hundred microlitres of serum was added to each well, followed by incubation at 37◦C for 1 h. After washing 3 times, each well was filled with 100 \u0026micro;l of HRP-labelled goat anti-rabbit IgG diluted 1:250 in blocking buffer and incubated at 37 ◦C for 1 h. After washing 5 times, 100 \u0026micro;l of TMB substrate solution (P0209, Beyotime) was added to each well, followed by incubation at 37 ◦C for 30 min. The reaction was stopped by adding 50 \u0026micro;l of stop solution to each well. The absorbance of the plates was measured at 450 nm.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 scRNA-seq\u003c/h2\u003e\u003cp\u003eExtract mouse tumor tissue and digest with type IV collagenase (1 mg/ml) and DNase I (30 U/ml) at 37\u0026deg;C for 30 minutes. Filter the digested suspension using a 70 \u0026micro;m cell strainer, wash with PBS, lyse red blood cells using red blood cell lysis buffer, and resuspend in PBS. Tumor-infiltrating immune cells (CD45\u003csup\u003e+\u003c/sup\u003e cells) are sorted using a FACSAria Fusion flow cytometer (BD Biosciences). The cell suspension (300\u0026ndash;600 viable cells per milliliter) is loaded onto a Chromium Single Cell Controller (10x Genomics), and single-cell gel beads are generated in emulsion according to the manufacturer\u0026rsquo;s protocol. The Single Cell 5\u0026rsquo; Library and Gel Bead Kit are used to prepare the library, followed by sequencing on an Illumina NovaSeq 6000 instrument using a paired-end 100 base pair (PE100) read strategy. The raw data is processed using CellRanger (version 5.0.0), with reads mapped to the mouse genome (mm10) to generate a digital gene expression matrix. The data is then loaded into the Seurat R package (version 4.0.4) for further processing. Lowly expressed genes (\u0026lt;\u0026thinsp;3) and lowly expressed cells (\u0026lt;\u0026thinsp;200) are removed. Cells with fewer than 200 or more than 5000 expressed genes are excluded as low-quality cells. The top 2500 variable genes, identified using the \u0026lsquo;vst\u0026rsquo; method, are used for principal component analysis, with 1\u0026ndash;30 principal components selected in the Find Neighbors function. Clusters are identified using the Find Clusters function (res\u0026thinsp;=\u0026thinsp;0.7) and visualized in a two-dimensional t-SNE plot. Differentially expressed genes and marker genes are identified using the Find Markers function, considering only genes with an adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25. To identify specific ligand-receptor pairs between antitumor macrophages and CD8\u003csup\u003e+\u003c/sup\u003e Teff cells, ligand-receptor interactions are analyzed based on scRNA-seq data using CellPhoneDB software (version 2.1.7), considering receptors and ligands expressed in at least 10% of cells.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Statistics analysis\u003c/h2\u003e\u003cp\u003eData analysis and graphical presentation were performed using SPSS 26.0 and GraphPad 8.3.1 statistical software. Comparisons of baseline characteristics between the two cohorts were conducted using the chi-square test or Fisher's exact probability test. Categorical data were analyzed using the chi-square test, while continuous measurements were analyzed using the t-test. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Clinical features and incidence of skin irAEs\u003c/h2\u003e\u003cp\u003eThis study included 47 patients who were treated with PD-1 monoclonal antibody for the first time in the Department of Oncology, Zhejiang Provincial People's Hospital, between December 2023 and December 2024. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the basic clinical characteristics of the patients. The follow-up period began in December 2023 and is ongoing. A subset of patients developed varying degrees of skin irAEs after initiating PD-1 monoclonal antibody therapy. Specifically, 2 patients developed grade III rash, 4 patients developed grade II rash, and 6 patients developed grade I rash. Thus, 25.6% of the patients experienced skin irAEs, of which 12.8% had grade II or higher skin irAEs, and 12.8% had grade I skin irAEs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA.B). With extended follow-up, the incidence of skin irAEs increased. Among them, patient 1021 discontinued immunotherapy due to extensive rash following treatment, while the remaining patients continued PD-1 inhibitor therapy after the rash was controlled. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC presents images of patients who experienced more severe skin immune-related adverse events.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Clinical Features of Immunotherapy Patients [n(%)]\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eclinical characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSkin irAEs Appears (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSkin irAEs Didn\u0026rsquo;t Appear (n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3(25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11(31.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9(75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24(68.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12(100.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31(88.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(11.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eECOG Performance Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u0026ndash;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9(75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29(82.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3(25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6(17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTumor Type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHead and neck cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5(41.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLung cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5(41.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18(51.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGastrointestinal cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13(37.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepatobiliary cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePancreatic cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrologic cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePelvic cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eImmunotherapy Agent\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTislelizumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5(41.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18(51.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSintilimab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2(16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12(34.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePembrolizumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3(25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eToripalimab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerplulimab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAtezolizumab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Cytokine Analysis in Venous Blood of Patients\u003c/h2\u003e\u003cp\u003eOur follow-up observations revealed that a subset of patients developed skin irAEs following treatment with PD-1 antibodies. To investigate the underlying mechanisms, we conducted cytokine assays on venous blood samples from all patients both prior to and following PD-1 monoclonal antibody therapy. Notably, patient 1021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and patient 1036 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) developed grade III skin irAEs after receiving PD-1 inhibitors. Cytokine profiling of peripheral blood indicated significant alterations in cytokine levels, with marked increases in IL-5 and IL-17 levels following treatment. Consequently, we extended our cytokine analysis to include all patients who developed skin irAEs (Grades I-III) and observed that most of these patients exhibited elevated levels of IL-5 and IL-17 after PD-1 inhibitor therapy (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC.D). In contrast, patients who did not experience skin irAEs showed minimal changes in IL-5 and IL-17 levels. These results suggest a potential correlation between elevated serum IL-5 and IL-17 levels and an increased risk of developing skin irAEs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Changes in the Immune Microenvironment of the Co-culture System\u003c/h2\u003e\u003cp\u003eTo further investigate the immune cell subsets, we performed in vitro cytotoxicity assays using patients who developed skin irAEs following PD-1 inhibitor treatment (patients 1045 and 1036) and compared them with patients who did not experience such skin adverse events (patients 1055 and 1037). The immune cells in the reaction systems from these patients were subjected to single-cell sequencing. A comparative analysis of the single-cell sequencing data between patient 1036 (who developed skin irAEs) and patient 1037 (who did not) revealed 10 distinct clusters, each representing a different immune cell population, including macrophages, dendritic cells (DC), NK cells, T cells, and B cells, identified through unsupervised clustering. Notably, patient 1036 exhibited a significant increase in PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells compared to patient 1037 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), while the levels of monocytes and macrophages were reduced.\u003c/p\u003e\u003cp\u003eIn a similar comparative analysis of patient 1045 (who developed skin irAEs) and patient 1055 (who did not) using single-cell sequencing, 11 distinct immune cell populations were also identified through unsupervised clustering. The results indicated a significant increase in PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells in patient 1045 compared to patient 1055 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). These findings suggest that a higher proportion of PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells within the immune cell population may contribute to an increased susceptibility to the development of skin irAEs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Changes in Cytokines in the Co-culture System\u003c/h2\u003e\u003cp\u003eAlterations in cytokine levels were observed in the serum of venous blood from the enrolled patients, with consistent increases in IL-5 and IL-17. To further explore these findings, cytokine analysis was performed on the in vitro immune response systems of patients 1045 and 1036, who developed skin irAEs after treatment with PD-1 inhibitors, and compared with patients 1055 and 1037, who did not experience such adverse reactions. The analysis revealed that, in comparison to the patients without skin irAEs, those who developed these events exhibited a significant increase in IL-5, IL-13, IL-17A, IL-17, and IL-22 levels in CD4\u003csup\u003e+\u003c/sup\u003e T cells, as well as a marked elevation of IL-6 in monocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). This indicates a correlation between changes in cytokine levels in venous blood and those in the immune microenvironment of the in vitro reaction system. Thus, our findings further substantiate the association between elevated IL-5 and IL-17 levels and an increased risk of developing skin irAEs. Although cytokine detection in the cellular immune microenvironment presents certain challenges, the observed correlation with cytokine changes in venous blood suggests that alterations in serum cytokine levels may serve as a predictive marker for immune-related skin adverse events.\u003c/p\u003e\u003cp\u003eTo further analyze CD4⁺ T cells, we performed subpopulation analysis. The results revealed that patient 1036 (with cutaneous irAEs) exhibited significantly elevated proportions of memory CD4⁺ T cells, Th17 cells, and na\u0026iuml;ve CD4⁺ T cells compared to patient 1037 (without cutaneous irAEs), while no significant changes were observed in Th1 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD.E). These findings suggest that enhanced Th17 polarization, combined with persistent activation of autoreactive T cells due to PD-1 blockade, may drive memory T cell expansion.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Multi-omics analysis of cells in co-culture system\u003c/h2\u003e\u003cp\u003eIn the differential expression analysis of CD4\u003csup\u003e+\u003c/sup\u003e T cells, it was found that pro-inflammatory genes were significantly up-regulated, and the expression of calcium-binding protein genes S100A8/S100A9 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF), chemokine CCL2, and Th17-associated cytokines was significantly elevated (red scatters, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Concurrently, the elevated expression of the cell cycle regulatory gene STMN1 may promote CD4\u003csup\u003e+\u003c/sup\u003e T-cell overactivation. The present findings provide a theoretical basis for targeted interventions (e.g. JAK-STAT inhibitors, S100A8/A9 antagonists) and suggest that CD4\u003csup\u003e+\u003c/sup\u003e T-cell activation markers may serve as clinical predictors.\u003c/p\u003e\u003cp\u003eKEGG pathway enrichment analysis revealed that the genes associated with skin irAEs were significantly enriched in immune-regulatory and inflammation-related pathways. Differentially expressed genes were significantly enriched in the JAK-STAT signaling pathway (hsa04630) and the T-cell receptor signaling pathway (hsa04660), containing 8 and 12 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG), respectively. The findings suggest that T cell activation and cytokine-mediated immune responses play a central role in cutaneous irAEs. Furthermore, it is demonstrated that metabolism-related pathways (e.g. drug metabolism, glucolipid metabolism) accounted for a very low percentage of genes (\u0026le;\u0026thinsp;2 genes), suggesting that cutaneous irAEs are mainly driven by immune dysregulation rather than metabolic abnormalities.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Skin irAEs prediction model\u003c/h2\u003e\u003cp\u003eBased on the clinical characteristics of enrolled patients, single-cell sequencing, and ELISA results, CD4\u003csup\u003e+\u003c/sup\u003e T-cell proportion, IL-5, and IL-17 were identified as core predictors. Forty-seven patients were randomly allocated in a 7:3 ratio to a training set (n\u0026thinsp;=\u0026thinsp;33) and a validation set (n\u0026thinsp;=\u0026thinsp;14), with no statistically significant differences (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in baseline characteristics (e.g., age, tumor type) between the two groups. A multivariate predictive model was developed using logistic regression algorithm, with parameters optimized through 10-fold cross-validation.\u003c/p\u003e\u003cp\u003eFinal model formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{l}\\varvec{o}\\varvec{g}\\varvec{i}\\varvec{t}\\left(\\varvec{p}\\right)\\:=\\:0.12\\times\\:\\left(\\varvec{C}\\varvec{D}4+\\varvec{T}\\right)\\:+\\:0.08\\times\\:\\left(\\varvec{I}\\varvec{L}-5\\:\\right)+\\:0.15\\times\\:\\left(\\varvec{I}\\varvec{L}-17\\right)\\:-\\:5.6$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eROC curve analysis demonstrated that this combined model achieved an AUC of 0.869 (95% CI: 0.693\u0026ndash;1.000) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) in the training set and 0.818 (95% CI: 0.657\u0026ndash;1.000) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) in the validation set, significantly outperforming predictions based on individual biomarkers (IL-5 AUC\u0026thinsp;=\u0026thinsp;0.792; IL-17 AUC\u0026thinsp;=\u0026thinsp;0.581; CD4\u003csup\u003e+\u003c/sup\u003e T-cell AUC\u0026thinsp;=\u0026thinsp;0.750) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). The model exhibited a sensitivity of 86.7% and specificity of 87.5%, indicating its effectiveness in distinguishing high-risk populations. Notably, at a prediction probability threshold of 0.35, the model achieved an accuracy of 91.0% and a positive predictive value (PPV) of 85.7% in identifying grade III or higher severe cutaneous irAEs, highlighting its clinical value for early warning of critical events (Supplementary Table\u0026nbsp;1). The model\u0026rsquo;s applicability was further validated through exemplary case predictions, with results aligning with expectations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). These findings suggest that this multidimensional immune biomarker-based model provides a reliable tool for early clinical identification of high-risk patients susceptible to PD-1 inhibitor-related cutaneous adverse reactions, facilitating personalized treatment adjustment and preventive interventions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study found that 18.6% of patients developed skin irAEs after receiving PD-1 antibody therapy, with grade III adverse reactions occurring in 4.3% of cases. Notably, patients with head and neck tumors exhibited a significantly higher incidence of skin irAEs (41.7% vs. 2.9%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which aligns with previous research indicating that patients with mucosa-associated lymphoid tissue tumors are more prone to developing skin toxicity. However, the incidence of skin irAEs in this study was slightly lower compared to previous reports (30%-40%)\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, likely due to the smaller sample size and shorter follow-up duration. Nevertheless, skin irAEs remain one of the most common adverse reactions associated with PD-1 antibody therapy, particularly those of grade II or higher severity, which may necessitate treatment discontinuation and negatively impact the patient's anti-tumor efficacy\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Therefore, early identification of high-risk patients and the adoption of preventive measures are crucial. At the mechanistic level, we are the first to provide direct experimental evidence, using an in vitro co-culture model, demonstrating that PD-1 inhibitors can induce patients' own T cells to specifically attack skin tissues, offering valuable insights into the pathogenesis of skin irAEs.\u003c/p\u003e\u003cp\u003eThis study demonstrates a significant association between elevated serum levels of IL-5 and IL-17 and the occurrence of skin irAEs. Notably, serum IL-17 levels in patients with grade III skin irAEs were increased by up to 3.8-fold compared to baseline (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), which is closely linked to the activation of the Th17 cell-mediated inflammatory pathway. IL-17 is known to induce keratinocytes to produce antimicrobial peptides and chemokines, recruit neutrophils, and promote epidermal hyperplasia\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. As a key inflammatory cytokine secreted by Th17 cells, IL-17 plays a critical role in several inflammatory skin diseases, including psoriasis and eczema, and may contribute to the pathogenesis of skin manifestations such as papules and plaques\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. In contrast, IL-5 is closely associated with the activation of eosinophils and the inflammatory response\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. PD-1 monoclonal antibodies, by relieving the inhibition on T cells, may activate Th17 cells, leading to the release of inflammatory cytokines such as IL-17, thereby triggering skin inflammation\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. This finding is consistent with previous studies and further substantiates the pivotal role of Th17 cells in the pathogenesis of skin irAEs\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Importantly, we also observed a concurrent increase in IL-22 (+\u0026thinsp;2.7-fold) in our in vitro model. IL-22 has been shown to promote epidermal hyperkeratosis via the STAT3 signaling pathway, offering new insights into the pathological features of PD-1 inhibitor-associated psoriasis-like rashes\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSingle-cell sequencing analysis revealed the pivotal role of PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells in the pathogenesis of skin irAEs. In patients with grade III skin toxicity, the proportion of this subset was found to be 4.2-fold higher compared to the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), accompanied by a distinctive TCR clonal expansion signature. PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells may represent an activated T cell subset that, under the influence of PD-1 antibody treatment, undergoes further activation, leading to self-tissue attack. Furthermore, the elevated proportion of PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells may reflect an underlying abnormal immune baseline in these patients, suggesting that they are more susceptible to breaking peripheral tolerance thresholds after PD-1 antibody therapy, thereby triggering skin irAEs. These findings provide novel biomarkers for predicting skin irAEs. These cells also exhibited significantly increased expression of CTLA-4 (+\u0026thinsp;3.1-fold) and ICOS (+\u0026thinsp;2.8-fold), indicating a potential mixed phenotype of regulatory and effector T cells. This observation aligns with the emerging concept of \"pathogenic Tregs,\" which postulates that these cells may acquire pro-inflammatory properties while still contributing to immune tolerance\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Notably, we observed a marked upregulation of EZH2 expression (+\u0026thinsp;2.3-fold) in PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells. This epigenetic regulator may promote Th17 differentiation by destabilizing Foxp3, providing a theoretical foundation for the development of epigenetic-targeted therapeutic strategies.\u003c/p\u003e\u003cp\u003eAlthough this study highlights the crucial roles of IL-5, IL-17, and PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells in skin irAEs, several limitations should be acknowledged. First, the study's limitations include a relatively small sample size (n\u0026thinsp;=\u0026thinsp;47) and a limited follow-up duration (median follow-up of 8 months), which may affect the external validity of the findings. Second, the study primarily focused on patients treated with PD-1 monoclonal antibodies and did not incorporate patients receiving other ICIs, such as CTLA-4 monoclonal antibodies. Future studies should aim to increase the sample size and include patients undergoing treatment with a broader range of ICIs to assess the generalizability of these results.\u003c/p\u003e\u003cp\u003eIn terms of clinical translation, the findings from this study offer novel insights into the prediction and prevention of skin irAEs. Serum levels of IL-5 and IL-17, along with PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells, may serve as potential biomarkers for the early identification of high-risk patients. For such high-risk individuals, preventive strategies, such as the use of topical anti-inflammatory agents or therapies targeting the IL-17/IL-23 axis, could be considered prior to PD-1 monoclonal antibody therapy to reduce the incidence of skin irAEs. Preclinical studies have demonstrated that anti-IL-17A monoclonal antibodies can significantly reduce CD4\u003csup\u003e+\u003c/sup\u003e T cell infiltration into skin tissues in vitro, while the JAK inhibitor tofacitinib effectively inhibits IL-6-mediated STAT3 phosphorylation (with an inhibition rate of 78%)\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Moreover, for PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells, the selective EZH2 inhibitor GSK126 has been shown to restore Foxp3 expression to baseline levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting that targeting PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells may offer a promising new therapeutic avenue for the management of skin-related irAEs.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, this study, integrating clinical data and in vitro experiments, reveals the underlying mechanisms of skin irAEs following PD-1 antibody therapy. It identifies elevated serum levels of IL-5 and IL-17, along with an increased proportion of PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells, as potential biomarkers for the prediction of skin irAEs. The results suggest that PD-1 monoclonal antibodies induce the activation of Th17 cells, leading to the release of inflammatory cytokines such as IL-17, which subsequently triggers the onset of skin-related irAEs. Multi-omics analysis indicates that immune dysregulation is the predominant molecular feature of skin irAEs. Targeting key inflammatory pathways, such as the JAK-STAT signaling pathway and S100A8/A9, may offer novel therapeutic strategies for clinical management. Additionally, future studies should further validate the predictive utility of these biomarkers and explore targeted therapies aimed at the IL-17/IL-23 axis and PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells, with the goal of mitigating the occurrence of skin irAEs and improving patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGuo-Qing Wu, Da-Hong Zhang conceived and designed the study. Zhuo-Nan Meng, Jian-Yuan Chen, Chong Yu, Yong-Rui Su, Shi-Tai Zhang conducted most of the experiments and data analysis and wrote the manuscript. Kai-Yan Liu, Fu-Wei Wang, Ai-Hong Zheng participated in collecting data and helped to draft the manuscript. All authors reviewed and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Science and Technology Program with Traditional Chinese Medicine of Zhejiang Province [2024ZL286].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analysed during the current study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe procedures for sampling and using human skin tissue were approved by the Ethics Committee of Zhejiang Provincial People\u0026apos;s Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate and publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe patient provided written informed consent for the publication of any potentially identifiable images or data in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could influence the work reported here.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQIU H, CAO S, XU R. 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Yale J Biol Med, 2020, 93(1): 123\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMUNTYANU A, NETCHIPOROUK E, GERSTEIN W, et al. Cutaneous Immune-Related Adverse Events (irAEs) to Immune Checkpoint Inhibitors: A Dermatology Perspective on Management [Formula: see text] [J]. J Cutan Med Surg, 2021, 25(1): 59\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eESEN B H, \u0026Ouml;ZBEK L, OĞUZ S, et al. Characterizing immune checkpoint inhibitor-related cutaneous adverse reactions: A comprehensive analysis of FDA adverse event reporting system (FAERS) database [J]. Heliyon, 2024, 10(13): e33765.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e[Chinese expert consensus on diagnosis and treatment of immune checkpoint inhibitor-related skin adverse reactions (2024 edition)] [J]. 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J Clin Invest, 2024, 134(20).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKEIR M, YI Y, LU T, et al. The role of IL-22 in intestinal health and disease [J]. J Exp Med, 2020, 217(3): e20192195.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZHANG P, LIU J, LEE A, et al. IL-22 resolves MASLD via enterocyte STAT3 restoration of diet-perturbed intestinal homeostasis [J]. Cell Metab, 2024, 36(10): 2341-54.e6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLOB\u0026Atilde;O B, LOUREN\u0026Ccedil;O D, GIGA A, et al. From PsO to PsA: the role of T(RM) and Tregs in psoriatic disease, a systematic review of the literature [J]. Front Med (Lausanne), 2024, 11: 1346757.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTRAVES P G, MURRAY B, CAMPIGOTTO F, et al. JAK selectivity and the implications for clinical inhibition of pharmacodynamic cytokine signalling by filgotinib, upadacitinib, tofacitinib and baricitinib [J]. Ann Rheum Dis, 2021, 80(7): 865\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"immune-related adverse events (irAEs), PD-1 antibody, single-cell RNA sequencing","lastPublishedDoi":"10.21203/rs.3.rs-7640849/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7640849/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eImmunotherapy has become the fifth major treatment modality in oncology, with immune checkpoint inhibitors (ICIs) being the most effective immunotherapeutic agents currently used in clinical practice. Although the majority of patients exhibit good tolerance to ICIs, a subset of patients may develop severe immune-related adverse events (irAEs) following treatment. In this study, we included 47 cancer patients receiving PD-1 antibody therapy for the first time. By measuring cytokines in the patients' serum and performing single-cell RNA sequencing on immune cells from an in vitro co-culture system, our results indicated that elevated serum levels of IL-5 and IL-17, along with an increased proportion of PD-1\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e T cells, may be closely associated with the occurrence of skin irAEs. Transcriptomic analysis revealed that differentially expressed genes were enriched in the JAK-STAT signaling pathway, with a significant upregulation of inflammation-related proteins such as S100A8/A9. This study provides new insights into the early prediction and mechanistic understanding of skin irAEs, suggesting that monitoring serum cytokine levels and changes in immune cell subsets may help optimize ICI treatment strategies and reduce the occurrence of irAEs. Targeting key inflammatory pathways may offer novel therapeutic strategies for clinical management.\u003c/p\u003e","manuscriptTitle":"Prediction and treatment of skin adverse reactions related to inhibitors at immune checkpoints","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-18 14:18:17","doi":"10.21203/rs.3.rs-7640849/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17a9d7d6-a8da-4ad8-919d-e9d1f4b5c2c9","owner":[],"postedDate":"October 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T02:10:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-18 14:18:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7640849","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7640849","identity":"rs-7640849","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}