Prospective multicenter study using artificial intelligence to improve dermoscopic melanoma diagnosis in patient care.

BACKGROUND: Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence (AI) has proven to be helpful for enhancing melanoma detection. However, there are few prospective studies confirming these promising results. Existing studies are limited by low sample sizes, too homogenous datasets, or lack of inclusion of rare melanoma subtypes, preventing a fair and thorough evaluation of AI and its generalizability, a crucial aspect for its application in the clinical setting. METHODS: Therefore, we assessed "All Data are Ext" (ADAE), an established open-source ensemble algorithm for detecting melanomas, by comparing its diagnostic accuracy to that of dermatologists on a prospectively collected, external, heterogeneous test set comprising eight distinct hospitals, four different camera setups, rare melanoma subtypes, and special anatomical sites. We advanced the algorithm with real test-time augmentation (R-TTA, i.e., providing real photographs of lesions taken from multiple angles and averaging the predictions), and evaluated its generalization capabilities. RESULTS: Overall, the AI shows higher balanced accuracy than dermatologists (0.798, 95% confidence interval (CI) 0.779-0.814 vs. 0.781, 95% CI 0.760-0.802; p = 4.0e-145), obtaining a higher sensitivity (0.921, 95% CI 0.900-0.942 vs. 0.734, 95% CI 0.701-0.770; p = 3.3e-165) at the cost of a lower specificity (0.673, 95% CI 0.641-0.702 vs. 0.828, 95% CI 0.804-0.852; p = 3.3e-165). CONCLUSION: As the algorithm exhibits a significant performance advantage on our heterogeneous dataset exclusively comprising melanoma-suspicious lesions, AI may offer the potential to support dermatologists, particularly in diagnosing challenging cases.

Melanoma is a type of skin cancer that can spread to other parts of the body, often resulting in death. Early detection improves survival rates. Computational tools that use artificial intelligence (AI) can be used to detect melanoma. However, few studies have checked how well the AI works on real-world data obtained from patients. We tested a previously developed AI tool on data obtained from eight different hospitals that used different types of cameras, which also included images taken of rare melanoma types and from a range of different parts of the body. The AI tool was more likely to correctly identify melanoma than dermatologists. This AI tool could be used to help dermatologists diagnose melanoma, particularly those that are difficult for dermatologists to diagnose.

Brief Communication: Treatment Outcomes for Advanced Melanoma of Unknown Primary Compared With Melanoma With Known Primary.

SUMMARY: Most patients with advanced melanomas have a known primary site [melanoma of known primary (MKP)]. However, 2%-9% of patients are diagnosed with melanoma metastasis of unknown primary (MUP). As MUP and MKP have similar UV-induced mutations and molecular signatures, it is proposed that the primary tumor has regressed completely in patients with MUP. As regression of the primary tumor could be indicative of enhanced recognition of melanoma antigens, we hypothesize that patients with advanced MUP have a better outcome compared with MKP.Patients with advanced MUP from 10 German university hospitals were retrospectively analyzed and matched with MKP based on the type of systemic treatment (BRAF and MEK inhibitors, PD-1 inhibitor monotherapy, combined CTLA-4 and PD-1 inhibitor therapy) therapy line (first or second line) and AJCC stage (IIIC, IV M1a-M1d). Three hundred thirty-seven patients with MUP were identified, and 152 treatments with PD-1 and CTLA-4 inhibitors, 142 treatments with PD-1 inhibitors, and 101 treatments with BRAF and MEK inhibitors were evaluated. Median time to treatment failure was significantly prolonged in patients with MUP treated with PD-1 monotherapy (17 mo, 95% CI: 9-25, P = 0.002) compared with MKP (5 mo, 95% CI: 3.4-6.6), as well as in MUP treated with combined PD-1 and CTLA-4 therapy (11 mo, 95% CI: 4.5-17.5, P < 0.0001) compared with MKP (4 mo, 95% CI: 2.9-5.1) Occurrence of immune-related adverse events and time to treatment failure for patients with BRAF and MEK inhibitors was similar in MKP and MUP. In our multicentre collective, patients with MUP have better outcomes under immunotherapy compared with MKP.

Optimizing immune checkpoint blockade in metastatic uveal melanoma: exploring the association of overall survival and the occurrence of adverse events.

Introduction: Despite recent advancements in the treatment of metastatic uveal melanoma (UM), the availability of further treatment options remains limited and the prognosis continues to be poor in many cases. In addition to tebentafusp, immune checkpoint blockade (ICB, PD-1 (+/-) CTLA-4 antibodies) is commonly used for metastatic UM, in particular in HLA-A 02:01-negative patients. However, ICB comes at the cost of potentially severe immune-related adverse events (irAE). Thus, the selection of patient groups that are more likely to benefit from ICB is desirable. Methods: In this analysis, 194 patients with metastatic UM undergoing ICB were included. Patients were recruited from German skin cancer sites and the ADOReg registry. To investigate the association of irAE occurrence with treatment response, progression-free survival (PFS), and overall survival (OS) two cohorts were compared: patients without irAE or grade 1/2 irAE (n=137) and patients with grade 3/4 irAE (n=57). Results: In the entire population, the median OS was 16.4 months, and the median PFS was 2.8 months. Patients with grade 3/4 irAE showed more favorable survival than patients without or grade 1/2 irAE (p=0.0071). IrAE occurred in 44.7% (87/194), and severe irAE in 29.4% (57/194) of patients. Interestingly, irColitis and irHepatitis were significantly associated with longer OS (p=0.0031 and p=0.011, respectively). Conclusions: This data may indicate an association between irAE and favorable survival outcomes in patients with metastatic UM undergoing ICB treatment and suggests that a reduced tolerance to tumor antigens could be linked to reduced tolerance to self-antigens.

Ultraviolet Filters: Dissecting Current Facts and Myths.

Skin cancer is a global and increasingly prevalent issue, causing significant individual and economic damage. UV filters in sunscreens play a major role in mitigating the risks that solar ultraviolet ra-diation poses to the human organism. While empirically effective, multiple adverse effects of these compounds are discussed in the media and in scientific research. UV filters are blamed for the dis-ruption of endocrine processes and vitamin D synthesis, damaging effects on the environment, induction of acne and neurotoxic and carcinogenic effects. Some of these allegations are based on scientific facts while others are simply arbitrary. This is especially dangerous considering the risks of exposing unprotected skin to the sun. In summary, UV filters approved by the respective governing bodies are safe for human use and their proven skin cancer-preventing properties make them in-dispensable for sensible sun protection habits. Nonetheless, compounds like octocrylene and ben-zophenone-3 that are linked to the harming of marine ecosystems could be omitted from skin care regimens in favor of the myriad of non-toxic UV filters.

Anti-PD-(L)1 plus BRAF/MEK inhibitors (triplet therapy) after failure of immune checkpoint inhibition and targeted therapy in patients with advanced melanoma.

BACKGROUND: Effective treatment options are limited for patients with advanced melanoma who have progressed on immune checkpoint inhibitors (ICI) and targeted therapies (TT). Preclinical models support the combination of ICI with TT; however, clinical trials evaluating the efficacy of triplet combinations in first-line setting showed limited advantage compared to TT only. METHODS: We conducted a retrospective, multicenter study, that included patients with advanced melanoma who were treated with BRAF/MEK inhibitors in combination with an anti-PD-(L)1 antibody (triplet therapy) after failure of at least one anti-PD-(L)1-based therapy and one TT in seven major melanoma centers between February 2016 and July 2022. RESULTS: A total of 48 patients were included, of which 32 patients, 66.7% had brain metastases, 37 patients (77.1%) had three or more metastatic organs and 21 patients (43.8%) had three or more treatment lines. The median follow-up time was 31.4 months (IQR, 22.27-40.45 months). The treatment with triplet therapy resulted in an ORR of 35.4% (n = 17) and a DCR of 47.9% (n = 23). The median DOR was 5.9 months (range, 3.39-14.27 months). Patients treated with BRAF/MEK inhibitors as the last treatment line showed a slightly lower ORR (29.6%) compared to patients who received ICI or chemotherapy last (ORR: 42.9%). Grade 3-4 treatment-related adverse events occurred in 25% of patients (n = 12), with seven patients (14.6%) requiring discontinuation of treatment with both or either drug. CONCLUSIONS: Triplet therapy has shown activity in heavily pretreated patients with advanced melanoma and may represent a potential treatment regimen after failure of ICI and TT.

Federated Learning for Decentralized Artificial Intelligence in Melanoma Diagnostics.

Importance: The development of artificial intelligence (AI)-based melanoma classifiers typically calls for large, centralized datasets, requiring hospitals to give away their patient data, which raises serious privacy concerns. To address this concern, decentralized federated learning has been proposed, where classifier development is distributed across hospitals. Objective: To investigate whether a more privacy-preserving federated learning approach can achieve comparable diagnostic performance to a classical centralized (ie, single-model) and ensemble learning approach for AI-based melanoma diagnostics. Design, Setting, and Participants: This multicentric, single-arm diagnostic study developed a federated model for melanoma-nevus classification using histopathological whole-slide images prospectively acquired at 6 German university hospitals between April 2021 and February 2023 and benchmarked it using both a holdout and an external test dataset. Data analysis was performed from February to April 2023. Exposures: All whole-slide images were retrospectively analyzed by an AI-based classifier without influencing routine clinical care. Main Outcomes and Measures: The area under the receiver operating characteristic curve (AUROC) served as the primary end point for evaluating the diagnostic performance. Secondary end points included balanced accuracy, sensitivity, and specificity. Results: The study included 1025 whole-slide images of clinically melanoma-suspicious skin lesions from 923 patients, consisting of 388 histopathologically confirmed invasive melanomas and 637 nevi. The median (range) age at diagnosis was 58 (18-95) years for the training set, 57 (18-93) years for the holdout test dataset, and 61 (18-95) years for the external test dataset; the median (range) Breslow thickness was 0.70 (0.10-34.00) mm, 0.70 (0.20-14.40) mm, and 0.80 (0.30-20.00) mm, respectively. The federated approach (0.8579; 95% CI, 0.7693-0.9299) performed significantly worse than the classical centralized approach (0.9024; 95% CI, 0.8379-0.9565) in terms of AUROC on a holdout test dataset (pairwise Wilcoxon signed-rank, P < .001) but performed significantly better (0.9126; 95% CI, 0.8810-0.9412) than the classical centralized approach (0.9045; 95% CI, 0.8701-0.9331) on an external test dataset (pairwise Wilcoxon signed-rank, P < .001). Notably, the federated approach performed significantly worse than the ensemble approach on both the holdout (0.8867; 95% CI, 0.8103-0.9481) and external test dataset (0.9227; 95% CI, 0.8941-0.9479). Conclusions and Relevance: The findings of this diagnostic study suggest that federated learning is a viable approach for the binary classification of invasive melanomas and nevi on a clinically representative distributed dataset. Federated learning can improve privacy protection in AI-based melanoma diagnostics while simultaneously promoting collaboration across institutions and countries. Moreover, it may have the potential to be extended to other image classification tasks in digital cancer histopathology and beyond.

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma.

Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists' decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists' diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists' confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists' willingness to adopt such XAI systems, promoting future use in the clinic.

Standardized Computer-Assisted Analysis of 5-hmC Immunoreactivity in Dysplastic Nevi and Superficial Spreading Melanomas.

5-Hydroxymethylcytosine (5-hmC) is an important intermediate of DNA demethylation. Hypomethylation of DNA is frequent in cancer, resulting in deregulation of 5-hmC levels in melanoma. However, the interpretation of the intensity and distribution of 5-hmC immunoreactivity is not very standardized, which makes its interpretation difficult. In this study, 5-hmC-stained histological slides of superficial spreading melanomas (SSM) and dysplastic compound nevi (DN) were digitized and analyzed using the digital pathology and image platform QuPath. Receiver operating characteristic/area under the curve (ROCAUC) and t-tests were performed. A p-value of <0.05 was used for statistical significance, and a ROCAUC score of >0.8 was considered a "good" result. In total, 92 5-hmC-stained specimens were analyzed, including 42 SSM (45.7%) and 50 DN (54.3%). The mean of 5-hmC-positive cells/mm2 for the epidermis and dermo-epidermal junction and the entire lesion differed significantly between DN and SSM (p = 0.002 and p = 0.006, respectively) and showed a trend towards higher immunoreactivity in the dermal component (p = 0.069). The ROCAUC of 5-hmC-positive cells of the epidermis and dermo-epidermal junction was 0.79, for the dermis 0.74, and for the entire lesion 0.76. These results show that the assessment of the epidermal with junctional expression of 5-hmC is slightly superior to dermal immunoreactivity in distinguishing between DN and SSM.

Threshold Optimization for Tumor Markers S100b and MIA in Uveal Melanoma - A Single Center Analysis.

BACKGROUND/AIM: Uveal melanoma (UM) is the most common malignant tumor of the eye in adults. Metastases develop in 50% of the patients, predominantly in the liver. In UM, the cut-off concentrations of the blood-based tumor markers S100b and MIA are inconclusive. PATIENTS AND METHODS: In this retrospective monocenter study, we statistically evaluated 1,878 S100b and 1,768 MIA measurements in 244 patients with UM from 2011-2020. Threshold optimization was performed using receiver operating characteristic (ROC) curves. RESULTS: A total of 171 patients with non-metastatic UM (nmUM) and 73 patients with metastatic UM (mUM) showed no differences in sex, age at diagnosis or the affected eye. In mUM, 80% of the patients developed metastases to the liver at a median of 46 months after initial diagnosis. The sensitivity and specificity of S100b was 16.10% and 94.52%, and that of MIA was 31.86% and 81.42%, respectively. ROC curves revealed poor values for the area under the curve of 0.57 for S100b and 0.55 for MIA. The optimal cut-off concentration to detect metastases was 0.14 µg/l for S100b and 17.4 ng/ml for MIA. With at least one tumor marker elevated, optimized sensitivity was 20.40% and specificity 96.76%. CONCLUSION: Current thresholds for S100b and MIA in UM are not able to detect early metastatic disease and require additional diagnostics to clarify false positive results. Threshold optimization considering both S100b and MIA results in a better diagnostic validity with an acceptable specificity and a poor sensitivity. Highly sensitive blood-based and imaging methods to detect metastases early in UM are urgently needed.

Adjuvant treatment and outcome of stage III melanoma patients: Results of a multicenter real-world German Dermatologic Cooperative Oncology Group (DeCOG) study.

PURPOSE: Clinical trials demonstrated significantly improved recurrence-free survival (RFS) of melanoma patients receiving adjuvant treatment. As data from controlled trials are based on selected populations, we investigated adjuvantly treated stage III melanoma patients under real-world conditions. PATIENTS AND METHODS: In a prior multicenter cohort study, stage III-IV melanoma patients were analysed for their choice of adjuvant therapy. In this follow-up study, we examined RFS, overall and melanoma-specific survival (MSS) and response to the subsequent treatment of 589 stage III patients (232 BRAF-mutated) receiving adjuvant PD-1 inhibitors (PD1; n = 479) or targeted therapy (TT; n = 110). RESULTS: The median follow-up of the total cohort was 25.7 months. The main reason for premature discontinuation of adjuvant therapy was disease progression in PD1- (28.8%, n = 138/479) and adverse events in TT-treated patients (28.2%, n = 31/110). Among BRAF-mutated patients, RFS at 24 months was 49% (95% CI 40.6-59.0%) for PD1- and 67% (95% CI 58-77%) for TT-treated patients. The risk of recurrence was higher for BRAF-mutated PD1 than TT (hazard ratio 1.99; 95% CI 1.34-2.96; hazard ratio adjusted for age, sex and tumour stage, 2.21; 95% CI 1.48-3.30). Twenty-four months MSS was 87% (95% CI 81.0-94.1) for PD1 and 92% (95% CI 86.6-97.0) for TT. Response to subsequent systemic treatment for unresectable disease was 22% for all PD1- and 16% for TT-treated patients. CONCLUSIONS: PD1-treated patients had more and earlier recurrences than TT patients. In BRAF-mutated patients, adjuvant TT might prevent early recurrences more effectively than PD1 treatment. Management of recurrence despite adjuvant treatment is challenging, with low response to current therapeutic options.

Tirbanibulin 1% Ointment Significantly Reduces the Actinic Keratosis Area and Severity Index in Patients with Actinic Keratosis: Results from a Real-World Study.

BACKGROUND: Actinic keratosis (AK) is a cutaneous lesion resulting from the proliferation of atypical epidermal keratinocytes caused by long-term exposure to ultraviolet radiation. AK may progress to cutaneous squamous cell carcinoma (cSCC) and therefore is often treated with topical agents such as 5-fluorouracil, diclofenac, imiquimod, and photodynamic therapy. Tirbanibulin has been approved based on two phase III trials in the USA. However, real-world evidence for tirbanibulin is absent. METHODS: This was a single-centre study of adult patients with clinically typical, visible AK on the face or scalp treated with tirbanibulin 1% ointment. Treatment was administered as per label once daily for 5 consecutive days on the same lesions or field. Treatment outcomes were assessed 4 weeks after treatment, with additional optional assessments conducted at later time points. Efficacy was measured using the actinic keratosis area and severity index (AKASI) and digital dermoscopy. RESULTS: A total of 33 patients were treated of whom 30 were analysed. The median AKASI score was 5.6 (1.4-11) pre-treatment and 1.2 (0-7.4) post-treatment (p < 0.0001). Complete clearance as defined by AKASI scores less than 1 was achieved in 47% (n = 14) and 57% (n = 13) at the first and second follow-up, respectively. All local reactions resolved spontaneously and without sequelae. The most common local reactions were erythema (80%, n = 26) and flaking or scaling (43%, n = 13). CONCLUSIONS: Tirbanibulin 1% ointment significantly and rapidly reduced the AKASI score in a real-world setting. The complete clearance rates were in line with those observed in the two pivotal trials.

Opportunities to inform German residents about the possibility of skin cancer screening and to inform stakeholders to take appropriate actions: A qualitative approach.

BACKGROUND: The national skin cancer screening (SCS) was introduced in Germany in 2008. However, public awareness and participation rates remain low. There are no campaigns or target group-specific invitation strategies for SCS yet. Thus, our aim was to derive potential suggestions on how to best inform German residents about the possibility of SCS. METHODS: Semi-structured, individual interviews with male and female German residents aged ≥35 years were conducted in Erlangen (Germany) to explore opportunities on raising awareness of SCS. Interviews were audiotaped, transcribed verbatim, and analyzed using qualitative content analysis. RESULTS: Overall, 39 persons were interviewed. About 79.5% (31/39) had already undergone at least one SCS. Numerous opportunities to raise awareness of the possibility of SCS were suggested which were categorized into three main topics: the role of public promotion, health-related caregivers, and health insurance. Similar themes were identified for inviting entitled persons to undergo SCS after 2 years. Furthermore, age-dependent communication approaches were proposed, that is, younger persons should be approached electronically, while the older generation should be targeted with traditional media like mail. CONCLUSIONS: The results of this project will inform stakeholders to take appropriate actions. The findings may contribute to increase participation rates in SCS and thus lead to earlier detection of skin cancer.

Standardized Computer-Assisted Analysis of PRAME Immunoreactivity in Dysplastic Nevi and Superficial Spreading Melanomas.

PRAME (PReferentially expressed Antigen in MElanoma) is a cancer testis antigen that is frequently expressed in melanoma compared to benign melanocytic proliferations and nevi. However, the interpretation of the intensity and distribution of PRAME immunostaining is not standardized a lot, which makes interpretation difficult. PRAME-stained histological slides of superficial spreading melanomas (SSM) and dysplastic nevi (DN) were digitized and analyzed using the digital pathology and image platform QuPath. t-tests and ROC AUCs were performed with SPSS. A p-value of <0.05 was used for statistical significance, and a ROC AUC score of >0.8 was considered a good result. A cut-off score was defined in an evaluation cohort and subsequently analyzed in an independent validation cohort. In total, 81 PRAME-stained specimens were included. The evaluation cohort included 32 (50%) SSM and 32 (50%) DN, and the mean of PRAME-positive cells/mm2 for the entire lesion was 455.3 (SD 428.2) in SSM and 60.5 (SD 130.1; p < 0.001) in DN. The ROC AUC of PRAME-positive cells of the entire lesion was 0.866, and in the epidermis it was 0.901. The defined cut-off score to distinguish between DN and SSM was 97.67 cells/mm2. In the validation cohort, 16 out of 17 cases (94.1%) were correctly classified by the cut-off score. The computer-aided assessment of PRAME immunostaining is a useful tool in dermatopathology to distinguish between DN and SSM. Lesions with a moderate expression and indifferent morphologic features will remain a challenge for dermatopathologists.

S1-guideline cutaneous and subcutaneous leiomyosarcoma.

Superficial leiomyosarcomas (LMS) are rare skin cancers (2-3% of cutaneous sarcomas) that originate from dermally located hair follicle muscles, dartos or areolar muscles (cutaneous/dermal LMS), or from vascular muscle cells of the subcutaneous adipose tissue (subcutaneous LMS). These superficial LMS are distinct from LMS of the deep soft tissues. Leiomyosarcomas are typically localized at the lower extremities, trunk or capillitium, and present as painful, erythematous to brownish nodules. Diagnosis is made by histopathology. The treatment of choice for primary LMS is complete (R0) microscopically controlled excision, with safety margins of 1 cm in dermal LMS, and 2 cm in subcutaneous LMS, if possible. Non-resectable or metastatic LMS require individual treatment decisions. After R0 resection with 1 cm safety margins, the local recurrence rate of dermal LMS is very low, and metastasis is very rare. Subcutaneous LMS, very large, or incompletely excised LMS recur and metastasize more frequently. For this reason, clinical follow-up examinations are recommended every six months for cutaneous LMS, and every three months for subcutaneous LMS within the first two years (in subcutaneous LMS including locoregional lymph node sonography). Imaging such as CT/MRI is indicated only in primary tumors with special features, recurrences, or already metastasized tumors.

Conventional and three-dimensional photography as a tool to map distribution patterns of in-transit melanoma metastases on the lower extremity.

Background: In melanoma, in-transit metastases characteristically occur at the lower extremity along lymphatic vessels. Objectives: The objective of this study was to evaluate conventional or three-dimensional photography as a tool to analyze in-transit metastasis pattern of melanoma of the lower extremity. In addition, we assessed risk factors for the development of in-transit metastases in cutaneous melanoma. Methods: In this retrospective, monocentric study first we compared the clinical data of all evaluable patients with in-transit metastases of melanoma on the lower extremity (n = 94) with melanoma patients without recurrence of disease (n = 288). In addition, based on conventional (n = 24) and three-dimensional photography (n = 22), we defined the specific distribution patterns of the in-transit metastases on the lower extremity. Results: Using a multivariate analysis we identified nodular melanoma, tumor thickness, and ulceration as independent risk factors to develop in-transit metastases ITM (n = 94). In patients with melanoma on the lower leg (n = 31), in-transit metastases preferentially developed along anatomically predefined lymphatic pathways. In contrast when analyzing in-transit metastases of melanoma on the foot (n = 15) no clear pattern could be visualized. In addition, no difference in distance between in-transit metastases and primary melanoma on the foot compared to the lower leg was observed using three-dimensional photography (n = 22). Conclusion: A risk-adapted follow-up of melanoma patients to detect in-transit metastases can be applied by knowledge of the specific lymphatic drainage of the lower extremity. Our current analysis suggests a more complex lymphatic drainage of the foot.

Immune signatures predict development of autoimmune toxicity in patients with cancer treated with immune checkpoint inhibitors.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are among the most promising treatment options for melanoma and non-small cell lung cancer (NSCLC). While ICIs can induce effective anti-tumor responses, they may also drive serious immune-related adverse events (irAEs). Identifying biomarkers to predict which patients will suffer from irAEs would enable more accurate clinical risk-benefit analysis for ICI treatment and may also shed light on common or distinct mechanisms underpinning treatment success and irAEs. METHODS: In this prospective multi-center study, we combined a multi-omics approach including unbiased single-cell profiling of over 300 peripheral blood mononuclear cell (PBMC) samples and high-throughput proteomics analysis of over 500 serum samples to characterize the systemic immune compartment of patients with melanoma or NSCLC before and during treatment with ICIs. FINDINGS: When we combined the parameters obtained from the multi-omics profiling of patient blood and serum, we identified potential predictive biomarkers for ICI-induced irAEs. Specifically, an early increase in CXCL9/CXCL10/CXCL11 and interferon-γ (IFN-γ) 1 to 2 weeks after the start of therapy are likely indicators of heightened risk of developing irAEs. In addition, an early expansion of Ki-67+ regulatory T cells (Tregs) and Ki-67+ CD8+ T cells is also likely to be associated with increased risk of irAEs. CONCLUSIONS: We suggest that the combination of these cellular and proteomic biomarkers may help to predict which patients are likely to benefit most from ICI therapy and those requiring intensive monitoring for irAEs. FUNDING: This work was primarily funded by the European Research Council, the Swiss National Science Foundation, the Swiss Cancer League, and the Forschungsförderung of the Kantonsspital St. Gallen.