Checkpoint Inhibitors In Melanoma Research Articles

Differential activity of MAPK signalling defines fibroblast subtypes in pancreatic cancer

Fibroblast heterogeneity is increasingly recognised across cancer conditions. Given their important contribution to disease progression, mapping fibroblasts’ heterogeneity is critical to devise effective anti-cancer therapies. Cancer-associated fibroblasts (CAFs) represent the most abundant cell population in pancreatic ductal adenocarcinoma (PDAC). Whether CAF phenotypes are differently specified by PDAC cell lineages remains to be elucidated. Here, we reveal an important role for the MAPK signalling pathway in defining PDAC CAF phenotypes. We show that epithelial MAPK activity promotes the myofibroblastic differentiation of CAFs by sustaining the expression and secretion of TGF-β1. We integrate single-cell profiling of post-perturbation transcriptional responses from mouse models with cellular and spatial profiles of human tissues to define a MAPKhigh CAF (mapCAF) phenotype. We show that this phenotype associates with basal-like tumour cells and reduced frequency of CD8+ T cells. In addition to elevated MAPK activity, this mapCAF phenotype is characterized by TGF-β signalling, hypoxia responsive signatures, and immunoregulatory gene programs. Furthermore, the mapCAF signature is enriched in myofibroblastic CAFs from various cancer conditions and correlates with reduced response to immune checkpoint inhibition in melanoma. Altogether, our data expand our knowledge on CAF phenotype heterogeneity and reveal a potential strategy for targeting myofibroblastic CAFs in vivo.

Notch1 blockade by a novel, selective anti-Notch1 neutralizing antibody improves immunotherapy efficacy in melanoma by promoting an inflamed TME

BackgroundImmune checkpoint inhibitors (ICI) have dramatically improved the life expectancy of patients with metastatic melanoma. However, about half of the patient population still present resistance to these treatments. We have previously shown Notch1 contributes to a non-inflamed TME in melanoma that reduces the response to ICI. Here, we addressed the therapeutic effects of a novel anti-Notch1 neutralizing antibody we produced, alone and in combination with immune checkpoint inhibition in melanoma models.MethodsAnti-Notch1 was designed to interfere with ligand binding. Mice were immunized with a peptide encompassing EGF-like repeats 11–15 of human Notch1, the minimal required region that allows ligand binding and Notch1 activation. Positive clones were expanded and tested for neutralizing capabilities. Anti-Notch1-NIC was used to determine whether anti-Notch1 was able to reduce Notch1 cleavage; while anti-SNAP23 and BCAT2 were used as downstream Notch1 and Notch2 targets, respectively. K457 human melanoma cells and the YUMM2.1 and 1.7 syngeneic mouse melanoma cells were used. Cell death after anti-Notch1 treatment was determined by trypan blue staining and compared to the effects of the gamma-secretase inhibitor DBZ. 10 mg/kg anti-Notch1 was used for in vivo tumor growth of YUMM2.1 and 1.7 cells. Tumors were measured and processed for flow cytometry using antibodies against major immune cell populations.ResultsAnti-Notch1 selectively inhibited Notch1 but not Notch2; caused significant melanoma cell death in vitro but did not affect normal melanocytes. In vivo, it delayed tumor growth without evident signs of gastro-intestinal toxicities; and importantly promoted an inflamed TME by increasing the cytotoxic CD8+ T cells while reducing the tolerogenic Tregs and MDSCs, resulting in enhanced efficacy of anti-PD-1.ConclusionsAnti-Notch1 safely exerts anti-melanoma effects and improves immune checkpoint inhibitor efficacy. Thus, anti-Notch1 could represent a novel addition to the immunotherapy repertoire for melanoma.

Tissue-Based Profiling Techniques to Achieve Precision Medicine in Cancer: Opportunities and Challenges in Melanoma.

Immunotherapies targeting the programmed cell death 1 (PD-1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) checkpoint receptors have revolutionized the treatment of metastatic melanoma. However, half of the treated patients do not respond to or eventually progress on standard therapies and many experience adverse events as a result of drug toxicity. The identification of accurate biomarkers of clinical outcomes are required in order to move away from the one-size-fits-all treatment approach of standard clinical practice and toward a more personalized approach to enable the administration of the optimal therapy for any given patient and further improve patient outcomes. Recent clinical trials have proven the potential of multiomics analyses, including genomic, gene expression, and tumor immune profiling, of patients' tumor biopsies, to predict a patient's response to subsequently administered immunotherapies. However, reproducibility of such multiomics analyses, tissue requirements, and clinical validation have limited the practical application of these approaches in routine clinical workflows. In this review, we discuss several pivotal tissue-based profiling techniques that can be utilized to identify potential genomic, transcriptomic, and immune biomarkers predictive of clinical outcomes following treatment with immune checkpoint inhibitors in melanoma. Furthermore, we highlight the key opportunities and challenges associated with the use of each of these techniques. The development and implementation of multimodal predictive models that combine data derived from these various methods is the future for achieving precision medicine for patients with melanoma.

Dual Immune Checkpoint Inhibition in Melanoma and PD-L1 Expression: The Jury Is Still Out.

This comment discusses the use of PD-L1 as a biomarker to guide treatment decisions for metastatic melanoma.

Dual Checkpoint Inhibition in Melanoma With ≥1% PD-L1—Time to Reassess the Evidence

This Viewpoint discusses use of anti–PD-1 monotherapy as the primary treatment option for patients with treatment-naive metastatic melanoma staining positive for PD-L1 over dual checkpoint inhibition therapy.

Identification of the transcriptomic alterations of resistance to immune checkpoint inhibitors in melanoma

Although immunotherapeutics like immune checkpoint inhibitor (ICI) therapy have greatly improved survival rates, death rates of melanoma still remain high. One of the reasons for this is that the solid tumor microenvironment creates obstacles for the effectiveness of anti-PD1 immunotherapy in patients. Therefore, it is crucial to identify potential biomarkers that could be used in combination therapy with anti-PD1 to modify the tumor microenvironment and enhance response to treatment. In this study, we examined clinical and tumor transcriptional sequencing data from 91 patients who received anti-PD1/anti-CTLA4 therapy. Through both bulk RNA sequencing analysis and single-cell RNA-sequencing (scRNA-seq), we discovered that 8 key pathways were upregulated in patients who responded well to the therapy. Interestingly, these pathways were found in myeloid and T cell populations, indicating their significant role in response to anti-PD1/anti-CTLA4 therapy. Among these pathways, genes such as IRF1, IRF2, C1, and C3 emerged as potential biomarkers that could potentially enhance the effectiveness of ICIs therapy. Further clinical research is required to validate the impact of these genes. The novelty of this study lies in the combination of bulk RNA sequencing and single RNA sequencing methods, which allowed us to uncover distinct differences in the transcriptomic landscape of solid tumors, particularly melanoma.

Association between immune-related adverse events and prognosis in patients treated with immune checkpoint inhibitors in melanoma: A surrogacy analysis.

Immune checkpoint inhibitors (ICI) represent a breakthrough in oncology in terms of prognosis and safety. They now constitute a cornerstone in the management of metastatic melanoma. However, a new kind of adverse event called immune-related adverse events (irAE) has emerged. These irAE could be conceptually considered as an indicator of the antitumoral immune response, but the association between irAE and prognosis is still a matter of debate. The purpose of this study was to investigate the association between the overall survival (OS) and the prevalence of irAE in melanoma. MEDLINE/PubMed, WebofScience, ClinicalTrials, and WHOTrials databases were searched to identify phase 3 randomized controlled trials (RCT) assessing ICI in melanoma and published up to April 2021. A weighted regression was performed to estimate this association according to standard method of surrogacy analysis. A total of 14 RCT including 7646 patients (median age: 59.3years) with melanoma were included. All types of ICI were represented (ipilimumab, tremelimumab, pembrolizumab, nivolumab, atezolizumab, as well as ipilimumab and nivolumab combination). irAE were frequent but rarely fatal. The combination of ICI caused more irAE than anti-PD1 (or PDL1) and anti-CTLA4 monotherapies. No relationship was found between the occurrence of irAE and OS (beta coefficient 0.078, R2 3%, p = 0.52), nor between cutaneous irAE and OS (beta coefficient 0.080, R2 6%, p = 0.33). Although limited by the heterogeneity of ICI included in the regression and the low number of included RCT, the present study suggests an absence of association between irAE and prognosis in melanoma.

LB1643 Novel insights into vitiligo-like depigmentation under immune checkpoint inhibitors in melanoma compared to classical vitiligo and healthy skin biopsies

LB1643 Novel insights into vitiligo-like depigmentation under immune checkpoint inhibitors in melanoma compared to classical vitiligo and healthy skin biopsies

Immunotherapy around the Clock: Impact of Infusion Timing on Stage IV Melanoma Outcomes.

Although the impact of circadian timing on immunotherapy has yet to be integrated into clinical practice, chronoimmunotherapy is an emerging and promising field as circadian oscillations are observed in immune cell numbers as well as the expression of immunotherapy targets, e.g., programmed cell death protein-1 and its ligand programmed death ligand 1. Concurrent retrospective studies suggest that morning infusions may lead to higher effectiveness of immune checkpoint inhibitors in melanoma, non-small cell lung cancer, and kidney cancer. This paper discusses the results of a retrospective study (2016-2022) exploring the impact of infusion timing on the outcomes of all 73 patients with stage IV melanoma receiving immunotherapy at a particular medical center. While the median overall survival (OS) was 24.2 months (95% confidence interval [CI] 9.04-39.8), for a median follow-up of 15.3 months, our results show that having more than 75% of infusions in the afternoon results in shorter median OS (14.9 vs. 38.1 months; hazard ratio 0.45 [CI 0.23-0.86]; p < 0.01) with more expressive impacts on particular subgroups: women, older patients, and patients with a lower tumor burden at the outset of immunotherapy. Our findings highlight the potential benefits of follow-up validation in prospective and translational randomized studies.

SETBP1 mutation determines sensitivity to immune checkpoint inhibitors in melanoma and NSCLC.

SET binding protein 1 (SETBP1) plays crucial roles in various biological processes; however, its involvement in cancer immune checkpoint inhibitor (ICI) treatments has never been studied. In this study, we collected a total of 631 melanoma and 109 non-small cell lung cancer (NSCLC) samples treated with ICI agents (i.e., anti-CTLA-4, anti-PD-1/PD-L1, or combination therapy). Additionally, we obtained their corresponding somatic mutational profiles. We observed that SETBP1 mutated (SETBP1-MUT) melanoma patients exhibited significantly prolonged ICI survival outcomes compared to wild-type patients (HR: 0.56, 95% CI: 0.38-0.81, P = 0.002). Consistently, an elevated ICI response rate was also noticed in the SETBP1-MUT group (42.9% vs. 29.1%, P = 0.016). The Association of SETBP1 mutations with favorable immunotherapeutic prognosis and response was further supported by an independent NSCLC cohort (both P < 0.05). Additional immunological analyses revealed that favorable immune infiltration, tumor immunogenicity, and immune response circuits were enriched in SETBP1-MUT patients. Overall, our findings suggest that SETBP1 mutations may serve as a new biomarker for stratifying beneficiaries of ICI treatments in melanoma and NSCLC, which provides possible evidence for tailoring clinical immunotherapeutic strategies.

Interleukin 17 signaling supports clinical benefit of dual CTLA-4 and PD-1 checkpoint inhibition in melanoma.

Recent studies suggest that BRAFV600-mutated melanomas in particular respond to dual anti-programmed cell death protein 1 (PD-1) and anti-cytotoxic T lymphocyte-associated protein 4 (CTLA-4) immune checkpoint inhibition (ICI). Here we identified an over-representation of interleukin (IL)-17-type 17 helper T (TH17) gene expression signatures (GES) in BRAFV600-mutated tumors. Moreover, high baseline IL-17 GES consistently predicted clinical responses in dual-ICI-treated patient cohorts but not in mono anti-CTLA-4 or anti-PD-1 ICI cohorts. High IL-17 GES corresponded to tumor infiltration with T cells and neutrophils. Accordingly, high neutrophil infiltration correlated with clinical response specifically to dual ICI, and tumor-associated neutrophils also showed strong IL-17-TH17 pathway activity and T cell activation capacity. Both the blockade of IL-17A and the depletion of neutrophils impaired dual-ICI response and decreased T cell activation. Finally, high IL-17A levels in the blood of patients with melanoma indicated a higher global TH17 cytokine profile preceding clinical response to dual ICI but not to anti-PD-1 monotherapy, suggesting a future role as a biomarker for patient stratification.

The validity of a machine learning algorithm in predicting response to immune checkpoint inhibitors in melanoma.

9523 Background: We previously reported the development of a machine learning algorithm to predict immunotherapy response in patients with advanced melanoma using retrospectively collected pretreatment histologic slides (Johannet et al, CCR 2021). In this study, we tested the validity of the same algorithm in two independent cohorts of melanoma patients enrolled in phase III clinical trials of immune checkpoint inhibitors (ICI), one metastatic, and one adjuvant. Methods: We examined 336 patients enrolled in CheckMate 067(NCT01844505) and CheckMate 238 (NCT02388906). We used deep convolutional neural networks (DCNN) to automatically segment images into three regions of interest: tumor, lymphocytes, and stroma. The algorithm was previously trained and tested to predict the complete and partial response (CR/PR) versus progression of disease (POD) and to predict the probability of progression-free survival (PFS) while on ICI. We tested the performance in the two cohorts; the first (CheckMate 067) included 164 patients with stage III/IV unresectable melanoma who received ipilimumab (n= 49), nivolumab (n = 59), or combination (n= 56) therapy as a first line, then tested whether the algorithm could perform as well in the second cohort (CheckMate 238) which included 172 patients with stage III/IV resectable melanoma who received adjuvant ipilimumab (n = 87) or nivolumab (n = 85) therapy as first line. Results: The segmentation classifier identified tumor within slides with an area under the curve (AUC) of 0.99. A combined model of DCCN and treatment predicted POD with an AUC of 0.72 in metastatic melanoma patients enrolled in Checkmate 067. The DCCN classified patients into high and low risk based on their likelihood of PFS (P &lt;0.0001). However, the same algorithm is not effective in predicting recurrence in patients treated in the adjuvant setting in Checkmate 238 (AUC 0.52). Retraining and testing using only patients treated in the adjuvant setting improved the AUC average to 0.65-0.70. Conclusions: Our results show the reproducibility of our previously developed algorithm in predicting response in patients with advanced metastatic melanoma. The inability of the model to predict recurrence in patients treated in the adjuvant setting might reflect the difference in the endpoint tested (response versus recurrence), which requires further training on larger datasets for this particular endpoint prediction, and/or the limited tumor volume in resected disease below a threshold that machine learning can predict a difference.

Cardiovascular Immunotoxicity Associated with Immune Checkpoint Inhibitors in Metastatic Melanoma

Checkpoint inhibitors, such as PD-1 inhibitors (nivolumab, pembrolizumab) and anti-CTLA-4 (CD152) (ipilimumab), are widely used in metastatic melanoma, and most immune-related adverse events are known. Several cardiovascular AEs (CVAEs) associated with immune checkpoint inhibitor exposure have been reported in post-marketing surveillance studies and represent major issues for patients with melanoma during and after cancer treatment. Data on CVAES induced by immune checkpoint inhibitors in melanoma, especially incidence and risk factors, are lacking. A systematic review of the literature up to 31 August 2020 was performed in Medline, the Cochrane Central Register of Controlled Trials (CENTRAL), and the ClinicalTrials.gov register according to prespecified selection criteria from inception to 7 April 2020. Statistics were performed on 3289 patients from five randomized clinical trials on melanoma. Patients with melanoma treated with immune checkpoint inhibitors had a significant risk of presenting dyslipidemia (Peto OR: 4.74, 95% CI: 2.16-10.41, p < 0.01, I2 = 0%, p = 0.94). The Peto OR was numerically significant for pericarditis, myocarditis, heart failure, myocardial infarction, cerebral ischemia, high pulmonary pressure, blood high pressure, arrhythmias, endocarditis, and conduction disturbances, but the confidence interval was not significant. The risk of CVAEs was not statistically different between melanoma treated with immune checkpoint inhibitors and other tumors treated with immune checkpoint inhibitors (range of p-value from 0.13 to 0.95). No interaction between follow-up length and CVAE reporting was found. Our study underlines that checkpoint inhibitors used for melanoma increase CVAEs, especially dyslipidemia, which could pave the way to chronic inflammatory processes, atherosclerosis, and, finally, ischemic cardiopathy. These cardiovascular adverse events could be acute or delayed, justifying the monitoring of lipidic biology and a baseline cardiology consultation.

CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma

IntroductionPredicting checkpoint inhibitors treatment outcomes in melanoma is a relevant task, due to the unpredictable and potentially fatal toxicity and high costs for society. However, accurate biomarkers for treatment outcomes are lacking. Radiomics are a technique to quantitatively capture tumour characteristics on readily available computed tomography (CT) imaging. The purpose of this study was to investigate the added value of radiomics for predicting clinical benefit from checkpoint inhibitors in melanoma in a large, multicenter cohort. MethodsPatients who received first-line anti-PD1±anti-CTLA4 treatment for advanced cutaneous melanoma were retrospectively identified from nine participating hospitals. For every patient, up to five representative lesions were segmented on baseline CT, and radiomics features were extracted. A machine learning pipeline was trained on the radiomics features to predict clinical benefit, defined as stable disease for more than 6 months or response per RECIST 1.1 criteria. This approach was evaluated using a leave-one-centre-out cross validation and compared to a model based on previously discovered clinical predictors. Lastly, a combination model was built on the radiomics and clinical model. ResultsA total of 620 patients were included, of which 59.2% experienced clinical benefit. The radiomics model achieved an area under the receiver operator characteristic curve (AUROC) of 0.607 [95% CI, 0.562–0.652], lower than that of the clinical model (AUROC=0.646 [95% CI, 0.600–0.692]). The combination model yielded no improvement over the clinical model in terms of discrimination (AUROC=0.636 [95% CI, 0.592–0.680]) or calibration. The output of the radiomics model was significantly correlated with three out of five input variables of the clinical model (p < 0.001). DiscussionThe radiomics model achieved a moderate predictive value of clinical benefit, which was statistically significant. However, a radiomics approach was unable to add value to a simpler clinical model, most likely due to the overlap in predictive information learned by both models. Future research should focus on the application of deep learning, spectral CT-derived radiomics, and a multimodal approach for accurately predicting benefit to checkpoint inhibitor treatment in advanced melanoma.

100P Immunotherapy around the clock: Impact on stage IV melanoma

Immunotherapy is currently the standard of care in the treatment of metastatic melanoma. Immune cells in the tumor microenvironment play a decisive role in tumor growth and response to therapy. NK and dendritic cells, monocytes, T and B lymphocytes exhibit circadian oscillations in the peripheral blood, as well as PD-L1 expression. Recent data from MEMOIR study suggests the effectiveness of immune checkpoint inhibitors in melanoma is lower when more than 20% of infusions are in the late afternoon.

Modern aspects of immunotherapy with checkpoint inhibitors in melanoma

Although melanoma is one of the most immunogenic tumors, it has an ability to evade anti-tumor immune responses by exploiting tolerance mechanisms. The most extensively studied checkpoints represent cytotoxic T lymphocyte-associated protein‑4 (CTLA‑4) and programmed cell death protein‑1 (PD‑1). Immune checkpoint inhibitors (ICI), which were broadly applied for melanoma treatment in the past decade, can unleash anti-tumor immune responses and result in melanoma regression. Patients responding to the ICI treatment showed long-lasting remission or disease control status. However, a large group of patients failed to respond to this therapy, indicating the development of resistance mechanisms. Among them are intrinsic tumor properties, the dysfunction of effector cells, and the generation of immunosuppressive tumor microenvironment (TME). This review discusses achievements of ICI treatment in melanoma, reasons for its failure, and promising approaches for overcoming the resistance. These methods include combinations of different ICI with each other, strategies for neutralizing the immunosuppressive TME and combining ICI with other anti-cancer therapies such as radiation, oncolytic viral, or targeted therapy. New therapeutic approaches targeting other immune checkpoint molecules are also discussed.

Activated Eosinophils Predict Longer Progression-Free Survival under Immune Checkpoint Inhibition in Melanoma.

Immune checkpoint inhibition (ICI) has yielded remarkable results in prolonging survival of metastatic melanoma patients but only a subset of individuals treated respond to therapy. Success of ICI treatment appears to depend on the number of tumor-infiltrating effector T-cells, which are known to be influenced by activated eosinophils. To verify the co-occurrence of activated eosinophils and T-cells in melanoma, immunofluorescence was performed in 285 primary or metastatic tumor tissue specimens from 118 patients. Moreover, eosinophil counts and activity markers such as eosinophil cationic protein (ECP) and eosinophil peroxidase (EPX) were measured in the serum before therapy start and before the 4th infusion of ICI in 45 metastatic unresected melanoma patients. We observed a positive correlation between increased tumor-infiltrating eosinophils and T-cells associated with delayed melanoma progression. High baseline levels of eosinophil count, serum ECP and EPX were linked to prolonged progression-free survival in metastatic melanoma. Our data provide first indications that activated eosinophils are related to the T-cell-inflamed tumor microenvironment and could be considered as potential future prognostic biomarkers in melanoma.

Abstract 5251: GRIN2A mutations as potential positive predictor for response of immune checkpoint inhibitors in melanoma

Abstract Background: Melanoma is a serious skin cancer. Immune checkpoint inhibitors (ICIs) including atezolizumab, pembrolizumab, nivolumab, ipilimumab have shown durable responses and have been approved by FDA. However, ICIs demonstrate antitumor effects only in a fraction of patients, and research exploring the association between gene mutation and clinical benefit is limited. Studies have shown that Tumor Mutation Burden (TMB) was significantly (p &amp;lt; 0.001) associated with mutations in genes like GRIN2A in Non-Small Cell Lung Cancer (NSCLC), which means that the mutation of GRIN2A gene may be related to the efficacy of immunotherapy in patients with NSCLC, but the association between GRIN2A mutation and TMB or survival in melanoma is unknown. Methods: The association between GRIN2A mutation with TMB and survival data was analyzed in melanoma patients from the public immunotherapy-treated cohort called Miao2018.Pancancer.249.WES, which worked as training cohort while the validation cohort was retrieved from Melanoma.Allen2015.WES.110. Wilcoxon test was used for the comparison of TMB and Tumor Neoantigen Burden (TNB). Progress Free Survival (PFS):Overall survival (OS) analyses were conducted in the public cohort using Kaplan-Meier curves and log-rank tests. Statistical significance was set at p=0.05. Results: In the training cohort, 33.8% (51/151) melanoma patients harbored GRIN2A mutation. GRIN2A mutation is associated with higher TMB (p&amp;lt;0.001) and higher TNB (p&amp;lt;0.001). Survival analysis demonstrated that GRIN2A mutation resulted in significantly longer PFS (5.6 vs 3.3months; HR, 0.58; p=0.027) and longer OS (22.5 vs 12.8 months; HR, 0.61; p=0.039) in melanoma patients treated with ICIs. While validation cohort1 showed that 22.7% (25/110) melanoma patients harbored GRIN2A mutation and GRIN2A mutation resulted in an increasing trend on TMB with strongly significant difference (p&amp;lt;0.001) and significantly longer OS (22.5 vs 8.3months; HR, 0.53; p=0.025). Conclusions: This study shows that GRIN2A mutation is correlated with higher TMB and TNB in melanoma and serve as a predictive biomarker of ICI benefit in melanoma. Citation Format: Ling Ye, Dandan Fan, Yaoxu Chen, Mengli Huang. GRIN2A mutations as potential positive predictor for response of immune checkpoint inhibitors in melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5251.

Abstract LB516: MDM2/MDM4 amplification and CDKN2A deletion in melanoma brain metastases and GBM may have implications for targeted therapeutics and immunotherapy

Abstract Melanoma has a five-year survival rate of 27% for distant metastatic disease, and there remains a paucity of targeted therapies for metastatic disease and biomarkers that predict metastasis to specific sites. We analyzed 1081 primary melanoma samples and 358 metastatic melanoma samples and found that metastatic disease is enriched for amplifications in both MDM2 and MDM4 compared to primary disease, and these amplifications are associated with a lower probability of overall survival. Two additional negative regulators of TP53, namely USP7 and PPM1D, are enriched for alterations in metastatic melanoma compared to primary melanoma. MDM4 amplifications are associated with a higher rate of metastasis to the brain, liver, and lungs, while MDM2 amplifications are associated with a higher rate of metastasis to the brain, liver, and adrenal glands. These findings suggest that patients with metastatic melanoma show an enhanced dysregulation of the TP53 pathway compared to primary disease; though still under ongoing preclinical evaluation to assess therapeutic implications, we propose that patients with metastatic melanoma and TP53 wild-type status may be more likely to benefit from MDM2, MDM4, USP7, and PPM1D inhibitors, both alone and in combination, compared to those with primary disease. Additionally, we found that patients with MDM2 alterations were more likely to have a deep deletion in CDKN2A, alterations that are also associated with a higher rate of metastasis to the brain. We found that patients with a CDKN2A deep deletion had a statistically significant higher rate of alterations in TTN, MUC16, LRP1B, NF1, and SERPINB4, alterations that have all been previously associated with a favorable response to immune checkpoint inhibitors in melanoma. We therefore propose that CDKN2A deletion may serve as a biomarker to predict response to immunotherapy in melanoma. Moreover, given prior documented cases of patients diagnosed with both melanoma and glioblastoma multiforme (GBM), we found that GBM displays the highest rate of deep deletions in CDKN2A (54.39%) across all cancer types screened. We analyzed 619 GBM samples and found that 9.16% display an MDM2 amplification and 9.52% display an MDM4 amplification. Given the genomic similarities between melanoma and glioblastoma, we suggest that patients with melanoma or GBM and amplifications in MDM2/4 and CDKN2A deletions may need the development of combinations of targeted inhibitors of MDM2/4, CDK’s and immunotherapy. We are currently pursuing these translational directions. Citation Format: Taylor E. Arnoff, Wafik S. El-Deiry. MDM2/MDM4 amplification and CDKN2A deletion in melanoma brain metastases and GBM may have implications for targeted therapeutics and immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB516.

Sarcoid-like Granulomatosis Associated with Immune Checkpoint Inhibitors in Melanoma.

Simple SummaryGranulomatosis is commonly observed in patients receiving immune checkpoint inhibitors (ICIs) for melanoma and other cancers. Recognizing this reaction early is critical to avoid confusing it with cancer progression. Our objectives were to characterize instances of granulomatosis triggered by immunotherapy, to question their relationship with sarcoidosis, to explore their potential pathophysiological mechanisms and to address the possibility of an association between such events and response to immunotherapy. Our work is based on a retrospective study of 18 cases and on a thorough review of the literature of melanoma patients developing ICI-associated granulomatosis. After analyzing the clinical, histopathological and biological results, we propose that immuno-induced granulomatosis corresponds to an experimental sarcoidosis and should be considered as an ICI-associated effect rather than a severe immune-related event. Indeed, ICI-associated granulomatosis seems to be associated with a good ICI response and usually does not require ICI interruption or symptomatic treatment. We aimed to review the clinical and biological presentation of granulomatosis associated with immune-checkpoint inhibitors (ICI) in patients with melanoma and to explore its association with classical sarcoidosis as well as with cancer response to ICI. To this end, a retrospective study on 18 melanoma patients with histologically proven ICI-induced granulomatosis over a 12-year period in a single center, as well as on 67 similar cases reported in the literature, was conducted. Results indicate ICI-induced granulomatosis is an early side effect (median time to onset: 2 months). Its clinical presentation, with predominant (90%) thoracic involvement, histopathological appearance and supposed underlying biology (involving the mTOR pathway in immune cells, Th17 polarization and TReg dysfunction) are indistinguishable from those of sarcoidosis. Moreover, it appears to be associated with ICI benefit (>65% objective response rate). Evolution is generally favorable, and symptomatic steroid treatment and/or ICI discontinuation are rarely necessary. ICI-associated granulomatosis is critical to explore for several reasons. Practically, it is essential to differentiate it from cancer progression. Secondly, this “experimental” sarcoidosis brings new elements that may help to address sarcoidosis origin and pathophysiology. Its association with ICI efficacy must be confirmed on a larger scale but could have significant impacts on patient management and biomarker definition.