Enhanced Apoptosis and Loss of Cell Viability in Melanoma Cells by Combined Inhibition of ERK and Mcl-1 Is Related to Loss of Mitochondrial Membrane Potential, Caspase Activation and Upregulation of Proapoptotic Bcl-2 Proteins

Targeting of MAP kinase pathways by BRAF inhibitors has evolved as a key therapy for BRAF-mutated melanoma. However, it cannot be applied for BRAF-WT melanoma, and also, in BRAF-mutated melanoma, tumor relapse often follows after an initial phase of tumor regression. Inhibition of MAP kinase pathways downstream at ERK1/2, or inhibitors of antiapoptotic Bcl-2 proteins, such as Mcl-1, may serve as alternative strategies. As shown here, the BRAF inhibitor vemurafenib and the ERK inhibitor SCH772984 showed only limited efficacy in melanoma cell lines, when applied alone. However, in combination with the Mcl-1 inhibitor S63845, the effects of vemurafenib were strongly enhanced in BRAF-mutated cell lines, and the effects of SCH772984 were enhanced in both BRAF-mutated and BRAF-WT cells. This resulted in up to 90% loss of cell viability and cell proliferation, as well as in induction of apoptosis in up to 60% of cells. The combination of SCH772984/S63845 resulted in caspase activation, processing of poly (ADP-ribose) polymerase (PARP), phosphorylation of histone H2AX, loss of mitochondrial membrane potential, and cytochrome c release. Proving the critical role of caspases, a pan-caspase inhibitor suppressed apoptosis induction, as well as loss of cell viability. As concerning Bcl-2 family proteins, SCH772984 enhanced expression of the proapoptotic Bim and Puma, as well as decreased phosphorylation of Bad. The combination finally resulted in downregulation of antiapoptotic Bcl-2 and enhanced expression of the proapoptotic Noxa. In conclusion, combined inhibition of ERK and Mcl-1 revealed an impressive efficacy both in BRAF-mutated and WT melanoma cells, and may thus represent a new strategy for overcoming drug resistance

Patients' and dermatologists' preferences in artificial intelligence–driven skin cancer diagnostics: a prospective multicentric survey study

To the Editor: Artificial intelligence (AI) has shown promise for improving diagnostics of skin cancer by matching or surpassing experienced clinicians.1 However, the successful clinical application depends on acceptance by patients and dermatologists. In this prospective multicentric survey study with a response rate of 63%, we therefore investigate the criteria required for patients and dermatologists to accept AI-systems and assess their importance on patients’ and dermatologists’ decision-making when considering the use of such systems. To this end, we perform an adaptive choice-based conjoint analysis and analyze it using hierarchical Bayes estimation.2 By employing an adaptive choice-based conjoint analysis, we investigate multiple influencing AI-features simultaneously (see Table I) whilst accounting for possible trade-offs (see Fig 1). For details on questionnaire development, participant recruitment, and statistical analysis, see Supplementary Methods, available via Mendeley at https://data.mendeley.com/datasets/2chcwnhpwj/1

Effective Targeting of Melanoma Cells by Combination of Mcl-1 and Bcl-2/Bcl-x_L/Bcl-w Inhibitors

Recent advances in melanoma therapy have significantly improved the prognosis of metastasized melanoma. However, large therapeutic gaps remain that need to be closed by new strategies. Antiapoptotic Bcl-2 proteins critically contribute to apoptosis deficiency and therapy resistance. They can be targeted by BH3 mimetics, small molecule antagonists that mimic the Bcl-2 homology domain 3 (BH3) of proapoptotic BH3-only proteins. By applying in vitro experiments, we aimed to obtain an overview of the possible suitability of BH3 mimetics for future melanoma therapy. Thus, we investigated the effects of ABT-737 and ABT-263, which target Bcl-2, Bcl-xL and Bcl-w as well as the Bcl-2-selective ABT-199 and the Mcl-1-selective S63845, in a panel of four BRAF-mutated and BRAF-WT melanoma cell lines. None of the inhibitors showed significant effectiveness when used alone; however, combination of S63845 with each one of the three ABTs almost completely abolished melanoma cell survival and induced apoptosis in up to 50–90% of the cells. Special emphasis was placed here on the understanding of the downstream pathways involved, which may allow improved applications of these strategies. Thus, cell death induction was correlated with caspase activation, loss of mitochondrial membrane potential, phosphorylation of histone H2AX, and ROS production. Caspase dependency was demonstrated by a caspase inhibitor, which blocked all effects. Upregulation of Mcl-1, induced by S63845 itself, as reported previously, was blocked by the combinations. Indeed, Mcl-1, as well as XIAP (X-linked inhibitor of apoptosis), were strongly downregulated by combination treatments. These findings demonstrate that melanoma cells can be efficiently targeted by BH3 mimetics, but the right combinations have to be selected. The observed pronounced activation of apoptosis pathways demonstrates the decisive role of apoptosis in the loss of cell viability by BH3 mimetics

Cytokine release syndrome

During the last decade the field of cancer immunotherapy has witnessed impressive progress. Highly effective immunotherapies such as immune checkpoint inhibition, and T-cell engaging therapies like bispecific T-cell engaging (BiTE) single-chain antibody constructs and chimeric antigen receptor (CAR) T cells have shown remarkable efficacy in clinical trials and some of these agents have already received regulatory approval. However, along with growing experience in the clinical application of these potent immunotherapeutic agents comes the increasing awareness of their inherent and potentially fatal adverse effects, most notably the cytokine release syndrome (CRS). This review provides a comprehensive overview of the mechanisms underlying CRS pathophysiology, risk factors, clinical presentation, differential diagnoses, and prognostic factors. In addition, based on the current evidence we give practical guidance to the management of the cytokine release syndrome

Treatment monitoring of immunotherapy and targeted therapy using FET PET in patients with melanoma and lung cancer brain metastases: Initial experiences.

Background: Due to the lack of specificity of contrast-enhanced (CE) MRI, the differentiation of progression from pseudoprogression (PsP) following immunotherapy using checkpoint inhibitors (IT) or targeted therapy (TT) may be challenging, especially when IT or TT is applied in combination with radiotherapy (RT). Similarly, for response assessment of RT plus IT or targeted therapy (TT), the use of CE MRI alone may also be difficult. For problem solving, the integration of advanced imaging methods may add valuable information. Here, we evaluated the value of amino acid PET using O-(2-[18F]fluoroethyl)-L-tyrosine (FET) in comparison to CE MRI for these important clinical situations in patients with brain metastases (BM) secondary to malignant melanoma (MM) and non-small cell lung cancer (NSCLC). Methods: From 2015-2018, we retrospectively identified 31 patients with 74 BM secondary to MM (n = 20 with 42 BM) and NSCLC (n = 11 with 32 BM) who underwent 52 FET PET scans during the course of disease. All patients had RT prior to IT or TT initiation (61%) or RT concurrent to IT or TT (39%). In 13 patients, FET PET was performed for treatment response assessment of IT or TT using baseline and follow-up scans (median time between scans, 4.2 months). In the remaining 18 patients, FET PET was used for the differentiation of progression from PsP related to RT plus IT or TT. In all BM, metabolic activity on FET PET was evaluated by calculation of tumor/brain ratios. FET PET imaging findings were compared to CE MRI and correlated to the clinical follow-up or neuropathological findings after neuroimaging. Results: In 4 of 13 patients (31%), FET PET provided additional information for treatment response evaluation beyond the information provided by CE MRI alone. Furthermore, responding patients on FET PET had a median stable clinical follow-up of 10 months. In 10 of 18 patients (56%) with CE MRI findings suggesting progression, FET PET detected PsP. In 9 of these 10 patients, PsP was confirmed by a median stable clinical follow-up of 11 months. Conclusions: FET PET may add valuable information for treatment monitoring in individual BM patients undergoing RT in combination with IT or TT

Ipilimumab alone or in combination with nivolumab after progression on anti-PD-1 therapy in advanced melanoma

BACKGROUND: The anti-programmed cell death-1 (PD-1) inhibitors pembrolizumab and nivolumab alone or in combination with ipilimumab have shown improved objective response rates and progression-free survival compared to ipilimumab only in advanced melanoma patients. Anti-PD-1 therapy demonstrated nearly equal clinical efficacy in patients who had progressed after ipilimumab or were treatment-naïve. However, only limited evidence exists regarding the efficacy of ipilimumab alone or in combination with nivolumab after treatment failure to anti-PD-therapy. PATIENTS AND METHODS: A multicenter retrospective study in advanced melanoma patients who were treated with nivolumab (1 or 3 mg/kg) and ipilimumab (1 mg or 3 mg/kg) or ipilimumab (3 mg/kg) alone after treatment failure to anti-PD-1 therapy was performed. Patient, tumour, pre- and post-treatment characteristics were analysed. RESULTS: In total, 47 patients were treated with ipilimumab (ipi-group) and 37 patients with ipilimumab and nivolumab (combination-group) after treatment failure to anti-PD-1 therapy. Overall response rates for the ipi- and the combination-group were 16% and 21%, respectively. Disease control rate was 42% for the ipi-group and 33% for the combination-group. One-year overall survival rates for the ipi- and the combination-group were 54% and 55%, respectively. CONCLUSIONS: Ipilimumab should be considered as a viable treatment option for patients with failure to prior anti-PD-1 therapy, including those with progressive disease as best response to prior anti-PD-1. In contrast, the combination of ipilimumab and nivolumab appears significantly less effective in this setting compared to treatment-naïve patients

Robustness of convolutional neural networks in recognition of pigmented skin lesions

Background: A basic requirement for artificial intelligence (AI)-based image analysis systems, which are to be integrated into clinical practice, is a high robustness. Minor changes in how those images are acquired, for example, during routine skin cancer screening, should not change the diagnosis of such assistance systems. Objective: To quantify to what extent minor image perturbations affect the convolutional neural network (CNN)-mediated skin lesion classification and to evaluate three possible solutions for this problem (additional data augmentation, test-time augmentation, anti-aliasing). Methods: We trained three commonly used CNN architectures to differentiate between dermoscopic melanoma and nevus images. Subsequently, their performance and susceptibility to minor changes ('brittleness') was tested on two distinct test sets with multiple images per lesion. For the first set, image changes, such as rotations or zooms, were generated artificially. The second set contained natural changes that stemmed from multiple photographs taken of the same lesions. Results: All architectures exhibited brittleness on the artificial and natural test set. The three reviewed methods were able to decrease brittleness to varying degrees while still maintaining performance. The observed improvement was greater for the artificial than for the natural test set, where enhancements were minor. Conclusions: Minor image changes, relatively inconspicuous for humans, can have an effect on the robustness of CNNs differentiating skin lesions. By the methods tested here, this effect can be reduced, but not fully eliminated. Thus, further research to sustain the performance of AI classifiers is needed to facilitate the translation of such systems into the clinic. (C) 2020 The Author(s). Published by Elsevier Ltd