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Merkel cell carcinoma (MCC) is a highly aggressive skin cancer with an increasing incidence. The understanding of the molecular carcinogenesis of MCC is limited. Here, we scrutinized the PI3K/AKT pathway, one of the major pathways activated in human cancer, in MCC. Immunohistochemical analysis of 41 tumor tissues and 9 MCC cell lines revealed high levels of AKT phosphorylation at threonine 308 in 88% of samples. Notably, the AKT phosphorylation was not correlated with the presence or absence of the Merkel cell polyoma virus (MCV). Accordingly, knock-down of the large and small T antigen by shRNA in MCV positive MCC cells did not affect phosphorylation of AKT. We also analyzed 46 MCC samples for activating PIK3CA and AKT1 mutations. Oncogenic PIK3CA mutations were found in 2/46 (4%) MCCs whereas mutations in exon 4 of AKT1 were absent. MCC cell lines demonstrated a high sensitivity towards the PI3K inhibitor LY-294002. This finding together with our observation that the PI3K/AKT pathway is activated in the majority of human MCCs identifies PI3K/AKT as a potential new therapeutic target for MCC patients.
Antibody–drug conjugates (ADCs) are an emerging class of therapeutics, with twelve FDA- and EMA-approved drugs for hematological and solid cancers. Such drugs consist in a monoclonal antibody linked to a cytotoxic agent, allowing a specific cytotoxicity to tumor cells. In recent years, tremendous progress has been observed in therapeutic approaches for advanced skin cancer patients. In this regard, targeted therapies (e.g., kinase inhibitors) or immune checkpoint-blocking antibodies outperformed conventional chemotherapy, with proven benefit to survival. Nevertheless, primary and acquired resistances as well as adverse events remain limitations of these therapies. Therefore, ADCs appear as an emerging therapeutic option in oncodermatology. After providing an overview of ADC design and development, the goal of this article is to review the potential ADC indications in the field of oncodermatology.
HRAS belongs to the RAS genes superfamily. RAS genes are important players in several human tumors and the single-nucleotide polymorphism rs12628 has been shown to contribute to the risk of bladder, colon, gastrointestinal, oral, and thyroid carcinoma. We hypothesized that this SNP may affect the risk of cutaneous melanoma as well. HRAS gene contains a polymorphic region (rs112587690), a repeated hexanucleotide -GGGCCT- located in intron 1. Three alleles of this region, P1, P2, and P3, have been identified that contain two, three, and four repeats of the hexanucleotide, respectively. We investigated the clinical impact of these polymorphisms in a case–control study. A total of 141 melanoma patients and 118 healthy donors from the North America Caucasian population were screened for rs12628 and rs112587690 polymorphisms. Genotypes were assessed by capillary sequencing or fragment analysis, respectively, and rs12628 CC and rs112587690 P1P1 genotypes significantly associated with increased melanoma risk (OR = 3.83, p = 0.003; OR = 11.3, p = 0.033, respectively), while rs112587690 P1P3 frequency resulted significantly higher in the control group (OR = 0.5, p = 0.017). These results suggest that rs12628 C homozygosis may be considered a potential risk factor for melanoma development in the North American population possibly through the linkage to rs112587690.
Background: Eosinophils appear to contribute to the efficacy of immunotherapy and their frequency was suggested as a predictive biomarker. Whether this observation could be transferred to patients treated with targeted therapy remains unknown. Methods: Blood and serum samples of healthy controls and 216 patients with advanced melanoma were prospectively and retrospectively collected. Freshly isolated eosinophils were phenotypically characterized by flow cytometry and co-cultured in vitro with melanoma cells to assess cytotoxicity. Soluble serum markers and peripheral blood counts were used for correlative studies. Results: Eosinophil-mediated cytotoxicity towards melanoma cells, as well as phenotypic characteristics, were similar when comparing healthy donors and patients. However, high relative pre-treatment eosinophil counts were significantly associated with response to MAPKi (p = 0.013). Eosinophil-mediated cytotoxicity towards melanoma cells is dose-dependent and requires proximity of eosinophils and their target in vitro. Treatment with targeted therapy in the presence of eosinophils results in an additive tumoricidal effect. Additionally, melanoma cells affected eosinophil phenotype upon co-culture. Conclusion: High pre-treatment eosinophil counts in advanced melanoma patients were associated with a significantly improved response to MAPKi. Functionally, eosinophils show potent cytotoxicity towards melanoma cells, which can be reinforced by MAPKi. Further studies are needed to unravel the molecular mechanisms of our observations.
Approximately half of all melanoma patients harbour activating mutations in the serine/threonine kinase BRAF. This is the basis for one of the main treatment strategies for this tumor type, the targeted therapy with BRAF and MEK inhibitors. While the initial responsiveness to these drugs is high, resistance develops after several months, frequently at sites of the previously responding tumor. This indicates that tumor response is incomplete and that a certain tumor fraction survives even in drug-sensitive patients, e.g., in a therapy-induced senescence-like state. Here, we show in several melanoma cell lines that BRAF inhibition induces a secretome with stimulating effect on fibroblasts and naive melanoma cells. Several senescence-associated factors were found to be transcribed and secreted in response to BRAF or MEK inhibition, among them members of the fibroblast growth factor family. We identified the growth factor FGF1 as mediator of resilience towards BRAF inhibition, which limits the pro-apoptotic effects of the drug and activates fibroblasts to secrete HGF. FGF1 regulation was mediated by the PI3K pathway and by FRA1, a direct target gene of the MAPK pathway. When FGFR inhibitors were applied in parallel to BRAF inhibitors, resilience was broken, thus providing a rationale for combined therapeutical application.
Cellular and cytokine-dependent immunosuppressive mechanisms of grm1-transgenic murine melanoma
(2012)
Grm1-transgenic mice spontaneously develop cutaneous melanoma. This model allowed us to scrutinize the generic immune responses over the course of melanoma development. To this end, lymphocytes obtained from spleens, unrelated lymph nodes and tumor-draining lymph nodes of mice with no evidence of disease, and low or high tumor burden were analyzed ex vivo and in vitro. Thereby, we could demonstrate an increase in the number of activated CD4\(^+\) and CD8+ lymphocytes in the respective organs with increasing tumor burden. However, mainly CD4\(^+\) T cells, which could constitute both T helper as well as immunosuppressive regulatory T cells, but not CD8\(^+\) T cells, expressed activation markers upon in vitro stimulation when obtained from tumor-bearing mice. Interestingly, these cells from tumor-burdened animals were also functionally hampered in their proliferative response even when subjected to strong in vitro stimulation. Further analyses revealed that the increased frequency of regulatory T cells in tumor-bearing mice is an early event present in all lymphoid organs. Additionally, expression of the immunosuppressive cytokines TGF-β1 and IL-10 became more evident with increased tumor burden. Notably, TGF-β1 is strongly expressed in both the tumor and the tumor-draining lymph node, whereas IL-10 expression is more pronounced in the lymph node, suggesting a more complex regulation of IL-10. Thus, similar to the situation in melanoma patients, both cytokines as well as cellular immune escape mechanisms seem to contribute to the observed immunosuppressed state of tumor-bearing grm1-transgenic mice, suggesting that this model is suitable for preclinical testing of immunomodulatory therapeutics.
Fish of the genus Xiphophorus belong to the oldest animal models in cancer research. The oncogene responsible for the generation of spontaneous aggressive melanoma encodes for a mutated epidermal growth factor receptor (Egfr) and is called xmrk for Xiphophorus melanoma receptor kinase. Xmrk constitutive activation mechanisms and subsequent signaling pathways have already been investigated and charaterized but it is still unknown if Egfr ligands may also play a role in Xmrk-driven melanoma formation. To investigate the potential role of Egfr ligands in Xmrk-driven melanoma, I firstly analyzed the evolution of teleost and tetrapod Egfr/Egfr ligand systems. I especially focused on the analysis on the medaka fish, a closely related species to Xiphophorus, for which the whole genome has been sequenced. I could identify all seven Egfr ligands in medaka and could show that the two teleost-specific Egfr copies of medaka display dissimilar expression patterns in adult tissues together with differential expression of Egfr ligand subsets, arguing for subfunctionalization of receptor functions in this fish. Our phylogenetic and synteny analyses supported the hypothesis that only one gene in the chordate ancestor gave rise to the diversity of Egfr ligands found in vertebrate genomes today. I also could show that the Egfr extracellular subdomains implicated in ligand binding are not evolutionary conserved between tetrapods and teleosts, making the use of heterologous ligands in experiments with fish cells debatable. Despite its well understood and straight-forward process, Xmrk-driven melanomagenesis in Xiphophorus is problematic to further investigate in vivo. Our laboratory recently established a new melanoma animal model by generating transgenic mitf::xmrk medaka fishes, a Xiphophorus closely related species offering many more advantages. These fishes express xmrk under the control of the pigment-cell specific Mitf promoter. During my PhD thesis, I participated in the molecular analysis of the stably transgenic medaka and could show that the Xmrk-induced signaling pathways are similar when comparing Xiphophorus with transgenic mitf::xmrk medaka. These data together with additional RNA expression, protein, and histology analyses showed that Xmrk expression under the control of a pigment cell-specific promoter is sufficient to induce melanoma in the transgenic medaka, which develop very stereotyped tumors, including uveal and extracutaneous melanoma, with early onset during larval stages. To further investigate the potential role of Egfr ligands in Xmrk-driven melanoma, I made use of two model systems. One of them was the above mentioned mitf::xmrk medaka, the other was an in-vitro cell culture system, where the EGF-inducible Xmrk chimera HERmrk is stably expressed in murine melanocytes. Here I could show that HERmrk activation strongly induced expression of amphiregulin (Areg) and heparin-binding EGF-like growth factor (Hbegf) in melanocytes. This regulation was dependent on the MAPK and SRC signaling pathways. Moreover, upregulation of Adam10 and Adam17, the two major sheddases of Egfr ligands, was observed. I also could demonstrate the functionality of the growth factors by invitro analyses. Using the mitf::xmrk medaka model I could also show the upregulation of a subset of ligand genes, namely egf, areg, betacellulin (btc) and epigen (epgn) as well as upregulation of medaka egfrb in tumors from fish with metastatic melanoma. All these results converge to support an Xmrk-induced autocrine Egfr ligand loop. Interestingly, my in-vitro experiments with conditioned supernatant from medaka Egf- and Hbegf-producing cells revealed that not only Xiphophorus Egfrb, but also the pre-activated Xmrk could be further stimulated by the ligands. Altogether, I could show with in-vitro and in-vivo experiments that Xmrk is capable of inducing a functional autocrine Egfr ligand loop. These data confirm the importance of autocrine loops in receptor tyrosine kinase (RTK)-dependent cancer development and show the possibility for a constitutively active RTK to strengthen its oncogenic signaling by ligand binding.
Background
Several recent publications have demonstrated the use of convolutional neural networks to classify images of melanoma at par with board-certified dermatologists. However, the non-availability of a public human benchmark restricts the comparability of the performance of these algorithms and thereby the technical progress in this field.
Methods
An electronic questionnaire was sent to dermatologists at 12 German university hospitals. Each questionnaire comprised 100 dermoscopic and 100 clinical images (80 nevi images and 20 biopsy-verified melanoma images, each), all open-source. The questionnaire recorded factors such as the years of experience in dermatology, performed skin checks, age, sex and the rank within the university hospital or the status as resident physician. For each image, the dermatologists were asked to provide a management decision (treat/biopsy lesion or reassure the patient). Main outcome measures were sensitivity, specificity and the receiver operating characteristics (ROC).
Results
Total 157 dermatologists assessed all 100 dermoscopic images with an overall sensitivity of 74.1%, specificity of 60.0% and an ROC of 0.67 (range = 0.538–0.769); 145 dermatologists assessed all 100 clinical images with an overall sensitivity of 89.4%, specificity of 64.4% and an ROC of 0.769 (range = 0.613–0.9). Results between test-sets were significantly different (P < 0.05) confirming the need for a standardised benchmark.
Conclusions
We present the first public melanoma classification benchmark for both non-dermoscopic and dermoscopic images for comparing artificial intelligence algorithms with diagnostic performance of 145 or 157 dermatologists. Melanoma Classification Benchmark should be considered as a reference standard for white-skinned Western populations in the field of binary algorithmic melanoma classification.
Bioprinting offers the opportunity to fabricate precise 3D tumor models to study tumor pathophysiology and progression. However, the choice of the bioink used is important. In this study, cell behavior was studied in three mechanically and biologically different hydrogels (alginate, alginate dialdehyde crosslinked with gelatin (ADA–GEL), and thiol-modified hyaluronan (HA-SH crosslinked with PEGDA)) with cells from breast cancer (MDA-MB-231 and MCF-7) and melanoma (Mel Im and MV3), by analyzing survival, growth, and the amount of metabolically active, living cells via WST-8 labeling. Material characteristics were analyzed by dynamic mechanical analysis. Cell lines revealed significantly increased cell numbers in low-percentage alginate and HA-SH from day 1 to 14, while only Mel Im also revealed an increase in ADA–GEL. MCF-7 showed a preference for 1% alginate. Melanoma cells tended to proliferate better in ADA–GEL and HA-SH than mammary carcinoma cells. In 1% alginate, breast cancer cells showed equally good proliferation compared to melanoma cell lines. A smaller area was colonized in high-percentage alginate-based hydrogels. Moreover, 3% alginate was the stiffest material, and 2.5% ADA–GEL was the softest material. The other hydrogels were in the same range in between. Therefore, cellular responses were not only stiffness-dependent. With 1% alginate and HA-SH, we identified matrices that enable proliferation of all tested tumor cell lines while maintaining expected tumor heterogeneity. By adapting hydrogels, differences could be accentuated. This opens up the possibility of understanding and analyzing tumor heterogeneity by biofabrication.
Background
Melanoma is the most dangerous type of skin cancer but is curable if detected early. Recent publications demonstrated that artificial intelligence is capable in classifying images of benign nevi and melanoma with dermatologist-level precision. However, a statistically significant improvement compared with dermatologist classification has not been reported to date.
Methods
For this comparative study, 4204 biopsy-proven images of melanoma and nevi (1:1) were used for the training of a convolutional neural network (CNN). New techniques of deep learning were integrated. For the experiment, an additional 804 biopsy-proven dermoscopic images of melanoma and nevi (1:1) were randomly presented to dermatologists of nine German university hospitals, who evaluated the quality of each image and stated their recommended treatment (19,296 recommendations in total). Three McNemar's tests comparing the results of the CNN's test runs in terms of sensitivity, specificity and overall correctness were predefined as the main outcomes.
Findings
The respective sensitivity and specificity of lesion classification by the dermatologists were 67.2% (95% confidence interval [CI]: 62.6%–71.7%) and 62.2% (95% CI: 57.6%–66.9%). In comparison, the trained CNN achieved a higher sensitivity of 82.3% (95% CI: 78.3%–85.7%) and a higher specificity of 77.9% (95% CI: 73.8%–81.8%). The three McNemar's tests in 2 × 2 tables all reached a significance level of p < 0.001. This significance level was sustained for both subgroups.
Interpretation
For the first time, automated dermoscopic melanoma image classification was shown to be significantly superior to both junior and board-certified dermatologists (p < 0.001).