Increased expression and signalling of WNT5A and interleukin-6 (IL-6) have both been shown to promote melanoma progression. Here, we investigated the proposed existence of a WNT5A-IL-6 positive feedback loop that drives melanoma migration and invasion. First, the HOPP algorithm revealed that the invasive phenotype of cultured melanoma cells was significantly correlated with increased expression of WNT5A or IL-6. In three invasive melanoma cell lines, endogenous WNT5A protein expression was related to IL-6 protein secretion. Knockdown with anti-IL-6 siRNAs or treating WM852 melanoma cells with a neutralising anti-IL-6 antibody reduced WNT5A protein expression. Conversely, the silencing of WNT5A expression by WNT5A siRNAs or treating WM852 melanoma cells with Box5 (a WNT5A antagonist) significantly reduced IL-6 secretion. Interestingly, these effects occurred at the protein level but not at the transcriptional levels. Functionally, we demonstrated that combined siRNA knockdown of WNT5A and IL-6 expression or the simultaneous inhibition of WNT5A and IL-6 signalling inhibited melanoma cell invasion more effectively than suppressing each factor individually. Together, our results demonstrate that WNT5A and IL-6 are connected through a positive feedback loop in melanoma cells and that the combined targeting of both molecules could serve as an effective therapeutic means to reduce melanoma metastasis.

Abstract. Community detection algorithms are widely used to study the structural properties of real-world networks. In this paper, we experimentally evaluate the qualitative performance of several community detection algorithms using large-scale email networks. The email networks were generated from real email traffic and contain both legitimate email (ham) and unsolicited email (spam). We compare the quality of the algorithms with respect to a number of structural quality functions and a logical quality measure which assesses the ability of the algorithms to separate ham and spam emails by clustering them into distinct communities. Our study reveals that the algorithms that perform well with respect to structural quality, don't achieve high logical quality. We also show that the algorithms with similar structural quality also have similar logical quality regardless of their approach to clustering. Finally, we reveal that the algorithm that performs link community detection is more suitable for clustering email networks than the node-based approaches, and it creates more distinct communities of ham and spam edges.

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Abstract-One of the widely studied structural properties of social and information networks is their community structure, and a vast variety of community detection algorithms have been proposed in the literature. Expansion of a seed node into a community is one of the most successful methods for local community detection, especially when the global structure of the network is not accessible. An algorithm for local community detection only requires a partial knowledge of the network and the computations can be done in parallel starting from seed nodes. The parallel nature of local algorithms allow for fast and scalable solutions, however, the coverage of the communities heavily depends on the seed selection. The communities identified by a local algorithm might cover only a subset of the nodes in a network if the seeds are not selected carefully.In this paper, we propose a novel seeding algorithm which is parameter free, utilizes merely the local structure of the network, and identifies good seeds which span over the whole network. In order to find such seeds, our algorithm first computes similarity indices from local link prediction techniques to assign a similarity score to each node, and then a biased graph coloring algorithm is used to enhance the seed selection. Our experiments using large-scale real-world networks show that our algorithm is able to select good seeds which are then expanded into high quality overlapping communities covering the vast majority of the nodes in the network using a personalized PageRank-based community detection algorithm. We also show that using our local seeding algorithm can dramatically reduce the execution time of community detection.

Overexpression of wingless-type MMTV integration site family 5A (WNT5A) plays a significant role in melanoma cancer progression; however, the mechanism(s) involved remains unknown. In breast cancer, the human antigen R (HuR) has been implicated in the regulation of WNT5A expression. Here, we demonstrate that endogenous expression of WNT5A correlates with levels of active HuR in HTB63 and WM852 melanoma cells and that HuR binds to WNT5A messenger RNA in both cell lines. Although the HuR inhibitor MS-444 significantly impaired migration in both melanoma cell lines, it reduced WNT5A expression only in HTB63 cells, as did small interfering RNA knockdown of HuR. Consistent with this finding, MS-444-induced inhibition of HTB63 cell migration was restored by the addition of recombinant WNT5A, whereas MS-444-induced inhibition of WM852 cell migration was restored by the addition of recombinant matrix metalloproteinase-9, another HuR-regulated protein. Clearly, HuR positively regulates melanoma cell migration via at least 2 distinct mechanisms making HuR an attractive therapeutic target for halting melanoma dissemination.

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Table of contentsMELANOMA BRIDGE 2015KEYNOTE SPEAKER PRESENTATIONSMolecular and immuno-advancesK1 Immunologic and metabolic consequences of PI3K/AKT/mTOR activation in melanomaVashisht G. Y. Nanda, Weiyi Peng, Patrick Hwu, Michael A. DaviesK2 Non-mutational adaptive changes in melanoma cells exposed to BRAF and MEK inhibitors help the establishment of drug resistanceGennaro Ciliberto, Luigi Fattore, Debora Malpicci, Luigi Aurisicchio, Paolo Antonio Ascierto, Carlo M. Croce, Rita ManciniK3 Tumor-intrinsic beta-catenin signaling mediates tumor-immune avoidanceStefani Spranger, Thomas F. GajewskiK4 Intracellular tumor antigens as a source of targets of antibody-based immunotherapy of melanomaYangyang Wang, Soldano FerroneCombination therapiesK5 Harnessing radiotherapy to improve responses to immunotherapy in cancerClaire Vanpouille-Box, Erik Wennerberg, Karsten A. Pilones, Silvia C. Formenti, Sandra DemariaK6 Creating a T cell-inflamed tumor microenvironment overcomes resistance to checkpoint blockadeHaidong Tang, Yang Wang, Yang-Xin FuK7 Biomarkers for treatment decisions?Reinhard DummerK8 Combining oncolytic therapies in the era of checkpoint inhibitorsIgor PuzanovK9 Immune checkpoint blockade for melanoma: should we combine or sequence ipilimumab and PD-1 antibody therapy?Michael A. PostowNews in immunotherapyK10 An update on adjuvant and neoadjuvant therapy for melanomAhmad TarhiniK11 Targeting multiple inhibitory receptors in melanomaJoe-Marc Chauvin, Ornella Pagliano, Julien Fourcade, Zhaojun Sun, Hong Wang, Cindy Sanders, John M. Kirkwood, Tseng-hui Timothy Chen, Mark Maurer, Alan J. Korman, Hassane M. ZarourK12 Improving adoptive immune therapy using genetically engineered T cellsDavid F. StroncekTumor microenvironment and biomarkersK13 Myeloid cells and tumor exosomes: a crosstalk for assessing immunosuppression?Veronica Huber, Licia RivoltiniK14 Update on the SITC biomarker taskforce: progress and challengesMagdalena ThurinWorld-wide immunoscore task force: an updateK15 The immunoscore in colorectal cancer highlights the importance of digital scoring systems in surgical pathologyTilman Rau, Alessandro LugliK16 The immunoscore: toward an integrated immunomonitoring from the diagnosis to the follow up of cancer’s patientsFranck PagèsEconomic sustainability of melanoma treatments: regulatory, health technology assessment and market access issuesK17 Nivolumab, the regulatory experience in immunotherapyJorge Camarero, Arantxa SanchoK18 Evidence to optimize access for immunotherapiesClaudio JommiORAL PRESENTATIONSMolecular and immuno-advancesO1 Ipilimumab treatment results in CD4 T cell activation that is concomitant with a reduction in Tregs and MDSCsYago Pico de Coaña, Maria Wolodarski, Yuya Yoshimoto, Giusy Gentilcore, Isabel Poschke, Giuseppe V. Masucci, Johan Hansson, Rolf KiesslingO2 Evaluation of prognostic and therapeutic potential of COX-2 and PD-L1 in primary and metastatic melanomaGiosuè Scognamiglio, Francesco Sabbatino, Federica Zito Marino, Anna Maria Anniciello, Monica Cantile, Margherita Cerrone,...

Identifying unsolicited email based on their network-level behavior rather than their content have received huge interest. In this study, we investigate the social network properties of large-scale email networks generated from real email traffic to reveal the properties that are indicative of spam as opposed to the expected legitimate behavior.By analyzing the structural and temporal properties of the email networks we confirm that legitimate email traffic generates a small-world, scale-free network similar to other social networks. However, email traffic as a whole contains unsolicited email, thus the structure of email networks deviates from that of social networks. Our study points out the distinctive characteristics of spam traffic and reveals that the anomalies in the structural properties of email networks are due to the unsocial behavior of spam.