WIPI1, BAG1 and PEX3 autophagy-related genes are relevant melanoma markers

ROS and oxidative stress may promote autophagy; on the other hand, autophagy may help reduce oxidative damages. According to the known interplay of ROS, autophagy, and melanoma onset, we hypothesized that autophagy-related genes (ARGs) may represent useful melanoma biomarkers. We therefore analyzed the gene and protein expression of 222 ARGs in human melanoma samples, from 5 independent expression databases (overall 572 patients). Gene expression was first evaluated in the GEO database. Forty-two genes showed extremely high ability to discriminate melanoma from nevi (63 samples) according to ROC (AUC ≥ 0.85) and Mann-Whitney (p < 0.0001) analyses. The 9 genes never related to melanoma before were then in silico validated in the IST online database. BAG1, CHMP2B, PEX3, and WIPI1 confirmed a strong differential gene expression, in 355 samples. A second-round validation performed on the Human Protein Atlas database showed strong differential protein expression for BAG1, PEX3, and WIPI1 in melanoma vs control samples, according to the image analysis of 80 human histological sections. WIPI1 gene expression also showed a significant prognostic value (p < 0.0001) according to 102 melanoma patients' survival data. We finally addressed in Oncomine database whether WIPI1 overexpression is melanoma-specific. Within more than 20 cancer types, the most relevant WIPI1 expression change (p = 0.00002; fold change = 3.1) was observed in melanoma. Molecular/functional relationships of the investigated molecules with melanoma and their molecular/functional network were analyzed via Chilibot software, STRING analysis, and gene ontology enrichment analysis. We conclude that WIPI1 (AUC = 0.99), BAG1 (AUC = 1), and PEX3 (AUC = 0.93) are relevant novel melanoma markers at both gene and protein levels

Ion channel expression in human melanoma samples. in silico identification and experimental validation of molecular targets

Expression of 328 ion channel genes was investigated, by in silico analysis, in 170 human melanoma samples and controls. Ninety-one members of this gene-family (i.e., about 28%) show a significant (p 0.90 and p 90% in most cases). Such five genes (namely, SCNN1A, GJB3, KCNK7, GJB1, KCNN2) are novel potential melanoma markers or molecular targets, never previously related to melanoma. The “druggable genome” analysis was then carried out. Miconazole, an antifungal drug commonly used in clinics, is known to target KCNN2, the best candidate among the five identified genes. Miconazole was then tested in vitro in proliferation assays; it dose-dependently inhibited proliferation up to 90% and potently induced cell-death in A-375 and SKMEL-28 melanoma cells, while it showed no effect in control cells. Moreover, specific silencing of KCNN2 ion channel was achieved by siRNA transfection; under such condition miconazole strongly increases its anti-proliferative effect. In conclusion, the present study identified five ion channels that can potentially serve as sensitive and specific markers in human melanoma specimens and demonstrates that the antifungal drug miconazole, known to target one of the five identified ion channels, exerts strong and specific anti-melanoma effects in vitro

c-Flip KO fibroblasts display lipid accumulation associated with endoplasmic reticulum stress

c-Flip proteins are well-known apoptosis modulators. They generally contribute to tissue homeostasis maintenance by inhibiting death-receptor-mediated cell death. In the present manuscript, we showthat c-Flip knock-out (KO) mouse embryonic fibroblasts (MEFs) kept in culture under starvation conditions gradually modify their phenotype and accumulate vacuoles, becoming progressively larger according to the duration of starvation. Large vacuoles are present in KO MEFs though not in WT MEFs, and are Oil Red-O positive, which indicates that they represent lipid droplets. Western blot experiments reveal that, unlikeWTMEFs, KOMEFs express high levels of the lipogenic transcription factor PPAR-γ. Lipid droplet accumulation was found to be associated with endoplasmic reticulum (ER) stress activation and autophagic modulation valuated by means of BIP increase, LC3 lipidation and AMP-activated protein kinase (AMPK) phosphorylation, and p62 accumulation. Interestingly, XBP-1, an ER stress-induced lipogenic transcription factor, was found to preferentially localize in the nucleus rather than in the cytoplasm of KO MEFs. These data demonstrate that, upon starvation, c-Flip affects lipid accumulation, ER stress and autophagy, thereby pointing to an important role of c-Flip in the adaptive response and ER stress response programs under both normal and pathological conditions

Lipid storage and autophagy in melanoma cancer cells

Cancer stem cells (CSC) represent a key cellular subpopulation controlling biological features such as cancer progression in all cancer types. By using melanospheres established from human melanoma patients, we compared less differentiated melanosphere-derived CSC to differentiating melanosphere-derived cells. Increased lipid uptake was found in melanosphere-derived CSC vs. differentiating melanosphere-derived cells, paralleled by strong expression of lipogenic factors Sterol Regulatory Element-Binding Protein-1 (SREBP-1) and Peroxisome Proliferator-Activated Receptor-γ (PPAR-γ). An inverse relation between lipid-storing phenotype and autophagy was also found, since microtubule-associated protein 1A/1B-Light Chain 3 (LC3) lipidation is reduced in melanosphere-derived CSC. To investigate upstream autophagy regulators, Phospho-AMP activated Protein Kinase (P-AMPK) and Phospho-mammalian Target of Rapamycin (P-mTOR) were analyzed; lower P-AMPK and higher P-mTOR expression in melanosphere-derived CSC were found, thus explaining, at least in part, their lower autophagic activity. In addition, co-localization of LC3-stained autophagosome spots and perilipin-stained lipid droplets was demonstrated mainly in differentiating melanosphere-derived cells, further supporting the role of autophagy in lipid droplets clearance. The present manuscript demonstrates an inverse relationship between lipid-storing phenotype and melanoma stem cells differentiation, providing novel indications involving autophagy in melanoma stem cells biology

Identification of a novel domain of fibroblast growth factor 2 controlling its angiogenic properties.

Fibroblast growth factor 2 (FGF-2) is a potent factor modulating the activity of many cell types. Its dimerization and binding to high affinity receptors are considered to be necessary steps to induce FGF receptor phosphorylation and signaling activation. A structural analysis was carried out and a region encompassing residues 48-58 of human FGF-2 was identified, as potentially involved in FGF-2 dimerization. A peptide (FREG-48-58) derived from this region strongly and specifically inhibited FGF-2 induced proliferation and migration of primary bovine aorta endothelial cells (BAEC) in vitro, and markedly reduced FGF-2-dependent angiogenesis in two distinct in vivo assays. To further investigate the role of region 48-58, a polyclonal antibody raised against FREG-(48-58) was tested and was found to block FGF-2 action in vitro. Human FGF-2 has three histidine residues, one falling within the region 48-58. Chemical modification of histidine residues blocked FGF-2 activity and FREG-(48-58) inhibitory effect in vitro, indicating that histidine residues, in particular the one within FREG-(48-58) region, play a crucial role in the observed activity. Additional experiments showed that FREG-(48-58) specifically interacted with FGF-2, impaired FGF-2-interaction with itself, with heparin and with FGF receptor 1, and inhibited FGF-2-induced receptor phosphorylation and FGF-2 internalization. These data indicate for the first time that region 48-58 of FGF-2 is a functional domain controlling FGF-2 activity

Cancer microenvironment and endoplasmic reticulum stress response

Different stressful conditions such as hypoxia, nutrient deprivation, pH changes, or reduced vascularization, potentially able to act as growth-limiting factors for tumor cells, activate the unfolded protein response (UPR). UPR is therefore involved in tumor growth and adaptation to severe environments and is generally cytoprotective in cancer. The present review describes the molecular mechanisms underlying UPR and able to promote survival and proliferation in cancer. The critical role of UPR activation in tumor growth promotion is discussed in detail for a few paradigmatic tumors such as prostate cancer and melanoma

Expression of genes related to lipid handling and the obesity paradox in melanoma: database analysis

Background: Publicly available genomic and transcriptomic data in searchable databases allow researchers to investigate specific medical issues in thousands of patients. Many studies have highlighted the role lipids play in cancer initiation and progression and reported nutritional interventions aimed at improving prognosis and survival. Therefore, there is an increasing interest in the role that fat intake may play in cancer. It is known that there is a relationship between BMI and survival in patients with cancer, and that there is an association between a high-fat diet and increased cancer risk. In some cancers, such as colorectal cancer, obesity and high fat intake are known to increase the risk of cancer initiation and progression. On the contrary, in patients undergoing treatment for melanoma, a higher BMI unexpectedly acts as a protective factor rather than a risk factor; this phenomenon is known as the obesity paradox. Objective: We aimed to identify the molecular mechanism underlying the obesity paradox, with the expectation that this could indicate new effective strategies to reduce risk factors and improve protective approaches. Methods: In order to determine the genes potentially involved in this process, we investigated the expression values of lipid-related genes in patients with melanoma or colorectal cancer. We used available data from 2990 patients from 3 public databases (IST [In Silico Transcriptomics] Online, GEO [Gene Expression Omnibus], and Oncomine) in an analysis that involved 3 consecutive validation steps. Of this group, data from 1410 individuals were analyzed in the IST Online database (208 patients with melanoma and 147 healthy controls, as well as 991 patients with colorectal cancer and 64 healthy controls). In addition, 45 melanoma, 18 nevi, and 7 healthy skin biopsies were analyzed in another database, GEO, to validate the IST Online data. Finally, using the Oncomine database, 318 patients with melanoma (312 controls) and 435 patients with colorectal cancer (445 controls) were analyzed. Results: In the first and second database investigated (IST Online and GEO, respectively), patients with melanoma consistently showed significantly (P&lt;.001) lower expression levels of 4 genes compared to healthy controls: CD36, MARCO, FABP4, and FABP7. This strong reduction was not observed in patients with colorectal cancer. An additional analysis was carried out on a DNA-TCGA data set from the Oncomine database, further validating CD36 and FABP4. Conclusions: The observed lower expression of genes such as CD36 and FABP4 in melanoma may reduce the cellular internalization of fat and therefore make patients with melanoma less sensitive to a high dietary fat intake, explaining in part the obesity paradox observed in patients with melanoma

A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry spectra, widely used in proteomics studies as a screening tool for protein profiling and to detect discriminatory signals, are high dimensional data. A large number of local maxima (a.k.a. <it>peaks</it>) have to be analyzed as part of computational pipelines aimed at the realization of efficient predictive and screening protocols. With this kind of data dimensions and samples size the risk of over-fitting and selection bias is pervasive. Therefore the development of bio-informatics methods based on unsupervised feature extraction can lead to general tools which can be applied to several fields of predictive proteomics.</p> <p>Results</p> <p>We propose a method for feature selection and extraction grounded on the theory of multi-scale spaces for high resolution spectra derived from analysis of serum. Then we use support vector machines for classification. In particular we use a database containing 216 samples spectra divided in 115 cancer and 91 control samples. The overall accuracy averaged over a large cross validation study is 98.18. The area under the ROC curve of the best selected model is 0.9962.</p> <p>Conclusion</p> <p>We improved previous known results on the problem on the same data, with the advantage that the proposed method has an unsupervised feature selection phase. All the developed code, as MATLAB scripts, can be downloaded from <url>http://medeaserver.isa.cnr.it/dacierno/spectracode.htm</url></p

The role of autophagy in liver epithelial cells and its Impact on systemic homeostasis

Autophagy plays a role in several physiological and pathological processes as it controls the turnover rate of cellular components and influences cellular homeostasis. The liver plays a central role in controlling organisms’ metabolism, regulating glucose storage, plasma proteins and bile synthesis and the removal of toxic substances. Liver functions are particularly sensitive to autophagy modulation. In this review we summarize studies investigating how autophagy influences the hepatic metabolism, focusing on fat accumulation and lipids turnover. We also describe how autophagy affects bile production and the scavenger function within the complex homeostasis of the liver. We underline the role of hepatic autophagy in counteracting the metabolic syndrome and the associated cardiovascular risk. Finally, we highlight recent reports demonstrating how the autophagy occurring within the liver may affect skeletal muscle homeostasis as well as different extrahepatic solid tumors, such as melanoma

Skin lesion image segmentation using Delaunay Triangulation for melanoma detection

Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortal- ity. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presented. Delaunay Triangulation is used to extract a binary mask of the lesion region, without the need of any training stage. A quantitative experimental evaluation has been conducted on a publicly available database, by taking into account six well-known state- of-the-art segmentation methods for comparison. The results of the experi- mental analysis demonstrate that the proposed approach is highly accurate when dealing with benign lesions, while the segmentation accuracy signi- cantly decreases when melanoma images are processed. This behavior led us to consider geometrical and color features extracted from the binary masks generated by our algorithm for classication, achieving promising results for melanoma detection