Gene-Specific Intron Retention Serves as Molecular Signature that Distinguishes Melanoma from Non-Melanoma Cancer Cells in Greek Patients

Background: Skin cancer represents the most common human malignancy, and it includes BCC, SCC, and melanoma. Since melanoma is one of the most aggressive types of cancer, we have herein attempted to develop a gene-specific intron retention signature that can distinguish BCC and SCC from melanoma biopsy tumors. Methods: Intron retention events were examined through RT-sqPCR protocols, using total RNA preparations derived from BCC, SCC, and melanoma Greek biopsy specimens. Intron-hosted miRNA species and their target transcripts were predicted via the miRbase and miRDB bioinformatics platforms, respectively. Ιntronic ORFs were recognized through the ORF Finder application. Generation and visualization of protein interactomes were achieved by the IntAct and Cytoscape softwares, while tertiary protein structures were produced by using the I-TASSER online server. Results: c-MYC and Sestrin-1 genes proved to undergo intron retention specifically in melanoma. Interaction maps of proteins encoded by genes being potentially targeted by retained intron-accommodated miRNAs were generated and SRPX2 was additionally delivered to our melanoma-specific signature. Novel ORFs were identified in MCT4 and Sestrin-1 introns, with potentially critical roles in melanoma development. Conclusions: The property of c-MYC, Sestrin-1, and SRPX2 genes to retain specific introns could be clinically used to molecularly differentiate non-melanoma from melanoma tumors.

Download Full-text

ANDROID APPLICATION FOR DETECTION OF SKIN CANCER USING EXPERT SYSTEM

Social Economics and Ecology International Journal (SEEIJ) ◽

10.31397/seeij.v2i1.12 ◽

2018 ◽

Vol 2 (1) ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

Yogi Udjaja

Keyword(s):

Risk Factor ◽

Expert System ◽

Skin Cancer ◽

Cancer Cells ◽

System Application ◽

Ultraviolet Rays ◽

The Sun ◽

Android Application ◽

Abnormal Growth ◽

Skin Cells

Skin cancer is an abnormal growth of human skin that can damage skin cells. By knowing the symptoms of skin cancer as early as posssible, it is helpful in preventing the spread of cancer cells and treatment. There are many factors that cause skin cancer, but in general the cause is exposure to ultraviolet rays from the sun. Therefore, an expert system application is required to detect skin cancer. By using backward chining and probalility methode; which data is in form of someone’s risk factor and clinical sympthoms, then the application will provide temporary diagnosis. This application is built in an android platfrom because in its development android is more used than other platforms. The accuracy obtained from this application is 96.67%.

Download Full-text

Enhanced Expression of Fibroblast Growth Factor Receptor 3 in Human Skin Cancer Cells

The Open Circulation & Vascular Journal ◽

10.2174/1877382600902010030 ◽

2009 ◽

Vol 2 (1) ◽

pp. 30-36 ◽

Cited By ~ 2

Author(s):

Motoki Terada ◽

Chikara Ohnishi ◽

Nobuhiro Ueno ◽

Akio Shimizu ◽

Michiyuki Kanai ◽

...

Keyword(s):

Growth Factor ◽

Skin Cancer ◽

Cancer Cells ◽

Fibroblast Growth Factor ◽

Human Skin ◽

Fibroblast Growth Factor Receptor ◽

Growth Factor Receptor ◽

Fibroblast Growth ◽

Enhanced Expression

Download Full-text

Single-chain antibody-decorated Au nanocages@liposomal layer nanoprobes for targeted SERS imaging and remote-controlled photothermal therapy of melanoma cancer cells

Materials Science and Engineering C ◽

10.1016/j.msec.2021.112086 ◽

2021 ◽

Vol 124 ◽

pp. 112086

Author(s):

Ghazal Farahavar ◽

Samira Sadat Abolmaali ◽

Foroogh Nejatollahi ◽

Amin Safaie ◽

Sanaz Javanmardi ◽

...

Keyword(s):

Cancer Cells ◽

Photothermal Therapy ◽

Single Chain ◽

Single Chain Antibody ◽

Melanoma Cancer ◽

Sers Imaging

Download Full-text

Computational Methods for Structure-to-Function Analysis of Diet-Derived Catechins-Mediated Targeting of In Vitro Vasculogenic Mimicry

Cancer Informatics ◽

10.1177/11769351211009229 ◽

2021 ◽

Vol 20 ◽

pp. 117693512110092

Author(s):

Abicumaran Uthamacumaran ◽

Narjara Gonzalez Suarez ◽

Abdoulaye Baniré Diallo ◽

Borhane Annabi

Keyword(s):

Machine Learning ◽

Cancer Cells ◽

Structural Changes ◽

Function Analysis ◽

Vasculogenic Mimicry ◽

Machine Learning Algorithms ◽

Emergent Behavior ◽

Molecular Signature ◽

Ovarian Cancer Cells

Background: Vasculogenic mimicry (VM) is an adaptive biological phenomenon wherein cancer cells spontaneously self-organize into 3-dimensional (3D) branching network structures. This emergent behavior is considered central in promoting an invasive, metastatic, and therapy resistance molecular signature to cancer cells. The quantitative analysis of such complex phenotypic systems could require the use of computational approaches including machine learning algorithms originating from complexity science. Procedures: In vitro 3D VM was performed with SKOV3 and ES2 ovarian cancer cells cultured on Matrigel. Diet-derived catechins disruption of VM was monitored at 24 hours with pictures taken with an inverted microscope. Three computational algorithms for complex feature extraction relevant for 3D VM, including 2D wavelet analysis, fractal dimension, and percolation clustering scores were assessed coupled with machine learning classifiers. Results: These algorithms demonstrated the structure-to-function galloyl moiety impact on VM for each of the gallated catechin tested, and shown applicable in quantifying the drug-mediated structural changes in VM processes. Conclusions: Our study provides evidence of how appropriate 3D VM compression and feature extractors coupled with classification/regression methods could be efficient to study in vitro drug-induced perturbation of complex processes. Such approaches could be exploited in the development and characterization of drugs targeting VM.

Download Full-text

B16 Melanoma Cancer Cells with Higher Metastatic Potential are More Deformable at a Whole-Cell Level

Cellular and Molecular Bioengineering ◽

10.1007/s12195-021-00677-w ◽

2021 ◽

Author(s):

Yoshihiro Ujihara ◽

Daichi Ono ◽

Koki Nishitsuji ◽

Megumi Ito ◽

Shukei Sugita ◽

...

Keyword(s):

Cancer Cells ◽

Metastatic Potential ◽

B16 Melanoma ◽

Cell Level ◽

Whole Cell ◽

Melanoma Cancer

Download Full-text

CD36 promotes vasculogenic mimicry in melanoma by mediating adhesion to the extracellular matrix

BMC Cancer ◽

10.1186/s12885-021-08482-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Carmela Martini ◽

Mark DeNichilo ◽

Danielle P. King ◽

Michaelia P. Cockshell ◽

Brenton Ebert ◽

...

Keyword(s):

Extracellular Matrix ◽

Cancer Cells ◽

Vasculogenic Mimicry ◽

Tumor Vasculature ◽

Melanoma Cells ◽

Human Melanoma ◽

Cell Surface Glycoprotein ◽

Melanoma Cancer ◽

In Vitro Angiogenesis

Abstract Background The formation of blood vessels within solid tumors directly contributes to cancer growth and metastasis. Until recently, tumor vasculature was thought to occur exclusively via endothelial cell (EC) lined structures (i.e. angiogenesis), but a second source of tumor vasculature arises from the cancer cells themselves, a process known as vasculogenic mimicry (VM). While it is generally understood that the function of VM vessels is the same as that of EC-lined vessels (i.e. to supply oxygen and nutrients to the proliferating cancer cells), the molecular mechanisms underpinning VM are yet to be fully elucidated. Methods Human VM-competent melanoma cell lines were examined for their VM potential using the in vitro angiogenesis assays (Matrigel), together with inhibition studies using small interfering RNA and blocking monoclonal antibodies. Invasion assays and adhesion assays were used to examine cancer cell function. Results Herein we demonstrate that CD36, a cell surface glycoprotein known to promote angiogenesis by ECs, also supports VM formation by human melanoma cancer cells. In silico analysis of CD36 expression within the melanoma cohort of The Cancer Genome Atlas suggests that melanoma patients with high expression of CD36 have a poorer clinical outcome. Using in vitro ‘angiogenesis’ assays and CD36-knockdown approaches, we reveal that CD36 supports VM formation by human melanoma cells as well as adhesion to, and invasion through, a cancer derived extracellular matrix substrate. Interestingly, thrombospondin-1 (TSP-1), a ligand for CD36 on ECs that inhibits angiogenesis, has no effect on VM formation. Further investigation revealed a role for laminin, but not collagen or fibronectin, as ligands for CD36 expressing melanoma cells. Conclusions Taken together, this study suggests that CD36 is a novel regulator of VM by melanoma cancer cells that is facilitated, at least in part, via integrin-α3 and laminin. Unlike angiogenesis, VM is not perturbed by the presence of TSP-1, thus providing new information on differences between these two processes of tumor vascularization which may be exploited to combat cancer progression.

Download Full-text