Dataset Information

Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer.

ABSTRACT: BACKGROUND:Malignant melanoma is an aggressive tumor of the skin and seems to be resistant to current therapeutic approaches. Melanocytic transformation is thought to occur by sequential accumulation of genetic and molecular alterations able to activate the Ras/Raf/MEK/ERK (MAPK) and/or the PI3K/AKT (AKT) signalling pathways. Specifically, mutations of B-RAF activate MAPK pathway resulting in cell cycle progression and apoptosis prevention. According to these findings, MAPK and AKT pathways may represent promising therapeutic targets for an otherwise devastating disease. RESULT:Here we show a computational model able to simulate the main biochemical and metabolic interactions in the PI3K/AKT and MAPK pathways potentially involved in melanoma development. Overall, this computational approach may accelerate the drug discovery process and encourages the identification of novel pathway activators with consequent development of novel antioncogenic compounds to overcome tumor cell resistance to conventional therapeutic agents. The source code of the various versions of the model are available as S1 Archive.

SUBMITTER: Pappalardo F

PROVIDER: S-EPMC4807832 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer.

Pappalardo Francesco F Russo Giulia G Candido Saverio S Pennisi Marzio M Cavalieri Salvatore S Motta Santo S McCubrey James A JA Nicoletti Ferdinando F Libra Massimo M

PloS one 20160325 3

<h4>Background</h4>Malignant melanoma is an aggressive tumor of the skin and seems to be resistant to current therapeutic approaches. Melanocytic transformation is thought to occur by sequential accumulation of genetic and molecular alterations able to activate the Ras/Raf/MEK/ERK (MAPK) and/or the PI3K/AKT (AKT) signalling pathways. Specifically, mutations of B-RAF activate MAPK pathway resulting in cell cycle progression and apoptosis prevention. According to these findings, MAPK and AKT pathw ...[more]

PMID: 27015094

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Project description:Vasculogenic mimicry (VM), a micro vessel-like structure formed by the cancer cells, plays a pivotal role in cancer malignancy and progression. Interleukin-1 beta (IL-1β) is an active pro-inflammatory cytokine and elevated in many tumor types, including breast cancer. However, the effect of IL-1β on the VM of breast cancer has not been clearly elucidated. In this study, breast cancer cells (MCF-7 and MDA-MB-231) were used to study the effect of IL-1β on the changes that can promote VM. The evidence for VM stimulated by IL-1β was acquired by analyzing the expression of VM-associated biomarkers (VE-cadherin, VEGFR-1, MMP-9, MMP-2, c-Fos, and c-Jun) via western blot, immunofluorescent staining, and Immunohistochemistry (IHC). Additionally, morphological evidence was collected via Matrigel-based cord formation assay under normoxic/hypoxic conditions and microvessel examination through Hematoxylin and Eosin staining (H&E). Furthermore, the STRING and Gene Ontology database was also used to analyze the VM-associated interacting molecules stimulated by IL-β. The results showed that the expression of VM biomarkers was increased in both MCF-7 and MDA-MB-231 cells after IL-1β treatment. The increase in VM response was observed in IL-1β treated cells under both normoxia and hypoxia. IL-1β also increased the activation of transcription factor AP-1 complex (c-Fos/c-Jun). The bioinformatics data indicated that p38/MAPK and PI3K/Akt signaling pathways were involved in the IL-1β stimulation. It was further confirmed by the downregulated expression of VM biomarkers and reduced formation of the intersections upon the addition of the signaling pathway inhibitors. The study suggests that IL-1β stimulates the VM and its associated events in breast cancer cells via p38/MAPK and PI3K/Akt signaling pathways. Aiming the VM-associated molecular targets promoted by IL-1β may offer a novel anti-angiogenic therapeutic strategy to control the aggressiveness of breast cancer cells.

Project description:Lung cancer is the most prevalent in cancer-related deaths, while breast carcinoma is the second most dominant cancer in women, accounting for the most number of deaths worldwide. Cancers are heterogeneous diseases that consist of several subtypes based on the presence or absence of hormone receptors and human epidermal growth factor receptor 2. Several drugs have been developed targeting cancer biomarkers; nonetheless, their efficiency are not adequate due to the high reemergence rate of cancers and fundamental or acquired resistance toward such drugs, which leads to partial therapeutic possibilities. Recent studies on cardiac glycosides (CGs) positioned them as potent cytotoxic agents that target multiple pathways to initiate apoptosis and autophagic cell death in many cancers. In the present study, our aim is to identify the anticancer activity of a naturally available CG (strophanthidin) in human breast (MCF-7), lung (A549), and liver cancer (HepG2) cells. Our results demonstrate a dose-dependent cytotoxic effect of strophanthidin in MCF-7, A549, and HepG2 cells, which was further supported by DNA damage on drug treatment. Strophanthidin arrested the cell cycle at the G2/M phase; this effect was further validated by checking the inhibited expressions of checkpoint and cyclin-dependent kinases in strophanthidin-induced cells. Moreover, strophanthidin inhibited the expression of several key proteins such as MEK1, PI3K, AKT, mTOR, Gsk3α, and β-catenin from MAPK, PI3K/AKT/mTOR, and Wnt/β-catenin signaling. The current study adequately exhibits the role of strophanthidin in modulating the expression of various key proteins involved in cell cycle arrest, apoptosis, and autophagic cell death. Our in silico studies revealed that strophanthidin can interact with several key proteins from various pathways. Taken together, this study demonstrates the viability of strophanthidin as a promising anticancer agent, which may serve as a new anticancer drug.

Dataset Information

Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer.

Publications

Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer.

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