<i>In Silico</i> Experimental Modeling of Cancer Treatment

Trisilowati,; Mallet, Daniel G.

doi:10.5402/2012/828701

Cited by 25 publications

(27 citation statements)

References 19 publications

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“…These are expensive and time consuming methods [23] . Therefore, pharmaceutical industries incorporate computer-aided drug design tools to mainly identify the hits and optimize them to the leads, which are then subjected to in vitro screening against the receptors for the therapeutic area under consideration [23,24] .…”

Section: Research Papermentioning

confidence: 99%

Therapeutic Potential of PI3K/Akt/mTOR Signalling Pathway: Effective Combination Therapy for Cancer

Kawade¹,

Satpute²,

Dhulap³

et al. 2018

pharmaceutical-sciences

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Kawade et al.: Therapeutic potential of PI3K/Akt/mTOR signalling pathway Cell signalling mechanism plays a vital role in cell functioning. Imbalance and disregulation between these signals, such as phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin signalling pathway may lead to uncontrolled cell proliferation. Generation of drug resistance is the hurdle in current cancer treatment. Designing an effective combination therapy for inhibition of two or more proteins of a given pathway might help to overcome the drug resistance and side effect related issues in cancer treatment. In this regard, application of computational tools firstly to predict newer combinations against phosphatidylinositol-3-kinase, protein kinase B and mammalian target of rapamycin involved in a single pathway have been proposed. The results obtained using the computational tools were shortlisted based on GlideScore and binding interactions of the drugs to the receptors of the pathway. One of the predicted combinations was further subjected to biological evaluation using the Western blot assay. The experimental results revealed synergistic effects that supported the predictions. The study also provided insights for the application and development of computational tools to predict newer combinations in a given network pharmacology.

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Section: Research Papermentioning

confidence: 99%

Therapeutic Potential of PI3K/Akt/mTOR Signalling Pathway: Effective Combination Therapy for Cancer

Kawade¹,

Satpute²,

Dhulap³

et al. 2018

pharmaceutical-sciences

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“…Nevertheless, the mathematical integration of information acquired from clinical and tumor microenvironment interactions into a common description is as difficult to achieve as it is to understand the underlying complexities of the tumor biology itself, and requires translational researchers, experimentalists and biomathematicians (18,19 Articles Tadeo et al Statistically significant levels are indicated by the gradient between these two colors; brighter colors represent higher significance. Differences were considered statistically significant for P values <0.05.…”

Section: Neuroblastoma Multiparametric Analysismentioning

confidence: 99%

Section: Neuroblastoma Multiparametric Analysismentioning

confidence: 99%

Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma

et al. 2013

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Background: Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. Methods: A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. results: New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. conclusion: The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma. t o clearly distinguish the heterogeneous spectrum of clinical, histological, and molecular markers of cancer, and thereafter determine the markers essential to diagnosing the degree of malignancy and predicting response to therapy, remains a difficult challenge. These essential markers may be elucidated by considering the patient's organism and transformed tissues as holistically interconnected and dependent on microenvironment interactions via biochemical and biophysical signals (1). Mathematical models enable us to integrate measures made at different levels and generate from relatively simple to highly complex computational descriptors of the disease process of human tumors (2). Digitization of clinical data is necessary to deal with the complex hallmarks of cancer (3). To achieve personalized therapy, wellness and image-defined risk factors must be quantified (4). Hanahan and Weinberg have proposed that eight hallmarks of cancer together constitute an organizing principle that provides a logical framework for understanding the remarkable diversity of neoplastic diseases (5,6). A novel ninth hallmark which includes the aspect of physics has recently been emphasized (7). The identification of these hallmarks by quantifying the structural variations in tumor tissues, at diagnosis as well as during tumor progression and after treatment, using whole histological sections or tissue microarrays with the human eye is a challenging process (8). However, the difficulty can be overcome by forming morphometric data to represent the histological texture and classify the structural changes via sophisticated computational methods (9-11...

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“…In addition, it has been suggested that miRNAs might interfere with numerous developmental processes, and could be considered as molecular biomarkers for several disorders (28). Since preclinical studies in cancer biology are time consuming and extremely expensive, and require in vitro and in vivo animal experiments (30), in silico approaches prior to laboratory studies have been widely considered in recent investigations. Overexpression of the human AEG-1 gene has been shown in malignant gliomas, breast carcinomas and melanomas (31), and we were able to identify putative miRTSs and affinity of candidate miRNAs in the presence of 3'UTR SNPs of this gene using the MicroSNiPer and MirSNP databases.…”

Section: Discussionmentioning

confidence: 99%

Prioritization of rs187728237 and rs80320514 as miRNA-related Variants of Human AEG-1 Gene

et al. 2018

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Background and Objectives: 3' untranslated region (3'UTR) single nucleotide polymorphisms (SNPs) represent genetic variations that may potentially affect binding of miRNA to coding genes, potentially leading to complex disorders. We aimed to perform in silico analysis of the potential phenotypic effect of 3'UTR SNPs on human astrocyte elevated gene-1 (AEG-1), a newly identified candidate cancer gene.Methods: We gathered a list of all 3'UTR SNPs located in the human AEG-1 gene from the SNP database. Analysis of the potential effects was done using MirSNP and MicroSNiper.Results: Analysis by the MirSNP estimated that rs187728237 might increase the affinity of two miRNAs and decrease the affinity of 10 other miRNAs to the AEG-1 transcript. Moreover, MicroSNiPer showed that rs80320514 might affect 24 putative miRNA binding sites in the 3'UTR of AEG-1.Conclusion: Based on our findings, it can be concluded that the 3'UTR SNPs located in the human AEG-1 gene may be within the miRNA targets of the transcript, therefore affecting the stability of putative miRNA-target interactions.

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In Silico Experimental Modeling of Cancer Treatment

Cited by 25 publications

References 19 publications

Therapeutic Potential of PI3K/Akt/mTOR Signalling Pathway: Effective Combination Therapy for Cancer

Therapeutic Potential of PI3K/Akt/mTOR Signalling Pathway: Effective Combination Therapy for Cancer

Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma

Prioritization of rs187728237 and rs80320514 as miRNA-related Variants of Human AEG-1 Gene

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