Recombinant anthrax lethal toxin inhibits cell motility and invasion in breast cancer cells through the dysregulation of Rho GTPases

El‐Chami, Dana; Haddad, Maria Al; Abi-Habib, Ralph J.; El‐Sibai, Mirvat

doi:10.3892/ol.2020.12424

Cited by 4 publications

(2 citation statements)

References 45 publications

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“…Breast cancer is a highly invasive tumor that primarily afects women [4]. Te high death rate among women makes it the second deadliest malignancy after lung cancer [5,6]. A study by the National Institute of Cancer in China found 1.67 million breast cancer and 522,000 deaths cases from 2008 to 2012 [7].…”

Section: Introductionmentioning

confidence: 99%

Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network

Bukht

Ahmad²,

Almadhor

et al. 2023

Computational Intelligence and Neuroscience

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Medical image analysis places a significant focus on breast cancer, which poses a significant threat to women’s health and contributes to many fatalities. An early and precise diagnosis of breast cancer through digital mammograms can significantly improve the accuracy of disease detection. Computer-aided diagnosis (CAD) systems must analyze the medical imagery and perform detection, segmentation, and classification processes to assist radiologists with accurately detecting breast lesions. However, early-stage mammography cancer detection is certainly difficult. The deep convolutional neural network has demonstrated exceptional results and is considered a highly effective tool in the field. This study proposes a computational framework for diagnosing breast cancer using a ResNet-50 convolutional neural network to classify mammogram images. To train and classify the INbreast dataset into benign or malignant categories, the framework utilizes transfer learning from the pretrained ResNet-50 CNN on ImageNet. The results revealed that the proposed framework achieved an outstanding classification accuracy of 93%, surpassing other models trained on the same dataset. This novel approach facilitates early diagnosis and classification of malignant and benign breast cancer, potentially saving lives and resources. These outcomes highlight that deep convolutional neural network algorithms can be trained to achieve highly accurate results in various mammograms, along with the capacity to enhance medical tools by reducing the error rate in screening mammograms.

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Section: Introductionmentioning

confidence: 99%

Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network

Bukht

Ahmad²,

Almadhor

et al. 2023

Computational Intelligence and Neuroscience

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show abstract

“…Another study on the effect of LeTx on breast cancer cells reported a major decrease in motility and invasion and an increase in adhesion all mediated by LeTx treatment (El-Chami et al, 2021).…”

Section: Previous Work On Anthrax Lethal Toxinmentioning

confidence: 97%

Effect of Anthrax Lethal Toxin on Activation of MAPK Pathway and Autophagy in AML Cell Lines. (c2021)

Rania¹

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Anthrax lethal toxin is an A-B toxin consisting of protective antigen (PrAg), the cell binding and translocation domain, and lethal factor (LF), the catalytic domain, which cleaves all mitogen-activated protein/extracellular regulated kinase kinases (MEKs), leading to the inhibition of the MAPK pathway. Anthrax lethal toxin has been extensively studied for its antitumor effect and showed potency against the majority of acute myeloid leukemia cell lines. In addition to that, previous data have shown that autophagy is activated in most AML cell lines. In this study we investigate the effect of anthrax lethal toxin on the downstream effectors of MEK in the Ras-Raf-MEK-ERK pathway, investigate the effect of MEK inhibition on the downregulation of ERK and try to explore the mechanism underlying autophagy which plays a protective role at later time points, as previously shown. This study aims to explain the difference in susceptibility of different AML cell lines. Flow cytometry analysis of downstream effectors of MEK showed decrease in phosphorylation of ERK and its downstream effectors only at early time points in sensitive cell lines. Whereas this pattern was not observed in resistant cell lines that showed a constant level of activation up to 120 hours after treatment. Finally, the effect on autophagy is to be more studied by testing for the expression of more proteins involved.

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Advanced Situation with Recombinant Toxins: Diversity, Production and Application Purposes

Ефременко

Aslanli

Lyagin

2023

IJMS

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Today, the production and use of various samples of recombinant protein/polypeptide toxins is known and is actively developing. This review presents state-of-the-art in research and development of such toxins and their mechanisms of action and useful properties that have allowed them to be implemented into practice to treat various medical conditions (including oncology and chronic inflammation applications) and diseases, as well as to identify novel compounds and to detoxify them by diverse approaches (including enzyme antidotes). Special attention is given to the problems and possibilities of the toxicity control of the obtained recombinant proteins. The recombinant prions are discussed in the frame of their possible detoxification by enzymes. The review discusses the feasibility of obtaining recombinant variants of toxins in the form of protein molecules modified with fluorescent proteins, affine sequences and genetic mutations, allowing us to investigate the mechanisms of toxins’ bindings to their natural receptors.

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Recombinant anthrax lethal toxin inhibits cell motility and invasion in breast cancer cells through the dysregulation of Rho GTPases

Cited by 4 publications

References 45 publications

Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network

Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network

Effect of Anthrax Lethal Toxin on Activation of MAPK Pathway and Autophagy in AML Cell Lines. (c2021)

Advanced Situation with Recombinant Toxins: Diversity, Production and Application Purposes

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