Size effect of human epidermal growth factor-conjugated polystyrene particles on cell proliferation

Yasami-Khiabani, Setayesh; Karkhaneh, Akbar; Shokrgozar, Mohammad Ali; Amanzadeh, Amir; Golkar, Majid

doi:10.1039/d0bm00183j

Cited by 5 publications

(5 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on these findings, Ketoconazole, Salicylic acid, Acetaminophen, Isoniazid, Piperazine, and Betahistine were not cytotoxic to A431 cells at the studied concentrations. Based on our previous work, EGF could induce Tyrosine 1173 (Y1173) phosphorylation of A431 cells [14]. Assessing the level of Y1173 phosphorylation following co-treatment with the drugs and EGF could be good evidence to investigate the drugs as potential EGFR-tyrosine kinase inhibitors.…”

Section: -3-results For the Experimental Sectionmentioning

confidence: 99%

Proposing New Potential Candidates to Inhibit EGFR via Machine Learning Algorithm

Torabi

Yasami-Khiabani

Sardari

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

One of the main issues in solid tumours is progressive mutation in epidermal growth factor receptors (EGFR) gene, which activates signalling pathways that create new blood vessels. In this study, it was attempted to find new a therapeutic candidate to inhibit EGFR. One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The critical point of computational drug repositioning method is saving time and cost to remove the pre-clinical step and accelerate the drug discovery process. Hence, an ensemble computational-experimental approach, consisting of three different steps, a machine learning model, simulation of drug-target interaction and experimental characterization, was developed. The machine learning type used here was different tree classification method, which is one of the best randomize machine learning model to identify potential inhibitors from weak inhibitors. The machine learning step aimed to discover the approved drugs with the highest possible success rate in the experimental step. Finally, out of the nine chosen drugs, seven compounds had been confirmed to inhibit EGFR in the published articles since 2019. Hence, two identified compounds, in addition to gefitinib, as a positive control, and one neutral, were considered via molecular docking study. Finally, eight proposed drugs, including gefitinib, were investigated using MTT assay and In-Cell ELISA to characterise the drugs effect on A431 cell growth and EGFR-signaling. From our experiments, we could conclude that salicylic acid and piperazine could play an EGFR-inhibitor role like gefitinib.

show abstract

Section: -3-results For the Experimental Sectionmentioning

confidence: 99%

Proposing New Potential Candidates to Inhibit EGFR via Machine Learning Algorithm

Torabi

Yasami-Khiabani

Sardari

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…It has been demonstrated that GFs' immobilization leads to enhanced cell signalling and prolonged biological activity of the GFs. Immobilization of GF prevents its internalization upon binding to the receptor, resulting in continued cell signalling and enhanced biological activities compared to soluble GFs 68–70 …”

Section: Discussionmentioning

confidence: 99%

“…67 Furthermore, an increase in expression of KRT10 and Involucrin GFs. [68][69][70] Since the high-affinity receptor for KGF, FGFR2-IIIb/KGFR, is predominantly expressed by cells of epithelial origin, we wonder if KGF receptors are present on ASCs. Several studies showed a combination of KGF and some stimulating factors induced the differentiation of MSCs towards keratinocyte lineage.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancement of keratinocyte growth factor potential in inducing adipose‐derived stem cells differentiation into keratinocytes by collagen‐targeting

Amidzadeh

Yasami-Khiabani

Rahimi

et al. 2022

J Cellular Molecular Medi

Self Cite

View full text Add to dashboard Cite

Different growth factors can regulate stem cell differentiation. We used keratinocyte growth factor (KGF) to direct adipose-derived stem cells (ASCs) differentiation into keratinocytes. To enhance KGF bioavailability, we targeted KGF for collagen by fusing it to collagen-binding domain from Vibrio mimicus metalloprotease (vibrioCBD-KGF). KGF and vibrioCBD-KGF were expressed in Escherichia coli and purified to homogeneity. Both proteins displayed comparable activities in stimulating proliferation of HEK-293 and MCF-7 cells. vibrioCBD-KGF demonstrated enhanced collagen-binding affinity in immunofluorescence and ELISA. KGF and vibrioCBD-KGF at different concentrations (2, 10, and 20 ng/ml) were applied for 21 days on ASCs cultured on collagen-coated plates. Keratinocyte differentiation was assessed based on morphological changes, the expression of keratinocyte markers (Keratin-10 and Involucrin), and stem cell markers (Collagen-I and Vimentin) by real-time PCR or immunofluorescence. Our results indicated that the expression of keratinocyte markers was substantially increased at all concentrations of vibrioCBD-KGF, while it was observed for KGF only at 20 ng/ml. Immunofluorescence staining approved this finding. Moreover, down-regulation of Collagen-I, an indicator of differentiation commitment, was more significant in samples treated with vibrioCBD-KGF. The present study showed that vibrioCBD-KGF is more potent in inducing the ASCs differentiation into keratinocytes compared to KGF. Our results have important implications for effective skin regeneration using collagen-based biomaterials.

show abstract

“…Limited by the micron scale, PLT@PDA‐DOX micromotors may be minimal to be uptaken by cells. [ 17 ] However, the nano‐sized PMP@PDA‐DOX are released when PLT@PDA‐DOX micromotors are activated by TME, which is easy to be uptake by cancer cells. Therefore, the red fluorescence signal characterized here inside cancer cells is speculated that mainly derived from the released PMP@PDA‐DOX in cancer cellular environment.…”

Section: Construction and Characterization Of Engineered Plt‐based Micro/nanomotorsmentioning

confidence: 99%

Engineered Platelet‐Based Micro/Nanomotors for Cancer Therapy

Chen

et al. 2021

Small

View full text Add to dashboard Cite

Engineered platelets (PLT) can bring new possibilities for diseases treatment due to the specific response for a variety of physiological disease environments. However, the deep penetration of engineered PLT in diseased tissues such as tumor is still an important challenge that restricts the therapeutic effect. Herein, the engineered PLT micromotor (PLT@PDA‐DOX) is constructed by a universal self‐polymerization modification method of dopamine, and the chemotherapeutic drug doxorubicin (DOX) is loaded by both π–π stacking interaction with polydopamine (PDA) and cellular endocytosis of PLT. The experimental results prove that PLT@PDA‐DOX can target to tumor site by the specific binding of PLT with cancer cells, and then the secondary PLT‐derived microparticles (PMP@PDA‐DOX) are released with the activation of PLT@PDA‐DOX by tumor microenvironment (TME). Besides, benefiting from the photothermal conversion capability of PDA, PLT@PDA‐DOX micromotors and PMP@PDA‐DOX nanomotors are driven by near‐infrared light to realize deep penetration. And the PLT‐based micro/nanomotors with propulsion capability possess good performance for tumor ablating in vitro and in vivo. In consideration of the operability, mildness, universality of this modification method and the good biocompatibility of PDA, this work may provide a general paradigm for the construction of engineered cells in disease treatment.

show abstract

Size effect of human epidermal growth factor-conjugated polystyrene particles on cell proliferation

Abstract: Conjugation of growth factors to a carrier is a favorable method to improve their efficacy as therapeutic molecules.

Cited by 5 publications

References 40 publications

Proposing New Potential Candidates to Inhibit EGFR via Machine Learning Algorithm

Proposing New Potential Candidates to Inhibit EGFR via Machine Learning Algorithm

Enhancement of keratinocyte growth factor potential in inducing adipose‐derived stem cells differentiation into keratinocytes by collagen‐targeting

Engineered Platelet‐Based Micro/Nanomotors for Cancer Therapy

Contact Info

Product

Resources

About