Evidence map›Paper›PMID 36840004›Full record

ArticlePharmaceutics2023

Anti-Tumor Activity of Orally Administered Gefitinib-Loaded Nanosized Cubosomes against Colon Cancer.

Ahmed A El-Shenawy, Mahmoud M A Elsayed, Gamal M K Atwa, Mohammed A S Abourehab, Mohamed S Mohamed, Mohammed M Ghoneim, Reda A Mahmoud, Shereen A Sabry, Walid Anwar, Mohamed El-Sherbiny and 3 more

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
6.7field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 29 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 8 institutions in 2 countries.

Ahmed A El-ShenawyDepartment of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Al-Azhar University, Assiut Branch, Assiut 71524, Egypt.ORCID 0000-0003-0875-1602
Mahmoud M A ElsayedDepartment of Pharmaceutics and Clinical Pharmacy, Faculty of Pharmacy, Sohag University, Sohag 82524, Egypt.ORCID 0000-0001-9547-2243
Gamal M K AtwaDepartment of Biochemistry, Faculty of Pharmacy, Port Said University, Port Said 42515, Egypt.
Mohammed A S AbourehabDepartment of Pharmaceutics, Faculty of Pharmacy, Umm Al-Qura University, Makkah 21955, Saudi Arabia.ORCID 0000-0003-1348-6567
Mohamed S MohamedDepartment of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Al-Azhar University, Assiut Branch, Assiut 71524, Egypt.
Mohammed M GhoneimDepartment of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Ad Diriyah 13713, Saudi Arabia.ORCID 0000-0002-9179-4373
Reda A MahmoudDepartment of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Al-Azhar University, Assiut Branch, Assiut 71524, Egypt.
Shereen A SabryDepartment of Pharmaceutics, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt.ORCID 0000-0001-8327-7192
Walid AnwarDepartment of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Al-Azhar University, Cairo 11751, Egypt.ORCID 0000-0003-0322-5064
Mohamed El-SherbinyDepartment of Basic Medical Sciences, College of Medicine, AlMaarefa University, P.O. Box 71666, Riyadh 11597, Saudi Arabia.ORCID 0000-0002-0814-1743
Yasser A HassanDepartment of Pharmaceutics, Faculty of Pharmacy, Delta University for Science and Technology, Gamasa 35712, Egypt.
Amany BelalMedicinal Chemistry Department, Faculty of Pharmacy, Beni-Suef University, Beni-Suef 62514, Egypt.ORCID 0000-0003-1045-0163
Abd El Hakim RamadanDepartment of Pharmaceutics, Faculty of Pharmacy, Port Said University, Port Said 42515, Egypt.ORCID 0000-0003-0812-0149
Al-Azhar University · EGAlfaisal University · SAPort Said University · EGBeni-Suef University · EGDelta University for Science and Technology · EGSohag University · EGUmm al-Qura University · SAZagazig University · EG

Funding

Umm al-Qura University 22UQU4290565DSR117
6 · The paper itself

Abstract

Gefitinib (GFT) is a tyrosine kinase inhibitor drug used as a first-line treatment for patients with advanced or metastatic non-small cell lung, colon, and breast cancer. GFT exhibits low solubility and hence low oral bioavailability, which restricts its clinical application. One of the most important trends in overcoming such problems is the use of a vesicular system. Cubosomes are considered one of the most important vesicular systems used to improve solubility and oral bioavailability. In this study, GFT cubosomal nanoparticles (GFT-CNPs) were prepared by the emulsification method. The selected formulation variables were analyzed and optimized by full factorial design and response surface methodology. Drug entrapment efficiency (EE%), transmission electron microscopy, particle size, polydispersity index, in vitro release and its kinetics, and the effect of storage studies were estimated. The chosen GFT-CNPs were subjected to further investigations as gene expression levels of tissue inhibitors of metalloproteinases-1 (TIMP-1) and matrix metalloproteinases-7 (MMP-7), colon biomarkers, and histopathological examination of colon tissues. The prepared GFT-CNPs were semi-cubic in shape, with high EE%, smaller vesicle size, and higher zeta potential values. The in vivo data showed a significant decrease in the serum level of embryonic antigen (CEA), carbohydrate antigen 19-9 (CA 19-9), and gene expression level of TIMP-1 and MMP-7. Histopathological examination showed enhancement in cancer tissue and highly decreased focal infiltration in the lamina propria after treatment with GFT-CNPs.

Indexed as

colon cancergefitinibgene expressionhistopathological examinationnanoparticlesnanosized cubosomes

Identifiers

PMID36840004
PMCPMC9960579
OpenAlexW4321248412

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.