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Afzali, F.

Publications and source records attributed to Afzali, F..

3 recordsLinked to original sources

Designing a novel multi-epitope T vaccine for targeting protein for Xklp-2 (TPX2) in hepatocellular carcinoma based on immunoinformatics approach

Hepatocellular carcinoma (HCC) is one of the leading cancer-related deaths worldwide. Recently, studies for HCC treatment are focused on cancer immunotherapy, particularly cancer vaccines, to complete and assist other therapies. TPX2 is a microtubule-associated protein necessary for cell division; therefore, alteration in its expression, especially up regulation, is associated with several human carcinomas such as HCC.\n\nIn this study, immunoinformatics tools were used to design a rational multi-epitope T vaccine against TPX2 in HCC. Cytotoxic T lymphocytes (CTL) and Helper T lymphocytes (HTL) epitopes were predicted and Maltose-binding protein (MBP) was added to the construct as an adjuvant. Evaluation of vaccine properties was indicated that our construct is stable and immunogenic enough to induce relevant responses besides not being allergic. After predicting the tertiary structure and energy minimization, protein-protein docking was performed to calculate the free energy of possible interactions between the vaccine and toll-like receptor 4 (TLR4) to assure that simultaneous complementary responses would be activated by our construct. Finally, Codon optimization and in-silico cloning were performed to ensure the vaccine expression efficiency in the desired host.

bioinformatics

Unearthing Regulatory Axes of Breast Cancer circRNAs Networks to Find Novel Targets and Fathom Pivotal Mechanisms

Circular RNAs (circRNAs) along other complementary regulatory elements in ceRNAs networks possess valuable characteristics for both diagnosis and treatment of several human cancers including breast cancer (BC). In this study, we combined several systems biology tools and approaches to identify influential BC circRNAs, RNA binding proteins (RBPs), miRNAs, and related mRNAs to study and decipher the BC triggering biological processes and pathways.\n\nRooting from the identified total of 25 co-differentially expressed circRNAs (DECs) between triple negative (TN) and luminal A subtypes of BC from microarray analysis, five hub DECs (hsa_circ_0003227, hsa_circ_0001955, hsa_circ_0020080, hsa_circ_0001666, and hsa_circ_0065173) and top eleven RBPs (AGO1, AGO2, EIF4A3, FMRP, HuR (ELAVL1), IGF2BP1, IGF2BP2, IGF2BP3, EWSR1, FUS, and PTB) were explored to form the upper stream regulatory elements. All the hub circRNAs were regarded as super sponge having multiple miRNA response elements (MREs) for numerous miRNAs. Then four leading miRNAs (hsa-miR-149, hsa-miR-182, hsa-miR-383, and hsa-miR-873) accountable for BC progression were also introduced from merging several ceRNAs networks. The predicted 7- and 8-mer MREs matches between hub circRNAs and leading miRNAs ensured their enduring regulatory capability. The mined downstream mRNAs of the circRNAs-miRNAs network then were presented to STRING database to form the PPI network and deciphering the issue from another point of view. The BC interconnected enriched pathways and processes guarantee the merits of the ceRNAs networks members as targetable therapeutic elements.\n\nThis study suggested extensive panels of novel covering therapeutic targets that are in charge of BC progression in every aspect, hence their impressive role cannot be excluded and needs deeper empirical laboratory designs.

bioinformatics

Molecular Correlations between Breast Cancer and Diabetes Mellitus Type 2 Examined by In Silico analyses and Drug Inhibitory Effects

Nearly 16% of people with breast cancer (BC) have Diabetes Mellitus type 2 (DM2) and are at a higher risk of death worldwide. Their common regulatory factors and functional mechanisms can be targeted applying multi-target drugs including Metformin (MTFN) and Curcumin (CURC). In this study, we used in-silico approaches to study the potential underlying mechanisms of this co-treatment strategy on BC and DM2 in order to introduce novel therapeutic targets.\n\nThe total number of 48 shared differentially expressed genes (17 up-regulated and 31 down-regulated) were identified through establishing diseases protein-protein network and BC RNA-sequencing expression data. The integration of functional clustering and pathway analyses revealed that the most involved cellular pathways and processes are regard to cells proliferation, death, migration, and response to external stimulus. Afterwards, the MTFN/CURC correlation and co-treatment optimization was probed through response surface methodology (RSM) based on MCF7 cell line and confirmed by MDA-MB-231. Combination index calculation by MTT viability assay proved supportive effects on both cell lines. The superior apoptotic potential of co-treatment compared to single treatments was shown on inhibition of MCF7 proliferation and induction of cell death demonstrated by cell body co-staining and flow cytometry as well as gene expression analysis via RT-PCR. Furthermore, wound-healing scratch assay showed that this co-treatment has a slightly higher effect on migration inhibition compared to single treatments.\n\nIn conclusion, our study used in-silico and in-vitro approaches and introduced a potential regulatory panel between BC and DM2. We also provided a linear model and equation that show the positive relation of drugs co-treatment. The proposed co-treatment strategy successfully controlled the biological processes under investigation.

cancer biology