Biology subjects

Minuchehr, Z.

Publications and source records attributed to Minuchehr, Z..

3 recordsLinked to original sources

bioRxiv2022

Gene Expression Profiles Reveal Potential Targets for Breast Cancer Diagnosis and Treatment

Figuring out the molecular mechanisms underlying breast cancer is essential for the diagnosis and treatment of this invasive disorder. Hence it is important to identify the most significant genes correlated with molecular events and to study their interactions in order to identify breast cancer mechanisms. Here we focus on the gene expression profiles, which we have detected in breast cancer. High-throughput genomic innovations such as microarray have helped us understand the complex dynamics of multisystem diseases such as diabetes and cancer. We performed an analysis using microarray datasets by the Networkanalyst bioinformatics tool, based on a random effect model (REM). We achieved pivotal differential expressed genes like ADAMTS5, SCARA5, IGSF10, and C2orf40 that had the most down-regulation, and also COL10A1, COL11A1, and UHRF1 that they had the most up-regulation in four-stage of breast cancer. We used CentiScape and AllegroMCODE plugins in CytoScape software in order to figure out hub genes in the protein-protein interactions network. Besides, we utilized DAVID online software to find involved biological pathways and Gene ontology, also used Expression2kinase software in order to find upstream regulatory transcription factors and kinases. In conclusion, we have found that the statistical network inference approach is useful in gene prioritization and is capable of contributing to practical network signature discovery and providing insights into the mechanisms relevant to the disease. Our research has also identified novel transcription factors, kinases, pathways, and genes that may serve as important targets for the development of diagnostic biomarkers and treatments.

cancer biology↗

bioRxiv2019

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↗

bioRxiv2019

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↗