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    Drug repositioning in non-small cell lung cancer (NSCLC) using gene co-expression and drug-gene interaction networks analysis
    (Nature, 2022) MotieGhader, Habib; Tabrizi-Nezhadi, Parinaz; Abad Paskeh, Mahshid Deldar; Baradaran, Behzad; Mokhtarzadeh, Ahad; Hashemi, Mehrdad; Lanjanian, Hossein; Jazayeri, Seyed Mehdi; Maleki, Masoud; Khodadadi, Ehsan; Nematzadeh, Sajjad; Maghsoudloo, Mazaher; Masoudi-Nejad, Ali; Kiani, Farzad
    Lung cancer is the most common cancer in men and women. This cancer is divided into two main types, namely non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Around 85 to 90 percent of lung cancers are NSCLC. Repositioning potent candidate drugs in NSCLC treatment is one of the important topics in cancer studies. Drug repositioning (DR) or drug repurposing is a method for identifying new therapeutic uses of existing drugs. The current study applies a computational drug repositioning method to identify candidate drugs to treat NSCLC patients. To this end, at frst, the transcriptomics profle of NSCLC and healthy (control) samples was obtained from the GEO database with the accession number GSE21933. Then, the gene co-expression network was reconstructed for NSCLC samples using the WGCNA, and two signifcant purple and magenta gene modules were extracted. Next, a list of transcription factor genes that regulate purple and magenta modules’ genes was extracted from the TRRUST V2.0 online database, and the TF–TG (transcription factors–target genes) network was drawn. Afterward, a list of drugs targeting TF–TG genes was obtained from the DGIdb V4.0 database, and two drug–gene interaction networks, including drug-TG and drug-TF, were drawn. After analyzing gene co-expression TF–TG, and drug–gene interaction networks, 16 drugs were selected as potent candidates for NSCLC treatment. Out of 16 selected drugs, nine drugs, namely Methotrexate, Olanzapine, Haloperidol, Fluorouracil, Nifedipine, Paclitaxel, Verapamil, Dexamethasone, and Docetaxel, were chosen from the drug-TG sub-network. In addition, nine drugs, including Cisplatin, Daunorubicin, Dexamethasone, Methotrexate, Hydrocortisone, Doxorubicin, Azacitidine, Vorinostat, and Doxorubicin Hydrochloride, were selected from the drug-TF sub-network. Methotrexate and Dexamethasone are common in drug-TG and drug-TF sub-networks. In conclusion, this study proposed 16 drugs as potent candidates for NSCLC treatment through analyzing gene co-expression, TF–TG, and drug–gene interaction networks.
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    High-throughput analysis of the interactions between viral proteins and host cell RNAs
    (Elsevier Ltd, 2021) Lanjanian, Hossein; Nematzadeh, Sajjad; Hosseini, Shadi; Torkamanian-Afshar, Mahsa; Kiani, Farzad; Moazzam-Jazi, Maryam; Aydin, Nizamettin; Masoudi-Nejad, Ali
    Indexed keywords Abstract RNA-protein interactions of a virus play a major role in the replication of RNA viruses. The replication and transcription of these viruses take place in the cytoplasm of the host cell; hence, there is a probability for the host RNA-viral protein and viral RNA-host protein interactions. The current study applies a high-throughput computational approach, including feature extraction and machine learning methods, to predict the affinity of protein sequences of ten viruses to three categories of RNA sequences. These categories include RNAs involved in the protein-RNA complexes stored in the RCSB database, the human miRNAs deposited at the mirBase database, and the lncRNA deposited in the LNCipedia database. The results show that evolution not only tries to conserve key viral proteins involved in the replication and transcription but also prunes their interaction capability. These proteins with specific interactions do not perturb the host cell through undesired interactions. On the other hand, the hypermutation rate of NSP3 is related to its affinity to host cell RNAs. The Gene Ontology (GO) analysis of the miRNA with affiliation to NSP3 suggests that these miRNAs show strongly significantly enriched GO terms related to the known symptoms of COVID-19. Docking and MD simulation study of the obtained miRNA through high-throughput analysis suggest a non-coding RNA (an RNA antitoxin, ToxI) as a natural aptamer drug candidate for NSP5 inhibition. Finally, a significant interplay of the host RNA-viral protein in the host cell can disrupt the host cell's system by influencing the RNA-dependent processes of the host cells, such as a differential expression in RNA. Furthermore, our results are useful to identify the side effects of mRNA-based vaccines, many of which are caused by the off-label interactions with the human lncRNAs.
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    Impact of 5HydroxyMethylCytosine (5hmC) on reverse/direct association of cell-cycle, apoptosis, and extracellular matrix pathways in gastrointestinal cancers
    (Springer, 2022) Moravveji, Sayyed Sajjad; Khoshbakht, Samane; Mokhtari, Majid; Salimi, Mahdieh; Lanjanian, Hossein; Nematzadeh, Sajjad; Torkamanian-Afshar, Mahsa; Masoudi-Nejad, Ali
    Background: Aberrant levels of 5-hydroxymethylcytosine (5-hmC) can lead to cancer progression. Identifcation of 5-hmC-related biological pathways in cancer studies can produce better understanding of gastrointestinal (GI) cancers. We conducted a network-based analysis on 5-hmC levels extracted from circulating free DNAs (cfDNA) in GI cancers including colon, gastric, and pancreatic cancers, and from healthy donors. The co-5-hmC network was reconstructed using the weighted-gene co-expression network method. The cancer-related modules/subnetworks were detected. Preservation of three detected 5-hmC-related modules was assessed in an external dataset. The 5-hmC-related modules were functionally enriched, and biological pathways were identifed. The relationship between modules was assessed using the Pearson correlation coefcient (p-value<0.05). An elastic network classifer was used to assess the potential of the 5-hmC modules in distinguishing cancer patients from healthy individuals. To assess the efciency of the model, the Area Under the Curve (AUC) was computed using fve-fold cross-validation in an external dataset. Results: The main biological pathways were the cell cycle, apoptosis, and extracellular matrix (ECM) organization. Direct association between the cell cycle and apoptosis, inverse association between apoptosis and ECM organiza? tion, and inverse association between the cell cycle and ECM organization were detected for the 5-hmC modules in GI cancers. An AUC of 92% (0.73–1.00) was observed for the predictive model including 11 genes. Conclusion: The intricate association between biological pathways of identifed modules may reveal the hidden signifcance of 5-hmC in GI cancers. The identifed predictive model and new biomarkers may be benefcial in cancer detection and precision medicine using liquid biopsy in the early stages.
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    Parallel molecular alteration between Alzheimer's disease and major depressive disorder in the human brain dorsolateral prefrontal cortex: an insight from gene expression and methylation profile analyses
    (Genetics Soc Japan, 2022) Rastad, Saber; Barjaste, Nadia; Lanjanian, Hossein; Moeini, Ali; Kiani, Farzad; Masoudi-Nejad, Ali
    Alzheimer's disease (AD) and major depressive disorder (MDD) are comorbid neuropsychiatric disorders that are among the leading causes of long-term disability worldwide. Recent research has indicated the existence of parallel molecular mechanisms between AD and MDD in the dorsolateral prefrontal cortex (DLPFC). However, the premorbid history and molecular mechanisms have not yet been well characterized. In this study, differentially expressed gene (DEG), differentially co-expressed gene and protein-protein interaction (PPI) network propagation analyses were applied to gene expression data of postmortem DLPFC samples from human individuals diagnosed with and without AD or MDD (AD: cases = 310, control = 157; MDD: cases = 75, control = 161) to identify the main genes in the two disorders' specific and shared biological pathways. Subsequently, the results were evaluated using another four assessment datasets (n1 = 230, n2 = 65, n3 = 58, n4 = 48). Moreover, the postmortem DLPFC methylation status of human subjects with AD or MDD was compared using 68 and 608 samples for AD and MDD, respectively. Eight genes (XIST, RPS4Y1, DDX3Y, USP9Y, DDX3X, TMSB4Y, ZFY and E1FAY) were common DEGs in DLPFC of subjects with AD or MDD. These genes play important roles in the nervous system and the innate immune system. Furthermore, we found HSPG2, DAB2IP, ARHGAP22, TXNRD1, MYO10, SDK1 and KRT82 as common differentially methylated genes in the DLPFC of cases with AD or MDD. Finally, as evidence of shared molecular mechanisms behind this comorbidity, we propose some genes as candidate biomarkers for both AD and MDD. However, more research is required to clarify the molecular mechanisms underlying the co-existence of these two important neuropsychiatric disorders.