Biology subjects

Sepahi, N.

Publications and source records attributed to Sepahi, N..

4 recordsLinked to original sources

bioRxiv2020

Identification of potential biomarkers associated with pathogenesis of primary prostate cancer based on meta-analysis approaches

Worldwide prostate cancer (PCa) is recognized as the second most common diagnosed cancer and the fifth leading cause of cancer death among men globally. Rising incidence rates of PCa have been observed over the last few decades. It is necessary to improve prostate cancer detection, diagnosis, treatment and survival. However, there are few reliable biomarkers for early prostate cancer diagnosis and prognosis. In the current study, systems biology method was applied for transcriptomic data analysis to identify potential biomarkers for primary PCa. We firstly identified differentially expressed genes (DEGs) between primary PCa and normal samples. Then the DEGs were mapped in Wikipathways and gene ontology database to conduct functional categories enrichment analysis. 1575 unique DEGs with adjusted p-value < 0.05 were achieved from two sets of DEGs. 132 common DEGs between two sets of DEGs were retrieved. The final DEGs were selected from 60 common upregulated and 72 common downregulated genes between datasets. In conclusion, we demonstrated some potential biomarkers (FOXA1, AGR2, EPCAM, CLDN3, ERBB3, GDF15, FHL1, NPY, DPP4, and GADD45A) and HIST2H2BE as a candidate one which are tightly correlated with the pathogenesis of PCa.

genomics↗

bioRxiv2020

Gene Expression Signature and Molecular Mechanism of Redox Homeostasis in Colorectal Cancer

Cellular redox homeostasis is the important tool for normal cell function and survival. Oxidants, reductants and antioxidants are the players to maintain cellular homeostasis balance. However, in some conditions like cancer, the concentration and activation of these players are disturbed. This study walks you through the molecular mechanism of redox homeostasis to describe how expression level of these players would help colorectal cancer (CRC) cells continue proliferation and survive in the hypoxic environment of tumor. We proposed that O2- concentration is not detrimentally high in CRC cells since expression level of MnSOD didnt change noticeably. We also suggested that High proliferative CRC cells obtain their energy by oxidation of H2S in or Electron transport chain (ETC) and keep the adequate concentration of H2S by diminishing the expression level of enzymes involved in sulfide oxidation pathway. Reduction in hydrogen sulfide oxidation results in a decrease in the level of GSH. Glutathione peroxidase enzyme requires GSH to convert H2O2 into oxygen and water. Therefore, Level of hydrogen peroxide stays high which leads to an increase in cell proliferation. Furthermore, we analyzed the expression level of transcription factors sensitive to redox messengers.

systems biology↗

bioRxiv2020

Systems Biomedicine of Colorectal Cancer Reveals Potential Targets for CRC treatment

Colorectal cancer (CRC) is one of the major causes of cancer deaths across the world. Patients survival time at time of diagnosis depends largely on stage of the tumor. Therefore, understanding the molecular mechanisms promoting cancer progression from early stages to high-grade stages is essential for implementing therapeutic approaches. To this end, we performed a unique meta-analysis flowchart by identifying differentially expressed genes (DEGs) between normal, primary and metastatic samples in some test datasets. DEGs were employed to construct a protein-protein interaction (PPI) network. Then, a smaller network containing 39 DEGs were extracted from the PPI network whose nodes expression induction or suppression alone or in combination with each other would inhibit tumor progression or metastasis. A number of these DEGs were then verified by gene expression profiling, survival analysis and a number of validation datasets from different genomic repositories. They were involved in cell proliferation, energy production under hypoxic conditions, epithelial to mesenchymal transition (EMT) and angiogenesis. Multiple combination targeting of these DEGs were proposed to have high potential in preventing cancer progression. Some genes were also presented as diagnostic biomarkers for colorectal cancer. Finally, TMEM131, DARS and SORD genes were identified in this study which had never been associated with any kind of cancer neither as a biomarker nor curative target.

systems biology↗

bioRxiv2020

Pathway Mining and Data Mining in Functional Genomics. An Integrative Approach to Delineate Boolean Relationships Between Src and Its targets

MotivationThere are important molecular information hidden in the ocean of big data could be achieved by recognizing true relationships between different molecules. Human mind is very limited to find all molecular connections. Therefore, we introduced an integrated data mining strategy to find all possible relationships between molecular components in a biological context. To demonstrate how this approach works, we applied it on proto-oncogene c-Src. ResultsHere we applied a data mining scheme on genomic, literature and signaling databases to obtain necessary biological information for pathway inference. Using R programming language, two large edgelists were constructed from KEGG and OmniPath signaling databases. Next, An R script was developed by which pathways were discovered by assembly of edge information in the constructed signaling networks. Then, valid pathways were distinguished from the invalid ones using molecular information in articles and genomic data analysis. Pathway inference was performed on predicted pathways starting with Src and ending with the DEGs whose expression were affected by c-Src overactivation. Moreover, some positive and negative feedback loops were proposed based on the gene expression results. In fact, this simple but practical flowchart will open new insights into interactions between cellular components and help biologists look for new possible molecular relationships that have not been reported neither in signaling databases nor as a signaling pathway.

bioinformatics↗