Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.

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.

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 O ₂ ^- concentration is not detrimentally high in CRC cells since expression level of MnSOD didn’t change noticeably. We also suggested that High proliferative CRC cells obtain their energy by oxidation of H ₂ S in or Electron transport chain (ETC) and keep the adequate concentration of H ₂ S 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 H ₂ O ₂ 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.

Epithelial ovarian cancer (EOC) can be considered as a stressful and challenging disease among all women in the world, which has been associated with a poor prognosis and its molecular pathogenesis has remained unclear. In recent years, RNA Sequencing (RNA-seq) has become a functional and amazing technology for profiling gene expression. In the present study, RNA-seq raw data from Sequence Read Archive (SRA) of six tumor and normal ovarian sample was extracted, and then analysis and statistical interpretation was done with Linux and R Packages from the open-source Bioconductor. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of key genes and pathways involved in EOC. We identified 1091 Differential Expression Genes (DEGs) which have been reported in various studies of ovarian cancer as well as other types of cancer. Among them, 333 genes were up-regulated and 273 genes were down-regulated. In addition, Differentially Expressed Genes (DEGs) including RPL41, ALDH3A2, ERBB2, MIEN1, RBM25, ATF4, UPF2, DDIT3, HOXB8 and IL17D as well as Ribosome and Glycolysis/Gluconeogenesis pathway have had the potentiality to be used as targets for EOC diagnosis and treatment. In this study, unlike that of any other studies on various cancers, ALDH3A2 was most down-regulated gene in most KEGG pathways, and ATF4 was most up-regulated gene in leucine zipper domain binding term. In the other hand, RPL41 as a regulatory of cellular ATF4 level was up-regulated in many term and pathways and augmentation of ATF4 could justify the increase of RPL41 in the EOC. Pivotal pathways and significant genes, which were identified in the present study, can be used for adaptation of different EOC study. However, further molecular biological experiments and computational processes are required to confirm the function of the identified genes associated with EOC.

Human T-lymphotropic virus 1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a progressive disease of the central nervous system that affected significantly spinal cord, nevertheless, the pathogenesis pathway. This study aimed to employ high throughput meta-analysis to find major genes involved in the pathogenesis of HAM/TSP. High-throughput statistical analyses identified 385, 49, and 22 differentially expressed genes for normal vs. ACs, normal vs. HAM/TSP and ACs vs. HAM/TSP groups, respectively. STRING and further network analyses highlighted 32, 29, and 13 hub genes for normal vs. ACs, normal vs. HAM/TSP, and ACs vs. HAM/TSP groups, respectively. Biological network analyses indicated the involvement of hub genes in the HAM/TSP group in many vital pathways like apoptosis and immune pathways. Moreover, the meta-analysis results disclosed three major genes including STAT1, TAP1, and PSMB8 which have function role in HAM/TSP progression. Real-time PCR revealed the meaningful down-regulation of STAT1 in HAM/TSP samples than AC and normal samples ( P =0.01 and P =0.02, respectively), up-regulation of PSMB8 in HAM/TSP samples than AC and normal samples ( P =0.04 and P =0.01, respectively), and down-regulation of TAP1 in HAM/TSP samples than those in AC and normal samples ( P =0.008 and P =0.02, respectively). No significant difference was found among three groups in terms of percentage of T helper and cytotoxic T lymphocytes ( P = 0.55 and P =0.12). Our results confirm that STAT1, TAP1, and PSMB8 are three important genes which their expressions levels were changed in three different groups. These proteins in association with other proteins can involve in the immune and apoptosis pathways.