Targeting the dynamic transcriptional landscape of Treg subpopulations in pancreatic ductal adenocarcinoma: Insights from single-cell RNA sequencing analysis with a focus on CTLA4 and TIGIT.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy that represents a significant challenge in cancer research and clinical management. In this study, we reanalyzed a published single-cell RNA sequencing (scRNA-seq) dataset from PDAC and adjacent tissues to investigate the heterogeneity of tumor and normal tissue, specifically focusing on the regulatory T cells (Tregs) and their interactions with other cells in the tumor microenvironment (TME). Treg cells were identified and clustered into natural Tregs (nTreg) and induced Tregs (iTreg) based on the expression of specific genes. It was found that the number of iTregs was higher in the tumor than in healthy tissues, while the number of n Tregs was higher in healthy tissues. Differential gene expression analysis was performed, and biological process analysis revealed that the Tregs in PDAC were mostly involved in protein targeting and translation pathways. In addition, ligand-receptor pairs between Tregs and other cell types were identified, and the critical communication pathways between Tregs and endothelial and ductal cells were revealed, which could potentially contribute to the immunosuppressive TME of PDAC. These findings provide insights into the role of Tregs in PDAC and their interactions with other cell types in the TME, highlighting potential targets for immunotherapy, such as the inhibitory immune checkpoint receptors CTLA4 and TIGIT, which are known to be expressed on Tregs and have been shown to play a role in suppressing anti-tumor immune responses.

Investigating the therapeutic potential of Bifidobacterium breve and Lactobacillus rhamnosus postbiotics through apoptosis induction in colorectal HT-29 cancer cells.

Background and Objectives: Colorectal cancer (CRC) is a prevalent form of cancer worldwide. Recent studies suggest that postbiotics derived from probiotic bacteria have the potential as an adjunct therapy for CRC. This study investigates the anti-cancer effects of Bifidobacterium breve (B. breve) and Lactobacillus rhamnosus (L. rhamnosus) postbiotics on the HT-29 cell line. Materials and Methods: Through MTT and scratch assay, we investigated the anti-proliferation and anti-migration effects of B. breve and L. rhamnosus postbiotics on HT-29 cells. Furthermore, postbiotic-mediated apoptosis was assessed by analyzing the expression of Bax, Bcl-2, and caspase-3. We also investigated the effects of B. breve postbiotics on the expression of three important genes involved in metastasis, including RSPO2, NGF, and MMP7. Consequently, we validated the expression of selected genes in twelve adenocarcinoma tissues. Results: The results demonstrated the significant impact of postbiotics on HT-29 cells, highlighting their ability to induce anti-proliferation, anti-migration, and apoptosis-related effects. Notably, these effects were more pronounced using B. breve postbiotics than L. rhamnosus. Additionally, B. breve postbiotics could inhibit metastasis through upregulation of RSPO2 while downregulating NGF and MMP7 expression in HT-29 cells. Conclusion: Our research suggests that postbiotic metabolites may be effective biological products for the prevention and treatment of cancer.

Holistic exploration of CHGA and hsa-miR-137 in colorectal cancer via multi-omic data Integration.

Colorectal cancer (CRC) ranks among the most widespread malignancies globally, with early detection significantly influencing prognosis. Employing a systems biology approach, we aimed to unravel the intricate mRNA-miRNA network linked to CRC pathogenesis, potentially yielding diagnostic biomarkers. Through an integrative analysis of microarray, Bulk RNA-seq, and single-cell RNA-seq data, we explored CRC-related transcriptomes comprehensively. Differential gene expression analysis uncovered crucial genes, while Weighted Gene Co-expression Network Analysis (WGCNA) identified key modules closely linked to CRC. Remarkably, CRC manifested its strongest correlation with the turquoise module, signifying its pivotal role. From the cohort of genes showing high Gene Significance (GS) and Module Membership (MM), and Differential Expression Genes (DEGs), we highlighted the downregulated Chromogranin A (CHGA) as a notable hub gene in CRC. This finding was corroborated by the Human Protein Atlas database, which illustrated decreased CHGA expression in CRC tissues. Additionally, CHGA displayed elevated expression in primary versus metastatic cell lines, as evidenced by the CCLE database. Subsequent RT-qPCR validation substantiated the marked downregulation of CHGA in CRC tissues, reinforcing the significance of our differential expression analysis. Analyzing the Space-Time Gut Cell Atlas dataset underscored specific CHGA expression in epithelial cell subclusters, a trend persisting across developmental stages. Furthermore, our scrutiny of colon and small intestine Enteroendocrine cells uncovered distinct CHGA expression patterns, accentuating its role in CRC pathogenesis. Utilizing the WGCNA algorithm and TargetScan database, we validated the downregulation of hsa-miR-137 in CRC, and integrated assessment highlighted its interplay with CHGA. Our findings advocate hsa-miR-137 and CHGA as promising CRC biomarkers, offering valuable insights into diagnosis and prognosis. Despite proteomic analysis yielding no direct correlation, our multifaceted approach contributes comprehensive understanding of CRC's intricate regulatory mechanisms. In conclusion, this study advances hsa-miR-137 and CHGA as promising CRC biomarkers through an integrated analysis of diverse datasets and network interactions.

Tumor-infiltrating CD8+ sub-populations in primary and recurrent glioblastoma: An in-silico study.

Background: Glioblastoma multiforme (GBM) remains an incurable primary brain tumor. CD8+ tumor-infiltrating lymphocytes (TILs) can target malignant cells; however, their anti-tumoral immune responses mostly do not lead to GBM rejection in GBM patients. We profiled the sub-populations of tumor-infiltrating CD8+ T-cells, i.e., naïve, cytotoxic, and exhausted cells, in primary and recurrent GBM tissues and provided a blueprint for future precision-based GBM immunotherapy. Method: We re-analyzed the raw data of single-cell RNA sequencing on the cells residing in the GBM microenvironment and leveraged tumor bulk RNA analyses to study the significance of CD8+ TILs sub-populations in primary and recurrent GBM. We investigated cell-cell interaction between exhausted CD8+ TILs and other immune cells residing in the primary and recurrent GBM microenvironments and profiled the expression changes following CD8+ TILs' transition from primary GBM to recurrent GBM. Results: Exhausted CD8+ TILs are the majority of CD8+ TILs sub-populations in primary and recurrent GBM, and cytotoxic CD8+ TILs display decreased expression of inhibitory immune checkpoint (IC) molecules in the primary and recurrent GBM. In the primary and recurrent GBM microenvironment, exhausted CD8+ TILs interact most with tumor-infiltrating dendritic cells. Conclusion: This study demonstrates the profiles of CD8+ TILs sub-populations in primary and recurrent GBM and provides a proof-of-concept for future precision-based GBM immunotherapy.

Deciphering the immune landscape of head and neck squamous cell carcinoma: A single-cell transcriptomic analysis of regulatory T cell responses to PD-1 blockade therapy.

Immunotherapy is changing the Head and Neck Squamous Cell Carcinoma (HNSCC) landscape and improving outcomes for patients with recurrent or metastatic HNSCC. A deeper understanding of the tumor microenvironment (TME) is required in light of the limitations of patients' responses to immunotherapy. Here, we aimed to examine how Nivolumab affects infiltrating Tregs in the HNSCC TME. We used single-cell RNA sequencing data from eight tissues isolated from four HNSCC donors before and after Nivolumab treatment. Interestingly, the study found that Treg counts and suppressive activity increased following Nivolumab therapy. We also discovered that changes in the CD44-SSP1 axis, NKG2C/D-HLA-E axis, and KRAS signaling may have contributed to the increase in Treg numbers. Furthermore, our study suggests that decreasing the activity of the KRAS and Notch signaling pathways, and increasing FOXP3, CTLA-4, LAG-3, and GZMA expression, may be mechanisms that enhance the killing and suppressive capacity of Tregs. Additionally, the result of pseudo-temporal analysis of the HNSCC TME indicated that after Nivolumab therapy, the expression of certain inhibitory immune checkpoints including TIGIT, ENTPD1, and CD276 and LY9, were decreased in Tregs, while LAG-3 showed an increased expression level. The study also found that Tregs had a dense communication network with cluster two, and that certain ligand-receptor pairs, including SPP1/CD44, HLA-E/KLRC2, HLA-E/KLRK1, ANXA1/FPR3, and CXCL9/FCGR2A, had notable changes after the therapy. These changes in gene expression and cell interactions may have implications for the role of Tregs in the TME and in response to Nivolumab therapy.

Characterization of Wnt signaling pathway under treatment of Lactobacillus acidophilus postbiotic in colorectal cancer using an integrated in silico and in vitro analysis.

Colorectal cancer (CRC) is a prevalent and life-threatening cancer closely associated with the gut microbiota. Probiotics, as a vital microbiota group, interact with the host's colonic epithelia and immune cells by releasing a diverse range of metabolites named postbiotics. The present study examined the effects of postbiotics on CRC's prominent differentially expressed genes (DEGs) using in silico and in vitro analysis. Through single-cell RNA sequencing (scRNA-seq), we identified four DEGs in CRC, including secreted frizzled-related protein 1 (SFRP1), secreted frizzled-related protein 2 (SFRP2), secreted frizzled-related protein 4 (SFRP4), and matrix metallopeptidase 7 (MMP7). Enrichment analysis and ExpiMap, a novel deep learning-based method, determined that these DEGs are involved in the Wnt signaling pathway as a primary cascade in CRC. Also, spatial transcriptome analysis showed specific expression patterns of the SFRP2 gene in fibroblast cell type. The expression of selected DEGs was confirmed on CRC and normal adjacent tissues using Real-Time quantitative PCR (RT-qPCR). Moreover, we examined the effects of postbiotics extracted from Lactobacillus acidophilus (L. acidophilus) on the proliferation, migration, and cell cycle distribution of HT-29 cells using MTT, scratch, and flow cytometry assays. Our results showed that L. acidophilus postbiotics induce cell cycle arrest at G1 phase and also had anti-proliferative and anti-migration effects on HT-29 cells, while it did not exert anti-proliferative activity on control fibroblasts. Finally, we revealed that treating HT-29 cells with postbiotics can affect the expression of selected DEGs. We suggested that L. acidophilus postbiotics have therapeutic potential in CRC by modulating key genes in the Wnt pathway.

Clinical and genetic screening in a large Iranian family with Marfan syndrome: A case study.

Background and Aims: Marfan syndrome (MFS) is an autosomal dominant genetic disorder caused by pathogenic variants of the fibrillin-1-encoding FBN1 gene that commonly affects the cardiovascular, skeletal, and ocular systems. This study aimed to evaluate the clinical features and genetic causes of the MFS phenotype in a large Iranian family. Methods: Seventeen affected family members were examined clinically by cardiologists and ophthalmologists. The proband, a 48-year-old woman with obvious signs of MFS, her DNA sample subjected to whole-exome sequencing (WES). The candidate variant was validated by bidirectional sequencing of proband and other available family members. In silico analysis and molecular modeling were conducted to determine the pathogenic effects of the candidate variants. Results: The most frequent cardiac complications are mitral valve prolapse and regurgitation. Ophthalmic examination revealed iridodonesis and ectopic lentis. A heterozygous missense variant (c.2179T>C/p.C727R) in exon 19 of FBN1 gene was identified and found to cosegregate with affected family members. Its pathogenicity has been predicted using several in silico predictive algorithms. Molecular docking analysis indicated that the variant might affect the binding affinity between FBN1 and LTBP1 proteins by impairing disulfide bond formation. Conclusion: Our report expands the spectrum of the Marfan phenotype by providing details of its clinical manifestations and disease-associated molecular changes. It also highlights the value of WES in genetic diagnosis and contributes to genetic counseling in families with MFS.

Anti-inflammatory Effects of Ziziphus Jujube Mill on LPS-induced Acute Lung Injury in Mice.

Ziziphus Jujuba Mill (Z.J) is a well-known ethnomedical source of biologically active compounds with anti-inflammatory effects. However, its significance in acute lung injury (ALI) has never been studied. The present study aimed to explore whether Z.J could attenuate lipopolysaccharide (LPS)-induced inflammatory responses in an experimental model of ALI. Male BALB/c mice received an intratracheal administration of LPS (n=32) or phosphate buffer saline (PBS) (control, n=8). Within 1, 11, and 23 h post-LPS injection, mice were randomly assigned to receive intraperitoneal treatments of saline, dexamethasone (2 mg/kg), and 100 and 200 mg/kg of Z.J extracts, respectively. 24 h after intratracheal administration of LPS, bronchoalveolar lavage fluid and lung tissues were harvested and assessed for inflammatory cell influx, tumor necrosis factor-α (TNF-α) levels, and histological assessments. Treatment with Z.J extracts (100 and 200 mg/kg) and dexamethasone effectively reduced LPS-induced neutrophil and other inflammatory cell influx into the lung tissue compared to the untreated group. additionally, both doses of Z.J extracts (100 and 200 mg/kg) significantly ameliorated the lung wet-to-dry ratio and histopathological damage. Furthermore, compared to the untreated ALI mice, Z.J extract at the highest dose could significantly reduce the TNF-α level.   The present findings indicated that Z.J could effectively ameliorate LPS-induced ALI inflammatory responses and might be considered a promising alternative therapy for the ALI phenotype.

Deep learning applications in single-cell genomics and transcriptomics data analysis.

Traditional bulk sequencing methods are limited to measuring the average signal in a group of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution, however, enhances our understanding of complex biological systems and diseases, such as cancer, the immune system, and chronic diseases. However, the single-cell technologies generate massive amounts of data that are often high-dimensional, sparse, and complex, thus making analysis with traditional computational approaches difficult and unfeasible. To tackle these challenges, many are turning to deep learning (DL) methods as potential alternatives to the conventional machine learning (ML) algorithms for single-cell studies. DL is a branch of ML capable of extracting high-level features from raw inputs in multiple stages. Compared to traditional ML, DL models have provided significant improvements across many domains and applications. In this work, we examine DL applications in genomics, transcriptomics, spatial transcriptomics, and multi-omics integration, and address whether DL techniques will prove to be advantageous or if the single-cell omics domain poses unique challenges. Through a systematic literature review, we have found that DL has not yet revolutionized the most pressing challenges of the single-cell omics field. However, using DL models for single-cell omics has shown promising results (in many cases outperforming the previous state-of-the-art models) in data preprocessing and downstream analysis. Although developments of DL algorithms for single-cell omics have generally been gradual, recent advances reveal that DL can offer valuable resources in fast-tracking and advancing research in single-cell.

Single-cell RNA sequencing uncovers heterogeneous transcriptional signatures in tumor-infiltrated dendritic cells in prostate cancer.

Prostate cancer (PCa) is one of the two solid malignancies in which a higher T cell infiltration in the tumor microenvironment (TME) corresponds with a worse prognosis for the tumor. The inability of T cells to eliminate tumor cells despite an increase in their number reinforces the possibility of impaired antigen presentation. In this study, we investigated the TME at single-cell resolution to understand the molecular function and communication of dendritic cells (DCs) (as professional antigen-presenting cells). According to our data, tumor cells stimulate the migration of immature DCs to the tumor site by inducing inflammatory chemokines. Many signaling pathways such as TNF-α/NF-κB, IL2/STAT5, and E2F up-regulated after DCs enter the tumor location. In addition, some molecules such as GPR34 and SLCO2B1 decreased on the surface of DCs. The analysis of molecular and signaling alterations in DCs revealed some suppression mechanisms of tumors, such as removing mature DCs, reducing the DC's survival, inducing anergy or exhaustion in the effector T cells, and enhancing the differentiation of T cells to Th2 and Tregs. In addition, we investigated the cellular and molecular communication between DCs and macrophages in the tumor site and found three molecular pairs including CCR5/CCL5, CD52/SIGLEC10, and HLA-DPB1/TNFSF13B. These molecular pairs are involved in the migration of immature DCs to the TME and disrupt the antigen-presenting function of DCs. Furthermore, we presented new therapeutic targets by the construction of a gene co-expression network. These data increase our knowledge of the heterogeneity and the role of DCs in PCa TME.

Experimental validation of in silico analysis estimated the reverse effect of upregulated hsa-miR-106a-5p and hsa-miR-223-3p on SLC4A4 gene expression in Iranian patients with colorectal adenocarcinoma by RT-qPCR.

BACKGROUND AND METHODS: Colorectal cancer (CRC) is considered one of the most common malignancies worldwide. The diagnosis and prognosis of the patients are very poor. In this study, we used in-silico analysis and experimental techniques to investigate novel co-expression genes and their associated miRNA networks in CRC. For this purpose, we conducted a comprehensive transcriptome analysis using online bulk and single-cell RNA-seq datasets. We then validated the results on tissue samples from cancerous and adjacent normal tissues from CRC patients by RT-qPCR. RESULTS: Using a weighted gene co-expression network algorithm, we identified SLC4A4 as a significantly downregulated hub gene in the CRC. The single-cell analysis indicated that the expression level of SLC4A4 in Paneth cells is higher than in other cell populations. Further computational analysis suggested hsa-miR-223-3p and hsa-miR-106a-5p as two specific hub-miRNAs for the SLC4A4 gene. RT-qPCR analysis showed a 2.60-fold downregulation of SLC4A4. Moreover, hsa-miR-223-3p and hsa-miR-106a-5p showed an increased expression level of 5.58-fold and 9.66-fold in CRC samples, respectively. Based on the marginal model analysis, by increasing the expression of hsa-miR-106a-5p, the average expression of the SLC4A4 gene significantly decreased by 103 units. Furthermore, ROC curves analysis indicated statistically significant for diagnostic ability of SLC4A4 (AUC: 0.94, Sensitivity: 95.5%, Specificity: 95.5%) and hsa-miR-106a-5p (AUC: 0.72, Sensitivity: 72.7%, Specificity: 100%). CONCLUSION: This study provides a framework of co-expression gene modules and miRNAs of CRC, which identifies some important biomarkers for CRC pathogenicity and diagnosis. Further experimental evidence will be required to support this study and validate the precise molecular pathways.

Identification of Potential Prognostic Markers and Key Therapeutic Targets in Hepatocellular Carcinoma Using Weighted Gene Co-Expression Network Analysis: A Systems Biology Approach.

Background: As the most prevalent form of liver cancer, hepatocellular carcinoma (HCC) ranks the fifth highest cause of cancer-related death worldwide. Despite recent advancements in diagnostic and therapeutic techniques, the prognosis for HCC is still unknown. Objectives: This study aimed to identify potential genes contributing to HCC pathogenicity. Materials and Methods: To this end, we examined the GSE39791 microarray dataset, which included 72 HCC samples and 72 normal samples. An investigation of co-expression networks using WGCNA found a highly conserved blue module with 665 genes that were strongly linked to HCC. Results: APOF, NAT2, LCAT, TTC36, IGFALS, ASPDH, and VIPR1 were the blue module's top 7 hub genes. According to the results of hub gene enrichment, the most related issues in the biological process and KEGG were peroxisome organization and metabolic pathways, respectively. In addition, using the drug-target network, we discovered 19 FDA-approved medication candidates for different reasons that might potentially be employed to treat HCC patients through the modulation of 3 hub genes of the co-expression network (LCAT, NAT2, and VIPR1). Our findings also demonstrated that the 3 scientifically validated miRNAs regulated the co-expression network by the VIPR1 hub gene. Conclusion: We found co-expressed gene modules and hub genes linked with HCC advancement, offering insights into the mechanisms underlying HCC progression as well as some potential HCC treatments.

The recent advancements in the early detection of cancer biomarkers by DNAzyme-assisted aptasensors.

Clinical diagnostics rely heavily on the detection and quantification of cancer biomarkers. The rapid detection of cancer-specific biomarkers is of great importance in the early diagnosis of cancers and plays a crucial role in the subsequent treatments. There are several different detection techniques available today for detecting cancer biomarkers. Because of target-related conformational alterations, high stability, and target variety, aptamers have received considerable interest as a biosensing system component. To date, several sensitivity-enhancement strategies have been used with a broad spectrum of nanomaterials and nanoparticles (NPs) to improve the limit and sensitivity of analyte detection in the construction of innovative aptasensors. The present article aims to outline the research developments on the potential of DNAzymes-based aptasensors for cancer biomarker detection.

Anti-Inflammatory Activity of Ferula assafoetida Oleo-Gum-Resin (Asafoetida) against TNF-α-Stimulated Human Umbilical Vein Endothelial Cells (HUVECs).

Inflammation is the body's biological reaction to endogenous and exogenous stimuli. Recent studies have demonstrated several anti-inflammatory properties of Ferula species. In this paper, we decided to study the anti-inflammatory effect of ethanolic extract of Ferula assafoetida oleo-gum-resin (asafoetida) against TNF-α-stimulated human umbilical vein endothelial cells (HUVECs). HUVECs were cultured in a flat-bottom plate and then treated with ethanolic extract of asafoetida (EEA, 0-500 µg/ml) and TNF-α (0-100 ng/ml) for 24 h. We used the MTT test to assess cell survival. In addition, the LC-MS analysis was performed to determine the active substances. HUVECs were pretreated with EEA and then induced by TNF-α. Intracellular reactive oxygen species (ROS) and adhesion of peripheral blood mononuclear cells (PBMCs) to HUVECs were evaluated with DCFH-DA and CFSE fluorescent probes, respectively. Gene expression of intercellular cell adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1), and E-selectin and surface expression of ICAM-1 protein were measured using real-time PCR and flow cytometry methods, respectively. While TNF-α significantly increased intracellular ROS formation and PBMC adhesion to TNF-α-induced HUVECs, the pretreatment of HUVECs with EEA (125 and 250 µg/ml) significantly reduced the parameters. In addition, EEA pretreatment decreased TNF-α-induced mRNA expression of VCAM-1 and surface protein expression of ICAM-1 in the target cells. Taken together, the results indicated that EEA prevented ROS generation, triggered by TNF-α, and inhibited the expression of VCAM-1 and ICAM-1, leading to reduced PBMC adhesion. These findings suggest that EEA can probably have anti-inflammatory properties.

CHAC1 as a novel biomarker for distinguishing alopecia from other dermatological diseases and determining its severity.

Alopecia Areata (AA) is characterised by an autoimmune response to hair follicles (HFs) and its exact pathobiology remains unclear. The current study aims to look into the molecular changes in the skin of AA patients as well as the potential underlying molecular mechanisms of AA in order to identify potential candidates for early detection and treatment of AA. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to identify key modules, hub genes, and mRNA-miRNA regulatory networks associated with AA. Furthermore, Chi2 as a machine-learning algorithm was used to compute the gene importance in AA. Finally, drug-target construction revealed the potential of repositioning drugs for the treatment of AA. Our analysis using four AA data sets established a network strongly correlated to AA pathogenicity based on GZMA, OXCT2, HOXC13, KRT40, COMP, CHAC1, and KRT83 hub genes. Interestingly, machine learning introduced these genes as important in AA pathogenicity. Besides that, using another ten data sets, we showed that CHAC1 could clearly distinguish AA from similar clinical phenotypes, such as scarring alopecia due to psoriasis. Also, two FDA-approved drug candidates and 30 experimentally validated miRNAs were identified that affected the co-expression network. Using transcriptome analysis, suggested CHAC1 as a potential diagnostic predictor to diagnose AA.

The Recent Progress in DNAzymes-Based Aptasensors for Thrombin Detection.

Thrombin (TB) is classified among human blood coagulation proteins with key functions in hemostasis of blood vessels, wound healing, atherosclerosis, tissue adhesion, etc. Moreover, TB is involved as the main enzyme in the conversion of the fibrinogen to fibrin. Given the importance of TB detection in the clinical area, the development of innovative methods can considerably improve TB detection. Newly, aptasensors or aptamer-based biosensors have received special attention for sensitive and facile TB detection. In addition, the aptamer/nanomaterial conjugates have presented new prospects in accurate TB detection as nanoaptasensors. DNA-based enzymes or DNAzymes, as new biocatalysts, have many advantages over protein enzymes and can be used in analytical tools. This article reviews a brief overview of significant progresses regarding the various types of DNAzymes-based aptasensors and nano aptasensors developed for thrombin detection. In the following, challenges and prospects of TB detection by DNAzymes-based aptasensors are discussed.

Treatment with Hydroxyurea Leads to Fetal Hemoglobin Reactivation through CA1 and LIN28B Genes: An In Vitro Study.

Hydroxyurea (HU) is an effective drug to increase fetal γ-globin gene (Hb F) expression, replacing the missing adult ß-globin gene. The mechanism of Hb F induction by HU and improvement in clinical symptoms are still poorly understood. The current study aimed to improve the molecular understanding of drug-induced alterations and reveals genes related to HU treatment responsiveness in ß-thalassemia (ß-thal). We analyzed the GSE109186 dataset using system biology and weighted gene coexpression network analysis (WGCNA) to identify and quantify gene expression changes reflected in the HU-treated human erythroblastic leukemia cells. The K562 cell line was treated in 50, 100, and 150 µM concentrations of HU for 24, 48, and 72 hours with three replications. The alteration of CA1, LIN28B and Hb F gene expression in HU-treated cells was evaluated using the real-time polymerase chain (real-time PCR) technique. The results showed that LIN28B has an increase of 4.27-fold on the first day of HU-treatment in 50 µM (p < 0.01). The CA1 expression showed a decrease at all times and doses of treatment, and the most decrease happened in 48 hours and 50 µM (p < 0.04). Hb F also showed the highest increase in 100 µM after 24 hours of treatment (5.18-fold). In summary, the data suggest that alteration of LIN28B and CA1 gene expression is associated with γ-globin increasing in HU-treated cells.

ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis.

BACKGROUND: Gastric cancer (GC) is a complex disorder with an inadequate response to treatment. Although many efforts have been made to clarify the development of GC, the exact etiology and molecular mechanisms of this malignancy remain unclear. This study was designed to identify and characterize essential associated genes with GC to construct a prognostic model. METHODS: In this Insilco study, the gene expression microarray dataset GSE122401 was downloaded from the Gene Expression Omnibus (GEO). The raw data were processed and quantile-normalized with the edgeR package of R ver.3.5.3. The module-trait relationship and hub-genes associated with GC were analyzed with Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Cluepedia and Enrichr Database. Finally, hub-genes were screened and validated by GEPIA online database. RESULTS: According to the WGCNA results, the blue module was found to be strongly correlated with the GC (r=0.91, p-value=1e-57). DEGs analysis was performed by edgeR package of R and indicated a total of 47 genes as hub-genes. Verifying the hub-genes expression using GEPIA online database showed a significantly increased level of ACAN gene expression in primary cancer cell line compared to metastatic cell line. On the other hand, the expression of MDFI and CHST1 genes in primary cell lines were lower compared to metastatic cancer cell lines. CONCLUSIONS: This study provides a framework of the co-expression gene modules ACAN, MDFI, and CHST1 as hub-genes. These hub-genes might offer candidate biomarkers to targeted therapy against GC. Further experiment validation and animal models are needed to reveal the exact mechanism of the above-mentioned genes in the pathogenesis and prognoses of GC.

Prediction and validation of GUCA2B as the hub-gene in colorectal cancer based on co-expression network analysis: In-silico and in-vivo study.

BACKGROUND: Several serious attempts to treat colorectal cancer have been made in recent decades. However, no effective treatment has yet been discovered due to the complexities of its etiology. METHODS: we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify key modules, hub-genes, and mRNA-miRNA regulatory networks associated with CRC. Next, enrichment analysis of modules has been performed using Cluepedia. Next, quantitative real-time PCR (RT-qPCR) was used to validate the expression of selected hub-genes in CRC tissues. RESULTS: Based on the WGCNA results, the brown module had a significant positive correlation (r = 0.98, p-value=9e-07) with CRC. Using the survival and DEGs analyses, 22 genes were identified as hub-genes. Next, three candidate hub-genes were selected for RT-qPCR validation, and 22 pairs of cancerous and non-cancerous tissues were collected from CRC patients referred to the Gastroenterology and Liver Clinic. The RT-qPCR results revealed that the expression of GUCA2B was significantly reduced in CRC tissues, which is consistent with the results of differential expression analysis. Finally, top miRNAs correlated with GUCA2B were identified, and ROC analyses revealed that GUCA2B has a high diagnostic performance for CRC. CONCLUSIONS: The current study discovered key modules and GUCA2B as a hub-gene associated with CRC, providing references to understand the pathogenesis and be considered a novel candidate to CRC target therapy.