scholarly journals Evaluation of SYK Gene as a Prognostic Biomarker and Suggested Aromatic Potential Phytochemicals to Halt the Colorectal Cancer

2021 ◽  
Author(s):  
Partha Biswas ◽  
Dipta Dey ◽  
Atikur Rahman ◽  
Md. Aminul Islam ◽  
Tasmina Ferdous Susmi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Drug Repositioning ◽  
Treatment Strategies ◽  
Interaction Network ◽  
Genetic Alterations ◽  
Gene Encoding ◽  
Protein Protein Interaction ◽  
Normal Tissues ◽  
Potential Biomarker

Background: Colorectal cancer is considered the third most fetal among all type of cancer. Spleen tyrosine kinase (SYK) is a non-receptor type tyrosine-protein that plays crucial role in signaling mediated via immune receptor. We adopted an onco-informatics analysis to evaluate the SYK expression and prognostic value of SYK in colorectal cancer, and identification of potential phytochemicals which may inhibit overexpression of SYK protein as well as minimized colorectal cancer. Materials & Methods: Differential expression of SYK gene was analyzed using the several transcriptomic databases including Oncomine, UALCAN, GENT2 and GEPIA2. The server, cBioPortal was used to analyze mutation and copy number alterations whereas GENT2, GEPIA, OncoLnc and PrognoScan were employed to examine the survival rate. A protein-protein interaction network of SYK and co-expressed genes of SYK was conducted via GeneMANIA. Considering SYK gene encoding protein as drug target, selected phytochemicals were assessed by molecular docking using PyRx 0.8 packages. YASARA molecular dynamics simulators were applied for the post validation of the molecular docking data. Results: We have observed significant overexpression of mRNA expression levels of SYK gene colorectal adenocarcinoma (COAD) samples compared with normal tissues. Significant methylation level and various genetic alterations are assembled in SYK gene which can lead to the development of colorectal cancer. As a result, lower level of SYK expression was related to the more chances of patients’ survival by which all the outcomes from the multiple bioinformatics platforms and web resources have demonstrated the significant evidences that the SYK kinsase can possess as a potential biomarker for the treatment of colorectal cancer. Here, aromatic phytochemicals namely, Kaempferol and Glabridin targeting SYK showed more stability compared to controls and may be useful for the treatment of colorectal cancer. Conclusion: Our study showed dysregulated expression of SYK in colorectal cancer and potentiality to act as a biomarker for the prognosis of CRC. Moreover, we have shown phytochemicals (Kaempferol and Glabridin) target SYK as potential treatment strategies and drug repositioning potentiality in colorectal cancer.

scholarly journals Hyaluronan-mediated motility receptor expression functions as a prognostic biomarker in uterine carcinosarcoma based on bioinformatics analysis

2021 ◽  
Vol 49 (6) ◽  
pp. 030006052110210
Author(s):  
Hui Sun ◽  
Li Ma ◽  
Jie Chen
Keyword(s):  
Interaction Network ◽  
Maximal Clique ◽  
Receptor Expression ◽  
The Cancer Genome Atlas ◽  
Uterine Carcinosarcoma ◽  
Sequencing Data ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Normal Tissues ◽  
Potential Biomarker

Objective Uterine carcinosarcoma (UCS) is a rare, aggressive tumour with a high metastasis rate and poor prognosis. This study aimed to explore potential key genes associated with the prognosis of UCS. Methods Transcriptional expression data were downloaded from the Gene Expression Profiling Interactive Analysis database and differentially expressed genes (DEGs) were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses using Metascape. A protein–protein interaction network was constructed using the STRING website and Cytoscape software, and the top 30 genes obtained through the Maximal Clique Centrality algorithm were selected as hub genes. These hub genes were validated by clinicopathological and sequencing data for 56 patients with UCS from The Cancer Genome Atlas database. Results A total of 1894 DEGs were identified, and the top 30 genes were considered as hub genes. Hyaluronan-mediated motility receptor (HMMR) expression was significantly higher in UCS tissues compared with normal tissues, and elevated expression of HMMR was identified as an independent prognostic factor for shorter survival in patients with UCS. Conclusions These results suggest that HMMR may be a potential biomarker for predicting the prognosis of patients with UCS.

scholarly journals Novel diagnostic and prognostic biomarkers of colorectal cancer: Capable to overcome the heterogeneity-specific barrier and valid for global applications

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256020
Author(s):  
Yasir Hameed ◽  
Muhammad Usman ◽  
Shufang Liang ◽  
Samina Ejaz
Keyword(s):  
Colorectal Cancer ◽  
Age Groups ◽  
Colon Adenocarcinoma ◽  
Interaction Network ◽  
Genetic Alterations ◽  
Copy Number Variations ◽  
Clinicopathological Features ◽  
Literature Mining ◽  
Hub Genes ◽  
Protein Protein Interaction

Introduction The heterogeneity-specific nature of the available colorectal cancer (CRC) biomarkers is significantly contributing to the cancer-associated high mortality rate worldwide. Hence, this study was initiated to investigate a system of novel CRC biomarkers that could commonly be employed to the CRC patients and helpful to overcome the heterogenetic-specific barrier. Methods Initially, CRC-related hub genes were extracted through PubMed based literature mining. A protein-protein interaction (PPI) network of the extracted hub genes was constructed and analyzed to identify few more closely CRC-related hub genes (real hub genes). Later, a comprehensive bioinformatics approach was applied to uncover the diagnostic and prognostic role of the identified real hub genes in CRC patients of various clinicopathological features. Results Out of 210 collected hub genes, in total 6 genes (CXCL12, CXCL8, AGT, GNB1, GNG4, and CXCL1) were identified as the real hub genes. We further revealed that all the six real hub genes were significantly dysregulated in colon adenocarcinoma (COAD) patients of various clinicopathological features including different races, cancer stages, genders, age groups, and body weights. Additionally, the dysregulation of real hub genes has shown different abnormal correlations with many other parameters including promoter methylation, overall survival (OS), genetic alterations and copy number variations (CNVs), and CD8+T immune cells level. Finally, we identified a potential miRNA and various chemotherapeutic drugs via miRNA, and real hub genes drug interaction network that could be used in the treatment of CRC by regulating the expression of real hub genes. Conclusion In conclusion, we have identified six real hub genes as potential biomarkers of CRC patients that could help to overcome the heterogenetic-specific barrier across different clinicopathological features.

scholarly journals Elucidating the Mechanisms of Action of Lianhua Qingwen decoction for the Treatment of COVID-19 via Systems Pharmacology Approaches

2021 ◽  
Author(s):  
Xiting Wang ◽  
Tao Lu
Keyword(s):  
Molecular Docking ◽  
Blood Circulation ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Detection Algorithm ◽  
Network Pharmacology ◽  
Systems Pharmacology ◽  
Protein Protein Interaction ◽  
Further Development ◽  
Protein Protein Interaction Network

Abstract Due to the severity of the COVID-19 epidemic, to identify a proper treatment for COVID-19 is of great significance. Traditional Chinese Medicine (TCM) has shown its great potential in the prevention and treatment of COVID-19. One of TCM decoction, Lianhua Qingwen decoction displayed promising treating efficacy. Nevertheless, the underlying molecular mechanism has not been explored for further development and treatment. Through systems pharmacology and network pharmacology approaches, we explored the potential mechanisms of Lianhua Qingwen treating COVID-19 and acting ingredients of Lianhua Qingwen decoction for COVID-19 treatment. Through this way, we generated an ingredients-targets database. We also used molecular docking to screen possible active ingredients. Also, we applied the protein-protein interaction network and detection algorithm to identify relevant protein groupings of Lianhua Qingwen. Totally, 605 ingredients and 1,089 targets were obtained. Molecular Docking analyses revealed that 35 components may be the promising acting ingredients, 7 of which were underlined according to the comprehensive analysis. Our enrichment analysis of the 7 highlighted ingredients showed relevant significant pathways that could be highly related to their potential mechanisms, e.g. oxidative stress response, inflammation, and blood circulation. In summary, this study suggests the promising mechanism of the Lianhua Qingwen decoction for COVID-19 treatment. Further experimental and clinical verifications are still needed.

scholarly journals Downregulation of KIF2C and TEKT2 is Associated with Male Infertility and Testicular Carcinoma

2021 ◽  
Author(s):  
Haiming Cao ◽  
Weiqiang Xu ◽  
Fei Wang ◽  
Xiaofeng LI ◽  
Jianquan Hou
Keyword(s):  
Target Gene ◽  
Interaction Network ◽  
Validation Dataset ◽  
Diagnostic Biomarkers ◽  
Protein Protein Interaction ◽  
Infertile Men ◽  
Potential Biomarker ◽  
Testicular Carcinoma ◽  
Limma Package ◽  
Protein Protein Interaction Network

Abstract Background: Genes have an important role in spermatogenesis and the maintenance of fertility, and may act as a potential biomarker for the clinical diagnosis of infertility. However, a comprehensive understanding of how these biological processes of infertility are regulated at the molecular level remains to be illustrated. Methods: In the present study, we sought to identify associated genes by reanalyzing separate studies from GEO datasets (GSE45885, GSE45887, and GSE9210) and validation dataset (GSE4797). DEGs were used the limma package. GO and KEGG pathway enrichment analyses were performed using the clusterprofier package. The STRING database was used construct a protein-protein interaction network. The interaction between mRNA and TF was predicted by using miRWalk. At last, the expression levels of hub genes were determined by TCGA data in GEPIA. Results: The results showed that several shared genes significantly associated with azoospermia. Finally, we effectively screen out two genes (KIF2C and TEKT2) for validation by GSE4797 in spermatozoa of infertile men with Johnsen score. Among these two genes, KIF2C and TEKT2 significantly down-regulated in spermatozoa of infertile men. The regulatory network of TF‐miRNA‐target gene was established, we found KIF2C-miRNAs(has-miR-3154,6075,6760-5p,1251-5p,186-sp)-TFs(EP300,SP1) might work in spermatozoa of infertile men.Conclusions: Our study might help to improve our understanding of the mechanisms in azoospermia and provide diagnostic biomarkers and therapeutics targets.

Identification and validation of a hub gene prognostic index for hepatocellular carcinoma

2021 ◽  
Author(s):  
Q Shi ◽  
Z Meng ◽  
XX Tian ◽  
YF Wang ◽  
WH Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Prognostic Index ◽  
Interaction Network ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
Cox Regression Analysis ◽  
Protein Protein Interaction ◽  
Normal Tissues ◽  
Significant Independent Prognostic Factor

Aims: We aim to provide new insights into the mechanisms of hepatocellular carcinoma (HCC) and identify key genes as biomarkers for the prognosis of HCC. Materials & methods: Differentially expressed genes between HCC tissues and normal tissues were identified via the Gene Expression Omnibus tool. The top ten hub genes screened by the degree of the protein nodes in the protein–protein interaction network also showed significant associations with overall survival in HCC patients. Results: A prognostic model containing a five-gene signature was constructed to predict the prognosis of HCC via multivariate Cox regression analysis. Conclusion: This study identified a novel five-gene signature ( CDK1, CCNB1, CCNB2, BUB1 and KIF11) as a significant independent prognostic factor.

scholarly journals Comparative proteomics—network analysis of proteins responsible for ursolic acid–induced cytotoxicity in colorectal cancer cells

Tumor Biology ◽  
2017 ◽  
Vol 39 (3) ◽  
pp. 101042831769501 ◽  
Author(s):  
Qiaoyan Cai ◽  
Jing Lin ◽  
Ling Zhang ◽  
Jiumao Lin ◽  
Lili Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Cells ◽  
Ursolic Acid ◽  
Protein Interactions ◽  
Direct Interaction ◽  
Interaction Network ◽  
Two Dimensional Gel Electrophoresis ◽  
Cellular Targets ◽  
Protein Protein Interaction ◽  
Colorectal Cancer Cells

Ursolic acid is a key active compound present in many medicinal herbs that have been widely used in traditional Chinese medicine for the clinical treatment of various cancers. However, the precise mechanisms of its antitumor activity have been poorly understood. To identify the cellular targets of ursolic acid, two-dimensional gel electrophoresis combined with mass spectrometry was performed in this study, which identified 15 proteins with significantly altered levels in protein expression. This demonstrated that ursolic acid–induced cytotoxicity in colorectal cancer cells involves dysregulation in protein folding, signal transduction, cell proliferation, cell cycle, and apoptosis. Corresponding protein regulation was also confirmed by Western blotting. Furthermore, the study of functional association between these 15 proteins revealed that 10 were closely related in a protein–protein interaction network, whereby the proteins either had a direct interaction with each other or were associated via only one intermediary protein. In this instance, the ATP5B/CALR/HSP90B1/HSPB1/HSPD1-signaling network was revealed as the predominant target which was associated with the majority of the observed protein–protein interactions. As a result, the identified targets may be useful in explaining the anticancer mechanisms of ursolic acid and as potential targets for colorectal cancer therapy.

scholarly journals Transcriptome and Gene Fusion Analysis of Synchronous Lesions Reveals lncMRPS31P5 as a Novel Transcript Involved in Colorectal Cancer

2020 ◽  
Vol 21 (19) ◽  
pp. 7120
Author(s):  
Anna Panza ◽  
Stefano Castellana ◽  
Giuseppe Biscaglia ◽  
Ada Piepoli ◽  
Luca Parca ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Chromosomal Translocation ◽  
Normal Tissues ◽  
Novel Transcript ◽  
Non Coding Rna ◽  
Genomic Landscape ◽  
Potential Biomarker ◽  
Fusion Analysis ◽  
Long Non Coding Rna ◽  
Increased Activity

Fusion genes and epigenetic regulators (i.e., miRNAs and long non-coding RNAs) constitute essential pieces of the puzzle of the tumor genomic landscape, in particular in mechanisms behind the adenoma-to-carcinoma progression of colorectal cancer (CRC). In this work, we aimed to identify molecular signatures of the different steps of sporadic CRC development in eleven patients, of which synchronous samples of adenomas, tumors, and normal tissues were analyzed by RNA-Seq. At a functional level, tumors and adenomas were all characterized by increased activity of the cell cycle, cell development, cell growth, and biological proliferation functions. In contrast, organic survival and apoptosis-related functions were inhibited both in tumors and adenomas at different levels. At a molecular level, we found that three individuals shared a tumor-specific fusion named MRPS31-SUGT1, generated through an intra-chromosomal translocation on chromosome 13, whose sequence resulted in being 100% identical to the long non-coding RNA (lncRNA) MRPS31P5. Our analyses suggest that MRPS31P5 could take part to a competitive endogenous (ce)RNA network by acting as a miRNA sponge or/and as an interactor of other mRNAs, and thus it may be an important gene expression regulatory factor and could be used as a potential biomarker for the detection of early CRC events.

scholarly journals Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis

Medicina ◽  
2019 ◽  
Vol 55 (1) ◽  
pp. 20 ◽  
Author(s):  
Md. Rezanur Rahman ◽  
Tania Islam ◽  
Esra Gov ◽  
Beste Turanli ◽  
Gizem Gulfidan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regulatory Networks ◽  
Prognostic Biomarker ◽  
Drug Repositioning ◽  
Gene Expression Omnibus ◽  
Transcriptional Regulatory Networks ◽  
Survival Analyses ◽  
Drug Candidates ◽  
Protein Protein Interaction ◽  
Kaplan Meier

Colorectal cancer (CRC) is the second most common cause of cancer-related death in the world, but early diagnosis ameliorates the survival of CRC. This report aimed to identify molecular biomarker signatures in CRC. We analyzed two microarray datasets (GSE35279 and GSE21815) from the Gene Expression Omnibus (GEO) to identify mutual differentially expressed genes (DEGs). We integrated DEGs with protein–protein interaction and transcriptional/post-transcriptional regulatory networks to identify reporter signaling and regulatory molecules; utilized functional overrepresentation and pathway enrichment analyses to elucidate their roles in biological processes and molecular pathways; performed survival analyses to evaluate their prognostic performance; and applied drug repositioning analyses through Connectivity Map (CMap) and geneXpharma tools to hypothesize possible drug candidates targeting reporter molecules. A total of 727 upregulated and 99 downregulated DEGs were detected. The PI3K/Akt signaling, Wnt signaling, extracellular matrix (ECM) interaction, and cell cycle were identified as significantly enriched pathways. Ten hub proteins (ADNP, CCND1, CD44, CDK4, CEBPB, CENPA, CENPH, CENPN, MYC, and RFC2), 10 transcription factors (ETS1, ESR1, GATA1, GATA2, GATA3, AR, YBX1, FOXP3, E2F4, and PRDM14) and two microRNAs (miRNAs) (miR-193b-3p and miR-615-3p) were detected as reporter molecules. The survival analyses through Kaplan–Meier curves indicated remarkable performance of reporter molecules in the estimation of survival probability in CRC patients. In addition, several drug candidates including anti-neoplastic and immunomodulating agents were repositioned. This study presents biomarker signatures at protein and RNA levels with prognostic capability in CRC. We think that the molecular signatures and candidate drugs presented in this study might be useful in future studies indenting the development of accurate diagnostic and/or prognostic biomarker screens and efficient therapeutic strategies in CRC.

scholarly journals Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ping Yang ◽  
Haifeng He ◽  
Shangfu Xu ◽  
Ping Liu ◽  
Xinyu Bai
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Target Prediction ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

scholarly journals Systematic Analysis of FASTK Gene Family Alterations in Cancer

2021 ◽  
Vol 22 (21) ◽  
pp. 11337
Author(s):  
Lorena Magraner-Pardo ◽  
Dino Gobelli ◽  
Miguel A. de la Fuente ◽  
Tirso Pons ◽  
María Simarro
Keyword(s):  
Mitochondrial Gene ◽  
Interaction Network ◽  
Genetic Alterations ◽  
Future Research ◽  
Mrna Levels ◽  
Systematic Analysis ◽  
Lung Cancers ◽  
Protein Protein Interaction ◽  
Starting Point ◽  
Post Transcriptional Regulation

The FASTK family of proteins have been recently reported to play a key role in the post-transcriptional regulation of mitochondrial gene expression, including mRNA stability and translation. Accumulated studies have provided evidence that the expression of some FASTK genes is altered in certain types of cancer, in agreement with the central role of mitochondria in cancer development. Here, we obtained a pan-cancer overview of the genomic and transcriptomic alterations of FASTK genes. FASTK, FASTKD1, FASTKD3 and FASTKD5 showed the highest rates of genetic alterations. FASTK and FASTKD3 alterations consisted mainly of amplifications that were seen in more than 8% of ovarian and lung cancers, respectively. FASTKD1 and FASTKD5 were the most frequently mutated FASTK genes, and the mutations were identified in 5–7% of uterine cancers, as well as in 4% of melanomas. Our results also showed that the mRNA levels of all FASTK members were strongly upregulated in esophageal, stomach, liver and lung cancers. Finally, the protein-protein interaction network for FASTK proteins uncovers the interaction of FASTK, FASTKD2, FASTKD4 and FASTKD5 with cancer signaling pathways. These results serve as a starting point for future research into the potential of the FASTK family members as diagnostic and therapeutic targets for certain types of cancer.

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