Up-regulation of GINS1 highlighted a good diagnostic and prognostic potential of survival in three different subtypes of human cancer

2024 ◽  
Vol 84 ◽  
Author(s):  
M. Ahmad ◽  
Y. Hameed ◽  
M. Khan ◽  
M Usman ◽  
A. Rehman ◽  
...  
Keyword(s):  
Immune Cells ◽  
Promoter Methylation ◽  
Prognostic Biomarker ◽  
Human Cancer ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Copy Number Variations ◽  
Pathway Enrichment Analysis ◽  
Poor Overall Survival ◽  
Cancer Subtypes

Abstract Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.

SHMT2 is Associated with Tumor Purity, CD8+ T Immune Cells Infiltration, and a Novel Therapeutic Target in Four Different Human Cancers

2022 ◽  
Vol 22 ◽  
Author(s):  
Muhammad Usman ◽  
Yasir Hameed ◽  
Mukhtiar Ahmad ◽  
Muhammad Junaid Iqbal ◽  
Aghna Maryam ◽  
...  
Keyword(s):  
Immune Cells ◽  
Promoter Methylation ◽  
In Silico ◽  
Human Cancer ◽  
Enrichment Analysis ◽  
Genetic Alterations ◽  
Pathway Enrichment Analysis ◽  
Human Cancers ◽  
Tumor Purity

Aims: This study was launched to identify the SHMT2 associated Human Cancer subtypes. Background: Cancer is the 2nd leading cause of death worldwide. Previous reports revealed the limited involvement of SHMT2 in human cancer. In the current study, we comprehensively analyzed the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Objective:: We aim to comprehensively analyze the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Earlier, limited knowledge exists in the medical literature regarding the involvement of Serine Hydroxymethyltransferase 2 (SHMT2) in human cancer. Methods: In the current study, we comprehensively analyzed the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Pan-cancer transcriptional expression profiling of SHMT2 was done using UALCAN while further validation was performed using GENT2. For translational profiling of SHMT2, we utilized Human Protein Atlas (HPA) platform. Promoter methylation, genetic alteration, and copy number variations (CNVs) profiles were analyzed through MEXPRESS and cBioPortal. Survival analysis was carried out through Kaplan–Meier (KM) plotter platform. Pathway enrichment analysis of SHMT2 was performed using DAVID, while the gene-drug network was drawn through CTD and Cytoscape. Furthermore, in the tumor microenvironment, a correlation between tumor purity, CD8+ T immune cells infiltration, and SHMT2 expression was accessed using TIMER. Results: SHMT2 was found overexpressed in 24 different subtypes of human cancers and its overexpression was significantly associated with the reduced Overall survival (OS) and Relapse-free survival durations of Breast cancer (BRCA), Kidney renal papillary cell carcinoma (KIRP), Liver hepatocellular carcinoma (LIHC), and Lung adenocarcinoma (LUAD) patients. This implies that SHMT2 plays a significant role in the development and progression of these cancers. We further noticed that SHMT2 was also up-regulated in BRCA, KIRP, LIHC, and LUAD patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of SHMT2 enriched genes in five diverse pathways. Furthermore, we also explored some interesting correlations between SHMT2 expression and promoter methylation, genetic alterations, CNVs, tumor purity, and CD8+ T immune cell infiltrates. Conclusion: Our results suggested that overexpressed SHMT2 is correlated with the reduced OS and RFS of the BRCA, KIRP, LIHC, and LUAD patients and can be a potential diagnostic and prognostic biomarker for these cancers.

scholarly journals CTHRC1 expression is a novel shared diagnostic and prognostic biomarker of survival in six different human cancer subtypes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nuzhat Sial ◽  
Mukhtiar Ahmad ◽  
Muhammad Safdar Hussain ◽  
Muhammad Junaid Iqbal ◽  
Yasir Hameed ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Prognostic Biomarker ◽  
Human Cancer ◽  
Enrichment Analysis ◽  
Genetic Alterations ◽  
Renal Clear Cell Carcinoma ◽  
Clinicopathological Features ◽  
Cancer Subtypes ◽  
Normal Tissues ◽  
Collagen Triple Helix

AbstractAccording to the previous reports, the collagen triple helix repeat containing 1 (CTHRC1) causes tumorigenesis by modulating the tumor microenvironment, however, the evidence is limited to a few human cancer subtypes. In the current study, we analyzed and validated the CTHRC1 expression variations in 24 different human cancer tissues paired with normal tissues using publically available databases. We observed that CTHRC1 was overexpressed in all the 24 major subtypes of human cancers and its overexpression was significantly associated with the reduced overall survival (OS) duration of head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), Lung adenocarcinoma (LUAD), stomach adenocarcinoma (STAD), and Uterine corpus endometrial carcinoma (UCEC). This implies that CTHRC1 plays a significant role in the development and progression of these cancers. We further noticed that CTHRC1 was also overexpressed in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of CTHRC1 associated genes in seven diverse pathways. We also explored few interesting correlations between CTHRC1 expression and promoter methylation, genetic alterations, CNVs, CD8+ T immune cells infiltration, and tumor purity. In conclusion, CTHRC1 can serve as a shared diagnostic and prognostic biomarker in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features.

scholarly journals Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suthanthiram Backiyarani ◽  
Rajendran Sasikala ◽  
Simeon Sharmiladevi ◽  
Subbaraya Uma
Keyword(s):  
Candidate Genes ◽  
Protein Interaction ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Auxin Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

scholarly journals Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minglong Guan ◽  
Lan Guo ◽  
Hengli Ma ◽  
Huimei Wu ◽  
Xiaoyun Fan
Keyword(s):  
Biological Activity ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Rosmarinic Acid ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

2021 ◽  
pp. 153537022110487
Author(s):  
Zirui Zhu ◽  
Rui Huang ◽  
Baojun Huang
Keyword(s):  
Messenger Rna ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rank Aggregation ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

scholarly journals In Silico Discovery of Candidate Drugs against Covid-19

Viruses ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 404 ◽  
Author(s):  
Claudia Cava ◽  
Gloria Bertoli ◽  
Isabella Castiglioni
Keyword(s):  
Gene Expression ◽  
In Silico ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Basic Mechanism ◽  
Cell Receptor ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.

scholarly journals Comparative Proteomic Analysis of Molecular Differences between Leaves of Wild-Type Upland Cotton and Its Fuzzless-Lintless Mutant

Molecules ◽  
2019 ◽  
Vol 24 (20) ◽  
pp. 3769
Author(s):  
Liping Zhu ◽  
Bowen Zheng ◽  
Wangyang Song ◽  
Chengcheng Tao ◽  
Xiang Jin ◽  
...  
Keyword(s):  
Proteomic Analysis ◽  
Upland Cotton ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gossypol Content ◽  
Pathway Enrichment Analysis ◽  
Protein Accumulation ◽  
Wild Type ◽  
Protein Protein Interaction ◽  
Comparative Proteomic Analysis

Fuzzless-lintless mutant (fl) ovules of upland cotton have been used to investigate cotton fiber development for decades. However, the molecular differences of green tissues between fl and wild-type (WT) cotton were barely reported. Here, we found that gossypol content, the most important secondary metabolite of cotton leaves, was higher in Gossypium hirsutum L. cv Xuzhou-142 (Xu142) WT than in fl. Then, we performed comparative proteomic analysis of the leaves from Xu142 WT and its fl. A total of 4506 proteins were identified, of which 103 and 164 appeared to be WT- and fl-specific, respectively. In the 4239 common-expressed proteins, 80 and 74 were preferentially accumulated in WT and fl, respectively. Pathway enrichment analysis and protein–protein interaction network analysis of both variety-specific and differential abundant proteins showed that secondary metabolism and chloroplast-related pathways were significantly enriched. Quantitative real-time PCR confirmed that the expression levels of 12 out of 16 selected genes from representative pathways were consistent with their protein accumulation patterns. Further analyses showed that the content of chlorophyll a in WT, but not chlorophyll b, was significantly increased compared to fl. This work provides the leaf proteome profiles of Xu142 and its fl mutant, indicating the necessity of further investigation of molecular differences between WT and fl leaves.

scholarly journals A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Sha Di ◽  
Lin Han ◽  
Qing Wang ◽  
Xinkui Liu ◽  
Yingying Yang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Regulation Of Blood Pressure ◽  
Protein Protein Interaction Network

Shen-Qi-Di-Huang decoction (SQDHD), a well-known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein-protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine-mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice.

scholarly journals Prediction and Validation of Hub Genes Associated with Colorectal Cancer by Integrating PPI Network and Gene Expression Data

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yongfu Xiong ◽  
Wenxian You ◽  
Rong Wang ◽  
Linglong Peng ◽  
Zhongxue Fu
Keyword(s):  
Colorectal Cancer ◽  
Mrna Expression ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Advanced Tumor Stage ◽  
Ppi Network ◽  
Hub Genes ◽  
Clinical Value ◽  
Advanced Tumor

Although hundreds of colorectal cancer- (CRC-) related genes have been screened, the significant hub genes still need to be further identified. The aim of this study was to identify the hub genes based on protein-protein interaction network and uncover their clinical value. Firstly, 645 CRC patients’ data from the Tumor Cancer Genome Atlas were downloaded and analyzed to screen the differential expression genes (DEGs). And then, the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed, and PPI network of the DEGs was constructed by Cytoscape software. Finally, four hub genes (CXCL3, ELF5, TIMP1, and PHLPP2) were obtained from four subnets and further validated in our clinical setting and TCGA dataset. The results showed that mRNA expression of CXCL3, ELF5, and TIMP1 was increased in CRC tissues, whereas PHLPP2 mRNA expression was decreased. More importantly, high expression of CXCL3, ELF5, and TIMP1 was significantly associated with lymphatic invasion, distance metastasis, and advanced tumor stage. In addition, a shorter overall survival was observed in patients with increased CXCL3, TIMP1, and ELF5 expression and decreased PHLPP2 expression. In conclusion, the four hub genes screened by our strategy could serve as novel biomarkers for prognosis prediction of CRC patients.

scholarly journals Identification of novel genes and pathways in carotid atheroma using integrated bioinformatic methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Wenqing Nai ◽  
Diane Threapleton ◽  
Jingbo Lu ◽  
Kewei Zhang ◽  
Hongyuan Wu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Transforming Growth Factor ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Transforming Growth Factor Β ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Atheromatous Plaques

Abstract Atherosclerosis is the primary cause of cardiovascular events and its molecular mechanism urgently needs to be clarified. In our study, atheromatous plaques (ATH) and macroscopically intact tissue (MIT) sampled from 32 patients were compared and an integrated series of bioinformatic microarray analyses were used to identify altered genes and pathways. Our work showed 816 genes were differentially expressed between ATH and MIT, including 443 that were up-regulated and 373 that were down-regulated in ATH tissues. GO functional-enrichment analysis for differentially expressed genes (DEGs) indicated that genes related to the “immune response” and “muscle contraction” were altered in ATHs. KEGG pathway-enrichment analysis showed that up-regulated DEGs were significantly enriched in the “FcεRI-mediated signaling pathway”, while down-regulated genes were significantly enriched in the “transforming growth factor-β signaling pathway”. Protein-protein interaction network and module analysis demonstrated that VAV1, SYK, LYN and PTPN6 may play critical roles in the network. Additionally, similar observations were seen in a validation study where SYK, LYN and PTPN6 were markedly elevated in ATH. All in all, identification of these genes and pathways not only provides new insights into the pathogenesis of atherosclerosis, but may also aid in the development of prognostic and therapeutic biomarkers for advanced atheroma.

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