Identification of Hub Genes and Discovery of Promising Compounds in Gastric Cancer Based on Bioinformatics Analysis

Huang, Jiani; Fang, Wen; Huang, Wenjie; Bai, Yingfeng; Lu, Xiaona; Shu, Ping

doi:10.2217/bmm-2019-0608

Cited by 8 publications

(5 citation statements)

References 64 publications

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“…HJURP [65], CENPA [66], PLK1 [67] and IFI6 [68] were found to significantly increase in gastric cancer tissues compared with normal tissues. In addition, HJURP [69], PLK1 [58], MKI67 [70] and IFI6 [71] have been identified as potential therapeutic target for COVID-19 patients.…”

Section: Discussionmentioning

confidence: 85%

“…A study of peripheral blood transcriptome sequencing in patients with pneumonia found that the expression of UBE2C in patients with severe pneumonia was higher than that in patients with mild pneumonia[64]. HJURP[65], CENPA[66], PLK1[67] and IFI6[68] were found to significantly increase in gastric cancer tissues compared with normal tissues. In addition, HJURP[69], PLK1[58], MKI67[70] and IFI6[71] have been identified as potential therapeutic target for COVID-19 patients.…”

Section: Discussionmentioning

confidence: 99%

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Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Ma,

Huang,

et al. 2024

Preprint

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Background: Coronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused a global pandemic. Gastric cancer (GC) poses a great threat to people's health, which is a high-risk factor for COVID-19. Previous studies have found some associations between GC and COVID-19, whereas the underlying molecular mechanisms are not well understood. Methods: We used a bioinformatics and systems biology approach to investigate the relationship between GC and COVID-19. The gene expression profiles of COVID-19 (GSE196822) and GC (GSE179252) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the shared differentially expressed genes (DEGs) for GC and COVID-19, functional annotation, protein-protein interaction (PPI) network, hub genes, transcriptional regulatory networks and candidate drugs were analyzed. Results: A total of 209 shared DEGs were identified to explore the linkages between COVID-19 and GC. Functional analyses showed that Immune-related pathway collectively participated in the development and progression of COVID-19 and GC. In addition, there are selected 10 hub genes including CDK1, KIF20A, TPX2, UBE2C, HJURP, CENPA, PLK1, MKI67, IFI6, and IFIT2. The transcription factor/gene and miRNA/gene interaction networks identified 38 transcription factors (TFs) and 234 miRNAs. More importantly, we identified ten potential therapeutic agents, including ciclopirox, resveratrol, etoposide, methotrexate, trifluridine, enterolactone, troglitazone, calcitriol, dasatinib and deferoxamine, some of which have been reported to improve and treat GC and COVID-19. This study also provides insight into the diseases most associated with mutual DEGs, which may provide new ideas for research on the treatment of COVID-19. Conclusions: This research has the possibility to be contributed to effective therapeutic in COVID-19 and GC.

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Section: Discussionmentioning

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Ma,

Huang,

et al. 2024

Preprint

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“…As the development of new drugs is a time-consuming and high-risk process, in this case, through gene expression profile technology to find anti-IBC drug targets, the use of drug repositioning technology to explore the novel efficacy of existing drugs, so as to achieve “new uses of old drugs,” which has become an effective measure to improve the input-output ratio of drug development and reduce the risk of failure [ 35 ]. In our study, ten candidate small molecular compounds were identified via CMap database.…”

Section: Discussionmentioning

confidence: 99%

CASP9 As a Prognostic Biomarker and Promising Drug Target Plays a Pivotal Role in Inflammatory Breast Cancer

Zhang

Wang

et al. 2022

International Journal of Analytical Chemistry

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Background. Inflammatory breast cancer (IBC) is one of the most rare and aggressive subtypes of primary breast cancer (BC). Our study aimed to explore hub genes related to the pathogenesis of IBC, which could be considered as novel molecular biomarkers for IBC diagnosis and prognosis. Material and Methods. Two datasets from gene expression omnibus database (GEO) were selected. Enrichment analysis and protein-protein interaction (PPI) network for the DEGs were performed. We analyzed the prognostic values of hub genes in the Kaplan-Meier Plotter. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) was used to find candidate small molecules capable to reverse the gene status of IBC. Results. 157 DEGs were selected in total. We constructed the PPI network with 154 nodes interconnected by 128 interactions. The KEGG pathway analysis indicated that the DEGs were enriched in apoptosis, pathways in cancer and insulin signaling pathway. PTEN, PSMF1, PSMC6, AURKB, FZR1, CASP9, CASP6, CASP8, BAD, AKR7A2, ZNF24, SSX2IP, SIGLEC1, MS4A4A, and VSIG4 were selected as hub genes based on the high degree of connectivity. Six hub genes (PSMC6, AURKB, CASP9, BAD, ZNF24, and SSX2IP) that were significantly associated with the prognosis of breast cancer. The expression of CASP9 protein was associated with prognosis and immune cells infiltration of breast cancer. CASP9- naringenin (NGE) is expected to be the most promising candidate gene-compound interaction for the treatment of IBC. Conclusion. Taken together, CASP9 can be used as a prognostic biomarker and a novel therapeutic target in IBC.

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“…Bioinformatics tools provide extensive technical support for the processing and analysis of gene expression profiles. As a result, bioinformatics analysis has been widely used in recent years to identify novel therapeutic targets and diagnostic markers [37]. In this study, four GEO datasets related to IBDs, GSE156044, GSE159008, GSE102746 and GSE159751, were examined using the Limma package in R statistical software and 368 DEGs were identified.…”

Section: Discussionmentioning

confidence: 99%

Identification of hub genes and potential molecular mechanisms associated with inflammatory bowel diseases using meta-analysis of gene expression data

Mousa

Nassar

2022

Highlights in BioScience

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Inflammatory bowel diseases (IBDs), which primarily include Crohn's disease (CD) and ulcerative colitis (UC), are chronic recurrent diseases of the gastrointestinal tract with increasing prevalence and incidence worldwide. In this study, we aimed to identify key factor genes that control the progression of inflammatory bowel disease, identify common and unique nodal genes, examine gene-protein interactions, assess current advances in the published literature on inflammatory bowel disease, and examine the impact of various biological pathways. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. We performed gene expression analysis to identify deferentially expressed genes. Subsequently, GO and KEGG pathway enrichment analyzes and protein-protein interaction network analyzes (PPI) of DEGs were performed. Text mining was used to examine the frequency of genes in the published IBD literature. Four GEO databases (GSE156044, GSE159751, GSE159008, and GSE102746) were downloaded from GEO databases. A total of 368 DEGs were identified. The results of GO term analysis showed that DEGs were mainly involved in the activity of cytokine receptors, integral components of the plasma membrane, and cytokine-mediated signaling. KEGG pathway analysis showed that DEGs were mainly enriched in bile secretion, mineral absorption, and cytokine-cytokine receptor interaction. The results of PPI analysis showed that about 10 genes were the key genes for the occurrence of CED. Text mining revealed the existence of 399 genes associated with CED. Our results suggest a possible link between CED and other diseases such as triple negative breast cancer (TNBC) and lung adenocarcinoma (LUAD), and provide new insights into the mechanisms of inflammatory bowel disease and new treatment targets.

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Identification of Hub Genes and Discovery of Promising Compounds in Gastric Cancer Based on Bioinformatics Analysis

Cited by 8 publications

References 64 publications

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

CASP9 As a Prognostic Biomarker and Promising Drug Target Plays a Pivotal Role in Inflammatory Breast Cancer

Identification of hub genes and potential molecular mechanisms associated with inflammatory bowel diseases using meta-analysis of gene expression data

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