key genes
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2022 ◽  
Vol 12 ◽  
Qingxia Yang ◽  
Yaguo Gong

Thyroid nodules are present in upto 50% of the population worldwide, and thyroid malignancy occurs in only 5–15% of nodules. Until now, fine-needle biopsy with cytologic evaluation remains the diagnostic choice to determine the risk of malignancy, yet it fails to discriminate as benign or malignant in one-third of cases. In order to improve the diagnostic accuracy and reliability, molecular testing based on transcriptomic data has developed rapidly. However, gene signatures of thyroid nodules identified in a plenty of transcriptomic studies are highly inconsistent and extremely difficult to be applied in clinical application. Therefore, it is highly necessary to identify consistent signatures to discriminate benign or malignant thyroid nodules. In this study, five independent transcriptomic studies were combined to discover the gene signature between benign and malignant thyroid nodules. This combined dataset comprises 150 malignant and 93 benign thyroid samples. Then, there were 279 differentially expressed genes (DEGs) discovered by the feature selection method (Student’s t test and fold change). And the weighted gene co-expression network analysis (WGCNA) was performed to identify the modules of highly co-expressed genes, and 454 genes in the gray module were discovered as the hub genes. The intersection between DEGs by the feature selection method and hub genes in the WGCNA model was identified as the key genes for thyroid nodules. Finally, four key genes (ST3GAL5, NRCAM, MT1F, and PROS1) participated in the pathogenesis of malignant thyroid nodules were validated using an independent dataset. Moreover, a high-performance classification model for discriminating thyroid nodules was constructed using these key genes. All in all, this study might provide a new insight into the key differentiation of benign and malignant thyroid nodules.

Plants ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 211
Erkui Yue ◽  
Yuqing Huang ◽  
Lihua Qian ◽  
Qiujun Lu ◽  
Xianbo Wang ◽  

Tetrastigma hemsleyanum Diels et Gilg is a rare and wild medicinal resource. Metabolites, especially secondary metabolites, have an important influence on T. hemsleyanum adaptability and its medicinal quality. The metabolite proanthocyanidin (PA) is a polyphenol compound widely distributed in land plants, which can be used as antioxidants and anticancer agents. Here, we discovered that three types of PA accumulated in large amounts in purple leaves (PL), but not in green leaves (RG), based on widely non-targeted metabolomics. In addition, we further found that catechins and their derivatives, which are the structural units of PA, are also enriched in PL. Afterwards, we screened and obtained five key genes, DNR1/2, ANS, ANR and LAR closely related to PA biosynthesis through transcriptome analysis and found they were all highly expressed in PL compared to RG. Therefore, observed the regulatory relationship between the main compounds and genes network, and the PA metabolism regulatory pathway was complicated, which may be different to other species.

2022 ◽  
Vol 12 ◽  
Zhixiao Xu ◽  
Chengshui Chen

Background: Interstitial lung disease in systemic sclerosis (SSc-ILD) is one of the most severe complications of systemic sclerosis (SSc) and is the main cause of mortality. In this study, we aimed to explore the key genes in SSc-ILD and analyze the relationship between key genes and immune cell infiltration as well as the key genes relevant to the hallmarks of cancer.Methods: Weighted gene co-expression network analysis (WGCNA) algorithm was implemented to explore hub genes in SSc-ILD samples from the Gene Expression Omnibus (GEO) database. Logistic regression analysis was performed to screen and verify the key gene related to SSc-ILD. CIBERSORT algorithms were utilized to analyze immune cell infiltration. Moreover, the correlation between the key genes and genes relevant to cancer was also evaluated. Furthermore, non-coding RNAs (ncRNAs) linking to PTGS2 were also explored.Results: In this study, we first performed WGCNA analysis for three GEO databases to find the potential hub genes in SSc-ILD. Subsequently, we determined PTGS2 was the key gene in SSC-ILD. Furthermore, in CIBERSORT analyses, PTGS2 were tightly correlated with immune cells such as regulatory T cells (Tregs) and was negatively correlated with CD20 expression. Moreover, PTGS2 was associated with tumor growth. Then, MALAT1, NEAT1, NORAD, XIST identified might be the most potential upstream lncRNAs, and LIMS1 and RANBP2 might be the two most potential upstream circRNAs.Conclusion: Collectively, our findings elucidated that ncRNAs-mediated downregulation of PTGS2, as a key gene in SSc-ILD, was positively related to the occurrence of SSc-ILD and abnormal immunocyte infiltration. It could be a promising factor for SSc-ILD progression to malignancy.

2022 ◽  
Vol 5 (1) ◽  
Xin Hua ◽  
Wei Song ◽  
Kangzong Wang ◽  
Xue Yin ◽  
Changqi Hao ◽  

AbstractThe genes in polyphyllins pathway mixed with other steroid biosynthetic genes form an extremely complex biosynthetic network in Paris polyphylla with a giant genome. The lack of genomic data and tissue specificity causes the study of the biosynthetic pathway notably difficult. Here, we report an effective method for the prediction of key genes of polyphyllin biosynthesis. Full-length transcriptome from eight different organs via hybrid sequencing of next generation sequencingand third generation sequencing platforms annotated two 2,3-oxidosqualene cyclases (OSCs), 216 cytochrome P450s (CYPs), and 199 UDP glycosyltransferases (UGTs). Combining metabolic differences, gene-weighted co-expression network analysis, and phylogenetic trees, the candidate ranges of OSC, CYP, and UGT genes were further narrowed down to 2, 15, and 24, respectively. Beside the three previously characterized CYPs, we identified the OSC involved in the synthesis of cycloartenol and the UGT (PpUGT73CR1) at the C-3 position of diosgenin and pennogenin in P. polyphylla. This study provides an idea for the investigation of gene cluster deficiency biosynthesis pathways in medicinal plants.

PeerJ ◽  
2022 ◽  
Vol 10 ◽  
pp. e12680
Peng Wang ◽  
Zexin Zhang ◽  
Bin Yin ◽  
Jiayuan Li ◽  
Cheng Xialin ◽  

Background Burn patients are prone to infection as well as immunosuppression, which is a significant cause of death. Currently, there is a lack of prognostic biomarkers for immunosuppression in burn patients. This study was conducted to identify immune-related genes that are prognosis biomarkers in post-burn immunosuppression and potential targets for immunotherapy. Methods We downloaded the gene expression profiles and clinical data of 213 burn patients and 79 healthy samples from the Gene Expression Omnibus (GEO) database. Immune infiltration analysis was used to identify the proportion of circulating immune cells. Functional enrichment analyses were carried out to identify immune-related genes that were used to build miRNA-mRNA networks to screen key genes. Next, we carried out correlation analysis between immune cells and key genes that were then used to construct logistic regression models in GSE77791 and were validated in GSE19743. Finally, we determined the expression of key genes in burn patients using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results A total of 745 differently expressed genes were screened out: 299 were up-regulated and 446 were down-regulated. The number of Th-cells (CD4+) decreased while neutrophils increased in burn patients. The enrichment analysis showed that down-regulated genes were enriched in the T-cell activation pathway, while up-regulated genes were enriched in neutrophil activation response in burn patients. We screened out key genes (NFATC2, RORA, and CAMK4) that could be regulated by miRNA. The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945. Finally, we determined that NFATC2, RORA, and CAMK4 were down-regulated in burn patients. Conclusion We found that NFATC2, RORA, and CAMK4 were likely prognostic biomarkers in post-burn immunosuppression and potential immunotherapeutic targets to convert Th-cell dysfunction.

2022 ◽  
Vol 11 ◽  
Lulu Wang ◽  
Dan Zeng ◽  
Qi Wang ◽  
Li Liu ◽  
Tao Lu ◽  

Brain metastases represent a major cause of mortality among patients with breast cancer, and few effective targeted treatment options are currently available. Development of new biomarkers and therapeutic targets for breast cancer brain metastases (BCBM) is therefore urgently needed. In this study, we compared the gene expression profiles of the brain metastatic cell line MDA-MB-231-BR (231-BR) and its parental MDA-MB-231, and identified a total of 84 genes in the primary screening through a series of bioinformatic analyses, including construction of protein-protein interaction (PPI) networks by STRING database, identification of hub genes by applying of MCODE and Cytohubba algorithms, identification of leading-edge subsets of Gene Set Enrichment Analysis (GSEA), and identification of most up-regulated genes. Eight genes were identified as candidate genes due to their elevated expression in brain metastatic 231-BR cells and prognostic values in patients with BCBM. Then we knocked down the eight individual candidate genes in 231-BR cells and evaluated their impact on cell migration through a wound-healing assay, and four of them (KRT19, FKBP10, GSK3B and SPANXB1) were finally identified as key genes. Furthermore, the expression of individual key genes showed a correlation with the infiltration of major immune cells in the brain tumor microenvironment (TME) as analyzed by Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA), suggesting possible roles of them in regulation of the tumor immune response in TME. Therefore, the present work may provide new potential biomarkers for BCBM. Additionally, using GSEA, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis, we determined the top enriched cellular functions or pathways in 231-BR cells, which may help better understand the biology governing the development and progression of BCBM.

Tingna Chen ◽  
Qiuming He ◽  
Zhenxian Xiang ◽  
Rongzhang Dou ◽  
Bin Xiong

Background: Gastric cancer (GC) is aggressive cancer with a poor prognosis. Previously bulk transcriptome analysis was utilized to identify key genes correlated with the development, progression and prognosis of GC. However, due to the complexity of the genetic mutations, there is still an urgent need to recognize core genes in the regulatory network of GC.Methods: Gene expression profiles (GSE66229) were retrieved from the GEO database. Weighted correlation network analysis (WGCNA) was employed to identify gene modules mostly correlated with GC carcinogenesis. R package ‘DiffCorr’ was applied to identify differentially correlated gene pairs in tumor and normal tissues. Cytoscape was adopted to construct and visualize the gene regulatory network.Results: A total of 15 modules were detected in WGCNA analysis, among which three modules were significantly correlated with GC. Then genes in these modules were analyzed separately by “DiffCorr”. Multiple differentially correlated gene pairs were recognized and the network was visualized by the software Cytoscape. Moreover, GEMIN5 and PFDN2, which were rarely discussed in GC, were identified as key genes in the regulatory network and the differential expression was validated by real-time qPCR, WB and IHC in cell lines and GC patient tissues.Conclusions: Our research has shed light on the carcinogenesis mechanism by revealing differentially correlated gene pairs during transition from normal to tumor. We believe the application of this network-based algorithm holds great potential in inferring relationships and detecting candidate biomarkers.

2022 ◽  
Chao Duan ◽  
Feng-Hua Tian ◽  
Lan Yao ◽  
Jian-Hua Lv ◽  
Chuan-Wen Jia ◽  

Abstract In order to explore the molecular mechanism of Sarcomyxa edulis response to lignocelluloses degradation, the developmental transcriptomes was analyzed for six stages covering the whole developmental process, including mycelium growing to half bag (B1), mycelium in cold stimulation after full bag (B2), mycelium in primordia appearing (B3), primordia (B4), mycelium at the harvest stage (B5) and mature fruiting body (B6). A total of 6 samples were used for transcriptome sequencing, with three biological replicates. Based on the above transcriptome data, we constructed a co-expression network of weighted genes associated with extracellular enzyme physiological traits by WGCNA, and obtained 19 gene co-expression modules closely related to lignocelluloses degradation. In addition, a number of key genes involved in lignocelluloses degradation pathways were discovered from the four modules with the highest correlation with target traits. These results provide clues for further study on the molecular genetic mechanisms of Sarcomyxa edulis lignocelluloses degradation.

2022 ◽  
Zhao-min XIE ◽  
Ying-sheng XIAO ◽  
Chun-yan XU ◽  
Qin XIE ◽  
Wen-de WANG ◽  

Abstract Background: Breast cancer (BC) patients have a greater risk of developing thyroid cancer (TC) than the general population. Similarly, TC patients are more likely to develop BC, suggesting an underlying common etiology. In this study, we sought to identify the potential cross-talking pathway and related molecular mechanisms conferring to the sequential development of BC and TC.Methods: We first used Multiple Primary-Standardized Incidence Ratios (MP-SIR) Program of SEER*Stat to calculate SIR to confirm the relationship between BC and TC. Then the RNA-seq was downloaded from The Cancer Genome Atlas (TCGA). And we built a co-expression network via Weighted Gene Co-expression Network Analysis (WGCNA) and obtained the most significant modules. The key genes were obtained by differential gene expression (DGE) analysis and WGCNA analysis. Furthermore, String database and Cytoscape software were used to construct protein-protein interactions (PPI), and defined the maximum Maximal Clique Centrality (MCC) value as hub gene.Then we performed prognosis analysis on the hub genes and obtained the prognostic genes of BC and TC. Finally, gene set enrichment analysis (GSEA) was used to investigate the molecular pathways associated with prognostic gene expressed both in BC and TC.Results: From the SEER database, we found that the risk of developing BC in TC patients was SIR 1.12, 95% CI [1.07, 1.18], and the risk of developing BC in TC patients was SIR 1.29, 95% CI [1.23, 1.26]. Fifty-nine key genes obtained by differential expression analysis and WGCNA identify that PI3K/AKT was the most enriched pathway in BC and TC. In addition, the Recombinant Fibulin 5 (FBLN5) was shown to be of significant prognostic value for both BC and TC and was down-regulated in BC and TC tissues. GSEA demonstrated that FBLN5 enrichment pathways associated with BC and TC mainly included: B cell receptor signaling pathway, steroid hormone biosynthesis, and pathways in cancer.Conclusions: The PI3K/AKT signaling is most co-enriched pathway in BC and TC. FBLN5 is the most relevant prognostic gene and an underlying common tumor suppressor in both BC and TC, with down-stream pathways involving immunity, hormone biosynthesis and carcinogenesis.

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