Autophagy plays an important role in immunity and inflammation. The present study aimed to explore the prognostic significance of autophagy-related genes (ARGs) in endometrial cancer (EC) using bioinformatics.
Methods
The list of ARGs was obtained from the Human Autophagy Database. The differentially expressed ARGs (DEARGs) between the EC and normal endometrial tissue samples were screened from The Cancer Genome Atlas database. Cox regression analysis was performed on the DEARGs to screen the prognostic ARGs and construct risk signatures for overall survival (OS) and progression-free survival (PFS). The hub ARGs were identified from a protein–protein interaction network, and CDKN2A was obtained from the intersection of prognostic ARGs and hub ARGs. The association of CDKN2A expression with clinical characteristics and immune infiltration were analyzed. Finally, the role of CDKN2A in autophagy was confirmed in EC cell lines.
Results
CDKN2A, PTK6 and DLC1 were used to establish risk signatures for predicting the survival of EC patients. Receiver operating characteristic curve analysis indicated that the risk signatures can accurately predict both OS and PFS. CDKN2A was the only hub prognostic ARG, and showed significant association with the age, survival status, grade, histological type, body mass index and FIGO (i.e. International Federation of Gynecology and Obstetrics) stage (p < 0.05). Furthermore, CDKN2A expression was also correlated with the infiltration of immune cells, indicating that CDKN2A might play a critical role in regulating the immune microenvironment and immune responses in EC. In addition, silencing of CDKN2A gene promoted autophagy in the HEC-1A cell line and upregulated the expression levels of autophagy-related proteins.
Conclusions
CDKN2A is a prognostic factor and therapeutic target in EC, and is likely associated with the tumor immune landscape and autophagy.
{"title":"Autophagy-related risk signature based on CDNK2A to facilitate survival prediction of patients with endometrial cancer","authors":"Chaomin Yue, Baohua Lin, Xiang Sun, Xindi Xu, Chufan Zhou, Jiaying Fan","doi":"10.1002/jgm.3648","DOIUrl":"https://doi.org/10.1002/jgm.3648","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Autophagy plays an important role in immunity and inflammation. The present study aimed to explore the prognostic significance of autophagy-related genes (ARGs) in endometrial cancer (EC) using bioinformatics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The list of ARGs was obtained from the Human Autophagy Database. The differentially expressed ARGs (DEARGs) between the EC and normal endometrial tissue samples were screened from The Cancer Genome Atlas database. Cox regression analysis was performed on the DEARGs to screen the prognostic ARGs and construct risk signatures for overall survival (OS) and progression-free survival (PFS). The hub ARGs were identified from a protein–protein interaction network, and <i>CDKN2A</i> was obtained from the intersection of prognostic ARGs and hub ARGs. The association of <i>CDKN2A</i> expression with clinical characteristics and immune infiltration were analyzed. Finally, the role of <i>CDKN2A</i> in autophagy was confirmed in EC cell lines.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p><i>CDKN2A, PTK6</i> and <i>DLC1</i> were used to establish risk signatures for predicting the survival of EC patients. Receiver operating characteristic curve analysis indicated that the risk signatures can accurately predict both OS and PFS. <i>CDKN2A</i> was the only hub prognostic ARG, and showed significant association with the age, survival status, grade, histological type, body mass index and FIGO (i.e. International Federation of Gynecology and Obstetrics) stage (<i>p</i> < 0.05). Furthermore, <i>CDKN2A</i> expression was also correlated with the infiltration of immune cells, indicating that <i>CDKN2A</i> might play a critical role in regulating the immune microenvironment and immune responses in EC. In addition, silencing of <i>CDKN2A</i> gene promoted autophagy in the HEC-1A cell line and upregulated the expression levels of autophagy-related proteins.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p><i>CDKN2A</i> is a prognostic factor and therapeutic target in EC, and is likely associated with the tumor immune landscape and autophagy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139110062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The induction of cardiomyocyte (CM) proliferation is a promising approach for cardiac regeneration following myocardial injury. MicroRNAs (miRNAs) have been reported to regulate CM proliferation. In particular, miR-431 expression decreases during cardiac development, according to Gene Expression Omnibus (GEO) microarray data. However, whether miR-431 regulates CM proliferation has not been thoroughly investigated.
Methods
We used integrated bioinformatics analysis of GEO datasets to identify the most significantly differentially expressed miRNAs. Real-time quantitative PCR and fluorescence in situ hybridization were performed to determine the miRNA expression patterns in hearts. Gain- and loss-of-function assays were conducted to detect the role of miRNA in CM proliferation. Additionally, we detected whether miR-431 affected CM proliferation in a myocardial infarction model. The TargetScan, miRDB and miRWalk online databases were used to predict the potential target genes of miRNAs. Luciferase reporter assays were used to study miRNA interactions with the targeting mRNA.
Results
First, we found a significant reduction in miR-431 levels during cardiac development. Then, by overexpression and inhibition of miR-431, we demonstrated that miR-431 promotes CM proliferation in vitro and in vivo, as determined by immunofluorescence assays of 5-ethynyl-2'-deoxyuridine (EdU), pH3, Aurora B and CM count, whereas miR-431 inhibition suppresses CM proliferation. Then, we found that miR-431 improved cardiac function post-myocardial infarction. In addition, we identified FBXO32 as a direct target gene of miR-431, with FBXO32 mRNA and protein expression being suppressed by miR-431. FBXO32 inhibited CM proliferation. Overexpression of FBXO32 blocks the enhanced effect of miR-431 on CM proliferation, suggesting that FBXO32 is a functional target of miR-431 during CM proliferation.
Conclusion
In summary, miR-431 promotes CM proliferation by targeting FBXO32, providing a potential molecular target for preventing myocardial injury.
背景诱导心肌细胞（CM）增殖是心肌损伤后心脏再生的一种可行方法。据报道，微小核糖核酸（miRNA）可调控心肌细胞的增殖。特别是，根据基因表达总库（GEO）的微阵列数据，miR-431 的表达在心脏发育过程中会减少。然而，miR-431 是否调控 CM 增殖尚未得到深入研究。 方法 我们对 GEO 数据集进行了综合生物信息学分析，以确定差异表达最显著的 miRNA。通过实时定量 PCR 和荧光原位杂交确定 miRNA 在心脏中的表达模式。我们还进行了功能增益和功能缺失试验，以检测 miRNA 在 CM 增殖中的作用。此外，我们还检测了 miR-431 是否会影响心肌梗死模型中 CM 的增殖。我们使用 TargetScan、miRDB 和 miRWalk 在线数据库预测 miRNA 的潜在靶基因。荧光素酶报告实验用于研究 miRNA 与靶标 mRNA 的相互作用。 结果 首先，我们发现在心脏发育过程中，miR-431 的水平明显下降。然后，通过过表达和抑制 miR-431，我们证明了 miR-431 在体外和体内促进了 CM 的增殖，这是由 5-乙炔基-2'-脱氧尿苷（EdU）、pH3、极光 B 和 CM 计数的免疫荧光测定确定的，而抑制 miR-431 则抑制了 CM 的增殖。随后，我们发现 miR-431 能改善心肌梗死后的心脏功能。此外，我们还发现 FBXO32 是 miR-431 的直接靶基因，miR-431 可抑制 FBXO32 mRNA 和蛋白的表达。FBXO32 可抑制 CM 增殖。过表达 FBXO32 可阻断 miR-431 对 CM 增殖的增强作用，这表明 FBXO32 是 miR-431 在 CM 增殖过程中的功能靶点。 结论 综上所述，miR-431 通过靶向 FBXO32 促进 CM 增殖，为预防心肌损伤提供了一个潜在的分子靶点。
{"title":"MiR-431 promotes cardiomyocyte proliferation by targeting FBXO32 expression","authors":"Mengsha Li, Chenrui Zhang, Lirong Tan, Tingyan Liu, Tingting Zhu, Xuejiao Wei, Jiacai Liu, Xiaoyun Si, Bing Li","doi":"10.1002/jgm.3656","DOIUrl":"https://doi.org/10.1002/jgm.3656","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The induction of cardiomyocyte (CM) proliferation is a promising approach for cardiac regeneration following myocardial injury. MicroRNAs (miRNAs) have been reported to regulate CM proliferation. In particular, miR-431 expression decreases during cardiac development, according to Gene Expression Omnibus (GEO) microarray data. However, whether miR-431 regulates CM proliferation has not been thoroughly investigated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used integrated bioinformatics analysis of GEO datasets to identify the most significantly differentially expressed miRNAs. Real-time quantitative PCR and fluorescence <i>in situ</i> hybridization were performed to determine the miRNA expression patterns in hearts. Gain- and loss-of-function assays were conducted to detect the role of miRNA in CM proliferation. Additionally, we detected whether miR-431 affected CM proliferation in a myocardial infarction model. The TargetScan, miRDB and miRWalk online databases were used to predict the potential target genes of miRNAs. Luciferase reporter assays were used to study miRNA interactions with the targeting mRNA.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>First, we found a significant reduction in miR-431 levels during cardiac development. Then, by overexpression and inhibition of miR-431, we demonstrated that miR-431 promotes CM proliferation <i>in vitro</i> and <i>in vivo</i>, as determined by immunofluorescence assays of 5-ethynyl-2'-deoxyuridine (EdU), pH3, Aurora B and CM count, whereas miR-431 inhibition suppresses CM proliferation. Then, we found that miR-431 improved cardiac function post-myocardial infarction. In addition, we identified FBXO32 as a direct target gene of miR-431, with FBXO32 mRNA and protein expression being suppressed by miR-431. FBXO32 inhibited CM proliferation. Overexpression of FBXO32 blocks the enhanced effect of miR-431 on CM proliferation, suggesting that FBXO32 is a functional target of miR-431 during CM proliferation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>In summary, miR-431 promotes CM proliferation by targeting FBXO32, providing a potential molecular target for preventing myocardial injury.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139110060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ovarian cancer (OVC) has emerged as a fatal gynecological malignancy as a result of a lack of reliable methods for early detection, limited biomarkers and few treatment options. Immune cell-related telomeric genes (ICRTGs) show promise as potential biomarkers.
Methods
ICRTGs were discovered using weighted gene co-expression network analysis (WGCNA). ICRTGs were screened for significant prognosis using one-way Cox regression analysis. Subsequently, molecular subtypes of prognosis-relevant ICRTGs were constructed and validated for OVC, and the immune microenvironment's landscape across subtypes was compared. OVC prognostic models were built and validated using prognosis-relevant ICRTGs. Additionally, chemotherapy susceptibility drugs for OVC patients in the low- and high-risk groups of ICRTGs were screened using genomics of drug susceptibility to cancer (GDSC). Finally, the immunotherapy response in the low- and high-risk groups was detected using the data from GSE78220. We conducted an immune index correlation analysis of ICRTGs with significant prognoses. The MAP3K4 gene, for which the prognostic correlation coefficient is the highest, was validated using tissue microarrays for a prognostic-immune index correlation.
Results
WGCNA analysis constructed a gene set of ICRTGs and screened 22 genes with prognostic significance. Unsupervised clustering analysis revealed the best molecular typing for two subtypes. The Gene Set Variation Analysis algorithm was used to calculate telomere scores and validate the molecular subtyping. A prognostic model was constructed using 17 ICRTGs. In the The Cancer Genome Atlas-OVC training set and the Gene Expression Omnibus validation set (GSE30161), the risk score model's predicted risk groups and the actual prognosis were shown to be significantly correlated. GDSC screened Axitinib, Bexarotene, Embelin and the GSE78220 datasets and demonstrated that ICRTGs effectively distinguished the group that responds to immunotherapy from the non-responsive group. Additionally, tissue microarray validation results revealed that MAP3K4 significantly predicted patient prognosis. Furthermore, MAP3K4 exhibited a positive association with PD-L1 and a negative relationship with the M1 macrophage markers CD86 and INOS.
Conclusions
ICRTGs may be reliable biomarkers for the molecular typing of patients with OVC, enabling the prediction of prognosis and immunotherapy efficacy.
{"title":"Construction and validation of molecular subtype and signature of immune cell-related telomeric genes and prediction of prognosis and immunotherapy efficacy in ovarian cancer patients","authors":"Lele Ling, Bingrong Li, Huijing Wu, Kaiyong Zhang, Siwen Li, Boliang Ke, Zhengyang Zhu, Te Liu, Peng Liu, Bimeng Zhang","doi":"10.1002/jgm.3606","DOIUrl":"https://doi.org/10.1002/jgm.3606","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Ovarian cancer (OVC) has emerged as a fatal gynecological malignancy as a result of a lack of reliable methods for early detection, limited biomarkers and few treatment options. Immune cell-related telomeric genes (ICRTGs) show promise as potential biomarkers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>ICRTGs were discovered using weighted gene co-expression network analysis (WGCNA). ICRTGs were screened for significant prognosis using one-way Cox regression analysis. Subsequently, molecular subtypes of prognosis-relevant ICRTGs were constructed and validated for OVC, and the immune microenvironment's landscape across subtypes was compared. OVC prognostic models were built and validated using prognosis-relevant ICRTGs. Additionally, chemotherapy susceptibility drugs for OVC patients in the low- and high-risk groups of ICRTGs were screened using genomics of drug susceptibility to cancer (GDSC). Finally, the immunotherapy response in the low- and high-risk groups was detected using the data from GSE78220. We conducted an immune index correlation analysis of ICRTGs with significant prognoses. The MAP3K4 gene, for which the prognostic correlation coefficient is the highest, was validated using tissue microarrays for a prognostic-immune index correlation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>WGCNA analysis constructed a gene set of ICRTGs and screened 22 genes with prognostic significance. Unsupervised clustering analysis revealed the best molecular typing for two subtypes. The Gene Set Variation Analysis algorithm was used to calculate telomere scores and validate the molecular subtyping. A prognostic model was constructed using 17 ICRTGs. In the The Cancer Genome Atlas-OVC training set and the Gene Expression Omnibus validation set (GSE30161), the risk score model's predicted risk groups and the actual prognosis were shown to be significantly correlated. GDSC screened Axitinib, Bexarotene, Embelin and the GSE78220 datasets and demonstrated that ICRTGs effectively distinguished the group that responds to immunotherapy from the non-responsive group. Additionally, tissue microarray validation results revealed that MAP3K4 significantly predicted patient prognosis. Furthermore, MAP3K4 exhibited a positive association with PD-L1 and a negative relationship with the M1 macrophage markers CD86 and INOS.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>ICRTGs may be reliable biomarkers for the molecular typing of patients with OVC, enabling the prediction of prognosis and immunotherapy efficacy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139110063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hao Su, Ziqi Liu, Chaoyue Zhang, Zebin Deng, Xiaozhe Su, Yinhuai Wang, Wentao Liu
Background
A prognostic model of bladder cancer was constructed based on costimulatory molecules, and its stability and accuracy were verified in different datasets.
Method
The expression profile of bladder cancer RNA and the corresponding clinical data in The Cancer Genome Atlas (TCGA) database were analyzed employing computational biology, and a prognostic model was constructed for costimulating molecule-related genes. The model was applied in GSE160693, GSE176307, Xiangya_Cohort, GSE13507, GSE19423, GSE31684, GSE32894, GSE48075, GSE69795 and GSE70691 in TCGA dataset and Gene Expression Omnibus database. The role of costimulating molecules in bladder cancer tumor subtypes was also explored. By consistent cluster analysis, bladder cancer in the TCGA dataset was categorized into two subtypes: C1 and C2. The C1 subtype exhibited a poor prognosis, high levels of immune cell infiltration and significant enrichment of natural killer cells, T cells and dendritic cells in the C1 subtype. In addition, the ImmuneScore calculated by the ESTIMATE algorithm differed greatly between the two subtypes, and the ImmuneScore of the C1 subtype was greater than the C2 subtype in a significant manner.
Results
This study also assessed the relationship between costimulating molecules and immunotherapy response. The high-risk group responded poorly to immunotherapy, with significant differences in the amount of most immune cells between the two groups. Further, three indices of the ESTIMATE algorithm and 22 immune cells of the CIBERSORT algorithm were significantly correlated with risk values. These findings suggest the potential value of costimulating molecules in predicting immunotherapy response.
Conclusion
A costimulatory molecule-based prognostic model for bladder cancer was established and validated across multiple datasets. This model introduces a novel mode for tailoring treatments to each individual with bladder cancer, and offers valuable insights for informed clinical choices. Simultaneously, this research also delved into the significance of costimulating molecules within distinct bladder cancer subtypes, shedding novel insights into improving immunotherapy strategies for the treatment of bladder cancer.
{"title":"Exploration of the prognostic effect of costimulatory genes in bladder cancer","authors":"Hao Su, Ziqi Liu, Chaoyue Zhang, Zebin Deng, Xiaozhe Su, Yinhuai Wang, Wentao Liu","doi":"10.1002/jgm.3655","DOIUrl":"https://doi.org/10.1002/jgm.3655","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>A prognostic model of bladder cancer was constructed based on costimulatory molecules, and its stability and accuracy were verified in different datasets.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>The expression profile of bladder cancer RNA and the corresponding clinical data in The Cancer Genome Atlas (TCGA) database were analyzed employing computational biology, and a prognostic model was constructed for costimulating molecule-related genes. The model was applied in GSE160693, GSE176307, Xiangya_Cohort, GSE13507, GSE19423, GSE31684, GSE32894, GSE48075, GSE69795 and GSE70691 in TCGA dataset and Gene Expression Omnibus database. The role of costimulating molecules in bladder cancer tumor subtypes was also explored. By consistent cluster analysis, bladder cancer in the TCGA dataset was categorized into two subtypes: C1 and C2. The C1 subtype exhibited a poor prognosis, high levels of immune cell infiltration and significant enrichment of natural killer cells, T cells and dendritic cells in the C1 subtype. In addition, the ImmuneScore calculated by the ESTIMATE algorithm differed greatly between the two subtypes, and the ImmuneScore of the C1 subtype was greater than the C2 subtype in a significant manner.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>This study also assessed the relationship between costimulating molecules and immunotherapy response. The high-risk group responded poorly to immunotherapy, with significant differences in the amount of most immune cells between the two groups. Further, three indices of the ESTIMATE algorithm and 22 immune cells of the CIBERSORT algorithm were significantly correlated with risk values. These findings suggest the potential value of costimulating molecules in predicting immunotherapy response.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>A costimulatory molecule-based prognostic model for bladder cancer was established and validated across multiple datasets. This model introduces a novel mode for tailoring treatments to each individual with bladder cancer, and offers valuable insights for informed clinical choices. Simultaneously, this research also delved into the significance of costimulating molecules within distinct bladder cancer subtypes, shedding novel insights into improving immunotherapy strategies for the treatment of bladder cancer.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139110061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ji-Lin Chen, Na Li, Min Xu, Lei Wang, Jie Sun, Li Liu, Yu-Fei Wang, Bao-Lei Zhang, Hai-Yang Suo, Ting-Hua Wang, Fang Wang
<div> <section> <h3> Background</h3> <p>The aim of this study was to determine the effect of human urine-derived stem cells (HUSCs) for the treatment of spinal cord injury (SCI) and investigate associated the molecular network mechanism by using bioinformatics combined with experimental validation.</p> </section> <section> <h3> Methods</h3> <p>After the contusive SCI model was established, the HUSC-expressed specific antigen marker was implanted into the injury site immediately, and the Basso, Beattie and Bresnahan locomotor rating scale (BBB scale) was utilized to evaluate motor function so as to determine the effect of HUSCs for the neural repair after SCI. Then, the geneCards database was used to collect related gene targets for both HUSCs and SCI, and cross genes were merged with the findings of PubMed screen. Subsequently, protein–protein interaction (PPI) network, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment, as well as core network construction, were performed using Cytoscape software. Lastly, real-time quantitative polymerase chain reaction (PCR) and immunofluorescence were employed to validate the mRNA expression and localization of 10 hub genes, and two of the most important, designated as cadherin 1 (CDH1) and integrin subunit beta 1 (ITGB1), were identified successfully.</p> </section> <section> <h3> Results</h3> <p>The immunophenotypes of HUSCs were marked by CD90+ and CD44+ but not CD45, and flow cytometry confirmed their character. The expression rates of CD90, CD73, CD44 and CD105 in HUSCs were 99.49, 99.77, 99.82 and 99.51%, respectively, while the expression rates of CD43, CD45, CD11b and HLA-DR were 0.08, 0.30, 1.34 and 0.02%, respectively. After SCI, all rats appeared to have severe motor dysfunction, but the BBB score was increased in HUSC-transplanted rats compared with control rats at 28 days. By using bioinformatics, we obtained 6668 targets for SCI and 1095 targets for HUSCs and identified a total of 645 cross targets between HUSCs and SCI. Based on the PPI and Cytoscape analysis, CD44, ACTB, FN1, ITGB1, HSPA8, CDH1, ALB, HSP90AA1 and GAPDH were identified as possible therapeutic targets. Enrichment analysis revealed that the involved signal pathways included complement and coagulation cascades, lysosome, systemic lupus erythematosus, etc. Lastly, quantificational real-time (qRT)-PCR confirmed the mRNA differential expression of CDH1/ITGB1 after HUSC therapy, and glial fibrillary acidic protein (GFAP) immunofluorescence staining showed that the astrocyte proliferation at the injured site could be reduced significantly after HUSC treatment.</p> </section> <section> <h3> Conclusions</h3>
{"title":"Implantation of human urine stem cells promotes neural repair in spinal cord injury rats associated cadeharin-1 and integrin subunit beta 1 expression","authors":"Ji-Lin Chen, Na Li, Min Xu, Lei Wang, Jie Sun, Li Liu, Yu-Fei Wang, Bao-Lei Zhang, Hai-Yang Suo, Ting-Hua Wang, Fang Wang","doi":"10.1002/jgm.3615","DOIUrl":"10.1002/jgm.3615","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The aim of this study was to determine the effect of human urine-derived stem cells (HUSCs) for the treatment of spinal cord injury (SCI) and investigate associated the molecular network mechanism by using bioinformatics combined with experimental validation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>After the contusive SCI model was established, the HUSC-expressed specific antigen marker was implanted into the injury site immediately, and the Basso, Beattie and Bresnahan locomotor rating scale (BBB scale) was utilized to evaluate motor function so as to determine the effect of HUSCs for the neural repair after SCI. Then, the geneCards database was used to collect related gene targets for both HUSCs and SCI, and cross genes were merged with the findings of PubMed screen. Subsequently, protein–protein interaction (PPI) network, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment, as well as core network construction, were performed using Cytoscape software. Lastly, real-time quantitative polymerase chain reaction (PCR) and immunofluorescence were employed to validate the mRNA expression and localization of 10 hub genes, and two of the most important, designated as cadherin 1 (CDH1) and integrin subunit beta 1 (ITGB1), were identified successfully.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The immunophenotypes of HUSCs were marked by CD90+ and CD44+ but not CD45, and flow cytometry confirmed their character. The expression rates of CD90, CD73, CD44 and CD105 in HUSCs were 99.49, 99.77, 99.82 and 99.51%, respectively, while the expression rates of CD43, CD45, CD11b and HLA-DR were 0.08, 0.30, 1.34 and 0.02%, respectively. After SCI, all rats appeared to have severe motor dysfunction, but the BBB score was increased in HUSC-transplanted rats compared with control rats at 28 days. By using bioinformatics, we obtained 6668 targets for SCI and 1095 targets for HUSCs and identified a total of 645 cross targets between HUSCs and SCI. Based on the PPI and Cytoscape analysis, CD44, ACTB, FN1, ITGB1, HSPA8, CDH1, ALB, HSP90AA1 and GAPDH were identified as possible therapeutic targets. Enrichment analysis revealed that the involved signal pathways included complement and coagulation cascades, lysosome, systemic lupus erythematosus, etc. Lastly, quantificational real-time (qRT)-PCR confirmed the mRNA differential expression of CDH1/ITGB1 after HUSC therapy, and glial fibrillary acidic protein (GFAP) immunofluorescence staining showed that the astrocyte proliferation at the injured site could be reduced significantly after HUSC treatment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 ","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138824281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The cover image is based on the Research Article Therapeutic strategy for Fabry disease by intravenous administration of adeno-associated virus 2 or 9 in α-galactosidase A-deficient mice by Yuka Hayashi et al., https://doi.org/10.1002/jgm.3560.
封面图片来自 Yuka Hayashi 等人撰写的研究文章《在α-半乳糖苷酶 A 缺失小鼠体内静脉注射腺相关病毒 2 或 9 治疗法布里病的策略》，https://doi.org/10.1002/jgm.3560。
{"title":"Featured Cover","authors":"Yuka Hayashi, Yoshihide Sehara, Ryota Watano, Kenji Ohba, Yuki Takayanagi, Kazuhiro Muramatsu, Yoshio Sakiyama, Hiroaki Mizukami","doi":"10.1002/jgm.3652","DOIUrl":"https://doi.org/10.1002/jgm.3652","url":null,"abstract":"<p>The cover image is based on the Research Article <i>Therapeutic strategy for Fabry disease by intravenous administration of adeno-associated virus 2 or 9 in α-galactosidase A-deficient mice</i> by Yuka Hayashi et al., https://doi.org/10.1002/jgm.3560.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"25 12","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jgm.3652","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138739907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Immune cell homeostasis plays a crucial role in cancer research and therapeutic response. While chemotherapy and immunotherapy hold promise in treating osteosarcoma (OS), identifying patients who are likely to respond would significantly improve clinical practices. Necroptosis, a fundamental mechanism mediating chemotherapy and immunotherapy efficacy, offers valuable insights. In this context, subtypes based on necroptosis-related genes have been established to predict the response of OS patients to immunotherapy and chemotherapy.
Methods
We conducted a high-throughput screening test to identify necroptosis-associated genes that regulate the development of osteosarcoma. Subsequently, the ConsensusClusterPlus package was employed to classify OS patients into subtypes, enabling comparisons of prognosis and clinical information between these subtypes. Patients from the TARGET-OS and GSE21257 datasets were stratified into high-risk and low-risk groups, and their prognoses were compared. Additionally, we assessed the accuracy of the Risk Scoring Model in predicting prognosis, identified independent prognostic factors and explored potential chemotherapeutic agents and immunotherapy drugs.
Results
Through the intersection of expression profiles from the TARGET-OS and GSE21257 datasets, we have identified a total of 92 genes associated with necroptosis. Based on differences in the expression of these genes, patients were divided into three subtypes, and we investigated the differences in tumor-infiltrating immune cells, immune-related pathways, and prognosis among these subtypes. Our nomogram effectively differentiated subtypes with distinct responses to chemotherapy and immunotherapy. The established signature demonstrated superior prediction ability compared with single clinical indicators.
Conclusions
This pioneering study unveils the prognostic role of necroptosis-related genes in OS patients, providing a promising alternative for prognostic prediction in clinical disease management. Moreover, our findings highlight the significance of immune cell homeostasis in cancer research and therapeutic response, underscoring its relevance in advancing current treatment strategies.
{"title":"Necrotizing apoptosis-related genes prognosis and treatment effect analysis of osteosarcoma in children","authors":"Yuanling Chen, Ling Wu, Yunyan Li, Jika Zheng, Shiling Zhong, Shirong Gu, Jingyang Chen","doi":"10.1002/jgm.3646","DOIUrl":"10.1002/jgm.3646","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Immune cell homeostasis plays a crucial role in cancer research and therapeutic response. While chemotherapy and immunotherapy hold promise in treating osteosarcoma (OS), identifying patients who are likely to respond would significantly improve clinical practices. Necroptosis, a fundamental mechanism mediating chemotherapy and immunotherapy efficacy, offers valuable insights. In this context, subtypes based on necroptosis-related genes have been established to predict the response of OS patients to immunotherapy and chemotherapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a high-throughput screening test to identify necroptosis-associated genes that regulate the development of osteosarcoma. Subsequently, the ConsensusClusterPlus package was employed to classify OS patients into subtypes, enabling comparisons of prognosis and clinical information between these subtypes. Patients from the TARGET-OS and GSE21257 datasets were stratified into high-risk and low-risk groups, and their prognoses were compared. Additionally, we assessed the accuracy of the Risk Scoring Model in predicting prognosis, identified independent prognostic factors and explored potential chemotherapeutic agents and immunotherapy drugs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Through the intersection of expression profiles from the TARGET-OS and GSE21257 datasets, we have identified a total of 92 genes associated with necroptosis. Based on differences in the expression of these genes, patients were divided into three subtypes, and we investigated the differences in tumor-infiltrating immune cells, immune-related pathways, and prognosis among these subtypes. Our nomogram effectively differentiated subtypes with distinct responses to chemotherapy and immunotherapy. The established signature demonstrated superior prediction ability compared with single clinical indicators.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This pioneering study unveils the prognostic role of necroptosis-related genes in OS patients, providing a promising alternative for prognostic prediction in clinical disease management. Moreover, our findings highlight the significance of immune cell homeostasis in cancer research and therapeutic response, underscoring its relevance in advancing current treatment strategies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138682253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Esophageal squamous cell carcinoma (ESCC) has poor survival. Effective prognostic models with high application value remain lack.
Methods
Bulk RNA seq and single cell RNA-seq data were retrieved from the XENA-TCGA-ESCC cohort and GSE188900. The anoikis-related gene score (ANO score) model and tumor microenvironment score (TME score) model were constructed and merged into three subgroups. Functional annotation was analyzed by Gene Ontology terms. Univariate and multivariate Cox regression analysis, least absolute shrinkage and selection operator regression analysis and weighted gene coexpression network analysis were performed to construct prognostic prediction models and identify prognostic value. Kaplan–Meier survival curves were drawn for evaluating the overall survival (OS) of patients classified by different score subgroups. Immunotherapy response and mutation analyses were also conducted.
Results
In the ANO score model, TNFSF10 was an independent factor for the prognosis of ESCC patients. The area under the curve values of the ANO–TME score model in predicting the OS were 0.638 at 5 years and 0.632 at 7 years. Patients in the ANO low score–TME high score group had a much longer OS than patients in any other ANO–TME score subgroup (p < 0.001), suggesting a higher prognostic value. The differentially expressed genes of the ANO low score–TME high score group were mainly involved in cell adhesion molecules, nucleotide excision repair, the TGF-β signaling pathway and mismatch repair. TP53 (92%), TTN (38%) and NFE2L2 (31%) were the top genes with highest mutant frequency in the ANO low score–TME high score group.
Conclusions
A novel prognostic prediction model with high application value was constructed and identified for ESCC patients, which may provide evidence for immunotherapy in the treatment of ESCC.
食管鳞状细胞癌（ESCC）的生存率很低。目前仍缺乏具有较高应用价值的有效预后模型。
{"title":"Identification of prognostic value of anoikis-related gene score model combined with tumor microenvironment score models in esophageal squamous cell carcinoma","authors":"Moyan Zhang, Yicheng Liang, Peng Song","doi":"10.1002/jgm.3624","DOIUrl":"10.1002/jgm.3624","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Esophageal squamous cell carcinoma (ESCC) has poor survival. Effective prognostic models with high application value remain lack.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Bulk RNA seq and single cell RNA-seq data were retrieved from the XENA-TCGA-ESCC cohort and GSE188900. The anoikis-related gene score (ANO score) model and tumor microenvironment score (TME score) model were constructed and merged into three subgroups. Functional annotation was analyzed by Gene Ontology terms. Univariate and multivariate Cox regression analysis, least absolute shrinkage and selection operator regression analysis and weighted gene coexpression network analysis were performed to construct prognostic prediction models and identify prognostic value. Kaplan–Meier survival curves were drawn for evaluating the overall survival (OS) of patients classified by different score subgroups. Immunotherapy response and mutation analyses were also conducted.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In the ANO score model, TNFSF10 was an independent factor for the prognosis of ESCC patients. The area under the curve values of the ANO–TME score model in predicting the OS were 0.638 at 5 years and 0.632 at 7 years. Patients in the ANO low score–TME high score group had a much longer OS than patients in any other ANO–TME score subgroup (<i>p</i> < 0.001), suggesting a higher prognostic value. The differentially expressed genes of the ANO low score–TME high score group were mainly involved in cell adhesion molecules, nucleotide excision repair, the TGF-<i>β</i> signaling pathway and mismatch repair. TP53 (92%), TTN (38%) and NFE2L2 (31%) were the top genes with highest mutant frequency in the ANO low score–TME high score group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>A novel prognostic prediction model with high application value was constructed and identified for ESCC patients, which may provide evidence for immunotherapy in the treatment of ESCC.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138682252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Breast cancer is the most commonly diagnosed cancer among women. The primary treatment options include surgery, radiotherapy, chemotherapy, targeted therapy and hormone therapy. The effectiveness of breast cancer therapy varies depending on the stage and aggressiveness of the cancer, as well as individual factors. Advances in early detection and improved treatments have significantly increased survival rates for breast cancer patients. Nevertheless, specific subtypes of breast cancer, particularly triple-negative breast cancer, still lack effective treatment strategies. Thus, novel and effective therapeutic targets for breast cancer need to be explored. As substrates of protein synthesis, amino acids are important sources of energy and nutrition, only secondly to glucose. The rich supply of amino acids enables the tumor to maintain its proliferative competence through participation in energy generation, nucleoside synthesis and maintenance of cellular redox balance. Amino acids also play an important role in immune-suppressive microenvironment formation. Thus, the biological effects of amino acids may change unexpectedly in tumor-specific or oncogene-dependent manners. In recent years, there has been significant progress in the study of amino acid metabolism, particularly in their potential application as therapeutic targets in breast cancer. In this review, we provide an update on amino acid metabolism and discuss the therapeutic implications of amino acids in breast cancer.
{"title":"Amino acids and their roles in tumor immunotherapy of breast cancer","authors":"Hongzhuo Xia, Jianyu Zhu, Zhuomeng Zheng, Peiyao Xiao, Xiaohui Yu, Muyao Wu, Lian Xue, Xi Xu, Xinyu Wang, Yuxuan Guo, Chanjuan Zheng, Siyu Ding, Yian Wang, Xiaoning Peng, Shujun Fu, Junjun Li, Xiyun Deng","doi":"10.1002/jgm.3647","DOIUrl":"10.1002/jgm.3647","url":null,"abstract":"<p>Breast cancer is the most commonly diagnosed cancer among women. The primary treatment options include surgery, radiotherapy, chemotherapy, targeted therapy and hormone therapy. The effectiveness of breast cancer therapy varies depending on the stage and aggressiveness of the cancer, as well as individual factors. Advances in early detection and improved treatments have significantly increased survival rates for breast cancer patients. Nevertheless, specific subtypes of breast cancer, particularly triple-negative breast cancer, still lack effective treatment strategies. Thus, novel and effective therapeutic targets for breast cancer need to be explored. As substrates of protein synthesis, amino acids are important sources of energy and nutrition, only secondly to glucose. The rich supply of amino acids enables the tumor to maintain its proliferative competence through participation in energy generation, nucleoside synthesis and maintenance of cellular redox balance. Amino acids also play an important role in immune-suppressive microenvironment formation. Thus, the biological effects of amino acids may change unexpectedly in tumor-specific or oncogene-dependent manners. In recent years, there has been significant progress in the study of amino acid metabolism, particularly in their potential application as therapeutic targets in breast cancer. In this review, we provide an update on amino acid metabolism and discuss the therapeutic implications of amino acids in breast cancer.</p>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138575144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Melanoma, a frequently encountered cutaneous malignancy characterized by a poor prognosis, persists in presenting formidable challenges despite the advancement in molecularly targeted drugs designed to improve survival rates significantly. Unfortunately, as more therapeutic choices have developed over time, the gradual emergence of drug resistance has become a notable impediment to the effectiveness of these therapeutic interventions. The hepatocyte growth factor (HGF)/c-met signaling pathway has attracted considerable attention, associated with drug resistance stemming from multiple potential mutations within the c-met gene. The activation of the HGF/c-met pathway operates in an autocrine manner in melanoma. Notably, a key player in the regulatory orchestration of HGF/c-met activation is the long non-coding RNA MEG3.
Methods
Melanoma tissues were collected to measure MEG3 expression. In vitro validation was performed on MEG3 to prove its oncogenic roles. Bioinformatic analyses were conducted on the TCGA database to build the MEG3-related score. The immune characteristics and mutation features of the MEG3-related score were explored.
Results
We revealed a negative correlation between HGF and MEG3. In melanoma cells, HGF inhibited MEG3 expression by augmenting the methylation of the MEG3 promoter. Significantly, MEG3 exhibits a suppressive impact on the proliferation and migration of melanoma cells, concurrently inhibiting c-met expression. Moreover, a predictive model centered around MEG3 demonstrates notable efficacy in forecasting critical prognostic indicators, immunological profiles, and mutation statuses among melanoma patients.
Conclusions
The present study highlights the potential of MEG3 as a pivotal regulator of c-met, establishing it as a promising candidate for targeted drug development in the ongoing pursuit of effective therapeutic interventions.
{"title":"HGF facilitates methylation of MEG3, potentially implicated in vemurafenib resistance in melanoma","authors":"Xiaomin Jia, Hao Feng, Shan He, Xiao Chen, Hao Feng, Mingliang Chen, Xing Hu","doi":"10.1002/jgm.3644","DOIUrl":"10.1002/jgm.3644","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Melanoma, a frequently encountered cutaneous malignancy characterized by a poor prognosis, persists in presenting formidable challenges despite the advancement in molecularly targeted drugs designed to improve survival rates significantly. Unfortunately, as more therapeutic choices have developed over time, the gradual emergence of drug resistance has become a notable impediment to the effectiveness of these therapeutic interventions. The hepatocyte growth factor (HGF)/c-met signaling pathway has attracted considerable attention, associated with drug resistance stemming from multiple potential mutations within the c-met gene. The activation of the HGF/c-met pathway operates in an autocrine manner in melanoma. Notably, a key player in the regulatory orchestration of HGF/c-met activation is the long non-coding RNA MEG3.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Melanoma tissues were collected to measure MEG3 expression. In vitro validation was performed on MEG3 to prove its oncogenic roles. Bioinformatic analyses were conducted on the TCGA database to build the MEG3-related score. The immune characteristics and mutation features of the MEG3-related score were explored.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We revealed a negative correlation between HGF and MEG3. In melanoma cells, HGF inhibited MEG3 expression by augmenting the methylation of the MEG3 promoter. Significantly, MEG3 exhibits a suppressive impact on the proliferation and migration of melanoma cells, concurrently inhibiting c-met expression. Moreover, a predictive model centered around MEG3 demonstrates notable efficacy in forecasting critical prognostic indicators, immunological profiles, and mutation statuses among melanoma patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The present study highlights the potential of MEG3 as a pivotal regulator of c-met, establishing it as a promising candidate for targeted drug development in the ongoing pursuit of effective therapeutic interventions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":"26 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138567065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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