{"title":"肝细胞癌 RAC1 相关免疫亚型和预后亚型的鉴定与特征描述。","authors":"Wei Wang, Hui Xia, Pei Feng, Bin Dai","doi":"10.1002/jgm.3719","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Hepatocellular carcinoma (HCC) is a malignant tumor with significant variability in prognosis among patients. Ras-related C3 botulinum toxin substrate 1 (RAC1) is a key focus in the area of cancer research. However, the molecular mechanisms of RAC1 in HCC remain incompletely elucidated.</p>\n </section>\n \n <section>\n \n <h3> Materials and methods</h3>\n \n <p>In this study, bioinformatics analysis was used, and public databases were used to obtain information about HCC cases. The samples were categorized into two groups of high and low expression based on the expression level of RAC1 gene. The limma package was used to calculate the differentially expressed genes between the two groups, and univariate Cox regression analysis was used to screen the prognostic related factors. Consensus clustering analysis was performed using the ConsensusClusterPlus package to identify molecular subtypes of HCC patients. Immune cell infiltration and ESTIMATE scores were assessed using the single sample gene set enrichment analysis and ESTIMATE algorithms. The sensitivity of different isoforms to chemotherapeutic agents was predicted by the oncoPredict package. Finally, we also performed cell function experiments to validate the biological role of RAC1 <i>in vitro</i>. Initially, we classified patients into high and low expression groups based on RAC1 gene expression levels and identified 195 up-regulated genes and 107 down-regulated genes. Through univariate Cox regression analysis, we screened out 169 prognosis-related factors. Furthermore, HCC patients were categorized into two subtypes. Subsequently, Kaplan–Meier survival curves showed that there was a significant difference in prognosis between the two molecular subtypes. Further analysis indicated substantial differences in gene expression levels and TIDE scores between two molecular subtypes. Moreover, these two subtypes exhibited varying sensitivity to chemotherapy drugs, as evidenced by differences in IC<sub>50</sub> values. In addition, we found that the silence of RAC1 could effectively inhibit the migration and invasion of HCC cells <i>in vitro</i>.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>This study sheds light on the molecular intricacies of RAC1 in HCC and identifies patient populations that may benefit from immunotherapeutic interventions, with potential implications for tailored treatment strategies.</p>\n </section>\n </div>","PeriodicalId":56122,"journal":{"name":"Journal of Gene Medicine","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification and characterization of RAC1-related immune and prognostic subtypes of hepatocellular carcinoma\",\"authors\":\"Wei Wang, Hui Xia, Pei Feng, Bin Dai\",\"doi\":\"10.1002/jgm.3719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Hepatocellular carcinoma (HCC) is a malignant tumor with significant variability in prognosis among patients. Ras-related C3 botulinum toxin substrate 1 (RAC1) is a key focus in the area of cancer research. However, the molecular mechanisms of RAC1 in HCC remain incompletely elucidated.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Materials and methods</h3>\\n \\n <p>In this study, bioinformatics analysis was used, and public databases were used to obtain information about HCC cases. The samples were categorized into two groups of high and low expression based on the expression level of RAC1 gene. The limma package was used to calculate the differentially expressed genes between the two groups, and univariate Cox regression analysis was used to screen the prognostic related factors. Consensus clustering analysis was performed using the ConsensusClusterPlus package to identify molecular subtypes of HCC patients. Immune cell infiltration and ESTIMATE scores were assessed using the single sample gene set enrichment analysis and ESTIMATE algorithms. The sensitivity of different isoforms to chemotherapeutic agents was predicted by the oncoPredict package. Finally, we also performed cell function experiments to validate the biological role of RAC1 <i>in vitro</i>. Initially, we classified patients into high and low expression groups based on RAC1 gene expression levels and identified 195 up-regulated genes and 107 down-regulated genes. Through univariate Cox regression analysis, we screened out 169 prognosis-related factors. Furthermore, HCC patients were categorized into two subtypes. Subsequently, Kaplan–Meier survival curves showed that there was a significant difference in prognosis between the two molecular subtypes. Further analysis indicated substantial differences in gene expression levels and TIDE scores between two molecular subtypes. Moreover, these two subtypes exhibited varying sensitivity to chemotherapy drugs, as evidenced by differences in IC<sub>50</sub> values. In addition, we found that the silence of RAC1 could effectively inhibit the migration and invasion of HCC cells <i>in vitro</i>.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>This study sheds light on the molecular intricacies of RAC1 in HCC and identifies patient populations that may benefit from immunotherapeutic interventions, with potential implications for tailored treatment strategies.</p>\\n </section>\\n </div>\",\"PeriodicalId\":56122,\"journal\":{\"name\":\"Journal of Gene Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Gene Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jgm.3719\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Gene Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jgm.3719","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
Identification and characterization of RAC1-related immune and prognostic subtypes of hepatocellular carcinoma
Background
Hepatocellular carcinoma (HCC) is a malignant tumor with significant variability in prognosis among patients. Ras-related C3 botulinum toxin substrate 1 (RAC1) is a key focus in the area of cancer research. However, the molecular mechanisms of RAC1 in HCC remain incompletely elucidated.
Materials and methods
In this study, bioinformatics analysis was used, and public databases were used to obtain information about HCC cases. The samples were categorized into two groups of high and low expression based on the expression level of RAC1 gene. The limma package was used to calculate the differentially expressed genes between the two groups, and univariate Cox regression analysis was used to screen the prognostic related factors. Consensus clustering analysis was performed using the ConsensusClusterPlus package to identify molecular subtypes of HCC patients. Immune cell infiltration and ESTIMATE scores were assessed using the single sample gene set enrichment analysis and ESTIMATE algorithms. The sensitivity of different isoforms to chemotherapeutic agents was predicted by the oncoPredict package. Finally, we also performed cell function experiments to validate the biological role of RAC1 in vitro. Initially, we classified patients into high and low expression groups based on RAC1 gene expression levels and identified 195 up-regulated genes and 107 down-regulated genes. Through univariate Cox regression analysis, we screened out 169 prognosis-related factors. Furthermore, HCC patients were categorized into two subtypes. Subsequently, Kaplan–Meier survival curves showed that there was a significant difference in prognosis between the two molecular subtypes. Further analysis indicated substantial differences in gene expression levels and TIDE scores between two molecular subtypes. Moreover, these two subtypes exhibited varying sensitivity to chemotherapy drugs, as evidenced by differences in IC50 values. In addition, we found that the silence of RAC1 could effectively inhibit the migration and invasion of HCC cells in vitro.
Conclusion
This study sheds light on the molecular intricacies of RAC1 in HCC and identifies patient populations that may benefit from immunotherapeutic interventions, with potential implications for tailored treatment strategies.
期刊介绍:
The aims and scope of The Journal of Gene Medicine include cutting-edge science of gene transfer and its applications in gene and cell therapy, genome editing with precision nucleases, epigenetic modifications of host genome by small molecules, siRNA, microRNA and other noncoding RNAs as therapeutic gene-modulating agents or targets, biomarkers for precision medicine, and gene-based prognostic/diagnostic studies.
Key areas of interest are the design of novel synthetic and viral vectors, novel therapeutic nucleic acids such as mRNA, modified microRNAs and siRNAs, antagomirs, aptamers, antisense and exon-skipping agents, refined genome editing tools using nucleic acid /protein combinations, physically or biologically targeted delivery and gene modulation, ex vivo or in vivo pharmacological studies including animal models, and human clinical trials.
Papers presenting research into the mechanisms underlying transfer and action of gene medicines, the application of the new technologies for stem cell modification or nucleic acid based vaccines, the identification of new genetic or epigenetic variations as biomarkers to direct precision medicine, and the preclinical/clinical development of gene/expression signatures indicative of diagnosis or predictive of prognosis are also encouraged.