Yakun Yang, Wei Han, Xiaoyu Zhang, Hao Yuan, Ran Wang, Jia Yang, Cuixia An, Dongyang Huang
{"title":"抑郁症相关先天免疫基因和泛癌症基因分析与验证。","authors":"Yakun Yang, Wei Han, Xiaoyu Zhang, Hao Yuan, Ran Wang, Jia Yang, Cuixia An, Dongyang Huang","doi":"10.3389/fgene.2024.1521238","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Depression, a prevalent chronic mental disorder, presents complexities and treatment challenges that drive researchers to seek new, precise therapeutic targets. Additionally, the potential connection between depression and cancer has garnered significant attention.</p><p><strong>Methods: </strong>This study analyzed depression-related gene expression data from the GEO database. Using data normalization, differential expression analysis, WGCNA, and machine learning, we identified core genes strongly associated with depression. These genes were validated in depression patients through q-PCR and examined for expression patterns and potential roles across various cancers.</p><p><strong>Results: </strong>We identified six core genes (GRB10, TDRD9, BCL7A, GPR18, KLRG1, and THEM4) significantly associated with depression and cancer. In depression, GRB10 and TDRD9, involved in cell growth and stress responses, exhibited elevated expression, while BCL7A, GPR18, KLRG1, and THEM4, linked to immune regulation and apoptosis, showed reduced expression, suggesting dysregulated cellular signaling and impaired immune function. In cancer, these genes displayed altered expression patterns across tumor types, influencing tumor progression, prognosis, and immune microenvironment modulation. Shared molecular pathways, such as immune dysregulation and apoptosis, highlight their potential as biomarkers and therapeutic targets for both depression and cancer.</p><p><strong>Conclusion: </strong>This study integrates bioinformatics and machine learning to uncover key molecular pathways and targets for depression, introducing innovative therapeutic prospects that may enhance precision treatment for depression. Furthermore, by revealing shared mechanisms between depression and cancer, we have identified six core genes with significant functional roles in immune regulation, apoptosis, and cellular signaling. These findings not only deepen our understanding of the molecular overlap between these conditions but also lay the groundwork for developing dual-targeted therapeutic strategies. This study uniquely contributes to bridging mental health and oncology research, offering new insights and hope for improving patient outcomes in both fields.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":"15 ","pages":"1521238"},"PeriodicalIF":2.8000,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11757255/pdf/","citationCount":"0","resultStr":"{\"title\":\"Depression-related innate immune genes and pan-cancer gene analysis and validation.\",\"authors\":\"Yakun Yang, Wei Han, Xiaoyu Zhang, Hao Yuan, Ran Wang, Jia Yang, Cuixia An, Dongyang Huang\",\"doi\":\"10.3389/fgene.2024.1521238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Depression, a prevalent chronic mental disorder, presents complexities and treatment challenges that drive researchers to seek new, precise therapeutic targets. Additionally, the potential connection between depression and cancer has garnered significant attention.</p><p><strong>Methods: </strong>This study analyzed depression-related gene expression data from the GEO database. Using data normalization, differential expression analysis, WGCNA, and machine learning, we identified core genes strongly associated with depression. These genes were validated in depression patients through q-PCR and examined for expression patterns and potential roles across various cancers.</p><p><strong>Results: </strong>We identified six core genes (GRB10, TDRD9, BCL7A, GPR18, KLRG1, and THEM4) significantly associated with depression and cancer. In depression, GRB10 and TDRD9, involved in cell growth and stress responses, exhibited elevated expression, while BCL7A, GPR18, KLRG1, and THEM4, linked to immune regulation and apoptosis, showed reduced expression, suggesting dysregulated cellular signaling and impaired immune function. In cancer, these genes displayed altered expression patterns across tumor types, influencing tumor progression, prognosis, and immune microenvironment modulation. Shared molecular pathways, such as immune dysregulation and apoptosis, highlight their potential as biomarkers and therapeutic targets for both depression and cancer.</p><p><strong>Conclusion: </strong>This study integrates bioinformatics and machine learning to uncover key molecular pathways and targets for depression, introducing innovative therapeutic prospects that may enhance precision treatment for depression. Furthermore, by revealing shared mechanisms between depression and cancer, we have identified six core genes with significant functional roles in immune regulation, apoptosis, and cellular signaling. These findings not only deepen our understanding of the molecular overlap between these conditions but also lay the groundwork for developing dual-targeted therapeutic strategies. This study uniquely contributes to bridging mental health and oncology research, offering new insights and hope for improving patient outcomes in both fields.</p>\",\"PeriodicalId\":12750,\"journal\":{\"name\":\"Frontiers in Genetics\",\"volume\":\"15 \",\"pages\":\"1521238\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11757255/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.3389/fgene.2024.1521238\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3389/fgene.2024.1521238","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Depression-related innate immune genes and pan-cancer gene analysis and validation.
Background: Depression, a prevalent chronic mental disorder, presents complexities and treatment challenges that drive researchers to seek new, precise therapeutic targets. Additionally, the potential connection between depression and cancer has garnered significant attention.
Methods: This study analyzed depression-related gene expression data from the GEO database. Using data normalization, differential expression analysis, WGCNA, and machine learning, we identified core genes strongly associated with depression. These genes were validated in depression patients through q-PCR and examined for expression patterns and potential roles across various cancers.
Results: We identified six core genes (GRB10, TDRD9, BCL7A, GPR18, KLRG1, and THEM4) significantly associated with depression and cancer. In depression, GRB10 and TDRD9, involved in cell growth and stress responses, exhibited elevated expression, while BCL7A, GPR18, KLRG1, and THEM4, linked to immune regulation and apoptosis, showed reduced expression, suggesting dysregulated cellular signaling and impaired immune function. In cancer, these genes displayed altered expression patterns across tumor types, influencing tumor progression, prognosis, and immune microenvironment modulation. Shared molecular pathways, such as immune dysregulation and apoptosis, highlight their potential as biomarkers and therapeutic targets for both depression and cancer.
Conclusion: This study integrates bioinformatics and machine learning to uncover key molecular pathways and targets for depression, introducing innovative therapeutic prospects that may enhance precision treatment for depression. Furthermore, by revealing shared mechanisms between depression and cancer, we have identified six core genes with significant functional roles in immune regulation, apoptosis, and cellular signaling. These findings not only deepen our understanding of the molecular overlap between these conditions but also lay the groundwork for developing dual-targeted therapeutic strategies. This study uniquely contributes to bridging mental health and oncology research, offering new insights and hope for improving patient outcomes in both fields.
Frontiers in GeneticsBiochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
5.50
自引率
8.10%
发文量
3491
审稿时长
14 weeks
期刊介绍:
Frontiers in Genetics publishes rigorously peer-reviewed research on genes and genomes relating to all the domains of life, from humans to plants to livestock and other model organisms. Led by an outstanding Editorial Board of the world’s leading experts, this multidisciplinary, open-access journal is at the forefront of communicating cutting-edge research to researchers, academics, clinicians, policy makers and the public.
The study of inheritance and the impact of the genome on various biological processes is well documented. However, the majority of discoveries are still to come. A new era is seeing major developments in the function and variability of the genome, the use of genetic and genomic tools and the analysis of the genetic basis of various biological phenomena.