Depression-related innate immune genes and pan-cancer gene analysis and validation.

IF 2.8 3区 生物学 Q2 GENETICS & HEREDITY Frontiers in Genetics Pub Date : 2025-01-10 eCollection Date: 2024-01-01 DOI:10.3389/fgene.2024.1521238
Yakun Yang, Wei Han, Xiaoyu Zhang, Hao Yuan, Ran Wang, Jia Yang, Cuixia An, Dongyang Huang
{"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}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
抑郁症相关先天免疫基因和泛癌症基因分析与验证。
背景:抑郁症是一种普遍存在的慢性精神障碍,其复杂性和治疗挑战促使研究人员寻求新的、精确的治疗靶点。此外,抑郁症和癌症之间的潜在联系也引起了人们的极大关注。方法:本研究分析来自GEO数据库的抑郁症相关基因表达数据。通过数据归一化、差异表达分析、WGCNA和机器学习,我们确定了与抑郁症密切相关的核心基因。这些基因通过q-PCR在抑郁症患者中得到验证,并检查了各种癌症的表达模式和潜在作用。结果:我们发现了6个核心基因(GRB10、TDRD9、BCL7A、GPR18、KLRG1和THEM4)与抑郁和癌症显著相关。在抑郁症中,参与细胞生长和应激反应的GRB10和TDRD9表达升高,而与免疫调节和细胞凋亡相关的BCL7A、GPR18、KLRG1和THEM4表达降低,提示细胞信号失调,免疫功能受损。在癌症中,这些基因在不同肿瘤类型中表现出不同的表达模式,影响肿瘤进展、预后和免疫微环境调节。共享的分子通路,如免疫失调和细胞凋亡,突出了它们作为抑郁症和癌症的生物标志物和治疗靶点的潜力。结论:本研究将生物信息学与机器学习相结合,揭示了抑郁症的关键分子通路和靶点,为抑郁症的精准治疗提供了创新的治疗前景。此外,通过揭示抑郁症和癌症之间的共同机制,我们已经确定了六个在免疫调节、细胞凋亡和细胞信号传导中发挥重要功能作用的核心基因。这些发现不仅加深了我们对这些疾病之间分子重叠的理解,而且为开发双靶向治疗策略奠定了基础。这项研究独特地为心理健康和肿瘤研究提供了桥梁,为改善这两个领域的患者预后提供了新的见解和希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Frontiers in Genetics
Frontiers in Genetics Biochemistry, 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.
期刊最新文献
BHLHE41-SLC7A11 transcriptional axis and chromatin remodeling signatures in osteogenic-lineage disulfidptosis-like stress in osteoporosis. Functional inactivation of MDR3 caused by a homozygous ABCB4 missense variant leading to liver failure. Multi-omics analysis to identify the dynamic changes of immune cells and marker genes in renal fibrosis. Single-cell sequencing reveals the functional heterogeneity of melanoma cells and their crosstalk with the tumor microenvironment. TTN variants in pediatric cardiomyopathy: a retrospective cohort study.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1