癌症研究中的基因表达:挑战与复杂性

IF 1 Q4 GENETICS & HEREDITY
Hengrui Liu , Zheng Guo , Panpan Wang
{"title":"癌症研究中的基因表达:挑战与复杂性","authors":"Hengrui Liu ,&nbsp;Zheng Guo ,&nbsp;Panpan Wang","doi":"10.1016/j.genrep.2024.102042","DOIUrl":null,"url":null,"abstract":"<div><div>Cancer research is profoundly influenced by the complex interplay of gene expression, yet conventional studies often emphasize genes with high expression levels, potentially overlooking those that contribute subtly to tumorigenesis. This review challenges the standard paradigms by questioning the direct causality often attributed to high gene expression in cancer progression and underscores the importance of distinguishing correlation from causation. It highlights how traditional bulk data analysis might mask crucial cell-specific gene activities, a limitation increasingly addressed by emerging single-cell and spatial transcriptomics, albeit with their own inherent challenges. Additionally, the review delves into the critical roles of both oncogenes and tumor driver genes, advocating for a precise differentiation in research and therapy. Furthermore, it discusses the revolutionary impact of CRISPR technology in identifying essential genes for cancer cell survival, which, while crucial, may not necessarily drive cancer. The complexities of epigenetic regulation and the discrepancies between mRNA and protein expression levels are also explored, emphasizing the necessity for integrated approaches that combine transcriptomics, proteomics, and computational models. This integrated perspective is vital for developing targeted therapies that address the multifaceted nature of gene expression and its regulation in cancer, aiming to refine therapeutic strategies and enhance clinical outcomes.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genetic expression in cancer research: Challenges and complexity\",\"authors\":\"Hengrui Liu ,&nbsp;Zheng Guo ,&nbsp;Panpan Wang\",\"doi\":\"10.1016/j.genrep.2024.102042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Cancer research is profoundly influenced by the complex interplay of gene expression, yet conventional studies often emphasize genes with high expression levels, potentially overlooking those that contribute subtly to tumorigenesis. This review challenges the standard paradigms by questioning the direct causality often attributed to high gene expression in cancer progression and underscores the importance of distinguishing correlation from causation. It highlights how traditional bulk data analysis might mask crucial cell-specific gene activities, a limitation increasingly addressed by emerging single-cell and spatial transcriptomics, albeit with their own inherent challenges. Additionally, the review delves into the critical roles of both oncogenes and tumor driver genes, advocating for a precise differentiation in research and therapy. Furthermore, it discusses the revolutionary impact of CRISPR technology in identifying essential genes for cancer cell survival, which, while crucial, may not necessarily drive cancer. The complexities of epigenetic regulation and the discrepancies between mRNA and protein expression levels are also explored, emphasizing the necessity for integrated approaches that combine transcriptomics, proteomics, and computational models. This integrated perspective is vital for developing targeted therapies that address the multifaceted nature of gene expression and its regulation in cancer, aiming to refine therapeutic strategies and enhance clinical outcomes.</div></div>\",\"PeriodicalId\":12673,\"journal\":{\"name\":\"Gene Reports\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gene Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2452014424001651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gene Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452014424001651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0

摘要

癌症研究受到基因表达复杂相互作用的深刻影响,然而传统研究往往强调高表达水平的基因,却有可能忽略那些对肿瘤发生有微妙作用的基因。这篇综述挑战了标准范式,质疑了高基因表达在癌症进展中通常被归因于直接因果关系的说法,并强调了区分相关性和因果关系的重要性。它强调了传统的批量数据分析如何可能掩盖关键的细胞特异性基因活动,而新兴的单细胞和空间转录组学越来越多地解决了这一局限性,尽管它们也有其固有的挑战。此外,综述还深入探讨了致癌基因和肿瘤驱动基因的关键作用,主张在研究和治疗中进行精确区分。此外,综述还讨论了 CRISPR 技术在确定癌细胞存活的关键基因方面的革命性影响,这些基因虽然至关重要,但不一定会导致癌症。报告还探讨了表观遗传调控的复杂性以及 mRNA 和蛋白质表达水平之间的差异,强调了结合转录组学、蛋白质组学和计算模型的综合方法的必要性。这种综合视角对于开发靶向疗法至关重要,可解决癌症中基因表达及其调控的多面性问题,从而完善治疗策略,提高临床疗效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic expression in cancer research: Challenges and complexity
Cancer research is profoundly influenced by the complex interplay of gene expression, yet conventional studies often emphasize genes with high expression levels, potentially overlooking those that contribute subtly to tumorigenesis. This review challenges the standard paradigms by questioning the direct causality often attributed to high gene expression in cancer progression and underscores the importance of distinguishing correlation from causation. It highlights how traditional bulk data analysis might mask crucial cell-specific gene activities, a limitation increasingly addressed by emerging single-cell and spatial transcriptomics, albeit with their own inherent challenges. Additionally, the review delves into the critical roles of both oncogenes and tumor driver genes, advocating for a precise differentiation in research and therapy. Furthermore, it discusses the revolutionary impact of CRISPR technology in identifying essential genes for cancer cell survival, which, while crucial, may not necessarily drive cancer. The complexities of epigenetic regulation and the discrepancies between mRNA and protein expression levels are also explored, emphasizing the necessity for integrated approaches that combine transcriptomics, proteomics, and computational models. This integrated perspective is vital for developing targeted therapies that address the multifaceted nature of gene expression and its regulation in cancer, aiming to refine therapeutic strategies and enhance clinical outcomes.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Gene Reports
Gene Reports Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
3.30
自引率
7.70%
发文量
246
审稿时长
49 days
期刊介绍: Gene Reports publishes papers that focus on the regulation, expression, function and evolution of genes in all biological contexts, including all prokaryotic and eukaryotic organisms, as well as viruses. Gene Reports strives to be a very diverse journal and topics in all fields will be considered for publication. Although not limited to the following, some general topics include: DNA Organization, Replication & Evolution -Focus on genomic DNA (chromosomal organization, comparative genomics, DNA replication, DNA repair, mobile DNA, mitochondrial DNA, chloroplast DNA). Expression & Function - Focus on functional RNAs (microRNAs, tRNAs, rRNAs, mRNA splicing, alternative polyadenylation) Regulation - Focus on processes that mediate gene-read out (epigenetics, chromatin, histone code, transcription, translation, protein degradation). Cell Signaling - Focus on mechanisms that control information flow into the nucleus to control gene expression (kinase and phosphatase pathways controlled by extra-cellular ligands, Wnt, Notch, TGFbeta/BMPs, FGFs, IGFs etc.) Profiling of gene expression and genetic variation - Focus on high throughput approaches (e.g., DeepSeq, ChIP-Seq, Affymetrix microarrays, proteomics) that define gene regulatory circuitry, molecular pathways and protein/protein networks. Genetics - Focus on development in model organisms (e.g., mouse, frog, fruit fly, worm), human genetic variation, population genetics, as well as agricultural and veterinary genetics. Molecular Pathology & Regenerative Medicine - Focus on the deregulation of molecular processes in human diseases and mechanisms supporting regeneration of tissues through pluripotent or multipotent stem cells.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信