• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

通过共识策略、富集方法分析和网络构建进行骨肉瘤发病机制的基因优先级排序。

Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis.

机构信息

Grupo de Bio-Quimioinformática, Universidad de Las Américas, Quito 170125, Ecuador.

Carrera de Enfermería, Facultad de Ciencias de la Salud, Universidad de Las Américas, Quito 170125, Ecuador.

出版信息

Int J Mol Sci. 2020 Feb 5;21(3):1053. doi: 10.3390/ijms21031053.

DOI:10.3390/ijms21031053
PMID:32033398
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7038221/
Abstract

Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein-protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events, such as and , and genes associated with DNA repair complexes, like , , , and . In this study, we have identified well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored.

摘要

骨肉瘤是原发性骨癌中最常见的亚型,主要影响青少年。近年来,已有多项研究致力于阐明这种肉瘤的分子机制;然而,其分子病因尚未被准确确定。因此,我们应用了一种共识策略,使用了几种生物信息学工具来优先考虑参与发病机制的基因。随后,我们评估了先前选择基因的物理相互作用,并对该蛋白质-蛋白质相互作用网络应用了共通性分析。共识策略优先考虑了一个总共 553 个基因的列表。我们的富集分析验证了几项描述信号通路 PI3K/AKT 和 MAPK/ERK 作为致病因素的研究。基因本体论将 TP53 描述为主要的信号转导因子,主要介导与细胞周期和 DNA 损伤反应相关的过程。有趣的是,共通性分析将几个涉及转移事件的成员聚类在一起,例如 和 ,以及与 DNA 修复复合物相关的基因,如 、 、 、和 。在这项研究中,我们已经确定了骨肉瘤的一些已知致病基因,并优先考虑了需要进一步探索的基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/ee89dd3b4e8b/ijms-21-01053-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/951a28bb94b3/ijms-21-01053-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/fe86e8ff386f/ijms-21-01053-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/e557718754a4/ijms-21-01053-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/ee89dd3b4e8b/ijms-21-01053-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/951a28bb94b3/ijms-21-01053-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/fe86e8ff386f/ijms-21-01053-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/e557718754a4/ijms-21-01053-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8016/7038221/ee89dd3b4e8b/ijms-21-01053-g004.jpg

相似文献

1
Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis.通过共识策略、富集方法分析和网络构建进行骨肉瘤发病机制的基因优先级排序。
Int J Mol Sci. 2020 Feb 5;21(3):1053. doi: 10.3390/ijms21031053.
2
Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis.基因优先级排序、共性分析、网络和代谢综合途径,以更好地理解乳腺癌发病机制。
Sci Rep. 2018 Nov 12;8(1):16679. doi: 10.1038/s41598-018-35149-1.
3
Identification of key biomarkers and functional pathways in osteosarcomas with lung metastasis: Evidence from bioinformatics analysis.基于生物信息学分析鉴定肺转移骨肉瘤的关键生物标志物和功能途径。
Medicine (Baltimore). 2021 Feb 12;100(6):e24471. doi: 10.1097/MD.0000000000024471.
4
Expression of miR‑542‑3p in osteosarcoma with miRNA microarray data, and its potential signaling pathways.miR-542-3p 在 miRNA 微阵列数据中的表达与骨肉瘤及其潜在信号通路
Mol Med Rep. 2019 Feb;19(2):974-983. doi: 10.3892/mmr.2018.9761. Epub 2018 Dec 13.
5
Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis.子痫前期发病机制中基因优先级确定及联合生物信息学分析的共识策略
BMC Med Genomics. 2017 Aug 8;10(1):50. doi: 10.1186/s12920-017-0286-x.
6
Exploring the association mechanism between metastatic osteosarcoma and non-metastatic osteosarcoma based on dysfunctionality module.基于失能模块探索转移性骨肉瘤与非转移性骨肉瘤的关联机制。
J BUON. 2020 May-Jun;25(3):1569-1578.
7
Identification of characteristic gene modules of osteosarcoma using bioinformatics analysis indicates the possible molecular pathogenesis.利用生物信息学分析鉴定骨肉瘤的特征基因模块,提示可能的分子发病机制。
Mol Med Rep. 2017 Apr;15(4):2113-2119. doi: 10.3892/mmr.2017.6245. Epub 2017 Feb 24.
8
Identification of Key Genes and Pathways in Osteosarcoma by Bioinformatics Analysis.生物信息学分析鉴定骨肉瘤中的关键基因和通路。
Comput Math Methods Med. 2022 Jan 15;2022:7549894. doi: 10.1155/2022/7549894. eCollection 2022.
9
Identification of potential key genes associated with osteosarcoma based on integrated bioinformatics analyses.基于整合生物信息学分析鉴定与骨肉瘤相关的潜在关键基因。
J Cell Biochem. 2019 Aug;120(8):13554-13561. doi: 10.1002/jcb.28630. Epub 2019 Mar 28.
10
Identification of hub genes related to metastasis and prognosis of osteosarcoma and establishment of a prognostic model with bioinformatic methods.基于生物信息学方法鉴定与骨肉瘤转移和预后相关的枢纽基因并构建预后模型。
Medicine (Baltimore). 2024 Jun 7;103(23):e38470. doi: 10.1097/MD.0000000000038470.

引用本文的文献

1
Urolithin A suppressed osteosarcoma cell migration and invasion via targeting MMPs and AKT1.尿石素A通过靶向基质金属蛋白酶(MMPs)和蛋白激酶B1(AKT1)抑制骨肉瘤细胞的迁移和侵袭。
Sci Rep. 2025 Jul 17;15(1):25941. doi: 10.1038/s41598-025-11804-2.
2
Global analysis of actionable genomic alterations in thyroid cancer and precision-based pharmacogenomic strategies.甲状腺癌中可操作基因组改变的全球分析及基于精准医学的药物基因组学策略
Front Pharmacol. 2025 Apr 14;16:1524623. doi: 10.3389/fphar.2025.1524623. eCollection 2025.
3
In Silico Approach for Antibacterial Discovery: PTML Modeling of Virtual Multi-Strain Inhibitors Against .

本文引用的文献

1
GTRD: a database on gene transcription regulation-2019 update.GTRD:一个关于基因转录调控的数据库-2019 年更新。
Nucleic Acids Res. 2019 Jan 8;47(D1):D100-D105. doi: 10.1093/nar/gky1128.
2
Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis.基因优先级排序、共性分析、网络和代谢综合途径,以更好地理解乳腺癌发病机制。
Sci Rep. 2018 Nov 12;8(1):16679. doi: 10.1038/s41598-018-35149-1.
3
The Human Transcription Factors.人类转录因子。
基于计算机模拟的抗菌药物发现方法:针对……的虚拟多菌株抑制剂的PTML建模
Pharmaceuticals (Basel). 2025 Jan 31;18(2):196. doi: 10.3390/ph18020196.
4
Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy.使用多种人工智能算法预测化合物-靶点相互作用并与基于共识的策略进行比较。
J Cheminform. 2024 Mar 7;16(1):27. doi: 10.1186/s13321-024-00816-1.
5
Osteosarcoma Multi-Omics Landscape and Subtypes.骨肉瘤的多组学格局与亚型
Cancers (Basel). 2023 Oct 13;15(20):4970. doi: 10.3390/cancers15204970.
6
Integrated multi-omics analysis reveals the molecular interplay between circadian clocks and cancer pathogenesis.整合多组学分析揭示了生物钟与癌症发病机制之间的分子相互作用。
Sci Rep. 2023 Aug 30;13(1):14198. doi: 10.1038/s41598-023-39401-1.
7
Resources and tools for rare disease variant interpretation.罕见病变异解读的资源与工具。
Front Mol Biosci. 2023 May 10;10:1169109. doi: 10.3389/fmolb.2023.1169109. eCollection 2023.
8
2-Hydroxy-3-methylanthraquinone inhibits homologous recombination repair in osteosarcoma through the MYC-CHK1-RAD51 axis.2-羟基-3-甲基蒽醌通过 MYC-CHK1-RAD51 轴抑制骨肉瘤的同源重组修复。
Mol Med. 2023 Jan 30;29(1):15. doi: 10.1186/s10020-023-00611-y.
9
Knowledge atlas and emerging trends on ncRNAs of osteosarcoma: A bibliometric analysis.骨肉瘤非编码 RNA 相关知识图谱和新兴趋势:文献计量分析。
Front Endocrinol (Lausanne). 2022 Nov 10;13:1028031. doi: 10.3389/fendo.2022.1028031. eCollection 2022.
10
Analyses of Immune System Protein Interactome Network, Single-Cell RNA Sequencing of Human Tissues, and Artificial Neural Networks Reveal Potential Therapeutic Targets for Drug Repurposing Against COVID-19.免疫系统蛋白质相互作用组网络分析、人体组织单细胞RNA测序及人工神经网络揭示了新冠病毒药物再利用的潜在治疗靶点。
Front Pharmacol. 2021 Feb 26;12:598925. doi: 10.3389/fphar.2021.598925. eCollection 2021.
Cell. 2018 Oct 4;175(2):598-599. doi: 10.1016/j.cell.2018.09.045.
4
IL-6 and CXCL8 mediate osteosarcoma-lung interactions critical to metastasis.IL-6 和 CXCL8 介导骨肉瘤-肺相互作用,对转移至关重要。
JCI Insight. 2018 Aug 23;3(16). doi: 10.1172/jci.insight.99791.
5
PML nuclear bodies: from architecture to function.多系统萎缩小体神经元包涵体:从结构到功能。
Curr Opin Cell Biol. 2018 Jun;52:154-161. doi: 10.1016/j.ceb.2018.03.011. Epub 2018 Apr 30.
6
The Role of FoxOs in Bone Health and Disease.FoxOs 在骨骼健康和疾病中的作用。
Curr Top Dev Biol. 2018;127:149-163. doi: 10.1016/bs.ctdb.2017.10.004. Epub 2017 Dec 14.
7
Pml nuclear body disruption cooperates in APL pathogenesis and impairs DNA damage repair pathways in mice.早幼粒细胞白血病核小体解体在 APL 发病机制中起协同作用,并损害小鼠的 DNA 损伤修复途径。
Blood. 2018 Feb 8;131(6):636-648. doi: 10.1182/blood-2017-07-794784. Epub 2017 Nov 30.
8
The Role of Next-Generation Sequencing in Sarcomas: Evolution From Light Microscope to Molecular Microscope.下一代测序技术在肉瘤中的作用:从光显微镜到分子显微镜的演变。
Curr Oncol Rep. 2017 Oct 13;19(12):78. doi: 10.1007/s11912-017-0641-2.
9
Exploring the key genes and pathways of osteosarcoma with pulmonary metastasis using a gene expression microarray.利用基因表达微阵列探索具有肺转移的骨肉瘤的关键基因和通路。
Mol Med Rep. 2017 Nov;16(5):7423-7431. doi: 10.3892/mmr.2017.7577. Epub 2017 Sep 21.
10
Tumor cell-targeted delivery of CRISPR/Cas9 by aptamer-functionalized lipopolymer for therapeutic genome editing of VEGFA in osteosarcoma.通过适配子功能化的脂质聚合物实现 CRISPR/Cas9 对肿瘤细胞的靶向递送,用于骨肉瘤中 VEGFA 的治疗性基因组编辑。
Biomaterials. 2017 Dec;147:68-85. doi: 10.1016/j.biomaterials.2017.09.015. Epub 2017 Sep 13.