• 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

从生物分子相互作用机制看癌症严重程度。

Insights into cancer severity from biomolecular interaction mechanisms.

机构信息

CellNetworks, Bioquant, Im Neuenheimer Feld 267, University of Heidelberg, 69120 Heidelberg, Germany.

Biochemie Zentrum Heidelberg, Im Neuenheimer Feld 328, University of Heidelberg, 69120 Heidelberg, Germany.

出版信息

Sci Rep. 2016 Oct 4;6:34490. doi: 10.1038/srep34490.

DOI:10.1038/srep34490
PMID:27698488
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5048291/
Abstract

To attain a deeper understanding of diseases like cancer, it is critical to couple genetics with biomolecular mechanisms. High-throughput sequencing has identified thousands of somatic mutations across dozens of cancers, and there is a pressing need to identify the few that are pathologically relevant. Here we use protein structure and interaction data to interrogate nonsynonymous somatic cancer mutations, identifying a set of 213 molecular interfaces (protein-protein, -small molecule or -nucleic acid) most often perturbed in cancer, highlighting several potentially novel cancer genes. Over half of these interfaces involve protein-small-molecule interactions highlighting their overall importance in cancer. We found distinct differences in the predominance of perturbed interfaces between cancers and histological subtypes and presence or absence of certain interfaces appears to correlate with cancer severity.

摘要

为了更深入地了解癌症等疾病,将遗传学与生物分子机制相结合至关重要。高通量测序已经在数十种癌症中鉴定出数千个体细胞突变,现在迫切需要确定少数与病理相关的突变。在这里,我们使用蛋白质结构和相互作用数据来研究非同义体细胞癌症突变,确定了一组在癌症中经常受到干扰的 213 个分子界面(蛋白质-蛋白质、-小分子或 -核酸),突出了几个潜在的新型癌症基因。这些界面中有一半以上涉及蛋白质-小分子相互作用,突出了它们在癌症中的总体重要性。我们发现,在癌症和组织学亚型之间,受干扰界面的优势存在明显差异,某些界面的存在或缺失似乎与癌症的严重程度相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/6dd9f5c6f340/srep34490-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/44c4b8d968ca/srep34490-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/bb9752f4178c/srep34490-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/5b535acc865a/srep34490-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/3c2ac6bc70d0/srep34490-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/6dd9f5c6f340/srep34490-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/44c4b8d968ca/srep34490-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/bb9752f4178c/srep34490-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/5b535acc865a/srep34490-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/3c2ac6bc70d0/srep34490-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2317/5048291/6dd9f5c6f340/srep34490-f5.jpg

相似文献

1
Insights into cancer severity from biomolecular interaction mechanisms.从生物分子相互作用机制看癌症严重程度。
Sci Rep. 2016 Oct 4;6:34490. doi: 10.1038/srep34490.
2
Identifying Driver Interfaces Enriched for Somatic Missense Mutations in Tumors.识别在肿瘤中因体细胞错义突变而富集的驱动接口。
Methods Mol Biol. 2019;1907:51-72. doi: 10.1007/978-1-4939-8967-6_4.
3
Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces.基于结构的分析揭示癌症错义突变靶向蛋白质相互作用界面。
PLoS One. 2016 Apr 4;11(4):e0152929. doi: 10.1371/journal.pone.0152929. eCollection 2016.
4
Frequent mutations in acetylation and ubiquitination sites suggest novel driver mechanisms of cancer.乙酰化和泛素化位点的频繁突变提示了癌症新的驱动机制。
Genome Med. 2016 May 12;8(1):55. doi: 10.1186/s13073-016-0311-2.
5
Comprehensive assessment of cancer missense mutation clustering in protein structures.蛋白质结构中癌症错义突变聚类的综合评估。
Proc Natl Acad Sci U S A. 2015 Oct 6;112(40):E5486-95. doi: 10.1073/pnas.1516373112. Epub 2015 Sep 21.
6
Proteogenomic Analysis of Single Amino Acid Polymorphisms in Cancer Research.癌症研究中单个氨基酸多态性的蛋白质基因组学分析
Adv Exp Med Biol. 2016;926:93-113. doi: 10.1007/978-3-319-42316-6_7.
7
Integrating mutation and gene expression cross-sectional data to infer cancer progression.整合突变和基因表达横断面数据以推断癌症进展。
BMC Syst Biol. 2016 Jan 25;10:12. doi: 10.1186/s12918-016-0255-6.
8
High-Throughput Genomic Profiling of Adult Solid Tumors Reveals Novel Insights into Cancer Pathogenesis.高通量基因组分析成人实体肿瘤揭示癌症发病机制的新见解。
Cancer Res. 2017 May 1;77(9):2464-2475. doi: 10.1158/0008-5472.CAN-16-2479. Epub 2017 Feb 24.
9
Cancer genetics meets biomolecular mechanism-bridging an age-old gulf.癌症遗传学与生物分子机制相遇——弥合古老的鸿沟。
FEBS Lett. 2018 Feb;592(4):463-474. doi: 10.1002/1873-3468.12988. Epub 2018 Feb 8.
10
Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.机制:预测突变和修饰对分子相互作用的机制影响。
Nucleic Acids Res. 2015 Jan;43(2):e10. doi: 10.1093/nar/gku1094. Epub 2014 Nov 11.

引用本文的文献

1
Comprehensive review of drug resistance in mammalian cancer stem cells: implications for cancer therapy.哺乳动物癌症干细胞耐药性的综合综述:对癌症治疗的启示
Cancer Cell Int. 2024 Dec 18;24(1):406. doi: 10.1186/s12935-024-03558-0.
2
Interface-guided phenotyping of coding variants in the transcription factor RUNX1.转录因子 RUNX1 中编码变异的接口引导表型分析。
Cell Rep. 2024 Jul 23;43(7):114436. doi: 10.1016/j.celrep.2024.114436. Epub 2024 Jul 4.
3
The structural coverage of the human proteome before and after AlphaFold.人类蛋白质组在 AlphaFold 前后的结构覆盖范围。

本文引用的文献

1
Protein-structure-guided discovery of functional mutations across 19 cancer types.基于蛋白质结构的19种癌症类型功能性突变的发现
Nat Genet. 2016 Aug;48(8):827-37. doi: 10.1038/ng.3586. Epub 2016 Jun 13.
2
An organelle-specific protein landscape identifies novel diseases and molecular mechanisms.细胞器特异性蛋白质组图谱鉴定新疾病和分子机制。
Nat Commun. 2016 May 13;7:11491. doi: 10.1038/ncomms11491.
3
Pan-Cancer Analysis of Mutation Hotspots in Protein Domains.蛋白质结构域突变热点的泛癌分析
PLoS Comput Biol. 2022 Jan 24;18(1):e1009818. doi: 10.1371/journal.pcbi.1009818. eCollection 2022 Jan.
4
Predicting functional consequences of mutations using molecular interaction network features.利用分子相互作用网络特征预测突变的功能后果。
Hum Genet. 2022 Jun;141(6):1195-1210. doi: 10.1007/s00439-021-02329-5. Epub 2021 Aug 25.
5
PertInInt: An Integrative, Analytical Approach to Rapidly Uncover Cancer Driver Genes with Perturbed Interactions and Functionalities.PertInInt:一种通过扰动的相互作用和功能快速发现癌症驱动基因的综合分析方法。
Cell Syst. 2020 Jul 22;11(1):63-74.e7. doi: 10.1016/j.cels.2020.06.005. Epub 2020 Jul 14.
6
Molecular switch from MYC to MYCN expression in MYC protein negative Burkitt lymphoma cases.MYC 蛋白阴性伯基特淋巴瘤病例中从 MYC 到 MYCN 表达的分子开关。
Blood Cancer J. 2019 Nov 20;9(12):91. doi: 10.1038/s41408-019-0252-2.
7
3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients.3D 空间组织和基于网络的胶质母细胞瘤突变谱比较揭示了患者间的相似性。
PLoS Comput Biol. 2019 Sep 17;15(9):e1006789. doi: 10.1371/journal.pcbi.1006789. eCollection 2019 Sep.
8
Rare, functional, somatic variants in gene families linked to cancer genes: GPCR signaling as a paradigm.罕见的、功能性的、与癌症基因相关的基因家族中的体细胞变异:以 GPCR 信号转导为例。
Oncogene. 2019 Sep;38(38):6491-6506. doi: 10.1038/s41388-019-0895-2. Epub 2019 Jul 23.
9
Integrating molecular networks with genetic variant interpretation for precision medicine.将分子网络与遗传变异解释相结合,以实现精准医疗。
Wiley Interdiscip Rev Syst Biol Med. 2019 May;11(3):e1443. doi: 10.1002/wsbm.1443. Epub 2018 Dec 12.
10
The Emerging Potential for Network Analysis to Inform Precision Cancer Medicine.网络分析在精准肿瘤医学中的新兴应用潜力
J Mol Biol. 2018 Sep 14;430(18 Pt A):2875-2899. doi: 10.1016/j.jmb.2018.06.016. Epub 2018 Jun 15.
Cell Syst. 2015 Sep 23;1(3):197-209. doi: 10.1016/j.cels.2015.08.014.
4
A Pan-Cancer Catalogue of Cancer Driver Protein Interaction Interfaces.一份癌症驱动蛋白相互作用界面的泛癌图谱。
PLoS Comput Biol. 2015 Oct 20;11(10):e1004518. doi: 10.1371/journal.pcbi.1004518. eCollection 2015 Oct.
5
Comprehensive assessment of cancer missense mutation clustering in protein structures.蛋白质结构中癌症错义突变聚类的综合评估。
Proc Natl Acad Sci U S A. 2015 Oct 6;112(40):E5486-95. doi: 10.1073/pnas.1516373112. Epub 2015 Sep 21.
6
Biochemical and Structural Analysis of Common Cancer-Associated KRAS Mutations.常见癌症相关 KRAS 突变的生化和结构分析。
Mol Cancer Res. 2015 Sep;13(9):1325-35. doi: 10.1158/1541-7786.MCR-15-0203. Epub 2015 Jun 2.
7
Widespread macromolecular interaction perturbations in human genetic disorders.人类遗传疾病中广泛存在的大分子相互作用扰动。
Cell. 2015 Apr 23;161(3):647-660. doi: 10.1016/j.cell.2015.04.013.
8
Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations.基于基因组改变的互斥性对癌症驱动信号通路进行系统鉴定。
Genome Biol. 2015 Feb 26;16(1):45. doi: 10.1186/s13059-015-0612-6.
9
Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets.肝细胞癌的外显子组测序鉴定出新的突变特征和潜在治疗靶点。
Nat Genet. 2015 May;47(5):505-511. doi: 10.1038/ng.3252. Epub 2015 Mar 30.
10
Protein domain-level landscape of cancer-type-specific somatic mutations.癌症类型特异性体细胞突变的蛋白质结构域水平图谱。
PLoS Comput Biol. 2015 Mar 20;11(3):e1004147. doi: 10.1371/journal.pcbi.1004147. eCollection 2015 Mar.