Suppr超能文献

精准基因组肿瘤学应用中变异解读的资源

Resources for Interpreting Variants in Precision Genomic Oncology Applications.

作者信息

Tsang Hsinyi, Addepalli KanakaDurga, Davis Sean R

机构信息

Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Gaithersburg, MD, United States.

Attain, LLC, McLean, VA, United States.

出版信息

Front Oncol. 2017 Sep 19;7:214. doi: 10.3389/fonc.2017.00214. eCollection 2017.

Abstract

Precision genomic oncology-applying high throughput sequencing (HTS) at the point-of-care to inform clinical decisions-is a developing precision medicine paradigm that is seeing increasing adoption. Simultaneously, new developments in targeted agents and immunotherapy, when informed by rich genomic characterization, offer potential benefit to a growing subset of patients. Multiple previous studies have commented on methods for identifying both germline and somatic variants. However, interpreting individual variants remains a significant challenge, relying in large part on the integration of observed variants with biological knowledge. A number of data and software resources have been developed to assist in interpreting observed variants, determining their potential clinical actionability, and augmenting them with ancillary information that can inform clinical decisions and even generate new hypotheses for exploration in the laboratory. Here, we review available variant catalogs, variant and functional annotation software and tools, and databases of clinically actionable variants that can be used in an approach with research samples or incorporated into a data platform for interpreting and formally reporting clinical results.

摘要

精准基因组肿瘤学——在临床护理点应用高通量测序(HTS)以指导临床决策——是一种正在逐渐被广泛采用的精准医学模式。同时,在丰富的基因组特征指导下,靶向药物和免疫疗法的新进展为越来越多的患者带来了潜在益处。此前已有多项研究对识别种系和体细胞变异的方法进行了评论。然而,解释单个变异仍然是一项重大挑战,这在很大程度上依赖于将观察到的变异与生物学知识相结合。已经开发了许多数据和软件资源来协助解释观察到的变异,确定其潜在的临床可操作性,并通过辅助信息对其进行补充,这些辅助信息可为临床决策提供依据,甚至为实验室探索产生新的假设。在此,我们综述了可用的变异目录、变异和功能注释软件及工具,以及可用于研究样本或纳入数据平台以解释和正式报告临床结果的临床可操作变异数据库。

相似文献

1
Resources for Interpreting Variants in Precision Genomic Oncology Applications.
Front Oncol. 2017 Sep 19;7:214. doi: 10.3389/fonc.2017.00214. eCollection 2017.
2
A variant by any name: quantifying annotation discordance across tools and clinical databases.
Genome Med. 2017 Jan 26;9(1):7. doi: 10.1186/s13073-016-0396-7.
4
Available resources and challenges for the clinical annotation of somatic variations.
Cancer Cytopathol. 2014 Oct;122(10):730-6. doi: 10.1002/cncy.21471. Epub 2014 Aug 8.
6
An integrated clinical and genomic information system for cancer precision medicine.
BMC Med Genomics. 2018 Apr 20;11(Suppl 2):34. doi: 10.1186/s12920-018-0347-9.
7
Data resources for the identification and interpretation of actionable mutations by clinicians.
Ann Oncol. 2017 May 1;28(5):946-957. doi: 10.1093/annonc/mdx023.
8
Identifying Actionable Variants in Cancer - The Dual Web and Batch Processing Tool MTB-Report.
Stud Health Technol Inform. 2022 Aug 17;296:73-80. doi: 10.3233/SHTI220806.
10
Oncologist use and perception of large panel next-generation tumor sequencing.
Ann Oncol. 2017 Sep 1;28(9):2298-2304. doi: 10.1093/annonc/mdx294.

引用本文的文献

1
RFC1 regulates the expansion of neural progenitors in the developing zebrafish cerebellum.
Nat Commun. 2025 Jul 1;16(1):6019. doi: 10.1038/s41467-025-60775-5.
2
Leveraging artificial intelligence in next generation sequencing for head & neck cancer: opportunities and challenges.
Eur Arch Otorhinolaryngol. 2025 Jun;282(6):3379-3380. doi: 10.1007/s00405-025-09256-5. Epub 2025 Mar 1.
3
Identification of germline population variants misclassified as cancer-associated somatic variants.
Front Med (Lausanne). 2024 Mar 20;11:1361317. doi: 10.3389/fmed.2024.1361317. eCollection 2024.
4
Comparison of Mutation Prevalence in Breast Cancer Across Predicted Ancestry Populations.
JCO Precis Oncol. 2022 Nov;6:e2200341. doi: 10.1200/PO.22.00341.
5
MUSTARD-a comprehensive resource of mutation-specific therapies in cancer.
Database (Oxford). 2021 Jul 26;2021. doi: 10.1093/database/baab042.
6
Knowledge bases and software support for variant interpretation in precision oncology.
Brief Bioinform. 2021 Nov 5;22(6). doi: 10.1093/bib/bbab134.
8
Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers.
PLoS Comput Biol. 2019 Mar 28;15(3):e1006658. doi: 10.1371/journal.pcbi.1006658. eCollection 2019 Mar.
9
Precision medicine review: rare driver mutations and their biophysical classification.
Biophys Rev. 2019 Feb;11(1):5-19. doi: 10.1007/s12551-018-0496-2. Epub 2019 Jan 4.
10
Distribution of KRAS, DDR2, and TP53 gene mutations in lung cancer: An analysis of Iranian patients.
PLoS One. 2018 Jul 26;13(7):e0200633. doi: 10.1371/journal.pone.0200633. eCollection 2018.

本文引用的文献

1
Inferring the molecular and phenotypic impact of amino acid variants with MutPred2.
Nat Commun. 2020 Nov 20;11(1):5918. doi: 10.1038/s41467-020-19669-x.
2
Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations.
Genome Med. 2018 Mar 28;10(1):25. doi: 10.1186/s13073-018-0531-8.
3
OncoKB: A Precision Oncology Knowledge Base.
JCO Precis Oncol. 2017 Jul;2017. doi: 10.1200/PO.17.00011. Epub 2017 May 16.
4
In a major shift, cancer drugs go 'tissue-agnostic'.
Science. 2017 Jun 16;356(6343):1111-1112. doi: 10.1126/science.356.6343.1111.
5
Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade.
Science. 2017 Jul 28;357(6349):409-413. doi: 10.1126/science.aan6733. Epub 2017 Jun 8.
6
Personalized T cell-mediated cancer immunotherapy: progress and challenges.
Curr Opin Biotechnol. 2017 Dec;48:142-152. doi: 10.1016/j.copbio.2017.03.024. Epub 2017 May 8.
8
Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden.
Genome Med. 2017 Apr 19;9(1):34. doi: 10.1186/s13073-017-0424-2.
9
Data resources for the identification and interpretation of actionable mutations by clinicians.
Ann Oncol. 2017 May 1;28(5):946-957. doi: 10.1093/annonc/mdx023.
10
Targeting neoantigens to augment antitumour immunity.
Nat Rev Cancer. 2017 Apr;17(4):209-222. doi: 10.1038/nrc.2016.154. Epub 2017 Feb 24.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验