Suppr超能文献

与生存结果相关的泛癌预后基因突变及临床病理因素:一项系统综述

Pan-cancer prognostic genetic mutations and clinicopathological factors associated with survival outcomes: a systematic review.

作者信息

Gammall Jurgita, Lai Alvina G

机构信息

Institute of Health Informatics, University College London, London, UK.

Cerner Limited, London, UK.

出版信息

NPJ Precis Oncol. 2022 Apr 20;6(1):27. doi: 10.1038/s41698-022-00269-5.

Abstract

Cancer is a leading cause of death, accounting for almost 10 million deaths annually worldwide. Personalised therapies harnessing genetic and clinical information may improve survival outcomes and reduce the side effects of treatments. The aim of this study is to appraise published evidence on clinicopathological factors and genetic mutations (single nucleotide polymorphisms [SNPs]) associated with prognosis across 11 cancer types: lung, colorectal, breast, prostate, melanoma, renal, glioma, bladder, leukaemia, endometrial, ovarian. A systematic literature search of PubMed/MEDLINE and Europe PMC was conducted from database inception to July 1, 2021. 2497 publications from PubMed/MEDLINE and 288 preprints from Europe PMC were included. Subsequent reference and citation search was conducted and a further 39 articles added. 2824 articles were reviewed by title/abstract and 247 articles were selected for systematic review. Majority of the articles were retrospective cohort studies focusing on one cancer type, 8 articles were on pan-cancer level and 6 articles were reviews. Studies analysing clinicopathological factors included 908,567 patients and identified 238 factors, including age, gender, stage, grade, size, site, subtype, invasion, lymph nodes. Genetic studies included 210,802 patients and identified 440 gene mutations associated with cancer survival, including genes TP53, BRCA1, BRCA2, BRAF, KRAS, BIRC5. We generated a comprehensive knowledge base of biomarkers that can be used to tailor treatment according to patients' unique genetic and clinical characteristics. Our pan-cancer investigation uncovers the biomarker landscape and their combined influence that may help guide health practitioners and researchers across the continuum of cancer care from drug development to long-term survivorship.

摘要

癌症是主要的死亡原因,全球每年有近1000万人死于癌症。利用基因和临床信息的个性化疗法可能会改善生存结果并减少治疗的副作用。本研究的目的是评估已发表的关于11种癌症类型(肺癌、结直肠癌、乳腺癌、前列腺癌、黑色素瘤、肾癌、神经胶质瘤、膀胱癌、白血病、子宫内膜癌、卵巢癌)中与预后相关的临床病理因素和基因突变(单核苷酸多态性[SNPs])的证据。从数据库建立到2021年7月1日,对PubMed/MEDLINE和欧洲PMC进行了系统的文献检索。纳入了PubMed/MEDLINE的2497篇出版物和欧洲PMC的288篇预印本。随后进行了参考文献和引文检索,并增加了39篇文章。通过标题/摘要对2824篇文章进行了审查,选择了247篇文章进行系统评价。大多数文章是针对一种癌症类型的回顾性队列研究,8篇文章是泛癌水平的研究,6篇文章是综述。分析临床病理因素的研究纳入了908567名患者,确定了238个因素,包括年龄、性别、分期、分级、大小、部位、亚型、浸润、淋巴结等。基因研究纳入了210802名患者,确定了440个与癌症生存相关的基因突变,包括TP53、BRCA1、BRCA2、BRAF、KRAS、BIRC5等基因。我们生成了一个全面的生物标志物知识库,可用于根据患者独特的基因和临床特征量身定制治疗方案。我们的泛癌研究揭示了生物标志物的全貌及其综合影响,这可能有助于指导医疗从业者和研究人员在从药物开发到长期生存的整个癌症治疗过程中提供帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13e9/9021198/843e2899fe04/41698_2022_269_Fig1_HTML.jpg

相似文献

8
Systemic treatments for metastatic cutaneous melanoma.
Cochrane Database Syst Rev. 2018 Feb 6;2(2):CD011123. doi: 10.1002/14651858.CD011123.pub2.

引用本文的文献

1
Pancancer outcome prediction via a unified weakly supervised deep learning model.
Signal Transduct Target Ther. 2025 Sep 3;10(1):285. doi: 10.1038/s41392-025-02374-w.
5
The Human Pathology Atlas for deciphering the prognostic features of human cancers.
EBioMedicine. 2025 Jan;111:105495. doi: 10.1016/j.ebiom.2024.105495. Epub 2024 Dec 10.
7
Enabling preprint discovery, evaluation, and analysis with Europe PMC.
PLoS One. 2024 Sep 26;19(9):e0303005. doi: 10.1371/journal.pone.0303005. eCollection 2024.
8
Clinical signature and associated immune metabolism of NLRP1 in pan-cancer.
J Cell Mol Med. 2024 Sep;28(18):e70100. doi: 10.1111/jcmm.70100.
10
Single-cell analysis reveals the disparities in immune profiles between younger and elder patients.
Eur Geriatr Med. 2024 Oct;15(5):1509-1522. doi: 10.1007/s41999-024-01032-8. Epub 2024 Sep 8.

本文引用的文献

1
The PRISMA 2020 statement: An updated guideline for reporting systematic reviews.
PLoS Med. 2021 Mar 29;18(3):e1003583. doi: 10.1371/journal.pmed.1003583. eCollection 2021 Mar.
2
Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.
CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4.
3
BIRC5 is a prognostic biomarker associated with tumor immune cell infiltration.
Sci Rep. 2021 Jan 11;11(1):390. doi: 10.1038/s41598-020-79736-7.
4
Biomarker-Driven Oncology Clinical Trials: Key Design Elements, Types, Features, and Practical Considerations.
JCO Precis Oncol. 2019 Oct 24;3. doi: 10.1200/PO.19.00086. eCollection 2019.
5
Biomarker-guided trials: Challenges in practice.
Contemp Clin Trials Commun. 2019 Nov 16;16:100493. doi: 10.1016/j.conctc.2019.100493. eCollection 2019 Dec.
7
Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer.
Br J Cancer. 2017 Aug 22;117(5):744-751. doi: 10.1038/bjc.2017.232. Epub 2017 Jul 20.
8
Making Meaningful Clinical Use of Biomarkers.
Biomark Insights. 2017 Jun 19;12:1177271917715236. doi: 10.1177/1177271917715236. eCollection 2017.
10
Biomarker development in the precision medicine era: lung cancer as a case study.
Nat Rev Cancer. 2016 Aug;16(8):525-37. doi: 10.1038/nrc.2016.56. Epub 2016 Jul 8.

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