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预测乳腺癌驱动突变的新进展:精准肿瘤学的工具(综述)。

Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review).

机构信息

Xinjiang Key Laboratory of Molecular Biology for Endemic Diseases, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang 830017, P.R. China.

Department of Pathology, Yale School of Medicine, Yale University, New Haven, CT 06510, USA.

出版信息

Int J Mol Med. 2025 Jan;55(1). doi: 10.3892/ijmm.2024.5447. Epub 2024 Oct 25.

DOI:10.3892/ijmm.2024.5447
PMID:39450552
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11537269/
Abstract

In the modern era of medicine, prognosis and treatment, options for a number of cancer types including breast cancer have been improved by the identification of cancer‑specific biomarkers. The availability of high‑throughput sequencing and analysis platforms, the growth of publicly available cancer databases and molecular and histological profiling facilitate the development of new drugs through a precision medicine approach. However, only a fraction of patients with breast cancer with few actionable mutations typically benefit from the precision medicine approach. In the present review, the current development in breast cancer driver gene identification, actionable breast cancer mutations, as well as the available therapeutic options, challenges and applications of breast precision oncology are systematically described. Breast cancer driver mutation‑based precision oncology helps to screen key drivers involved in disease development and progression, drug sensitivity and the genes responsible for drug resistance. Advances in precision oncology will provide more targeted therapeutic options for patients with breast cancer, improving disease‑free survival and potentially leading to significant successes in breast cancer treatment in the near future. Identification of driver mutations has allowed new targeted therapeutic approaches in combination with standard chemo‑ and immunotherapies in breast cancer. Developing new driver mutation identification strategies will help to define new therapeutic targets and improve the overall and disease‑free survival of patients with breast cancer through efficient medicine.

摘要

在现代医学的预后和治疗中,通过鉴定癌症特异性生物标志物,包括乳腺癌在内的许多癌症类型的预后和治疗选择都得到了改善。高通量测序和分析平台的出现、公开可用的癌症数据库的增长以及分子和组织学分析的普及,通过精准医学方法促进了新药的开发。然而,只有少数具有少数可操作突变的乳腺癌患者通常受益于精准医学方法。在本综述中,系统描述了乳腺癌驱动基因鉴定、可操作的乳腺癌突变以及现有的治疗选择、乳腺癌精准肿瘤学的挑战和应用方面的当前进展。基于乳腺癌驱动基因突变的精准肿瘤学有助于筛选参与疾病发展和进展、药物敏感性以及耐药基因的关键驱动因素。精准肿瘤学的进步将为乳腺癌患者提供更多针对性的治疗选择,提高无病生存率,并有望在不久的将来在乳腺癌治疗方面取得重大成功。驱动基因突变的鉴定允许在乳腺癌中结合标准化疗和免疫疗法进行新的靶向治疗方法。开发新的驱动基因突变鉴定策略将有助于确定新的治疗靶点,并通过有效的药物提高乳腺癌患者的总生存率和无病生存率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be43/11537269/e5600db95b10/ijmm-55-01-05447-g00.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be43/11537269/e5600db95b10/ijmm-55-01-05447-g00.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be43/11537269/e5600db95b10/ijmm-55-01-05447-g00.jpg

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Longitudinal profiling identifies co-occurring BRCA1/2 reversions, TP53BP1, RIF1 and PAXIP1 mutations in PARP inhibitor-resistant advanced breast cancer.纵向分析鉴定出 PARP 抑制剂耐药的晚期乳腺癌中同时存在 BRCA1/2 回复突变、TP53BP1、RIF1 和 PAXIP1 突变。
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