Targeting the Fibroblast Growth Factor Receptor (FGFR) Family in Lung Cancer

成纤维细胞生长因子受体 癌症研究 克拉斯 肺癌 受体酪氨酸激酶 癌症 表皮生长因子受体 靶向治疗 医学 酪氨酸激酶 生物 成纤维细胞生长因子 肿瘤科 内科学 受体 结直肠癌
作者
Laura Pacini,Andrew Jenks,Nadia Carvalho Lima,Paul H. Huang
出处
期刊:Cells [Multidisciplinary Digital Publishing Institute]
卷期号:10 (5): 1154-1154 被引量:45
标识
DOI:10.3390/cells10051154
摘要

Lung cancer is the most common cause of cancer-related deaths globally. Genetic alterations, such as amplifications, mutations and translocations in the fibroblast growth factor receptor (FGFR) family have been found in non-small cell lung cancer (NSCLC) where they have a role in cancer initiation and progression. FGFR aberrations have also been identified as key compensatory bypass mechanisms of resistance to targeted therapy against mutant epidermal growth factor receptor (EGFR) and mutant Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) in lung cancer. Targeting FGFR is, therefore, of clinical relevance for this cancer type, and several selective and nonselective FGFR inhibitors have been developed in recent years. Despite promising preclinical data, clinical trials have largely shown low efficacy of these agents in lung cancer patients with FGFR alterations. Preclinical studies have highlighted the emergence of multiple intrinsic and acquired resistance mechanisms to FGFR tyrosine kinase inhibitors, which include on-target FGFR gatekeeper mutations and activation of bypass signalling pathways and alternative receptor tyrosine kinases. Here, we review the landscape of FGFR aberrations in lung cancer and the array of targeted therapies under clinical evaluation. We also discuss the current understanding of the mechanisms of resistance to FGFR-targeting compounds and therapeutic strategies to circumvent resistance. Finally, we highlight our perspectives on the development of new biomarkers for stratification and prediction of FGFR inhibitor response to enable personalisation of treatment in patients with lung cancer.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
灰雁应助昏睡的藏鸟采纳,获得10
1秒前
Joye完成签到,获得积分10
2秒前
Oxidase发布了新的文献求助10
2秒前
yyx完成签到,获得积分10
2秒前
彭于晏应助QQ采纳,获得10
3秒前
萍乡斌乃完成签到,获得积分10
4秒前
jobeco应助ASH采纳,获得10
4秒前
5秒前
万能图书馆应助四月妹妹采纳,获得10
6秒前
橘字完成签到,获得积分10
6秒前
6秒前
香蕉觅云应助KBRS采纳,获得10
7秒前
月季花季完成签到 ,获得积分10
7秒前
hoyden完成签到,获得积分10
8秒前
JNN完成签到,获得积分10
8秒前
yh完成签到,获得积分10
9秒前
9秒前
闵杰完成签到,获得积分10
10秒前
科目三应助薄荷采纳,获得10
10秒前
10秒前
完美世界应助sun采纳,获得10
11秒前
11秒前
11秒前
pig_chivalrous完成签到,获得积分10
12秒前
Whywhy发布了新的文献求助10
12秒前
lucky发布了新的文献求助10
12秒前
倾城关注了科研通微信公众号
14秒前
Resign发布了新的文献求助10
14秒前
15秒前
桃柠发布了新的文献求助10
17秒前
Vincent完成签到 ,获得积分10
18秒前
18秒前
Owen应助细腻戒指采纳,获得10
19秒前
20秒前
王爷教你白给完成签到,获得积分10
20秒前
研友_Z6Qrbn完成签到,获得积分10
21秒前
SERINA发布了新的文献求助30
21秒前
21秒前
21秒前
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
DIPPR Project 801 - Full Version 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7767737
求助须知:如何正确求助?哪些是违规求助? 9311262
关于积分的说明 20322524
捐赠科研通 7352659
什么是DOI,文献DOI怎么找? 3315451
关于科研通互助平台的介绍 2464733
邀请新用户注册赠送积分活动 2330087