The NSCLC immunotherapy response predicted by tumor-infiltrating T cells via a non-invasive radiomic approach

免疫疗法 医学 癌症研究 肿瘤科 内科学 癌症
作者
Jie Min,Fei Dong,Yongyuan Chen,Wenshan Li,Yimin Wu,Yanbin Tan,Fan Yang,Pin Wu,Ying Chai
出处
期刊:Frontiers in Immunology [Frontiers Media SA]
卷期号:15: 1379812-1379812 被引量:6
标识
DOI:10.3389/fimmu.2024.1379812
摘要

Introductions Identifying patients with non-small cell lung cancer (NSCLC) who are optimal candidates for immunotherapy is a cornerstone in clinical decision-making. The tumor immune microenvironment (TIME) is intricately linked with both the prognosis of the malignancy and the efficacy of immunotherapeutic interventions. CD8+ T cells, and more specifically, tissue-resident memory CD8+ T cells [CD8+ tissue-resident memory T (TRM) cells] are postulated to be pivotal in orchestrating the immune system's assault on tumor cells. Nevertheless, the accurate quantification of immune cell infiltration—and by extension, the prediction of immunotherapeutic efficacy—remains a significant scientific frontier. Methods In this study, we introduce a cutting-edge non-invasive radiomic model, grounded in TIME markers (CD3+ T, CD8+ T, and CD8+ TRM cells), to infer the levels of immune cell infiltration in NSCLC patients receiving immune checkpoint inhibitors and ultimately predict their response to immunotherapy. Data from patients who had surgical resections (cohort 1) were employed to construct a radiomic model capable of predicting the TIME. This model was then applied to forecast the TIME for patients under immunotherapy (cohort 2). Conclusively, the study delved into the association between the predicted TIME from the radiomic model and the immunotherapeutic outcomes of the patients. Result For the immune cell infiltration radiomic prediction models in cohort 1, the AUC values achieved 0.765, 0.763, and 0.675 in the test set of CD3+ T, CD8+ T, and CD8+ TRM, respectively. While the AUC values for the TIME-immunotherapy predictive value were 0.651, 0.763, and 0.829 in the CD3-immunotherapy response model, CD8-immunotherapy response model, and CD8+ TRM-immunotherapy response model in cohort 2, respectively. The CD8+ TRM-immunotherapy model exhibited the highest predictive value and was significantly better than the CD3-immunotherapy model in predicting the immunotherapy response. The progression-free survival (PFS) analysis based on the predicted levels of CD3+ T, CD8+ T, and CD8+ TRM immune cell infiltration showed that the CD8+ T cell infiltration level was an independent factor (P=0.014, HR=0.218) with an AUC value of 0.938. Discussion Our empirical evidence reveals that patients with substantial CD8+ T cell infiltration experience a markedly improved PFS compared with those with minimal infiltration, asserting the status of the CD8+ T cell as an independent prognosticator of PFS in the context of immunotherapy. Although CD8+ TRM cells demonstrated the greatest predictive accuracy for immunotherapy response, their predictive strength for PFS was marginally surpassed by that of CD8+ T cells. These insights advocate for the application of the proposed non-invasive radiomic model, which utilizes TIME analysis, as a reliable predictor for immunotherapy outcomes and PFS in NSCLC patients.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
Li发布了新的文献求助10
刚刚
小禾同学发布了新的文献求助10
1秒前
寒酥完成签到,获得积分10
2秒前
jimmyhui完成签到,获得积分10
2秒前
2秒前
Kenneth关注了科研通微信公众号
4秒前
st发布了新的文献求助30
5秒前
Jiang发布了新的文献求助10
5秒前
5秒前
烟花应助寒酥采纳,获得10
6秒前
哦哦哦发布了新的文献求助10
6秒前
7秒前
fairy完成签到,获得积分10
9秒前
Vitalis完成签到,获得积分10
9秒前
CY发布了新的文献求助30
10秒前
科研通AI6应助bbbuuu采纳,获得10
11秒前
天天快乐应助Jiang采纳,获得10
12秒前
12秒前
12秒前
悦耳康发布了新的文献求助10
12秒前
14秒前
水濑心源发布了新的文献求助20
15秒前
李一一完成签到 ,获得积分10
16秒前
bkagyin应助眯眯眼的以彤采纳,获得10
16秒前
vigourc完成签到,获得积分10
17秒前
17秒前
科研通AI6应助zhang采纳,获得10
17秒前
tutoutou完成签到,获得积分20
17秒前
17秒前
18秒前
19秒前
卜天亦完成签到,获得积分10
19秒前
20秒前
淡淡土豆应助科研通管家采纳,获得10
20秒前
zj杰完成签到,获得积分20
20秒前
科目三应助科研通管家采纳,获得10
20秒前
Hello应助科研通管家采纳,获得30
20秒前
BowieHuang应助科研通管家采纳,获得10
20秒前
blackddl应助科研通管家采纳,获得10
20秒前
CipherSage应助科研通管家采纳,获得10
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
Theoretical modelling of unbonded flexible pipe cross-sections 2000
List of 1,091 Public Pension Profiles by Region 1581
Encyclopedia of Agriculture and Food Systems Third Edition 1500
Specialist Periodical Reports - Organometallic Chemistry Organometallic Chemistry: Volume 46 1000
Current Trends in Drug Discovery, Development and Delivery (CTD4-2022) 800
Minimizing the Effects of Phase Quantization Errors in an Electronically Scanned Array 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5533498
求助须知:如何正确求助?哪些是违规求助? 4621711
关于积分的说明 14580035
捐赠科研通 4561794
什么是DOI,文献DOI怎么找? 2499622
邀请新用户注册赠送积分活动 1479350
关于科研通互助平台的介绍 1450588