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中国非小细胞肺癌的驱动基因改变分析及共发生改变对免疫治疗的影响。

Driver gene alterations profiling of Chinese non-small cell lung cancer and the effects of co-occurring alterations on immunotherapy.

机构信息

Medical Oncology Department, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.

Training Department of Medical Service Department, General Hospital of People's Liberation Army, Beijing, China.

出版信息

Cancer Med. 2021 Oct;10(20):7360-7372. doi: 10.1002/cam4.4178. Epub 2021 Oct 2.

DOI:10.1002/cam4.4178
PMID:34599863
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8525092/
Abstract

BACKGROUND

Molecular testing for alterations in oncogenic driver genes and targeted therapies have become standard procedures for non-small cell lung cancer (NSCLC) patients. However, little evidence has shed light on the pattern of co-existence of driver genes in NSCLC, and whether they may have different tumor features affecting immunotherapy is still unclarified.

METHODS

Genomic alterations in 14 lung cancer-related genes were conducted in 3440 Chinese NSCLC patients using next-generation sequencing. Meanwhile, tumor mutational burden and immunotherapy dataset from the Memorial sloan kettering cancer center (MSKCC) and lung adenocarcinoma dataset from The Cancer Genome Atlas (TCGA) were utilized for analyzing the impact of the co-occurring alterations on patients' survival following immunotherapy.

RESULTS

In this cohort, 90.17% of patients had at least one somatic alteration in the 14 genes, including 51% of co-occurring alterations. TP53 and epidermal growth factor receptor (EGFR) were the most prevalent genes (54.74% and 53.55%, respectively), followed by KRAS, ERBB2, ALK, PIK3CA, ROS1, RET, MET, BRAF, KIT, FGFR1, PDGFRA, and NRAS. The prevalence of TP53, EGFR, and ERBB2 in our cohort were significantly higher than that from the TCGA database, whereas KRAS, BRAF, and PDGFRA were significantly lower than the latter. Furthermore, the patients who harbored multiple alterations (8.86%, 31/350) in eight driver genes survived longer and have a higher tumor mutation burden compared to the patients with a single alteration. Similar result was found between the patients with co-occurring alteration of EGFR and other driver genes and the patients with single EGFR alteration. Meanwhile, we found a distinct immune cell infiltration feature between patients with single and multiple driver gene alterations, as well as between patients with only EGFR alteration and co-occurring groups.

CONCLUSION

This study identified a unique driver gene feature and found patients harboring co-occurring alterations of EGFR and other driver genes may benefit from immunotherapy, which may provide more therapeutic selections for EGFR-mutated NSCLC patients and merit additional investigation.

摘要

背景

针对致癌驱动基因改变的分子检测和靶向治疗已成为非小细胞肺癌(NSCLC)患者的标准治疗程序。然而,目前很少有证据表明 NSCLC 中驱动基因的共存模式,以及它们是否可能具有不同的肿瘤特征从而影响免疫治疗效果。

方法

对 3440 例中国 NSCLC 患者使用下一代测序技术进行了 14 个肺癌相关基因的基因组改变检测。同时,利用 Memorial sloan kettering 癌症中心(MSKCC)的肿瘤突变负荷和免疫治疗数据集以及 The Cancer Genome Atlas(TCGA)的肺腺癌数据集,分析了共存改变对免疫治疗后患者生存的影响。

结果

在该队列中,90.17%的患者在 14 个基因中至少有一个体细胞改变,其中 51%为共存改变。TP53 和表皮生长因子受体(EGFR)是最常见的基因(分别为 54.74%和 53.55%),其次是 KRAS、ERBB2、ALK、PIK3CA、ROS1、RET、MET、BRAF、KIT、FGFR1、PDGFRA 和 NRAS。与 TCGA 数据库相比,我们队列中 TP53、EGFR 和 ERBB2 的发生率明显更高,而 KRAS、BRAF 和 PDGFRA 的发生率明显更低。此外,与单一改变的患者相比,在 8 个驱动基因中存在多个改变(8.86%,31/350)的患者生存期更长,肿瘤突变负荷更高。在 EGFR 与其他驱动基因共存改变的患者与单一 EGFR 改变的患者之间也发现了类似的结果。同时,我们发现单一和多个驱动基因改变的患者之间以及仅有 EGFR 改变和共存组的患者之间存在明显不同的免疫细胞浸润特征。

结论

本研究确定了一个独特的驱动基因特征,并发现 EGFR 和其他驱动基因共存改变的患者可能受益于免疫治疗,这可能为 EGFR 突变 NSCLC 患者提供更多的治疗选择,值得进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/e550f6c8b726/CAM4-10-7360-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/8374ed97810c/CAM4-10-7360-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/115917d70de1/CAM4-10-7360-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/ea6fc18c5349/CAM4-10-7360-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/e550f6c8b726/CAM4-10-7360-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/8374ed97810c/CAM4-10-7360-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/aadc428acc4e/CAM4-10-7360-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/3b02011a80a4/CAM4-10-7360-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/115917d70de1/CAM4-10-7360-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5c2/8525092/e550f6c8b726/CAM4-10-7360-g001.jpg

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