A prediction model integrated genomic alterations and immune signatures of tumor immune microenvironment for early recurrence of stage I NSCLC after curative resection.
A prediction model integrated genomic alterations and immune signatures of tumor immune microenvironment for early recurrence of stage I NSCLC after curative resection.
复制标题
DOI：
10.21037/tlcr-21-751
复制
发表时间：
2022-01
影响因子：
4
通讯作者：
Wu F
中科院分区：
文献类型：
--
作者：
Hu C;Shu L;Chen C;Fan S;Liang Q;Zheng H;Pan Y;Zhao L;Zou F;Liu C;Liu W;Yu FL;Liu X;Liu L;Yang L;Shao Y;Wu F
手术是I期非小细胞肺癌(NSCLC)患者的标准治疗方法。然而，术后复发导致患者预后不良。目前，对于I期非小细胞肺癌患者，还没有有效的预后生物标志物和围手术期治疗方法。纳入130例手术切除的I期非小细胞肺癌患者，其中69例3年内复发，61例无复发(随访5年以上)。采用外显子组全序列测定基因突变、拷贝数变异和肿瘤突变负荷(TMB)。免疫组织化学方法检测PD-L1的表达及CD3+、CD8+肿瘤浸润性淋巴细胞(TIL)水平。用Lasso回归分析确定复发相关基因，构建肿瘤突变评分(TMS)。根据CD3+和CD8+TIL的位置和密度建立免疫核心(IS)。采用Logistic回归建立预测模型。70%的患者包括在培训队列中，30%的患者包括在测试队列中。P<；0.05被认为具有统计学意义。单因素分析显示，肺腺癌、MUC4基因突变和高TMB与早期复发有关(P分别为0.008、0.0008和0.0001)。肿瘤中心和浸润缘CD3+、CD8+TIL与复发呈显著负相关。EGFR突变和PD-L1表达与复发无关。早期复发组TMS显著高于对照组(P<；0.0001)，IS显著低于对照组(P=0.0003)。多因素分析显示，高TMS和低IS是早期复发的独立预测因素(P<；0.0001和P=0.001)。结合TMS和IS，我们在训练队列(AUC=0.935；HL检验，P=0.2885)和测试队列(AUC=0.932；HL检验，P=0.5515)中建立了具有很大区分度和校正性的回归模型。高TMS和低IS都是I期NSCLC复发的不良预后因素。综合复发模型有助于识别复发风险较高的患者，为今后的围手术期治疗研究提供依据。
Surgery is the standard treatment for patients with stage I non-small cell lung cancer (NSCLC). However, postoperative recurrence leads to a poor prognosis of patients. Currently, there is no effective prognostic biomarker and perioperative treatment for patients with stage I NSCLC. One hundred thirty stage I NSCLC patients who had surgical resection were enrolled, including 69 patients who had recurrence within three years and 61 patients who had no recurrence (follow up more than five years). Whole exome sequencing was performed to evaluate gene mutation, copy number variation, and tumor mutation burden (TMB). Immunohistochemistry was carried out to assess the expression of PD-L1 and the level of CD3+ and CD8+ tumor-infiltrating lymphocytes (TILs). Tumor mutation score (TMS) was constructed with the recurrence-associated genes identified by Lasso regression. Immunoscore (IS) was built based on the location and density of CD3+ and CD8+ TILs. Logistic regression was performed to build a prediction model. Seventy percent of patients were included in the training cohort and 30% patients in the testing cohort. P<0.05 was considered to be statistically significant. Univariate analysis showed that lung adenocarcinoma (LUAD), MUC4 mutation, and high TMB were related to early recurrence (P=0.008, 0.0008, and <0.0001, respectively). CD3+ and CD8+ TILs within tumor center and invasive margin significantly negatively correlated with recurrence. EGFR mutation and PD-L1 expression had no association with recurrence. Early recurrence group had significantly higher TMS and lower IS (P<0.0001 and P=0.0003, respectively). Multivariate analysis showed that high TMS and low IS were independent predictors for early recurrence (P<0.0001 and P=0.001, respectively). Integrating TMS and IS, we built a recurrence-model with great discrimination and calibration in the training cohort (AUC =0.935; HL test, P=0.2885) and testing cohort (AUC =0.932; HL test, P=0.5515). High TMS and low IS were both poor prognostic factors for recurrence in stage I NSCLC. The integrated recurrence-model helps identify patients with high recurrence risk, which provides evidence for future research about perioperative treatment.
登录
查看更多内容
影响因子：
5.3
作者：
Kang, Yeon-koo;Song, Yoo Sung;Kim, Sang Eun
通讯作者：
Kim, Sang Eun
影响因子：
4.6
作者：
Izar, Benjamin;Sequist, Lecia;Lanuti, Michael
通讯作者：
Lanuti, Michael
影响因子：
5.4
作者：
Lasoudris, Fanette;Cousin, Celine;Molinier-Frenkel, Valerie
通讯作者：
Molinier-Frenkel, Valerie
影响因子：
10.9
作者：
Enfield, Katey S. S.;Martin, Spencer D.;Guillaud, Martial
通讯作者：
Guillaud, Martial
影响因子：
10.6
作者：
Kelemen, Olga;Pla, Indira;Marko-Varga, Gyorgy
通讯作者：
Marko-Varga, Gyorgy