HER2 阳性乳腺癌的综合分子和免疫表型与新辅助治疗的反应：NeoALTTO 探索性分析。
Integrated Molecular and Immune Phenotype of HER2-Positive Breast Cancer and Response to Neoadjuvant Therapy: A NeoALTTO Exploratory Analysis.
机构信息
Unit of Bioinformatics and Biostatistics, Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Molecular Targeting Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
出版信息
Clin Cancer Res. 2021 Dec 1;27(23):6307-6313. doi: 10.1158/1078-0432.CCR-21-1600. Epub 2021 Sep 21.
PURPOSE
Little is known about the efficacy of HER2-targeted therapy in patients with breast cancer showing different HER2-pathway dependence and immune phenotypes. Herein, we report a NeoALTTO exploratory analysis evaluating the clinical value of 22 types of tumor-infiltrating immune cells by CIBERSORT and 5 immune-related metagenes in the overall patient population, and in subgroups defined by the TRAR classifier as HER2-addicted (TRAR-low) or not (TRAR-high).
PATIENTS AND METHODS
Association of baseline TRAR, immune-related metagenes, and CIBERSORT data with pathologic complete response (pCR) and event-free survival (EFS) were assessed using logistic and Cox regression models. Corrections for multiple testing were performed by the Bonferroni method.
RESULTS
A total of 226 patients were analyzed: 80 (35%) achieved a pCR, and 64 (28%) experienced a relapse with a median follow-up of 6.7 (interquartile range 6.1-6.8) years; 108 cases were classified as TRAR-low, and 118 TRAR-high. Overall, γδ T-cell fraction [OR = 2.69; 95% confidence interval (CI), 1.40-5.18], and no immune-related metagenes were predictive of pCR. Notably, lymphocyte-specific kinase (LCK) predicted pCR to combination (OR = 2.53; 95% CI, 1.12-5.69), but not to single-agent trastuzumab or lapatinib [OR = 0.74; 95% CI, 0.45-1.22 ( = 0.01)]. Integrating LCK with γδ T cells in a multivariate model added to the discriminatory capability of clinical and molecular variables with a shift in AUC from 0.80 (95% CI, 0.74-0.86) to 0.83 (95% CI, 0.78-0.89). In TRAR-low cases, activated mast cells, IFN and MHCII were reduced, and STAT1, HCK1, and γδ T cells were associated with pCR. STAT1 was broadly associated with improved EFS regardless of pCR, and nodal status in overall (HR = 0.68; 95% CI, 0.49-0.94) and in TRAR-low cases (HR = 0.50; 95% CI, 0.30-0.86).
CONCLUSIONS
Immuno-phenotyping holds the promise to complement current predictive models in HER2-positive breast cancer and to assist in new therapeutic development.
目的
对于表现出不同 HER2 通路依赖性和免疫表型的乳腺癌患者，HER2 靶向治疗的疗效知之甚少。在此，我们报告了一项 NeoALTTO 探索性分析，该分析通过 CIBERSORT 评估了 22 种肿瘤浸润免疫细胞的临床价值，并评估了整体患者人群和根据 TRAR 分类器定义为 HER2 依赖（TRAR-低）或非 HER2 依赖（TRAR-高）的亚组中 5 种免疫相关基因。
患者和方法
使用逻辑回归和 Cox 回归模型评估基线 TRAR、免疫相关基因和 CIBERSORT 数据与病理完全缓解（pCR）和无事件生存（EFS）的关系。通过 Bonferroni 方法进行了多次测试校正。
结果
共分析了 226 例患者：80 例（35%）达到 pCR，64 例（28%）复发，中位随访 6.7 年（四分位距 6.1-6.8）；108 例为 TRAR-低，118 例为 TRAR-高。总体而言，γδ T 细胞分数[OR=2.69；95%置信区间（CI），1.40-5.18]和无免疫相关基因可预测 pCR。值得注意的是，淋巴细胞特异性激酶（LCK）预测联合治疗（OR=2.53；95%CI，1.12-5.69）而非单药曲妥珠单抗或拉帕替尼（OR=0.74；95%CI，0.45-1.22；=0.01）达到 pCR。将 LCK 与γδ T 细胞整合到多变量模型中，与临床和分子变量的鉴别能力相结合，AUC 从 0.80（95%CI，0.74-0.86）增加到 0.83（95%CI，0.78-0.89）。在 TRAR-低的情况下，激活的肥大细胞、IFN 和 MHCII 减少，STAT1、HCK1 和γδ T 细胞与 pCR 相关。STAT1 与 EFS 改善广泛相关，与 pCR 无关，与整体（HR=0.68；95%CI，0.49-0.94）和 TRAR-低的病例（HR=0.50；95%CI，0.30-0.86）的淋巴结状态相关。
结论
免疫表型有望补充 HER2 阳性乳腺癌的现有预测模型，并有助于新的治疗方法的开发。
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