下一代肿瘤不可知靶点即将出现
Next-generation tumor-agnostic targets on the horizon.
肿瘤不可知药物开发将肿瘤学重新聚焦于共享的分子依赖性而非组织来源,从而能够针对跨肿瘤的罕见可操作驱动因素进行高效开发。
英文原题:Integrated Molecular and Immune Phenotype of HER2-Positive Breast Cancer and Response to Neoadjuvant Therapy: A NeoALTTO Exploratory Analysis.
免疫表型分析有望补充当前HER2阳性乳腺癌的预测模型,并助力新疗法的开发。
关于HER2靶向治疗在不同HER2通路依赖性和免疫表型的乳腺癌患者中的疗效,目前知之甚少。在此,我们报告一项NeoALTTO探索性分析,通过CIBERSORT评估22种肿瘤浸润免疫细胞和5个免疫相关宏基因在总体患者人群中的临床价值,以及在按TRAR分类器定义为HER2依赖型(TRAR-low)或非HER2依赖型(TRAR-high)的亚组中的临床价值。
使用logistic和Cox回归模型评估基线TRAR、免疫相关元基因及CIBERSORT数据与病理完全缓解(pCR)和无事件生存期(EFS)的关联。采用Bonferroni方法进行多重检验校正。
共分析226例患者:80例(35%)达到pCR,64例(28%)出现复发,中位随访时间为6.7(四分位距6.1-6.8)年;108例被归类为TRAR-low,118例为TRAR-high。总体而言,γδ T细胞比例[OR = 2.69;95%置信区间(CI),1.40-5.18]可预测pCR,而未发现免疫相关元基因可预测pCR。值得注意的是,淋巴细胞特异性激酶(LCK)可预测联合治疗的pCR(OR = 2.53;95% CI,1.12-5.69),但不能预测单药曲妥珠单抗或拉帕替尼的pCR[OR = 0.74;95% CI,0.45-1.22(P交互 = 0.01)]。将LCK与γδ T细胞整合入多变量模型后,提高了临床和分子变量的判别能力,AUC从0.80(95% CI,0.74-0.86)提升至0.83(95% CI,0.78-0.89)。在TRAR-low病例中,活化肥大细胞、IFN和MHCII减少,STAT1、HCK1和γδ T细胞与pCR相关。STAT1在总体(HR = 0.68;95% CI,0.49-0.94)和TRAR-low病例(HR = 0.50;95% CI,0.30-0.86)中均与EFS改善广泛相关,且不受pCR影响,并与淋巴结状态相关。
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 ( P interaction = 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.
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