PO.IM02.04 · 免疫学

基于免疫荧光的适应性免疫亚型与Carolina乳腺癌研究第三期长期无病间期的关联

Immunofluorescence-based adaptive immune subtypes in an association with long-term disease-free interval in the Carolina Breast Cancer Study Phase III

海报缩略图:基于免疫荧光的适应性免疫亚型与Carolina乳腺癌研究第三期长期无病间期的关联
编号 4237 展板 5 时间 4/21 09:00–12:00 区域 Section 6 主讲 Qichen Wang, BS;MS;PhD
分会场 Adaptive Immunity in Cancer
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作者与单位 Authors & Affiliations

Qichen Wang1, Timothy Patrick Sheahan1, Alyssa Joy Cozzo2, Sarah Christine Van Alsten2, Eboneé Nicole Butler1, James Stephen Marron3, Katherine A. Hoadley4, Melissa A. Troester1

1Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC,2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC,3Department of Statistics and Operations Research, College of Arts and Science, University of North Carolina at Chapel Hill, Chapel Hill, NC,4Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC

摘要 Abstract

中文摘要
使用大体RNA表达定义的适应性免疫亚型与乳腺癌复发风险较低相关。在病灶内异质性的背景下,这些估计可能无法捕捉相关的局部免疫浸润模式。我们旨在:1)比较基于大体RNA和基于免疫荧光(IF)的免疫亚型,以更好地表征肿瘤免疫微环境;2)评估使用IF定义的空间分辨适应性免疫表型与乳腺癌复发之间的关联。我们分析了来自基于人群的Carolina乳腺癌研究第三期的1,665个浸润性乳腺癌肿瘤,使用了5,276个1毫米肿瘤微阵列核心(每个肿瘤最多4个)。通过多重IF对六种适应性标志物(PD-1、CD3、CD4、CD8a、CD8、FOXP3)进行定量。核心水平适应性免疫亚型(适应性高 vs 适应性低)通过对每种标志物HALO估计的阳性百分比细胞进行k均值聚类来定义。参与者水平免疫亚型使用对核心水平标志物值的加权平均值(按总细胞计数加权)进行k均值聚类来定义。如果所有核心均与参与者水平亚型匹配,则肿瘤被标记为'一致'。作为比较,我们还在肿瘤水平上仅使用CD8阳性百分比(高 vs 低)进行了k均值聚类。计算了比较IF(多标志物)与基于大体RNA的适应性分类器(先前定义)的一致性百分比。我们使用Cox模型估计适应性亚型与10年无病间期(DFI)之间的关联,按雌激素受体(ER)状态分层,并针对年龄、种族和分期进行校正。我们观察到参与者水平IF和RNA适应性分类器之间有65%的一致性。多标志物IF定义的适应性低肿瘤具有更差的10年DFI [ER+:风险比(HR)1.54,95%置信区间(CI)1.07-2.22;ER-:HR 1.72,95% CI 1.11-2.68]。CD8低簇在ER+肿瘤中显示出相似的关联 [HR 1.52,95% CI 1.06-2.19],在ER-肿瘤中无关联 [HR 1.31,95% CI 0.83-2.06]。基于RNA的关联强于基于IF的关联 [HR RNA 2.00,95% CI 1.48-2.70,非适应性 vs. 适应性,总体]。暴露错误分类可能减弱了关联,因为具有不一致多标志物适应性高IF亚型的肿瘤与那些一致的肿瘤相比,与更差的10年DFI显著相关 [HR 1.83,95% CI 1.18-2.85]。总体而言,适应性免疫在乳腺癌中具有预后价值,但适应性反应的错误分类是生物标志物开发的一个隐忧。使用反映适应性免疫群落的多种标志物可能部分克服病灶内异质性,但大体分析掩盖了空间特征。理想的预后免疫生物标志物必须能够可重复地测量,并对检测最具影响力的免疫特征敏感。
查看英文原文 English abstract
Adaptive immune subtype defined using bulk RNA expression has been associated with lower risk of breast cancer recurrence. In the context of intralesional heterogeneity, these estimates may not capture relevant localized patterns of immune infiltration. We aimed to 1) compare bulk RNA-based and immunofluorescence (IF)-based immune subtypes to better characterize the tumor immune microenvironment and 2) evaluate associations between spatially-resolved adaptive immunophenotypes defined using IF and breast cancer recurrence. We analyzed 1,665 invasive breast cancer tumors from the population-based Carolina Breast Cancer Study Phase 3, using 5,276 1-mm tumor microarrays cores (up to 4 per tumor). Six adaptive markers (PD-1, CD3, CD4, CD8a, CD8, FOXP3) were quantified by multiplex IF. Core-level adaptive immune subtypes (adaptive-high vs adaptive-low) were defined with k-mean clustering of HALO-estimated percent-positive cells for each marker. Participant-level immune subtypes were defined using k-means clustering on weighted averages of core-level marker values, weighted by total cell count. Tumors were labeled as ‘consistent' if all cores matched the participant-level subtypes. As a comparison, we also performed k-mean clustering using only CD8 percent positive (high vs low) on tumor level. Percent agreement was calculated comparing IF (multi-marker) with bulk RNA-based adaptive classifiers (previously defined). We used Cox models to estimate associations between adaptive subtype and 10-year disease-free interval (DFI) stratified by estrogen receptor (ER) status, and adjusted for age, race, and stage. We observed 65% agreement between participant-level IF and RNA adaptive classifiers. Multi-marker IF-defined adaptive-low tumors had worse 10-year DFI [ER+: Hazard Ratio (HR) 1.54, 95% Confidence Interval (CI) 1.07-2.22; ER-: HR 1.72, 95% CI 1.11-2.68]. CD8-low cluster showed a similar association among ER+ tumors [HR 1.52, 95% CI 1.06-2.19], no association among ER- tumors [HR 1.31, 95% CI 0.83-2.06]. RNA-based associations were stronger than those for IF [HR RNA 2.00, 95% CI 1.48-2.70, non-adaptive vs. adaptive, overall]. Exposure misclassification may have attenuated associations because tumors with inconsistent multi-marker adaptive-high IF subtype were significantly associated with worse 10-year DFI compared to those were consistent [HR 1.83, 95% CI 1.18-2.85]. Overall, adaptive immunity is prognostic in breast cancers, but misclassification of adaptive response is a concern for biomarker development. Use of multiple markers reflecting the adaptive immune community may partially overcome intralesional heterogeneity, but bulk profiling masks spatial characteristics. Ideal immune biomarkers for prognosis must be reproducibly measured and sensitive to detect the most impactful immune characteristics.
利益披露 Disclosure
Q. Wang, None.. T. P. Sheahan, None.. A. J. Cozzo, None.. S. C. Van Alsten, None.. E. N. Butler, None.. J. S. Marron, None.. K. A. Hoadley, None.. M. A. Troester, None.

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