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癌细胞内在和免疫表型决定基底样乳腺癌的临床结局。

Cancer Cell Intrinsic and Immunologic Phenotypes Determine Clinical Outcomes in Basal-like Breast Cancer.

作者信息

Li Christopher I, Zhang Yuping, Cieślik Marcin, Wu Yi-Mi, Xiao Lanbo, Cobain Erin, Tang Mei-Tzu C, Cao Xuhong, Porter Peggy, Guenthoer Jamie, Robinson Dan R, Chinnaiyan Arul M

机构信息

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.

Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, Michigan.

出版信息

Clin Cancer Res. 2021 Jun 1;27(11):3079-3093. doi: 10.1158/1078-0432.CCR-20-3890. Epub 2021 Mar 22.

Abstract

PURPOSE

Basal-like breast cancer (BLBC) is a particularly aggressive intrinsic molecular subtype of breast cancer that lacks targeted therapies. There is also no clinically useful test to risk stratify patients with BLBC. We hypothesized that a transcriptome-based phenotypic characterization of BLBC tumors and their microenvironments may overcome these challenges.

EXPERIMENTAL DESIGN

We conducted a retrospective correlative genomic sequencing study using a matched pairs design with validation in five independent cohorts. The study was conducted on a large population-based prospective cohort of the major molecular subtypes of breast cancer conducted in the greater Seattle-Puget Sound metropolitan area. Cases consisted of women 20-69 years of age first diagnosed with invasive breast cancer identified through the population-based Surveillance Epidemiology and End Results program. Patients for this analysis ( = 949) were identified from the 1,408 patients with stage I-III triple-negative breast cancer [estrogen receptor-negative (ER), progesterone receptor-negative (PR), HER2]. Of the 949 women, 248 developed a recurrence after their initial diagnosis. A matched set of 67 recurrent and nonrecurrent BLBC tumors was subjected to transcriptome sequencing. Through RNA sequencing of the matched sets of recurrent and nonrecurrent BLBC tumors, we aimed to identify prognostic phenotypes.To identify nonredundant and uncorrelated prognostic genes, we used an ensemble of variable selection algorithms, which resulted in a ranking of genes on the basis of their expected utility in classification. Using leave-one-out cross-validation, we trained a random forest classifier on the basis of the top 21 genes (BRAVO-DX). Validations were performed in five independent triple-negative or BLBC cohorts, and biomarker robustness and transferability were demonstrated by employing real-time PCR.

RESULTS

We found that cancer cell intrinsic and immunologic phenotypes are independent predictors of recurrence. By simultaneously interrogating the tumor and its microenvironment, we developed a compound risk model that stratified patients into low-, medium-, and high-risk groups, with a 14%/56%/74% chance of recurrence, respectively. Biologically, the primary tumors of patients who developed a recurrence had increased growth factor signaling and stem-like features, while nonrecurrent tumors showed high lymphocyte infiltration with clonal expansion of T and B cells, as well as antitumor polarization of macrophages. We validated our model in five independent cohorts, including three large cohorts, where BRAVO-DX was highly informative in identifying patients with disease recurrence [HR, 6.79 (95% confidence interval (CI), 1.89-24.37); HR, 3.45 (95% CI, 2.41-4.93); and HR, 1.69 (95% CI, 1.17-2.46)]. A smaller gene set focused on the tumor immunophenotype, BRAVO-IMMUNE, was highly prognostic in all five cohorts.

CONCLUSIONS

Together, these results indicate that phenotypic characteristics of BLBCs and their microenvironment are associated with recurrence-free survival and demonstrate the utility of intrinsic and extrinsic phenotypes as independent prognostic biomarkers in BLBC. Pending further evaluation and validation, our prognostic model has the potential to inform clinical decision-making for patients with BLBC as it identifies those at high risk of rapidly progressing on standard chemotherapy, as well as those who may benefit from alternative first-line therapies.

摘要

目的

基底样乳腺癌(BLBC)是一种侵袭性特别强的乳腺癌内在分子亚型,缺乏靶向治疗方法。目前也没有临床上有用的检测手段来对BLBC患者进行风险分层。我们假设基于转录组的BLBC肿瘤及其微环境的表型特征分析可能会克服这些挑战。

实验设计

我们采用配对设计进行了一项回顾性相关基因组测序研究,并在五个独立队列中进行了验证。该研究是在大西雅图 - 普吉特海湾大都市地区进行的一项基于人群的大型前瞻性乳腺癌主要分子亚型队列研究的基础上开展的。病例包括通过基于人群的监测、流行病学和最终结果计划确定的首次诊断为浸润性乳腺癌的20 - 69岁女性。本分析的患者(n = 949)是从1408例I - III期三阴性乳腺癌(雌激素受体阴性(ER)、孕激素受体阴性(PR)、HER2)患者中确定的。在这949名女性中,有248人在初次诊断后出现复发。对一组匹配的67例复发和未复发的BLBC肿瘤进行了转录组测序。通过对复发和未复发的BLBC肿瘤匹配组进行RNA测序,我们旨在识别预后表型。为了识别非冗余且不相关的预后基因,我们使用了一组变量选择算法,从而根据基因在分类中的预期效用对其进行排名。使用留一法交叉验证,我们基于排名前21的基因(BRAVO - DX)训练了一个随机森林分类器。在五个独立的三阴性或BLBC队列中进行了验证,并通过实时PCR证明了生物标志物的稳健性和可转移性。

结果

我们发现癌细胞内在和免疫表型是复发的独立预测因素。通过同时研究肿瘤及其微环境,我们开发了一种复合风险模型,该模型将患者分为低风险、中风险和高风险组,复发几率分别为14%/56%/74%。从生物学角度来看,出现复发的患者的原发性肿瘤具有增强的生长因子信号传导和干细胞样特征,而未复发的肿瘤表现出高淋巴细胞浸润,伴有T细胞和B细胞的克隆扩增,以及巨噬细胞的抗肿瘤极化。我们在五个独立队列中验证了我们的模型,包括三个大型队列,其中BRAVO - DX在识别疾病复发患者方面具有很高的信息量[风险比(HR),6.79(95%置信区间(CI),1.89 - 24.37);HR,3.45(95%CI,2.41 - 4.93);以及HR,1.69(95%CI,1.17 - 2.46)]。一个关注肿瘤免疫表型的较小基因集BRAVO - IMMUNE在所有五个队列中都具有很高的预后价值。

结论

总之,这些结果表明BLBC及其微环境的表型特征与无复发生存相关,并证明了内在和外在表型作为BLBC中独立预后生物标志物的效用。在进一步评估和验证之前,我们的预后模型有可能为BLBC患者的临床决策提供参考,因为它可以识别出那些在标准化疗下快速进展风险高的患者,以及那些可能从替代一线治疗中受益的患者。

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