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在巴西公共卫生系统中攻克乳腺癌:利用组织微阵列进行准确的免疫组织化学评估,但在亚型分类方面存在局限性。

Unlocking breast cancer in Brazilian public health system: Using tissue microarray for accurate immunohistochemical evaluation with limitations in subtyping.

作者信息

Ruppenthal Rubia Denise, Pilar Emily Ferreira Salles, Santos Jordan Boeira Dos, Coelho Rafael Correa, Henriques Carina Machado Costamilan, Uchôa Diego de Mendonça, Graudenz Marcia Silveira

机构信息

Department of Pathology, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.

Laboratory of Pathology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil.

出版信息

Womens Health (Lond). 2025 Jan-Dec;21:17455057241304654. doi: 10.1177/17455057241304654.

DOI:10.1177/17455057241304654
PMID:39745077
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11694303/
Abstract

BACKGROUND

Breast cancer (BC) is a significant burden on healthcare systems, especially in low- and middle-income countries where access to diagnosis and treatment is challenging.

OBJECTIVES

The purpose of this study was to assess the diagnostic accuracy and cost using tissue microarray (TMA) instead of traditional immunohistochemical (IHC) evaluation for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2), and the proliferation marker Ki-67 and BC subtyping within the Brazilian public health system.

DESIGN

This is a retrospective cohort study comparing TMA slides with traditional whole-slide evaluation for IHC markers in 242 BC cases.

METHODS

We used formalin-fixed tissue blocks for TMA assembly. Clinical data and IHC scores for ER, PR, HER2, and Ki-67 were obtained from pathology reports. Cohen's kappa () was used to assess TMA performance.

RESULTS

BC samples were distributed in 10 TMAs and 968 cores were scored (242 BC cases × 4 markers). In 97% of these, TMA reached high quality to adequate IHC scoring with minimal technical issues. Inter-examiner agreement was almost perfect for all markers (ranging from 0.85 for HER2 to 0.91 for ER,  < 0.001). The intratumoral heterogeneity ranged from almost perfect agreement for ER and HER2 to moderate to substantial for PR and Ki-67. TMA offers substantial time and cost savings, with an approximately 11-fold reduction compared to traditional methods. The concordance between TMA and original reports was almost perfect, with 93% overall agreement ( = 0.81,  < 0.001). However, TMA performance varied between markers, with intratumoral heterogeneity significantly impacting discordant results, particularly for Ki-67 and HER2. This ultimately affected the accuracy of BC subtyping. TMA performed well in identifying luminal A and triple-negative cases, but misclassification was common for luminal B and HER2-positive cases.

CONCLUSION

TMA offers accurate and lower-cost results in the individualized IHC assessment of BC markers. However, we do not recommend the use of TMA in the subtyping of BC, where analysis of the whole section remains necessary for more accurate results. We advocate more studies using the TMA approach in the Brazilian public health system to advance women's health care.

摘要

背景

乳腺癌(BC)给医疗系统带来了沉重负担,尤其是在中低收入国家,这些国家在获取诊断和治疗方面面临挑战。

目的

本研究旨在评估在巴西公共卫生系统中,使用组织微阵列(TMA)而非传统免疫组织化学(IHC)评估雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子2(HER2)、增殖标志物Ki-67以及BC亚型的诊断准确性和成本。

设计

这是一项回顾性队列研究,比较了242例BC病例中TMA载玻片与传统全玻片IHC标志物评估。

方法

我们使用福尔马林固定的组织块进行TMA组装。从病理报告中获取ER、PR、HER2和Ki-67的临床数据和IHC评分。使用Cohen's kappa(κ)评估TMA性能。

结果

BC样本分布在10个TMA中,共对968个芯进行了评分(242例BC病例×4种标志物)。其中97%的样本中,TMA达到了高质量,可进行充分的IHC评分,技术问题最少。所有标志物的检查者间一致性几乎完美(HER2为0.85,ER为0.91,P<0.001)。肿瘤内异质性范围从ER和HER2的几乎完美一致到PR和Ki-67的中度到高度一致。TMA可大幅节省时间和成本,与传统方法相比减少了约11倍。TMA与原始报告之间的一致性几乎完美,总体一致性为93%(κ=0.81,P<0.001)。然而,TMA性能在不同标志物之间存在差异,肿瘤内异质性显著影响不一致结果,尤其是对于Ki-67和HER2。这最终影响了BC亚型分类的准确性。TMA在识别管腔A型和三阴性病例方面表现良好,但管腔B型和HER2阳性病例的错误分类很常见。

结论

TMA在BC标志物的个体化IHC评估中提供了准确且低成本的结果。然而,我们不建议在BC亚型分类中使用TMA,在BC亚型分类中,为了获得更准确的结果,仍需要对整个切片进行分析。我们提倡在巴西公共卫生系统中开展更多使用TMA方法的研究,以推进女性医疗保健。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02ef/11694303/c59c6577ca51/10.1177_17455057241304654-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02ef/11694303/c59c6577ca51/10.1177_17455057241304654-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02ef/11694303/c59c6577ca51/10.1177_17455057241304654-fig1.jpg

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