Histological grade (HG) is commonly adopted as a prognostic factor for ER-positive breast cancer patients. However, HG evaluation methods, such as the pathological Nottingham grading system, are highly subjective with only 50–85% inter-observer agreements. Specifically, the subjectivity in the pathological assignment of the intermediate grade (HG2) breast cancers, comprising of about half of breast cancer cases, results in uncertain disease outcomes prediction. Here, we developed a qualitative transcriptional signature, based on within-sample relative expression orderings (REOs) of gene pairs, to define HG1 and HG3 and reclassify pathologically-determined HG2 (denoted as pHG2) breast cancer patients. From the gene pairs with significantly stable REOs in pathologically-determined HG1 (denoted as pHG1) samples and reversely stable REOs in pathologically-determined HG3 (denoted as pHG3) samples, concordantly identified from seven datasets, we extracted a signature which could determine the HG state of samples through evaluating whether the within-sample REOs match with the patterns of the pHG1 REOs or pHG3 REOs. A sample was classified into the HG3 group if at least a half of the REOs of the 10 gene pairs signature within this sample voted for HG3; otherwise, HG1. Using four datasets including samples of early stage (I–II) ER-positive breast cancer patients who accepted surgery only, we validated that this signature was able to reclassify pHG2 patients into HG1 and HG3 groups with significantly different survival time. For the original pHG1 and pHG3 patients, the signature could also more accurately and objectively stratify them into distinct prognostic groups. And the up-regulated and down down-regulated genes in HG1 compared with HG3 involved in cell proliferation and extracellular signal transduction pathways respectively. By comparing with existing signatures, 10-GPS was with prognostic significance and was more aligned with survival of patients especially for pHG2 samples. The transcriptional qualitative signature can provide an objective assessment of HG states of ER-positive breast cancer patients, especially for reclassifying patients with pHG2, to assist decision making on clinical therapy.

中文翻译：

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用于重新分类 ER 阳性乳腺癌患者组织学分级的定性转录特征


组织学分级（HG）通常被用作 ER 阳性乳腺癌患者的预后因素。然而，HG 评估方法，例如病理诺丁汉分级系统，具有很强的主观性，观察者间的一致性只有 50-85%。具体而言，约占乳腺癌病例一半的中级（HG2）乳腺癌病理分配的主观性导致疾病结果预测不确定。在这里，我们基于基因对的样本内相对表达顺序 (REO) 开发了一个定性转录特征，以定义 HG1 和 HG3 并对病理确定的 HG2（表示为 pHG2）乳腺癌患者进行重新分类。从病理确定的 HG1（表示为 pHG1）样品中具有显着稳定 REO 的基因对和病理确定的 HG3（表示为 pHG3）样品中具有反向稳定 REO 的基因对，从七个数据集中一致鉴定，我们提取了可以确定 HG 的特征通过评估样品内 REO 是否与 pHG1 REO 或 pHG3 REO 的模式匹配来确定样品的状态。如果该样本中 10 个基因对签名的 REO 中至少有一半投票支持 HG3，则该样本被分类为 HG3 组；否则，HG1。使用四个数据集，包括仅接受手术的早期 (I–II) ER 阳性乳腺癌患者的样本，我们验证了该特征能够将 pHG2 患者重新分类为生存时间显着不同的 HG1 和 HG3 组。对于最初的 pHG1 和 pHG3 患者，该特征还可以更准确、客观地将他们分为不同的预后组。 HG1较HG3上调和下调的基因分别参与细胞增殖和细胞外信号转导通路。通过与现有特征进行比较，10-GPS 具有预后意义，并且与患者的生存更加一致，尤其是对于 pHG2 样本。转录定性特征可以客观评估 ER 阳性乳腺癌患者的 HG 状态，特别是对 pHG2 患者进行重新分类，以协助临床治疗决策。