Classical pathology and mutational load of breast cancer - integration of two worlds.
Classical pathology and mutational load of breast cancer - integration of two worlds.
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DOI：
10.1002/cjp2.25
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发表时间：
2015-10
期刊：
影响因子：
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通讯作者：
Stenzinger A
中科院分区：
文献类型：
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作者：
Budczies J;Bockmayr M;Denkert C;Klauschen F;Lennerz JK;Györffy B;Dietel M;Loibl S;Weichert W;Stenzinger A
乳腺癌是一种复杂的分子疾病，由几种生物学亚型组成。然而，日常的常规诊断仍然是基于一小部分具有良好特征的临床病理变量。在这里，我们试图通过分析乳腺癌的临床病理表型和突变负荷之间的关系，将外科病理学和多层分子图谱这两个世界联系起来。我们根据临床病理，包括免疫组织化学和肿瘤特征，评估了乳腺癌不同亚组中具有体细胞非沉默突变的突变基因的数量。这项分析是根据癌症基因组图谱(TCGA)项目提供的突变图谱、基因表达和临床病理数据对687名原发乳腺癌患者进行的。突变基因的数量与较高的肿瘤分级(p = 1.4E−14)以及不同的免疫组织化学和PAM50分子亚型(分别为p = 1.4E−10和p = 4.3E−10)呈显著正相关。我们观察到在整个队列和激素受体阳性队列中，突变基因的丰度和与增殖相关的基因的表达水平之间存在显著的相关性(|R| >； 0.4)，包括复发评分基因签名(例如，MYBL2和BIRC5.特异性突变基因(TP53、NCOR1、NF1、PTPRD和RB1)与突变基因的高负载量显著相关。总体生存(OS)多因素分析显示，突变基因数目多的患者生存较差(风险比 = 4.6，95%CI：1.0~2 0.0，p = 0.044)。在这里，我们报告了乳腺癌中突变基因的数量与免疫组织化学、PAM50亚型和肿瘤分级之间的强烈关联。我们提供的证据表明，特定水平的突变负荷构成了不同的形态和生物学表型，这些表型共同构成了目前病理诊断的基础。我们的研究是迈向基因组学乳腺病理学的一步，并将为该领域未来的研究提供基础，弥合形态学、肿瘤生物学和医学肿瘤学之间的差距。
Breast cancer is a complex molecular disease comprising several biological subtypes. However, daily routine diagnosis is still based on a small set of well‐characterized clinico‐pathological variables. Here, we try to link the two worlds of surgical pathology and multilayered molecular profiling by analyzing the relationships between clinico‐pathological phenotypes and mutational loads of breast cancer. We evaluated the number of mutated genes with somatic non‐silent mutations in different subgroups of breast cancer based on clinico‐pathological, including immunohistochemical and tumour characteristics. The analysis was performed for a cohort of 687 primary breast cancer patients with mutational profiling, gene expression and clinico‐pathological data available from The Cancer Genome Atlas (TCGA) project. The number of mutated genes was strongly positively associated with higher tumour grade (p = 1.4e−14) and with the different immunohistochemical and PAM50 molecular subtypes of breast cancer (p = 1.4e−10 and p = 4.3e−10, respectively). We observed significant associations (|R| > 0.4) between the abundance of mutated genes and expression levels of genes related to proliferation in the overall cohort and hormone receptor positive cohort, including the Recurrence Score gene signature (e.g., MYBL2 and BIRC5). Specific mutated genes (TP53, NCOR1, NF1, PTPRD and RB1) were highly significantly associated with high loads of mutated genes. Multivariate analysis for overall survival (OS) revealed a worse survival for patients with high numbers of mutated genes (hazard ratio = 4.6, 95% CI: 1.0 – 20.0, p = 0.044). Here, we report a strong association of the number of mutated genes with immunohistochemical and PAM50 subtypes and tumour grade in breast cancer. We provide evidence that specific levels of the mutational load underlie different morphological and biological phenotypes, which collectively constitute the current basis of pathological diagnosis. Our study is a step towards genomics‐informed breast pathology and will provide a basis for future studies in this field bridging the gap between morphology, tumour biology and medical oncology.