Molecular classification of non-invasive breast lesions for personalised therapy and chemoprevention.
Molecular classification of non-invasive breast lesions for personalised therapy and chemoprevention.
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DOI：
10.18632/oncotarget.6525
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发表时间：
2015-12-22
期刊：
影响因子：
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通讯作者：
Salto-Tellez M
中科院分区：
文献类型：
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作者：
Buckley N;Boyle D;McArt D;Irwin G;Harkin DP;Lioe T;McQuaid S;James JA;Maxwell P;Hamilton P;Mullan PB;Salto-Tellez M
乳腺癌筛查导致了对浸润前乳房病变的检测急剧增加。虽然乳房切除术几乎可以保证治疗该疾病，但如果可以根据共存或复发性侵袭性疾病的风险对患者进行分层，则更保守的方法可能同样有效。在这里，我们使用一系列生物标志物来询问和分类纯非侵入性病变（PNL）和共存的浸润性乳腺癌（CEIN）。除了导管原位癌（DCIS）外，其他肿瘤均呈相对均匀性。DCIS包含更广泛的分子亚型。有趣的是，p-mTOR在所有PNL中均高表达，在DCIS和浸润性癌中表达较低，而TOP2A的表达模式相反。将PNL与CEIN进行比较，我们发现p53和Ki67是CEIN的预测因子，其PPV和NPV分别为90.48%和43.3%。此外，HER2表达在DCIS和浸润性DCIS中表现出最好的一致性。我们建议，在进一步的验证和临床试验之后，这些生物标志物可以用于改善浸润前乳腺病变患者的管理。p53和Ki67可用于将患者分为低危组和高危组。了解HER2或TOP2A等可操作靶点的表达可用于设计化学预防或新辅助策略。增加对侵袭前病变分子特征的了解只会增强我们对这种疾病的理解，并且在个性化医疗时代，使我们更接近改善乳腺癌护理。
Breast cancer screening has led to a dramatic increase in the detection of pre-invasive breast lesions. While mastectomy is almost guaranteed to treat the disease, more conservative approaches could be as effective if patients can be stratified based on risk of co-existing or recurrent invasive disease. Here we use a range of biomarkers to interrogate and classify purely non-invasive lesions (PNL) and those with co-existing invasive breast cancer (CEIN). Apart from Ductal Carcinoma in situ (DCIS), relative homogeneity is observed. DCIS contained a greater spread of molecular subtypes. Interestingly, high expression of p-mTOR was observed in all PNL with lower expression in DCIS and invasive carcinoma while the opposite expression pattern was observed for TOP2A. Comparing PNL with CEIN, we have identified p53 and Ki67 as predictors of CEIN with a combined PPV and NPV of 90.48% and 43.3% respectively. Furthermore, HER2 expression showed the best concordance between DCIS and its invasive counterpart. We propose that these biomarkers can be used to improve the management of patients with pre-invasive breast lesions following further validation and clinical trials. p53 and Ki67 could be used to stratify patients into low and high-risk groups for co-existing disease. Knowledge of expression of more actionable targets such as HER2 or TOP2A can be used to design chemoprevention or neo-adjuvant strategies. Increased knowledge of the molecular profile of pre-invasive lesions can only serve to enhance our understanding of the disease and, in the era of personalised medicine, bring us closer to improving breast cancer care.