Diotaiuti Sergio, De Summa Simona, Altieri Rosanna, Dantona Caterina, Tommasi Stefania, Di Gennaro Maria, Rubini Giuseppe, Pastena Maria Irene, Argentiero Antonella, Zito Francesco Alfredo, Silvestris Nicola, Paradiso Angelo Virgilio
Senology Unit, IRCCS Istituto Tumori 'Giovanni Paolo II' of Bari, I-70124 Bari, Italy.
Molecular Biology and Pharmacogenomics Laboratory, IRCCS Istituto Tumori 'Giovanni Paolo II' of Bari, I-70124 Bari, Italy.
Oncol Lett. 2020 Sep;20(3):2469-2476. doi: 10.3892/ol.2020.11793. Epub 2020 Jul 1.
The current study examined if cancer biomarker phenotyping could predict the clinical/pathological status of axillary nodes in women with primary breast cancer. Primary breast cancers from 2002 were analyzed for tumor size, estrogen receptor (ER), progesterone receptor (PgR), Ki-67MIB expression and Her2/neu amplification. Relationships between the clinical and pathological status of the axilla and the biological subtypes classification were analyzed using univariate, multivariate and regression tree analysis. A total of 65% of women with axillary nodes clinically involved had complete axillary node dissection (ALND) while 705 women with clinically negative axillary underwent sentinel lymph node biopsy (SLNB), 18.5% of the latter had at least one pathologically SLNB involved node. Multivariate analysis revealed that the Luminal A subtype was significantly associated (OR 0.62; P<10) with clinical negative axilla while HER2pos/not Luminal was associated with clinical positivity (OR 1.71; P<0.01). No significant association between biological subtypes and SLNB status was demonstrated. Regression tree analysis revealed that subgroups with significantly different probability of SLNB status were separated according to tumor size and PgR values. In conclusion, the current study demonstrated that biomarker breast cancer phenotyping is significantly associated with clinical status of axillary nodes but not with pathological involvement of nodes at SLNB. Regression tree analysis could represent a valid attempt to individualize some patients subgroups candidate to different surgical axilla approaches.
本研究探讨了癌症生物标志物表型分析能否预测原发性乳腺癌女性腋窝淋巴结的临床/病理状态。对2002年的原发性乳腺癌进行分析,检测肿瘤大小、雌激素受体(ER)、孕激素受体(PgR)、Ki-67MIB表达及Her2/neu扩增情况。采用单因素、多因素及回归树分析方法,分析腋窝临床及病理状态与生物学亚型分类之间的关系。共有65%临床腋窝淋巴结受累的女性接受了腋窝淋巴结清扫术(ALND),而705例临床腋窝淋巴结阴性的女性接受了前哨淋巴结活检(SLNB),其中18.5%的后者至少有一个前哨淋巴结病理检查发现有转移。多因素分析显示,Luminal A亚型与临床腋窝淋巴结阴性显著相关(OR 0.62;P<0.01),而HER2阳性/非Luminal亚型与临床腋窝淋巴结阳性相关(OR 1.71;P<0.01)。未发现生物学亚型与前哨淋巴结活检状态之间存在显著关联。回归树分析显示,根据肿瘤大小和PgR值可将前哨淋巴结活检状态概率有显著差异的亚组区分开来。总之,本研究表明,乳腺癌生物标志物表型分析与腋窝淋巴结的临床状态显著相关,但与前哨淋巴结活检时的淋巴结病理受累情况无关。回归树分析可能是一种有效的尝试,用于将一些患者亚组个体化,使其适合不同的腋窝手术方式。