Disciplina de Oncologia, Departamento Radiologia e Oncologia, Faculdade de Medicina da Universidade de São Paulo, Brazil.
Acta Oncol. 2012 Jan;51(1):77-85. doi: 10.3109/0284186X.2011.620619. Epub 2011 Oct 10.
Previous knowledge of cervical lymph node compromise may be crucial to choose the best treatment strategy in oral squamous cell carcinoma (OSCC). Here we propose a set four genes, whose mRNA expression in the primary tumor predicts nodal status in OSCC, excluding tongue.
We identified differentially expressed genes in OSCC with and without compromised lymph nodes using Differential Display RT-PCR. Known genes were chosen to be validated by means of Northern blotting or real time RT-PCR (qRT-PCR). Thereafter we constructed a Nodal Index (NI) using discriminant analysis in a learning set of 35 patients, which was further validated in a second independent group of 20 patients.
Of the 63 differentially expressed known genes identified comparing three lymph node positive (pN +) and three negative (pN0) primary tumors, 23 were analyzed by Northern analysis or RT-PCR in 49 primary tumors. Six genes confirmed as differentially expressed were used to construct a NI, as the best set predictive of lymph nodal status, with the final result including four genes. The NI was able to correctly classify 32 of 35 patients comprising the learning group (88.6%; p = 0.009). Casein kinase 1alpha1 and scavenger receptor class B, member 2 were found to be up regulated in pN + group in contrast to small proline-rich protein 2B and Ras-GTPase activating protein SH3 domain-binding protein 2 which were upregulated in the pN0 group. We validated further our NI in an independent set of 20 primary tumors, 11 of them pN0 and nine pN + with an accuracy of 80.0% (p = 0.012).
The NI was an independent predictor of compromised lymph nodes, taking into the consideration tumor size and histological grade. The genes identified here that integrate our "Nodal Index" model are predictive of lymph node metastasis in OSCC.
在口腔鳞状细胞癌(OSCC)中,对颈部淋巴结受累的先前了解可能对选择最佳治疗策略至关重要。在这里,我们提出了一组四个基因,其在原发性肿瘤中的 mRNA 表达可预测 OSCC 中的淋巴结状态,不包括舌。
我们使用差异显示 RT-PCR 鉴定了伴有和不伴有淋巴结受累的 OSCC 中的差异表达基因。选择已知基因通过 Northern 印迹或实时 RT-PCR(qRT-PCR)进行验证。此后,我们在 35 例患者的学习组中使用判别分析构建了一个节点指数(NI),并在另一个 20 例患者的独立组中进行了验证。
在比较三个淋巴结阳性(pN +)和三个阴性(pN0)原发性肿瘤的 63 个差异表达已知基因中,有 23 个在 49 个原发性肿瘤中通过 Northern 分析或 RT-PCR 进行了分析。6 个被证实差异表达的基因被用于构建 NI,作为预测淋巴结状态的最佳基因集,最终结果包括 4 个基因。NI 能够正确分类学习组中的 35 例患者中的 32 例(88.6%;p = 0.009)。与在 pN0 组中上调的小富含脯氨酸蛋白 2B 和 Ras-GTPase 激活蛋白 SH3 结构域结合蛋白 2 相反,在 pN + 组中发现角蛋白激酶 1alpha1 和清道夫受体 B,成员 2 上调。我们在另一个由 20 个原发性肿瘤组成的独立组中进一步验证了我们的 NI,其中 11 个为 pN0,9 个为 pN +,准确率为 80.0%(p = 0.012)。
NI 是淋巴结受累的独立预测因子,同时考虑了肿瘤大小和组织学分级。在这里确定的整合我们“节点指数”模型的基因可预测 OSCC 中的淋巴结转移。