RNA from Brush Cytology to Identify Aggressive Squamous Cell Carcinoma

描述(申请人提供)：鳞状细胞癌(SCC)，一种癌症，困扰部位包括胃肠道和呼吸道粘膜，是目前为止口腔癌的主要形式。尽管目前在治疗方面取得了进展，但口腔鳞状细胞癌(OSCC)的存活率仍然很低，主要是因为原发肿瘤在确诊后3-5年内复发。晚期肿瘤或侵袭性肿瘤复发的时间要早得多。肿瘤的各种临床和病理参数，如侵袭性生长和分化状态，已经被测试它们预测肿瘤侵袭性的能力。淋巴结转移到多个结节，或扩散到结节包膜外，是高复发风险的侵袭性肿瘤的关键指标，但检测这些因素并不总是准确或容易的任务。最近的工作强调了使用从手术获得的原发肿瘤组织中的RNA来进行全球基因表达分析，以识别与淋巴转移相关的基因表达模式，从而识别高危肿瘤。我们希望扩展这一方法，以利用可以用细胞学刷子非侵入性获得的细胞，而不需要使用手术刀活检。我们之前发表了这一方法，并在仓鼠和人类中发现了口腔鳞状细胞癌的两个特异性标志物，即β2微球蛋白(B2M)和细胞色素P450 1B1(CYP1B1)。我们已经使用刷检细胞学中的RNA鉴定了口腔鳞癌的初步基因表达分类器，准确率为91%。虽然刷状细胞学细胞的细胞形态检查已经被证明有助于肿瘤的检测，但对这些细胞的RNA分析有可能有助于真正的诊断和预后。我们的长期目标是开发一个平台，使临床医生能够以非侵入性的方式制定恶性病变的预后。在为期两年的研究中，我们建议开发一种基于口腔细胞学的可测试的基因表达分类器，该分类器将区分具有多个淋巴结转移、包膜外扩散、神经侵袭和/或低分化的肿瘤-四个侵袭性肿瘤生长的临床/病理指标，这些指标在侵袭性较低且不易扩散的肿瘤中很少发现。我们将使用相同的患者基因表达数据来创建一个基于基因表达的试验性分类器，该分类器直接预测治疗后第一年复发和导致死亡的肿瘤。这些基于基因表达的分类器最终将有助于治疗决策。1

DESCRIPTION (provided by applicant): Squamous cell carcinoma (SCC), a cancer which afflicts sites including the gastrointestinal and airway mucosa, is by far the predominant form of oral cancer. Despite current advances in treatment, survival from oral SCC (OSCC) remains poor, chiefly due to recurrence of the primary tumor within 3-5 years after diagnosis. Advanced stage tumors, or those of aggressive nature, recur much earlier. Various clinical and pathological parameters of the tumor, such as invasive growth, and state of differentiation have been tested for their ability to predict tumor aggressiveness. Lymph node metastasis to multiple nodes, or spread outside the node capsule, are key indicators of aggressive tumors at high risk for recurrence but detection of these factors is not always accurate or an easy task. Recent work has highlighted the usage of RNA from surgically obtained primary tumor tissue to allow global gene expression analysis that identifies gene expression patterns associated with lymph node metastasis - thus identifying high risk tumors. We would like to extend this approach to take advantage of cells that can be obtained noninvasively with a cytology brush without the use a of scalpel biopsy. We previously published this method and have identified 2 specific markers for OSCC, in hamsters and humans, beta 2 microglobulin (B2M) and cytochrome p450 1B1 (CYP1B1). We have gone on to identify a pilot gene expression classifier for OSCC using RNA from brush cytology with an accuracy of 91%. While examination of cell morphology from brush cytology cells has already proven helpful in tumor detection, RNA analysis of these cells has the potential to contribute to true diagnosis and prognosis. Our long term goal is to develop a platform that will allow the clinician to develop a prognosis for malignant lesions in a noninvasiv manner. In the time frame of a two year study, we propose to develop a testable oral cytology based gene expression classifier that will differentiate tumors with multiple lymph node metastasis, extracapsular spread, perineural invasion and/or poor differentiation- four clinical/pathological indicators of aggressive tumor growth that are seldom found in less aggressive tumors that are less prone to spread. We will use the same patient gene expression data to create a pilot gene expression based classifier that directly predicts tumors that recur and cause mortality the first year after treatment. These gene expression based classifiers will ultimately aid in treatment decisions. 1