RNA from Brush Cytology to Identify Aggressive Squamous Cell Carcinoma

描述（由申请人提供）：鳞状细胞癌（SCC）是一种包括胃肠道和气道粘膜在内的部位的癌症，是目前口腔癌的主要形式。尽管目前治疗取得了进展，但口腔鳞状细胞癌（OSCC）的生存率仍然很低，主要原因是原发肿瘤在诊断后3-5年内复发。晚期肿瘤或侵袭性肿瘤的复发时间要早得多。肿瘤的各种临床和病理参数，如侵袭性生长和分化状态，已经测试了它们预测肿瘤侵袭性的能力。淋巴结转移到多个淋巴结，或扩散到淋巴结囊外，是侵袭性肿瘤复发高风险的关键指标，但这些因素的检测并不总是准确或容易的任务。最近的工作强调了从手术获得的原发肿瘤组织中提取RNA的使用，允许进行全局基因表达分析，确定与淋巴结转移相关的基因表达模式，从而识别高风险肿瘤。我们希望将这种方法扩展到利用细胞学刷无创获得的细胞，而无需使用手术刀活检。我们之前发表了这种方法，并在仓鼠和人类中鉴定了2种特异性OSCC标志物，β 2微球蛋白（B2M）和细胞色素p450 1B1 （CYP1B1）。我们继续使用刷细胞学的RNA鉴定OSCC的先导基因表达分类器，准确率为91%。虽然刷状细胞学细胞的细胞形态检查已被证明有助于肿瘤检测，但这些细胞的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，使临床医生能够以无创的方式对恶性病变进行预后。在一项为期两年的研究中，我们建议开发一种可测试的基于口腔细胞学的基因表达分类器，用于区分多发性淋巴结转移、囊外扩散、神经周围浸润和/或分化差的肿瘤——侵袭性肿瘤生长的四个临床/病理指标，这些指标在侵袭性较低、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先导分类器，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