Immune and transcriptomic biomarkers of progressive oral premalignant lesions

项目总结 口腔鳞状细胞癌(OSCC)是全球第六大癌症相关死亡原因。OSCC是 如果及早发现，可以治愈，并有良好的生存结果。大多数口腔鳞状细胞癌在口腔之前 潜在恶性疾病(OPMD)，口腔白斑或白色病变是最常见的类型。 然而，并不是所有的口腔白斑都进展为口腔鳞癌。准确识别可能会 OSCC的进展为OSCC的预防和管理提供了最佳策略，并可能导致 通过早期检测患者的发病率和死亡率。尽管证明不充分，但显微镜检查 组织学分级仍然是预测恶变的金标准。例如，一些 低等级OPMD会进展到OSCC，但并不是所有高等级OPMDs都会进展到OSCC。有一件急事 以及对用于识别具有口腔鳞癌高风险的进行性白斑的高效生物标记物的需求未得到满足 转换。解决这一知识差距可以导致HPV阴性口腔鳞癌的早期发现并改善 病人存活率。检查有无恶变的OPMDs，我们发现了特定的 与进行性OPMDs相关的转录切割签名。使用空间转录和 多重免疫荧光(MIF)，我们观察到恶性转化的OPMD具有明显的 免疫抑制肿瘤相关巨噬细胞增多(富含ARG1)和低水平CD8+T- 细胞。我们的中心假设是，这些信号在组织中的水平和轨迹可以预测 OPMDs恶性转化为口腔鳞状细胞癌。这一多学科U01协作的主要目标 研究是识别和验证可以区分预测的OPMD的转录和免疫特征 以恶性进展和开发、验证和改进基于已识别的风险分层模型 生物标志物和临床变量。在目标1和目标2中，我们将利用一个特点良好、种族多样的 超过500人患有组织学确诊的OPMDs。我们将验证我们的转录本名单 和免疫相关生物标记物，并执行RNA测序和空间转录组学以确定潜在的 与OPMDs恶性进展相关的其他转录本。在目标3中，我们将制定一个 基于选定的转录和免疫生物标记物的组合风险评分公式 根据我们的内部队列预测OMPD恶性进展的临床人口统计学变量。我们会 在300名患者的独立队列中验证组合风险评分公式。风险分值公式可以 供临床医生用于风险评估和临床决策。这个项目的贡献是 预计将具有重大意义，因为它可能导致引入个性化风险分层方法 OPMD的管理。检测高恶变风险的癌前病变将大大 在提高患者存活率的同时最大限度地提高口腔鳞癌筛查的好处。

PROJECT SUMMARY Oral squamous cell carcinoma (OSCC) is the 6th leading cause of cancer-related mortality worldwide. OSCC is curable with favorable survival outcomes if detected early. The majority of OSCCs are preceded by oral potentially malignant disorders (OPMDs) with oral leukoplakia or white lesions being the most common type. However, not all oral leukoplakia progresses to OSCC. Accurate identification of OPMDs that are likely to progress to OSCC offers the best strategy for OSCC prevention and management and can lead to decreasing patients’ morbidity and mortality through earlier detection. Although proven inadequate, microscopic examination and histological grading remain the gold standard for predication of malignant transformation. For instance, some low-grade OPMDs will progress to OSCC but not all high-grade OPMDs progress to OSCC. There is an urgent and unmet demand for highly efficacious biomarkers to identify progressive leukoplakias with a high risk of OSCC conversion. Addressing this knowledge gap can lead to early detection of HPV-negative OSCC and improve patient survival. Examining OPMDs with and without malignant transformation, we have found specific transcriptomic signatures which are associated with progressive OPMDs. Using spatial transcriptomics and multiplex immune fluorescence (mIF), we observed that malignantly transformed OPMDs have significantly increased immunosuppressive tumor-associated macrophages (enriched in ARG1) and low levels of CD8+ T- cells. Our central hypothesis is that the levels and trajectories of such signatures in tissues are predictive of the malignant conversion of OPMDs to OSCC. The primary objective of this multi-disciplinary U01 collaborative study is to identify and validate transcriptomic and immune signatures that can discriminate OPMDs predicted to malignantly progress and develop, validate, and refine a risk stratification model based on identified biomarkers and clinical variables. In Aims 1 and 2, we will leverage a well-characterized, racially diverse population of over 500 individuals with histologically confirmed OPMDs. We will validate our list of transcriptomic and immune-related biomarkers and perform RNA sequencing and spatial transcriptomics to identify potential additional transcripts associated with the malignant progression of OPMDs. In Aim 3, we will develop a combination risk score formula based on selected transcriptomics and immune biomarkers and clinicodemographic variables to predict OMPD malignant progression based on our internal cohort. We will validate the combination risk score formula in an independent cohort of 300 patients. The risk score formula can be used by clinicians for risk assessment and clinical decision making. The contribution from this project is expected to be significant as it can lead to introduction of a personalized risk stratification approach for management of OPMDs. Detecting preneoplastic lesions with high malignant transformation risk will substantially increase patient survival while maximizing OSCC screening benefits.