Interrogation of the Impact of Selection on the Evolution of Human Pancreatic Cancer Precursor Lesions

项目摘要 胰腺癌起源于癌前病变，如果及早发现和治疗，是可以治愈的。 胰腺导管内乳头状癌前病变的多区域基因组分析 粘液性肿瘤（IPMN），表明IPMN独特的进化和选择性压力相比， 浸润性癌症，强调了选择在癌前病变进展中的潜在重要性。 病变我们建议使用全面的分子生物学方法来表征选择力在IPMN中的作用。 人IPMN组织样品和类器官培养物的分析和计算数据整合。我们 将使用多区域PCR技术确定人IPMN样品中进展的亚克隆的分子特征。 全基因组测序和RNA测序。此外，我们将开发和应用新型多组学 整合DNA和RNA测序数据以描绘人类选择力的计算方法 IPMN。我们将确定通过全基因组DNA测序鉴定的进展克隆的功能， 在一个新的半监督框架中从大量转录数据推断的基因签名。然后我们将 采用人IPMN细胞的三维体外类器官培养模型来表征相对于人IPMN细胞的相对生物学特性。 随着时间的推移，选择性压力的贡献。我们将结合DNA测序和单细胞RNA 测序以鉴定我们的类器官模型中进展的亚克隆的基因表达特征，进一步 使我们的计算框架适应单细胞RNA测序数据。综合考虑， 研究联合收割机了人体组织样本的直接分析和人类癌前细胞的操作， 三维文化与新的多组学计算集成，大大扩展了我们的知识， 选择在胰腺癌前病变中的作用。

Project Summary Pancreatic cancer arises from precancerous lesions that are curable if detected and treated early enough. Recent multi-region genomic analyses of one type of precancerous pancreatic lesion, intraductal papillary mucinous neoplasm (IPMN), suggest unique evolutionary and selective pressures in IPMNs compared to invasive cancers, underscoring the potential importance of selection in the progression of precancerous lesions. We propose to characterize the role of selective forces in IPMNs using comprehensive molecular analyses and computational data integration of both human IPMN tissue samples and organoid cultures. We will determine the molecular features of progressed subclones in human IPMN samples using multi-region whole genome sequencing and RNA-sequencing. In addition, we will develop and apply novel multi-omics computational methods to integrate DNA and RNA-sequencing data to delineate selective forces in human IPMNs. We will determine the function of progressed clones identified by whole genome DNA sequencing with gene signatures inferred from bulk transcriptional data in a new semi-supervised framework. We will then employ a three-dimensional in vitro organoid culture model of human IPMN cells to characterize the relative contributions of selective pressures over time. We will use combined DNA sequencing and single-cell RNA- sequencing to identify gene expression signatures of progressed subclones in our organoid model, further adapting our computational framework to single cell RNA-sequencing data. Taken together, the proposed studies combine direct analysis of human tissue samples and manipulation of human precancerous cells in three-dimensional culture with novel multi-omics computational integration to greatly expand our knowledge of the role of selection in pancreatic cancer precursor lesions.