Delineation of tumor, stromal and immune transcriptomes at the infiltrating interface of muscle invasive bladder cancer

项目摘要 肿瘤侵袭到膀胱粘膜下肌肉的存在定义了从 非致命性膀胱癌；然而，这一过程在分子水平上还没有被很好地理解。基因组学 肌肉浸润性膀胱癌(MIBC)的转录图谱最近发现了突变和基因 与已建立的MIBC相关的表达谱。尽管膀胱癌的一个重大进展 菲尔德，这些分析无法确定在单个肿瘤中激活的独特转录程序， MIBC侵袭界面的间质和免疫群体。这主要是由于 准确收集浸润性肿瘤及其邻近/混合间质和浸润性免疫细胞的空间信息。AS 因此，早期的转录研究，甚至最近使用单细胞RNAseq的研究都依赖于异质性 实体瘤，包括非侵袭性和正常间质以及空间距离较远的免疫成分 从入侵的边界。这种异质性使得精确地去卷曲基因表达变得困难 肿瘤细胞、间质和浸润性免疫细胞所特有的征象 环境。我们假设不同的基因网络在单个肿瘤、间质和 MIBC侵袭性界面的免疫群体。RNAseq分析和生物信息学分析应该 揭示个体群体丰富而独特的转录特征。这项研究将 通过识别不同细胞群体的细胞和分子特征来产生积极影响 侵袭性进展。这些发现可能导致对候选基因网络的检查，这些网络将服务于 作为生物学功能的基础，识别潜在的生物标记物和需要的新的治疗靶点 适用于已被诊断为肌肉浸润性疾病或复发的膀胱癌患者。

Project Summary The presence of tumor invasion into the submucosal muscle of the bladder defines the progression from nonlethal to lethal bladder cancer; however, this process is not well understood at the molecular level. Genomic and transcriptomic profiling of muscle invasive bladder cancer (MIBC) has recently identified mutations and gene expression profiles associated with established MIBC. Although a major advancement in the bladder cancer field, these analyses were unable to determine the unique transcriptional programs activated in individual tumor, stromal and immune populations at the invasive interface of MIBC. This was primarily due to the limitations of accurate spatial collection of infiltrating tumor and adjacent/intermingled stroma and infiltrating immune cells. As a result, earlier transcriptomic studies and even recent studies using single cell RNAseq relied on heterogeneous bulk tumor, which includes both noninvasive as well as normal stroma and immune components spatially distant from the invasive border. This heterogeneity makes it difficult to accurately de-convolute gene expression signatures unique to tumor cells, stroma and infiltrating immune cells in the immediate invasive micro- environment. We hypothesize that distinct gene networks are activated in individual tumor, stromal and immune populations at the invasive interface of MIBC. RNAseq profiling and bioinformatic analysis should reveal enriched and distinct transcriptomic signatures from the individual populations. This research would provide positive impact by identifying cellular and molecular signatures of distinct cellular populations driving invasive progression. These findings could then lead to examination of candidate gene networks that will serve as the basis for biological function, potential biomarker identification and new therapeutic targets that are needed for bladder cancer patients who have been diagnosed with or have relapsed with muscle invasive disease.